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UBC Theses and Dissertations

An analysis of the effects of M.U.R.B. legislation on Vancouver’s rental housing market Wicks, Anne Patricia 1982

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AN ANALYSIS OF THE EFFECTS OF M.U.R.B. LEGISLATION ON VANCOUVER'S RENTAL HOUSING MARKET by ANNE PATRICIA WICKS B.COMM., UNIVERSITY OF BRITISH COLUMBIA, 1978 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUSINESS ADMINISTRATION in THE FACULTY OF COMMERCE AND BUSINESS ADMINISTRATION (URBAN LAND ECONOMICS DIVISION) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA April, 1982 c \ Anne P a t r i c i a Wicks, 1982 I n p r e s e n t i n g t h i s t h e s i s i n p a r t i a l f u l f i l m e n t o f t h e r e q u i r e m e n t s f o r an a d v a n c e d d e g r e e a t t h e U n i v e r s i t y o f B r i t i s h C o l u m b i a , I a g r e e t h a t t h e L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and s t u d y . I f u r t h e r a g r e e t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y p u r p o s e s may be g r a n t e d by t h e h e a d o f my d e p a r t m e n t o r by h i s o r h e r r e p r e s e n t a t i v e s . I t i s u n d e r s t o o d t h a t c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l n o t be a l l o w e d w i t h o u t my w r i t t e n p e r m i s s i o n . D e p a r t m e n t O f URBAN LAND ECONOMICS The U n i v e r s i t y o f B r i t i s h C o l u m b i a 1956 Main Mall V a n c o u v e r , Canada V6T 1Y3 A P R I L 2 5 , 1 9 8 2 A B S T R A C T The purpose of this paper is to examine the. impact of federal M.U.R.B.I legislation on Vancouver's rental housing market, and to see what conclusions can be drawn about the effectiveness of this subsidy policy in achieving its objective, which was to increase the allocation of resources to the housing sector of the economy by stimulating the construction of rental units. It is the thesis of this paper that the M.U.R.B. legislation was not effective in achieving its objective, since the inelasticity of the land supply function, as imposed by junior levels of government through zoning and other supply constraints, prevented the rental market from responding to these incentives in the form of increased production. It is hypothesized that the real effect of the program was to create windfall gains for existing owners of multiple family zoned land at the time the legislation was passed. It is argued further that real estate markets are more efficient than they are generally given credit for, in the sense that tax shelter benefits associated with M.U.R.B. properties will be fully capitalized into the value of such properties, thus preventing M.U.R.B. investors from earning rates of return superior to those earned by owners of comparable non-M.U.R.B. properties. The paper begins with a brief history of M.U.R.B. legislation, and an analysis of the magnitude and cost of the program to the Canadian government. This is followed by a graphical analysis of the impact of M.U.R.B. legislation on the multiple family housing market, and a discussion and review of the literature pertaining to the (ii) t h e o r y o f e f f i c i e n t m a r k e t s , t h e c a p i t a l i z a t i o n o f c o s t s a n d b e n e f i t s i n t o v a l u e , a n d t h e v a r i o u s m o d e l s o f l a n d v a l u e w h i c h h a v e b e e n f o r m u l a t e d . T w o t h e o r e t i c a l m o d e l s a r e t h e n p r e s e n t e d a s t h e u n d e r l y i n g b a s i s f o r t h e e m p i r i c a l r e s e a r c h i n t h e p a p e r . T h e f i r s t i s a v a l u a t i o n f u n c t i o n f o r a p a r t m e n t i n v e s t m e n t s , w h e r e t h e d e p e n d e n t v a r i a b l e i s t h e s e l l i n g p r i c e o f a n a p a r t m e n t b u i l d i n g ; t h e s e c o n d i s a m o d e l o f t h e d e t e r m i n a n t s o f m u l t i p l e f a m i l y l a n d v a l u e s , w h e r e t h e d e p e n d e n t v a r i a b l e i s t h e p r i c e o f a s i t e . T h e t w o t h e o r e t i c a l m o d e l s a r e t e s t e d u s i n g m u l t i p l e r e g r e s s i o n t e c h n i q u e s . T h e d a t a r e s u l t s p r o v i d e e v i d e n c e w h i c h c o n t r a d i c t s t h e g e n e r a l c a s e f o r t h e o p e r a t i o n o f t h e m u l t i p l e f a m i l y h o u s i n g m a r k e t , w h e r e r e n t e r s s h o u l d r e c e i v e t h e f u l l b e n e f i t s o f t h e M . U . R . B . p r o g r a m i n t h e f o r m o f l o w e r r e n t s . T h e r e s e a r c h s h o w s t h a t t h e f u t u r e t a x s h e l t e r b e n e f i t s a s s o c i a t e d w i t h M.U.R.B. p r o p e r t i e s a r e f u l l y c a p i t a l i z e d i n t o t h e m a r k e t v a l u e s o f c o m p l e t e d M . U . R . B . b u i l d i n g s , a n d t h a t M . U . R . B J i n v e s t o r s d o n o t e a r n r a t e s o f r e t u r n s u p e r i o r t o t h o s e o f i n v e s t o r s i n n o n - M . U . R . B . a p a r t m e n t p r o p e r t i e s . T h e r e s e a r c h s u g g e s t s f u r t h e r t h a t t h e e x p e c t e d M.U.R.B./ t a x s h e l t e r b e n e f i t s w e r e o v e r - c a p i t a l i z e d i n t o h i g h e r l a n d v a l u e p r e m i u m s d u r i n g t h e l i f e o f t h e p r o g r a m , t h u s c r e a t i n g w i n d f a l l g a i n s f o r e x i s t i n g l a n d o w n e r s a t t h e t i m e t h e p r o g r a m w a s i n t r o d u c e d . T h e r e s u l t s s u g g e s t t h a t t h e f u l l c a p i t a l i z a t i o n o f M . U . R . B . b e n e f i t s i n t o b o t h l a n d a n d a p a r t m e n t b l o c k v a l u e s r e s u l t e d i n a l l o f t h e b e n e f i t s o f t h e s u b s i d y p o l i c y n o t f i l t e r i n g t h r o u g h t o r e n t e r s . S o m e b e n e f i t s m o s t l i k e l y d i d r e a c h r e n t e r s , s i n c e i t i s u n r e a l i s t i c t o a s s u m e n o s u b s t i t u t i o n i n t h e p r o d u c t i o n f u n c t i o n f o r a p a r t m e n t s , b u t t h e a c t u a l d i s t r i b u t i o n o f p o l i c y b e n e f i t s b e t w e e n r e n t e r s a n d e x i s t i n g l a n d o w n e r s c a n n o t b e m e a s u r e d w i t h i n t h e s c o p e o f t h i s r e s e a r c h . ( i i i ) TABLE OF CONTENTS Page Number ABSTRACT (ii) TABLE OF CONTENTS (iv) LIST OF TABLES (v) ACKNOWLEDGEMENTS (vi) 1.0 INTRODUCTION 1 2.0 HISTORY OF THE M.U.R.B. PROGRAM 3 3.0 THEORETICAL FRAMEWORK 10 3.1 The Multiple Family Housing Market 10 3.2 Efficient Markets 17 3.3 Capitalization 19 3.4 Land Price Models 24 4.0 DATA BASE 32 4.1 M.U.R.B. Resale Sample 32 4.2 Land Sale Sample 33 5.0 ESTIMATION OF APARTMENT VALUATION FUNCTION 36 5.1 Capitalization 36 5.2 Rates of Return to M.U.R.B. vs. Non-M.U.R.B. Investors 40 6.0 ESTIMATION OF MULTIPLE FAMILY LAND PRICE MODEL 45 6.1 Description of Variables 45 6.2 Empirical Results 52 7.0 CONCLUSIONS AND IMPLICATIONS 65 FOOTNOTES 70 BIBLIOGRAPHY 72 APPENDIX "A" - VARIABLE LISTS 74 APPENDIX "B" - DESCRIPTIVE STATISTICS 87 APPENDIX "C" - SCATTER PLOTS 94 APPENDIX "D" - RESIDUAL PLOTS 100 APPENDIX "E" - DATA FILE LISTINGS 139 (iv) LIST OF TABLES ESTIMATED M.U.R.BJFEDERAL REVENUE LOSSES (1975- 1980) APARTMENT BLOCK VALUATION FUNCTION RATES OF RETURN: M.U.R.B./VS. NON-M.U.R.B.iAPARTMENTS THE REGRESSION EQUATIONS FOR MULTIPLE FAMILY LAND VALUES CORRELATION MATRIX - FULL MODEL VARIABLES (v) ACKNOWLEDGEMENTS There are many individuals and organizations who have assisted me during the course of this research, either through their explicit participation in i t or through their general encouragement and support. It is not possible to acknowledge a l l of them, but some do deserve special recognition here. I would like to thank the B.C. Assessment Authority and B.C. Land Title Office for allowing me to search their records to gather my data, and special thanks should go to Canada Mortgage and Housing Corporation, firstly for the graduate scholarship which they awarded me in 1979, and secondly for the statistical data which was provided by Ted Mitchell and Helmut Pastrick. I would like to thank my committee chairman, Professor George W. Gau, for his invaluable guidance and encouragement throughout the somewhat lengthy period of this research, and I would also like to thank the other members of my committee, Professors Dennis R. Capozza and Norman Carrothers, for their assistance. For their assistance in data collection, I would like to thank Darryl Yea, Paul Smith, Craig Homewood and Helen Evans. For their assistance in coding, thanks should go to Melaney Gleeson-Lyall and Michael Wicks. For their excellent word processing and production assistance, I would like to thank Kelly Gariepy, Renate Vetter and 3oan Choo. I would also like to say a special thank you to my sister, Mary Gleeson, for her valuable assistance and stamina in data collection, coding, proofing and production. (vi) Finally, there are two people who deserve special mention for their long-standing moral support throughout my university career. I would like to thank my mother, Mrs. Kathleen W. L y a l l , for her continual encouragement. Most of a l l , I would like to thank my husband, Michael, for his undying tolerance and understanding, throughout what sometimes seemed an endless task. (vii) 1.0 I N T R O D U C T I O N In 1972, the Federal Government removed the tax shelter benefits available to owners of residential real estate investments, resulting in severe c r i t i c i s m from the real estate industry, and in claims that construction of rental housing would decline or even terminate as a result. Since the demographic characteristics of Canada's population continued to put pressure on the market for rental accom-modation (given that the peak of the baby boom cohort was s t i l l only 1<V years of age at the time, and the front end was 27 years of age),* the public pressure which ensued prompted the Federal Government in 1974 to reinstate tax shelter benefits on a limited basis. This took the form of the Multiple Unit Residential Building (M.U.R.B.) Program, whose objective was to increase the allocation of resources to the housing sector of the economy by stimulating the construction of rental units. The purpose of this paper is to examine the impact of this legislation on Vancouver's rental housing market, and to see what conclusions can be drawn about the effectiveness of the policy in achieving this objective. It is the thesis of this paper that the M.U.R.B. legislation was not effective in achieving its objective, since the inelasticity of the land supply function, as imposed by junior levels of government through zoning and other supply constraints, prevented the rental market from responding to these incentives in the form of increased production. It is hypothesized that the real e f fect of the program was to create windfall gains for existing owners of multiple family zoned land at the time the legislation was passed. It is argued further that real estate markets are more efficient than they are generally given credit for, in the sense . - 1 -that tax shelter benefits associated with M.U.R.B. properties will be fully capitalized into the value of such properties, thus preventing M.U.R.B. investors from earning rates of return superior to those earned by owners of comparable non-M.U.R.B. properties. The paper begins with a brief history of M.U.R.B.J legislation in Canada, and an analysis of the magnitude and cost of the program to the government. This is followed by a graphical analysis of the impact of M.U.R.B. legislation on the multiple family housing market, and a discussion and review of the literature pertaining to the theory of efficient markets, the capitalization of costs and benefits into value, and the various models of land value which have been formulated. Two theoretical models are then presented as the underlying basis for the empirical research in this paper. The first is a valuation function for apartment investments, where the dependent variable is the selling price of an apartment building; the second is a model of the determinants of multiple family land values, where the dependent variable is the price of a site. The empirical testing of the two theoretical models utilizes multiple regression techniques. The objective will be to estimate the magnitude and significance of the M.U.R.B. tax shelter benefits in the determination of the capital value of apartment buildings sold during 1979 and 1980 and in the determination of multiple family zoned land values in the City of Vancouver from 1972 to 1978. The final section of this paper will discuss the implications of the empirical findings in the context of Vancouver's rental housing market. The broader implications for government policy will also be addressed. - 2 -2.0 HISTORY OF THE FEDERAL M.U.R.B. PROGRAM The new Canadian Income Tax Act which came into effect on January 1, 1972, introduced major changes in tax law relating to capital gains tax provisions, income 2 tax rates, income averaging, corporate tax treatment, and resource taxation. The tax change most pertinent to the analysis in this paper was the elimination of tax sheltering of "other" income by capital cost allowance (CCA) deductions claimed on residential investment properties. C C A deductions could only be used to offset any positive income on a particular investment property, rather than other non-real estate income of the taxpayer. The new Act also eliminated the "pooling" of assets with values exceeding $50,000, thus preventing a taxpayer from deferring recapture on disposition of one asset by adding new assets to the same class. The federal budget presented in November, 1974 re-introduced limited provisions for the fu l l deductibility of capital cost allowances on residential investment properties from any income source of the taxpayer. As a consequence, two new — / asset classes were created under the Income Tax A c t which were exempted from the 1972 tax reform removal of tax shelter benefits: Class 31 frame buildings (10 per cent annual C C A on a declining balance) and Class 32 concrete buildings (5 per cent annual C C A on a declining balance). These two asset classes were obtainable only through C.M.H.C. certification on new residential construction containing at least two units, and where at least 80 per cent of the gross floor area 3 of the proposed building was to be allocated to residential use. - 3-The M.U.R.B. designation provided annual capital cost allowance deductibility against any income of the taxpayer, as well as the traditional deductibility of front-end "soft costs" associated with the development of the building. These soft costs, which generally comprise between 15 and 25 per cent of the total capital value of a building, include the following: • survey, engineering and architects' fees • legal and accounting fees • property taxes • interim financing • marketing and administrative expenses • landscaping costs • limited servicing costs Although init i a l l y the M.U.R.B. program was intended to remain in effect only until December 31, 1975, subsequent revisions to the Income Tax Act extended i t on an annual basis until the end of 1979. As of December 31,1979, the Act was amended in such a way that any transfer of a M.U.R.B.-designated building with Class 31 status (10 per cent C CA) would automatically move the building into the Class 32 asset class (5 per cent CCA), this presumably a first step towards the elimination of the program altogether. However, the program was reintroduced in late 1980 with a termination date of December 31, 1981. The federal budget announced on November 12, 1981, and subsequent revisions, indicated that the M.U.R.B.'program would not be continued beyond 1981, but that certification would s t i l l be available until May 31, 1982 to those developers/investors who had submitted application for M.U.R.B. designation prior to the budget date. - 4 -As a supplement to the M.U.R.B. program in stimulating construction of multiple-unit rental buildings, the Federal Government, in 1975 and in 1976, in concert with several provincial governments, introduced the Assisted Rental Program (A.R.P.)., This program initi a l l y involved an outright monthly per-unit grant of $900 to the developer through Canada Mortgage and Housing Corporation, with annual reductions in the grant over a ten-year period and accompanying escalations in economic rent, effectively allowing the developer a constant rate of return on equity from operating flows over the ten-year period The involvement of provincial governments in 1976, most notably B.Cfand Ontario, resulted in variations in A.R.P. program provisions, so that CM.H.C's commitment was in the form of a second mortgage which accumulated over a ten-year interest-free period, while the provincial government provided annual per-unit grants. Units were rented at market levels, while annual reductions in both the federal second mortgage and provincial grant ensured a constant rate of return on equity to the developer over the ten-year contract period. Thus, the combination of the M.U.R.B. and A.R.P. program provisions created very attractive tax incentives to potential investors and developers of multi-unit residential properties. The question is, of course, whether the tax revenues foregone by the Federal Government induced an increase in the construction of rental units which would not otherwise have occurred Unfortunately, the actual cost to the Federal Government of the estimated 195,000 units built under the M.U.R.B. program is not publicly available, although future - 5 -lost tax revenue has been estimated at $514 million in 1981 dollars, assuming a discount rate of 12 per cent and an average marginal tax rate of 40 per cent for M.U.R.B./investors (Clayton Research, 1981). However, this estimate is based on the unrealistic assumption that none of the tax shelter benefits w i l l be recaptured by the government upon disposition of these properties over the next 30 years. Table 1 sets out an estimate of accumulated federal tax losses associated with M.U.R.B.; units built from 1975 to 1979. Due to the "off and on" nature of the program in both 1980 and 1981, estimates for these years have been om i t t e d Based on estimates in the Clayton Research Associates study, 60 per cent of those units with M.U.R.B. certification actually were built and operated as M.U.R.B.!s. Assuming an average federal marginal tax rate of 40 per cent, a one-year construction period, an average C C A rate of 7.5 per cent (reflecting an equal weighting of properties in the 5 per cent and 10 per cent asset classes), and an opportunity cost of 12 per cent per annum to the government on foregone tax revenues from 1975 to 1979, the federal tax losses accumulated by 1981 as a result of the M.U.R.B. program amounted to some $304 million. These estimates assume further that one-half of the C C A deductions are claims that can be attributable only to the M.U.R.B. program. The exact portion of C C A that can be deducted solely due to the M.U.R.B.I exemption is quite difficult to estimate since i t would differ among properties depending on financing arrang-ments and among investors depending on their other real estate holdings. For non-M.U.R.B. properties, the general rule is that "annual capital cost allowances on al l - 6 -Table 1 ESTIMATED M.U.R.B. FEDERAL TAX REVENUE LOSSES (1975 - 1980)  Multiple starts M.U.R.B. c e r t i f i -cates issued 3 Rental units Per unit construc-tion cost 1975 1976 107,527 138,890 8,517 35,219 5,110 21,131 $35,000 $ 39,000 1977 1978 137,321 117,638 82,265 80,089 49,359 48,043 $42,650 $46,650 Present Value of Foregone Revenue 1979 1981 ($000) 87,932 76,550 45,930 $51,350 Deductible C C A ($000) 1976 $13,414 1977 $12,408 $ 61,809 1978 $11,478 $ 57,174 $157,887 1979 $10,617 $ 52,886 $146,046 $168,127 1980 $ 9,821 $ 48,919 $135,092 $115,517 $176,888 Tax Loss ($000) 1976 $ 2,683 1977 $ 2,482 $ 12,362 1978 $ 2,296 $ 11,435 1979 $ 2,123 $ 10 ,577 1980 $ 1,964 $ 9,784 $ 4,728 $ 23,357 $31,577 63,654 $29,209 $33,625 94,750 $27,018 $31,103 $35,378 $117,877 $304,366 1) C.M.H.C., Canadian Housing Statistics, 1976-1980. 2) Clayton Research Associates, Tax Expenditures - Housing, p. B./2. 3) Assumed to be 60 per cent of M.U.R.B.1 certificates, based on results of Clayton Reasearch Associates study. 4) C.M.H.C., 1975 - Table 90; 1980 - Table 100. - 7 -of the taxpayer's rental properties combined is limited to the amount, if any, of his net income minus losses on those properties computed before deducting capital cost allowance" (Harris, 1979: 223). Thus, the incremental C C A benefit of a M.U.R.B. is dependent on the difference between the available C C A claim and the remaining aggregate rental income of the investor after deducting operating and interest expenses (the C C A that could be claimed on a non-M.U.R.B.). In this analysis, it is assumed that half of the total C C A deductions would have been claimed in the absence of M.U.R.B.Is, offsetting positive rental income flowing from rental properties. Offsetting the estimated federal tax losses in the future wi l l be the federal tax revenue resulting from any recapture of the C C A at the time of sale of the M.U.R.B./properties. Since 1972, the Income Tax A c t requires that any C C A claimed during an investment which is greater than the actual economic depreciation of the asset be recaptured upon sale and taxed as ordinary income. This "excess" C C A is effectively an interest-free loan provided by the government during the holding period of the investment. The net cost over time of the incremental C C A claimed under the M.U.R.B. program is therefore an interest expense to the federal government of this C C A loan. With interest rates for government borrowings at the 15 per cent level, and assuming a l l the incremental C C A w i l l be recaptured, the annual federal interest expense of the above foregone tax revenue is approximately $46 m i l l i o a In the context of the Vancouver rental market, which is the subject of the analysis in this paper, 448 M.U.R.B. projects were started during the period 1975 through - 8 -May 31, 1981. If each of these properties contained an average of 20 suites, a total of about 9,000 multiple family rental units in the c i t y would be presently under the M.U.R.B. program. This represents approximately 10 per cent of the current stock of multiple family dwellings.*' The next section of this paper presents a theoretical framework for analysing the impact of the M.U.R.B. program on Vancouver's rental housing market. Two models w i l l be presented. The first is a valuation function for apartment buildings, while the second is a model of the determinants of multiple family land values - 9 -3.0 THEORETICAL FRAMEWORK T h i s s e c t i o n o f t h e p a p e r p r e s e n t s a t h e o r e t i c a l f r a m e w o r k f o r a n a l y z i n g t h e i m p a c t o f t h e M . U . R . B . p r o g r a m o n V a n c o u v e r ' s r e n t a l h o u s i n g m a r k e t . T h e t h e o r e t i c a l d i s c u s s i o n b e g i n s w i t h a g r a p h i c a l a n a l y s i s o f t h e e x p e c t e d i m p a c t o f M . U . R . B . / l e g i s l a t i o n o n t h e s u b - s e c t o r s o f t h e m u l t i p l e f a m i l y h o u s i n g m a r k e t u n d e r v a r i o u s a s s u m p t i o n s . T h e c o n c e p t o f e f f i c i e n t m a r k e t s i s t h e n e x a m i n e d , f o l l o w e d b y a d i s c u s s i o n o f c a p i t a l i z a t i o n a n d a r e v i e w o f t h e l a n d p r i c e m o d e l s w h i c h h a v e b e e n f o r m u l a t e d t h r o u g h p r e v i o u s e m p i r i c a l r e s e a r c h . 3.1 THE MULTIPLE FAMILY HOUSING MARKET W i t h i n t h e m u l t i p l e f a m i l y h o u s i n g m a r k e t , t h e r e a r e t h r e e g r o u p s w h o w o u l d r e a c t t o o r b e n e f i t f r o m t h e i n t r o d u c t i o n o f t h e p r e f e r e n t i a l t a x t r e a t m e n t a s s o c i a t e d w i t h M . U . R . B . ' s - l a n d o w n e r s , i n v e s t o r s a n d r e n t e r s . In t h i s c o n t e x t , d e v e l o p e r s m e r e l y a c t a s t h e m i d d l e m e n b e t w e e n l a n d o w n e r s a n d i n v e s t o r s , t h u s t h e y c a n p l a y e i t h e r o f t w o r o l e s i n t h e m a r k e t , d e p e n d i n g u p o n w h e t h e r t h e y o w n e d t h e l a n d p r i o r t o d e v e l o p m e n t , o r w e r e e x p e c t i n g t o h o l d t h e p r o p e r t y o v e r t h e l o n g t e r m a f t e r c o m p l e t i o n . T h e f o l l o w i n g p a r a g r a p h s r e v i e w t h e i m p a c t w h i c h M . U . R . B . / l e g i s l a t i o n s h o u l d h a v e o n e a c h o f t h e t h r e e s u b - g r o u p s w i t h i n t h e m u l t i p l e f a m i l y h o u s i n g m a r k e t , u n d e r - 10 -various assumptions concerning the elasticity of the supply and demand schedules for each of these groups. Case 1; General Case In the general case, the supply arid demand schedules for landowners, investors and renters are a l l neither perfectly elastic nor perfectly inelastic. Under these conditions, the introduction of M.U.R.B. legislation should cause a shift in the demand schedule of landowners (as shown in Figure 1), resulting in higher prices for multiple family sites and an increased supply of such sites available for development. Similarly, the demand schedule of apartment block investors should shift upward in response to the special M.U.R.B. tax benefits, resulting in higher apartment block prices and higher production of units. This increase in supply of apartment units w i l l cause a corresponding shift in the supply schedule for renters, who w i l l thus benefit in the form of lower rents. Landowners Investors Renters FIGURE 1 - 11 -In the above case, because of the slope of the demand and supply schedules, the increase in the price of both land and apartment blocks should be less than the actual present value of the M.U.R.B. tax shelter benefits to either landowners or investors. Furthermore, i f there is substitution in the production function for apartment blocks, l e . if the increase in demand induces substitution of capital for land and higher density apartment blocks are produced, the supply curve for investors should be more elastic than that for landowners, and the increase in apartment block prices should be lower than the increase in land prices as a result of the M.U.R.B. program, assuming of course that the slope of both demand curves is equivalent. i Case 2; Perfectly Elastic Investor Demand In this case, the demand curve for investors is perfectly elastic, Le. it is horizontal This would be the case where there is a totally efficient apartment investment market, where an increase in expected profits causes an equivalent increase in the price of apartments (see Figure 2). The shape of the supply schedule for investors under such conditions would have no effect on the magnitude of the increase in price of apartment blocks, although it would certainly affect the magnitude of increased production of apartments as a result of the shift in demand. - 12 -Landowners Investors Renters FIGURE 2 The impact of the M.U.R.B. on landowners and renters in this case should not vary from Case 1, since i t does not follow that their demand curves would also be perfectly elastic. Case 3: Inelastic Land Supply If the multiple family land supply function were perfectly inelastic, a shift in the demand schedule for landowners as a result of higher demand for sites by investors would induce a proportionate increase in prices of such land, and no additional land would be made available for the production of multiple family housing (see Figure 3). However, if there is substitution in production, the higher demand for apartments by investors would result in production to higher densities of existing multiple family sites, through demolition of structures not presently representing f u l l capacity on these sites. Thus, the supply curve for - 13 -investors would be flatter than the land supply curve; the actual slope of this curve would of course depend upon the magnitude of substitution and hence the shape of the production function. FIGURE 3 Case 4; Inelastic Land Supply and Perfectly Elastic Investor Demand If the supply of multiple family land were inelastic and the demand for apartment blocks by investors were perfectly elastic, the impact of M.U.R.B. legislation should be as shown in Figure 4. No additional land would be made available for production, and land prices should rise at least by the amount of the present value of the M.U.R.B. benefits. If there is substitution in production, more sites should be redeveloped to higher densities, but to a lesser extent than in Case 3, since more of the M.U.R.B. tax benefits w i l l go into higher prices because of the f l a t investor demand curve. Renters should s t i l l benefit under these conditions, but again to a lesser degree than in Case 3. The magnitude of their benefit would - 14 -depend upon the slope of the investors' supply curve, and hence on the degree of substitution in production. Landowners Investors Renters FIGURE * Case 5: Inelastic Land and Apartment Supply Figure 5 illustrates the impact of M.U.R.B. legislation where both the land supply and apartment supply functions are inelastic. Under these circumstances, no increase in apartment production would result from the introduction of M.U.R.B.!s, and land and apartment block prices would rise by the equivalent of the present value of the M.U.R.B. benefits. There would be no benefits accruing to renters because of M.U.R.B.'s; however, it does not follow that the renters supply curve is inelastic, since there can be tenure changes in existing multiple family properties from condominium to rental. - 15 -p, h -FIGURE 5 The conditions necessary for this case to be true, however, are not very realistic. In order for apartment supply to be perfectly inelastic, there can be no substitution of capital for land in the production of apartments. This implies that a l l existing multiple family sites are built to capacity, which is clearly not the case in many metropolitan areas, and Vancouver is no exception. It is hoped that the research in this paper wi l l provide some evidence as to the filtering of the M.U.R.B. tax shelter benefits through to the various sub-groups of the multiple family housing market. The following paragraphs review previous work which has been done in real estate and other capital markets relating to these concepts. - 16 -EFFICIENT MARKETS Considerable research has been undertaken to test the efficiency of competitive speculative markets, particularly with respect to the stock market (Fama, 1970X An efficient market has been defined as one in which current market prices "fully reflect" available information, and it is assumed that such information is fully and rapidly capitalized into prices. Fama has distinguished three types of market efficiency: • weak form - where market prices are a reflection of historical price information; • semi-strong form - where market prices fully reflect public information, e.g. dividend declarations; • strong form - where market prices take into account a l l available information, even that held by those with special knowledge, such as professional speculators or management. The empirical research of stock market prices which has been done to test the efficient markets model has generally supported both the weak and semi-strong concepts of efficiency (Fama, 1970). However, strong form efficiency has not held up well, as seen in the work of Figlewski, who found that "when there is a wide range of forecasting ability or a diversity of expectations among the participants, the market may deviate relatively far from efficiency" (1978: 597X - 17 -Efficiency in the context of real estate markets is to date a relatively untested concept, although i t has been argued that numerous characteristics of real estate markets preclude their efficient operation, characteristics such as: • the local orientation of real estate markets; • a lower incidence of transactions for specific properties; • the uniqueness and lack of comparability of various parcels of real estate vis-a-vis different common stocks; • the importance of financing and the specialized nature of some real estate financing techniques; • the lack of sophistication of investors; • a dearth of disciplined analysis of future events and the use of crude rule-of-thumb techniques; • the divergence between expectations and actual accomplishments of participants, and their widely varying investment objectives; • the extreme volatility in construction activity, which leads to sharp swings in vacancy factors and related short-term cash flow yields (Roulac, 1976). Although real estate markets do suffer from these deficiencies, i t nevertheless seems reasonable that prudent investors would compare expected investment returns on real estate assets to expected returns on other capital assets, and that public information, such as the announcement of the M.U.R.B. program in 1974, would be reflected in subsequent transactions prices of both multiple family zoned land, whose future cash flow benefits would be considerably enhanced, as well as the transactions prices of M.U.R.B. properties once built. Although this paper wi l l not test the speed of the market's reaction to M.U.R.B. legislation, i t w i l l nevertheless seek some evidence of semi-strong form efficiency to the extent that the change in expected cash flows associated with M.U.R.B. properties caused a proportionate increase in their values relative to comparable non-M.U.R.B./ properties of similar risk, and that investors in M.U.R.B. properties earn equivalent rates of return to investors in non-M.U.R.B. properties in the same risk class. CAPITALIZATION The empirical research which has been undertaken on the concept of capitalization does have some overlap with the efficient markets concept, in the sense that it is measuring the extent to which (although not the speed with which) market values of assets have capitalized changes in expected future costs or benefits. Work by Tullock (1975) suggests that changes in government regulation which create preferential benefits for certain groups (e.g., owners of taxi cab medallions) effectively create windfall gains for persons already in the group, since these benefits are competed away and hence become capitalized into the value of the - 19 -commodity by other market participants trying to obtain it. As Krueger has pointed out in her study of import licenses in India, the efforts of persons trying to obtain the special benefits associated with import licenses actually change the optimal allocation of goods in the domestic economy, since resources are diverted from other sectors in the attempt to attain those "rents". Hence, as argued by Posner, the competition to obtain special rights of a monopolistic nature results in the transformation of potential monopoly profits into social costs (1975: 807X The property tax literature lends support to the concept of capitalization of future benefits into real estate values. Hamilton's (1976) study of the effects of interjurisdictional differences in tax rates supported previous work (Mieszkowski, 1969, 1972) on the capitalization of varying rates of property taxation into property values across localities, although he demonstrated further that it is these tax rate differentials relative to public sector benefits which should be capitalized rather than just the tax differentials themselves. His model reflects an arbitrage process whereby the fiscal surplus or deficit created by the difference between actual tax rates and the level of public sector benefits results in proportional variations in the values of properties owned by high and low income households. He concludes, among other things, that in communities containing a variety of high-value and low-value dwellings, land value differentials between those properties w i l l exactly reflect the present value of their fi s c a l surplus differentials. Further work on property taxation by Mills (1981) indicated that the nature of property taxes does have an effect on the land-use allocation of land, as a result of the impact of the tax on the income streams of different land uses. For example, a - 20 -property tax on the value of land rather than the income generated from that land w i l l favour the construction of projects with earlier income streams, since the effective discount rate or required rate of return is increased by the property tax on vacant land Thus, the research relating to the capitalization concept has shown that some real estate markets have responded to differential future costs and benefits and to changes in public regulation, by bidding up the prices of capital assets to yield returns similar to those which existed before the change occurred. In the context of this paper, the impact of the M.U . R . B . program on the value of M . U . R e -certified apartment buildings can be analyzed through a valuation model, in which the value of a real estate investment is equal to the present value of its future g after-tax cash flows. In the form of a before-financing framework: V n 0{ - ( O j - n + i = 1 (1+k)1 where V market value of the property; 0. net operating income in year i ; C capital cost allowance in year i ; - 21 -n e t s a l e s p r i c e o f t h e p r o p e r t y a t t h e e n d o f t h e i n v e s t o r ' s h o l d i n g p e r i o d ( i = n ) ; T t a x e s r e s u l t i n g f r o m s a l e o f p r o p e r t y ; n t m a r g i n a l t a x r a t e ; k m a r k e t r a t e o f r e t u r n . T h e o p e r a t i n g f l o w s r e c e i v e d e a c h y e a r d u r i n g t h e i n v e s t o r ' s h o l d i n g p e r i o d ( i = 1,. . . , n ) a r e e q u a l t o t h e n e t r e n t a l i n c o m e a f t e r o p e r a t i n g e x p e n s e s , Ch , m i n u s t a x e s ( d e t e r m i n e d b y t h e t a x a b l e i n c o m e , 0. - C j , a n d t h e t a x r a t e ) . T h e f i n a l c a s h f l o w a t t h e e n d o f t h e h o l d i n g p e r i o d i s t h e a f t e r - t a x p r o c e e d s r e s u l t i n g f r o m t h e s a l e o f t h e p r o p e r t y . If a n i n v e s t o r a c q u i r e s a p r o p e r t y f o r a p r i c e e q u a l t o V , h i s e x p e c t e d r a t e o f r e t u r n , r , i s e q u a l t o k , t h e r e t u r n r e q u i r e d i n t h e m a r k e t g i v e n t h e r i s k l e v e l o f t h e i n v e s t m e n t . I f , h o w e v e r , t h e p r i c e i s l e s s t h a n V , r w o u l d b e g r e a t e r t h a n k . W i t h a l l f l o w s h e l d c o n s t a n t , t h e r e i s a n i n v e r s e r e l a t i o n s h i p b e t w e e n t h e a c q u i s i t i o n p r i c e o f a p r o p e r t y a n d a n i n v e s t o r ' s e x p e c t e d r a t e o f r e t u r n . A s d i s c u s s e d e a r l i e r , t h e p u r p o s e o f t h e M . U . R . B . p r o g r a m w a s t o i n c r e a s e t h e a l l o c a t i o n o f r e s o u r c e s t o m u l t i p l e f a m i l y r e n t a l h o u s i n g a n d s t i m u l a t e c o n s t r u c t i o n b y i n c r e a s i n g t h e r a t e s o f r e t u r n o f i n v e s t o r s i n p r o p e r t i e s u n d e r t h e p r o g r a m . In t e r m s o f t h e v a l u a t i o n f r a m e w o r k , t h e M . U . R . B . / p r o g r a m , b y r a i s i n g C. i n t h e e q u a t i o n , c a u s e s t h e t a x a b l e i n c o m e o f t h e i n v e s t m e n t t o b e n e g a t i v e a n d t h e r e b y i n c r e a s e s t h e a f t e r - t a x c a s h f l o w s t o t h e M . U . R . B . i n v e s t o r . If t h e p r i c e s o f t h e s e - 22 -properties were not affected by being in the program, the r of M.U.R.B. investments would be greater than k (the rate of return expected on other investments of equivalent risk), and investors would be encouraged to allocate more funds to rental housing. However, in competitive real estate markets, there is l i t t l e reason to believe that the market value of M.U.R.B. properties would be unaffected by the tax subsidies available under the program. If investors recognize and respond to the additional cash-flow benefits, they should increase their demand for these properties and bid up the price of the investments. Acquisition prices would rise until r equals k. Real estate investors should not be able to earn abnormal or superior returns from the benefits of publicly-known tax incentive programs. Real estate markets would be expected to capitalize into property values the tax benefits of this program by competing away the excess cash flow benefits until the rate of return of M.U.R.B. investors is the same as the rate expected on other investments of similar risk. Thus, the benefits of the program would accrue to existing owners at the time of its introduction. The analytical framework for assessing the impact of the M.U.R.B. program on land values (as apart from completed M.U.R.B. apartment buildings) w i l l be addressed in the next subsection of this paper. - 23 -LAND PRICE MODELS There have been numerous empirical investigations of the determinants of urban land values, but there are four studies which seem most relevant to the topic of this paper - Brigham (1965), Adams (1968), Witte (1975), and Diamond (1980X A l l of these studies examine residential land value determinants, albeit for single family dwellings rather than medium or high density residential properties. Brigham's study is the most pertinent to the present analysis, since it is a cross-sectional study of residential land values within a single metropolitan area. The underlying model in his study assumes that the value of an urban site is functionally related to its accessibility to economic activities, to its topography, to its present and future use, and to certain historical factors that affect its utilization (1968: 325). He employed multiple regression to analyze a sample of land values by census tract within the Los Angeles metropolitan area in 1964. His estimation of residential land values was able to explain 79 to 89 per cent of variations in price, where the independent variables included accessibility to employment opportunities and the central business di s t r i c t , the level of median family income, a measure of crowding, average value of dwellings in the neighbourhood, and a dichotomous topography dummy variable. The major difficulties he faced were the highly collinear nature of some of the data, and the instability of some of the coefficients. Adams et al (1968) also developed an intrametropolitan model of the determinants of peripheral land value, using a series of over 1,100 transactions in Philadelphia - 24 -between 1945 and 1962. Their empirical results showed that variation in the price of residential sites during this period could be 60 per cent explained by distance from the central business di s t r i c t , distance to public transportation, location on a major ar t e r i a l , zoning, and "state of the land" variables (e.g. servicing availability). However, the authors do not employ any measures of income or population over the 17-year period, factors which one would expect to have an impact on residential land values, particularly at the periphery of an urban area. Witte (1975) develops and estimates a derived demand model for single family residential sites, in an attempt to explain differences in residential land values across SMSA's from 1966 to 1969. Her model, which explained 78 per cent of the variation in average prices per square foot of residential sites across SMSA's, suggests that average residential site values are determined primarily by the average size of sites in various urban areas, the value of agricultural land, population density, current annual family income levels, and the rate of change in population (as a proxy for households). It is interesting to note that average site size is a significant determinant, possibly a reflection of economies of scale or decreasing marginal returns as site sizes rise above what is considered "essential" for the average homebuyer. The absence of location or amenity variables as determinants of residential land value is explained by the very aggregate nature of her data (e.g. average price of land in an SMSA). Further work on intraurban land values was done recently by Diamond, who utilized bid-price theory to strengthen the empirical relationship between land prices and locational amenities (1980: 32). His results were similar to previous studies in - 25 -terms of the importance of proximity to the central business district and public transit. However, his amenity variable measures differed somewhat from those used in other studies - they included crime rates, particulate pollution levels, distance to a lake, and topography, a l l of which were important determinants of land value ( R 2 = 0.75). In the context of the present analysis, the theoretical framework for estimating the determinants of multiple family zoned (RM-3)^ land values is a derived demand model similar to that employed by Witte (1975), since the value of multiple family zoned land w i l l be derived from the demand for multiple family housing. Since land is a residual in the development process, we would expect the value of land to vary with the expected future costs and benefits associated with multiple family housing, which in turn will be affected by broad demand and supply variables influencing the rental market. The basic land residual equation states that land value is equal to the difference between the selling price of the lot fully developed and the cost to construct the building on the site: Land Value = (Selling Price - Construction Costs) The selling price of the fully developed site w i l l be a function of the net income accruing to the property, the investor's required rate of return, C C A deductions, the investor's marginal tax rate, and the expected capital gains accruing to the property over the investor's holding period. The valuation function described in Section 3.2 represents the selling price portion of the land value equation above, - 26 -while construction costs are deducted from this selling price to yield the residual land value. Thus, using the net cash flow equation, residual land value is equal to: Oj -(OJ - C i ) t i = 1 (1+k)1 S„ - T n n (l+k) r C C The following paragraphs break, down the land value equation into the various demand and supply variables which w i l l affect the net cash flows accruing to multiple family zoned sites, and hence the residual value of such sites. The dependent variable in this model of the determinants of multiple family land value is the price of a multiple family zoned site (P g), which is a function of both d s the demand for (Q ) and the supply of (Q ) such sites, as shown in (1): (1) P s = f ( Q d , Q s ) o The quantity demanded of multiple family zoned sites w i l l be a function of the net cash flows accruing to the developer, including the income generated from the property ( I ), the cost of construction ( C C ), and the price of the land (P ), as shown in (2): (2) Q d = g( I, CC, P s ) - 27 -The income generated from multiple family housing w i l l be a function of numerous cash flow variables: the potential rents attainable by any specific property ( R ), the cost of debt ( i ) , apartment vacancy rates ( VR ), the cost of equity or required rate of return ( k ), which w i l l determine the present value of the future income stream to the investor, and any special tax benefits available, in this case the M.U.R.B. benefits. A l l of these variables w i l l affect the holding period cash flow of a multiple family property, as shown in (3): (3) I = h( R, i , VR, k, MURB ) Thus, I represents the entire bracketed expression in the LV cash flow equation presented above. The rent component of income can be divided into two functions - current rents ( R c ) and expected future rents (R^ ). Current rents w i l l be a function of general market rent levels per unit (R ), the number of units which can be built on the r m site ( UNITS ), market vacancy rates ( VR ), and the location of the site ( L ): (4) R c = j ( R m , UNITS, V R , L ) Future rents ( R^ ) w i l l be a function of growth in the number of non-family households (A. HH ), who are the primary demanders of multiple family housing, growth in future income levels of non-family households ( A Y ) — under the assumption that the marginal propensity to consume housing is positive ~ and a supply constraint ( STARTS ), which w i l l affect the level of future competition for -28-multiple family housing and hence future rents. Growth in household income •X-( A Y ) can be specified either in nominal ( A Y ) or real ( A Y ) terms. The equation, which represents a growth function, is shown as (5) : (5) R f =m ( Z i HH,A.Y , STARTS) STARTS are expected to have a negative influence on land value since increased future competition implies lower future rent levels attainable by the developer, and hence lower residual land value. On the other hand, HH, UNITS and A Y are expected to have a positive influence on land value, since as they rise, so does the demand for multiple-family housing and hence future rent levels. The nominal capitalization rate or required rate of return on multiple family properties, k, has three components: inflation (1V), the real interest rate ( i ) or return on risk-free capital assets, and the excess return or risk premium required to invest in multiple family properties ( ER ). This relationship is shown in (6), while (7) and (8) show the derivation of ER , which is simply the real capitalization a rate ( k ) minus i . (6) k = 1f + i * + ER* a (7) k = k* + T f (8) E R* = k*- i * d - 29 -The real capitalization rate is equal to the nominal capitalization rate ( k ) minus If" , where the nominal capitalization rate represents the overall rate of return on typical multiple family investment properties, Le. gross income divided by selling price. Turning to the supply side of equation (1), the quantity of multiple family sites supplied w i l l be a function £(9)j of the price of sites ( P g ), the size of sites ( SS ), and zoning ( Z ). (9) Q s = m( P s, SS, Z) The zoning variable w i l l constrain the supply of multiple family land, since unless a site is included in the appropriate zoning category, it is not available to be developed as multiple family housing. The size of sites affects supply in the sense that a large number of small sites would prevent economies of scale in develop-ment and hence the effective supply of sites would be reduced. By substituting a l l of the supply and demand equations into (1), one obtains: (10) P g = f ( R m , UNITS, L, A Y * , A HH , STARTS, i , VR, ER*, MURB, CC, SS, Z) cL - 30 -By dividing through by SS and converting to real terms where appropriate, the reduced theoretical model of multiple family land values, where the dependent variable is the real price per square foot of sites, becomes: (11) P*/SS = f ( R * UNITS, L, A Y*, A HH, STARTS, i * , O i l l j VR, ER*, MURB, CC*, Z) 3, In the context of the land residual equation discussed previously, LV = ( SP - C C ) 4 a l l of the variables except C C in equation (10) wil l determine the selling price or value of a fully developed site. Thus, P g = ( SP - C C ) and from (11) P s / S S = ( SP - C C )* /SS Equation (11) is thus the land model to be tested in the empirical section of this paper, where the c r i t i c a l concern wi l l be the significance and sign of the MURB variable in the land value equation. - 31 -4.0 DATA BASE The major portion of the data for this research was collected during the summer and f a l l of 1980; i t was later supplemented in the spring and summer of 1981. The primary sources of data were the B.C. Assessment Authority, the B.C. Land Title Office, Canada Mortgage and Housing Corporation, and Statistics Canada. Two separate samples were collected: a sample of sales transactions of M.U.R.B. apartment buildings and a matching set of non-M.U.R.B.iapartment buildings (the "RESALES" f i l e ) , and a sample of multiple family land sale transactions (the "LANDSALES" file). The RESALES sample wi l l be used to estimate the apartment block valuation function presented in Section 3.2, while the LANDSALES sample wi l l be used to estimate the land price model presented in Section 3.3. The characteristics of the data contained in each of these files w i l l be discussed in turn in the next two subsections. 4.1 M.U.R.B. RESALE SAMPLE A sample of 46 apartment block transactions in the City of Vancouver in 1979 and 1980 were identified through B.C. Assessment Authority records. This sample consists of 7 M.U.R.B. apartment buildings and 39 matching non-M.U.R.B apart-ment buildings sold during the same time period. These non-M.U.R.B. properties are similar to the M.U.R.B.'s in terms of number of suites in the building, location within the city and holding p e r i o d . ^ Although the non-M.U.R.B. buildings in the - 32-matching sample do vary in age, and in a l l cases are older than the M.U.R.B.'s, they are nevertheless considered comparable in terms of total investment risk. For each of these apartment blocks in the sample, information was obtained from the B.C. Assessment Authority and B.C. Land Title Office concerning the physical characteristics of the property (e.g., number of suites, lot size, number of storeys, etc.), construction and land costs, and the rental incomes earned during the investor's holding period. A complete list of the data collected on a variable-by-variable basis is included as Appendix Table A - l . The data were sufficient to allow for an accurate measurement of the actual operating cash flows and capital gains received by owners of both M.U.R.B. and non-M.U.R.B. properties, as well as an analysis of the determinants of the market prices of these properties. Appendix Table B- l contains the descriptive statistics for a l l variables in this sample, which includes for each variable the minimum value, maximum value, mean and standard deviation. The average sales price in the sample is $785,220, the average building size 27 suites, the average lot size 10,566 square feet, and the average age 26 years. LAND SALE SAMPLE A sample of 115 arms length sales transactions of RM-3 zoned land which occurred in the City of Vancouver from 1972 to 1978 were identified through the B.C. Assessment Authority and B.C. Land Title Office records.** The site-specific - 33 -information for each transaction includes the lot size, location, selling price and date of sale, on a quarterly basis. The location variable is disaggregated into four sub-areas: Vancouver Number of Sub area Observations West End 10 Kitsilano 33 Marpole 2 East Vancouver 70 115 In addition to the site-specific information on the land sales, the 90 variables in the "LANDSALES" data fil e include measures, ^  in varying forms, of a l l of the determinants of multiple family land values identified in the theoretical model (refer to Appendix Table A-2). Data were gathered from Statistics Canada and Canada Mortgage and Housing Corporation on measures of population, income, unemployment, interest rates, housing construction activity, rent levels, construc-tion costs, vacancy rates, and various measures of inflation. The existence of M.U.R.B. legislation is specified in this data set as a dichotomous dummy variable with a value of 0.0 during the period preceding the introduction of the M.U.R.B. program in 1974 (0.0 for sales during the first quarter of 1972 through the fourth quarter of 1974), and a value of 1.0 during the period following the legislation. Since the 1972 to 1974 period was one characterized by a slowdown in - 34 -apartment construction activity, it was diff i c u l t to find a large number of land transactions during that period. Nevertheless, 19 transactions were identified from 1972 to 1974, with the remaining 96 transactions in the sample occurring after the M.U.R.B. program was introduced. This 5 to 1 ratio of non-M.U.R.B. to M.U.R.B. transactions in the sample is not considered large enough to bias the data results. As Appendix Table B-2 indicates, the average real sales price (indexed by the general CPI for Vancouver) of the land transactions is $10.81 per square foot, while the average lot size is 9,285 square feet. - 35 -5.0 ESTIMATION OF APARTMENT VALUATION FUNCTION This section of the paper presents two methods for analyzing the impact of the M.U.R.B. program on the resale values of M.U.R.B. apartment buildings. These analyses were done using the matching sample in the "RESALES" fi l e which, as discussed, contains 7 M.U.R.B. properties and 39 matching non-M.U.R.B. properties, a l l of which have holding periods terminating in 1979 and 1980. 5.1 CAPITALIZATION In order to measure the extent of the capitalization of M.U.R.B. tax shelter benefits into market values of M.U.R.B. properties, a valuation function is estimated from the "RESALES" sample using multiple regression analysis. This valuation function shows the relationship between the selling price of an apartment block and its physical and financial characteristics, such as age, number of suites, gross income, and cost of debt. Numerous runs on the dependent variable (selling price) were made using various combinations of the variables in the data f i l e in an attempt to find the best f i t of variables which fully represents the determinants of apartment block value, and which best explains the variation in prices of apartment blocks, in both a statistically significant and intuitive sense. Table 2 presents the best estimation of the apartment block valuation function, which explains 84.5 per cent of the - 36 -Table 2 APARTMENT BLOCK VALUATION FUNCTION SP = 481600. + 10.831 GI + 63526. MURB - 13758. I - 452.32 AGE (2.084)* (14.342)* (2.082)* (-1.239) (-1.864) R 2 = .845 F = 51.202 SE = 293010. n = 46 = sales price MURB = 0-1 variable with 1 = M.U.R.B. = gross income at time of sale AGE = number of years since construction = interest rate statistics in parentheses, coefficients significant at .05 l e v e l - 37 -variation in apartment block prices. According to this equation, the price of an apartment building w i l l be determined by its gross income, the existence of M.U.R.B./tax shelter benefits, the cost of debt (the weighted average interest rate on a l l financing at the time of sale), and the age of the building; as expected, the former two variables have a positive and significant effect on value (at the .05 level), while the latter two have a negative effect on value. MURB is a dichotomous dummy variable, with a value of 1.0 for M.U.R.B. properties and 0.0 for non-M.U.R.B. properties. In the context of the theoretical apartment block valuation function discussed in Section 3.3, GI in the estimated equation is a measure of Oj , MURB is a measure of C. , AGE w i l l have an impact on operating expenses and hence CX , and the cost of debt, I, represents one component of the investor's required rate of return, k. The disposition term does not enter into the estimated equation, since there is no way of measuring an investor's expectations concerning either his optimal holding period or the anticipated selling price of the property. Presumably, such expectations are part of the 15.5 per cent of selling price variations which cannot be explained by the estimated equation. These regression results clearly show that the presence of M.U.R.B. benefits in an apartment investment do have a significant impact on value. Given the magnitude of the M.U.R.B. coefficient, M.U.R.B. investors in this sample apparently paid an average premium of $63,526 to acquire these properties. At the 5 per cent level of significance, this represents a confidence interval of $63,526 + $59,800. The actual - 38 -value of the M.U.R.B. benefits to an apartment block investor can be calculated in terms of the following present value equation: PV MURB C C A MURB i = 1 ( 1 + r ) l Recapture ( l + r ) n S P M U R B " S P n o n M U R B ( l + r ) n where PV,, I i r i n = the present value of the M.U.R.B. tax shelter MURB . benefits. ^ ^ M U R B = t' i e m a r 8 ^ n a ^ C C A deductions allowed on a M.U.R.B. building over and above what would be available on a non-M.U.R.B. building. Recapture = the recapture of the marginal M.U.R.B. C C A deductions upon disposition of the property. S P M i m n - SP , , t , r , n = the sales premium which the investor MURB nonMURB . £ , .. . . .. .. „ _, receives because of the remaining M.U.R.B benefits available to the purchaser of his building. r = the investor's discount rate. n = the investor's holding period. Based on an average depreciable basis of the properties in the sample of i o $560,000, a C C A rate of 5 per cent (all are Class 31 properties), a marginal tax 13 rate of 55 per cent, and a discount rate of 12 per cent, the present value at the - 39 -time of purchase of the future M.U.R.B. tax shelter benefits, assuming a seven-year holding period, is $61,972. This is extremely close to (and lower than) the M.U.R.B. premium estimated in the equation; however, it does not take into account the sales premium on disposition, since this is not possible to measure. This is nevertheless strong evidence that M.U.R.B. subsidies are fully capitalized into the market values of M.U.R.B. properties. RATES OF RETURN TO M.U.R.B. VS. NON-M.U.R.B. INVESTORS In order to determine whether M.U.R.B. investors actually achieved rates of return superior to those of non-M.U.R.B. investors, the seven M.U.R.B. apartment properties identified as having complete holding periods by the end of 1980 (Le., they were built, rented and sold to investors by that year) are matched with seven comparable non-M.U.R.B. apartment properties with similar holding periods. Again, comparability was defined in terms of size of building and location. To eliminate the influence on the rates of return of specific financing arrangements by investors, the before-financing rates of return are calculated recognizing the income, capital appreciation, and, i f applicable, the tax shelter benefits accruing to each investment in the sample. The returns are after-tax, assuming a marginal tax rate of 55 per cent. The comparative rates of return for the M.U.R.B. and non-M.U.R.B. properties are presented in Table 3. The average returns earned on the two groups of real estate investments are essentially equivalent - 12.8 per cent for the M.U.R.B. properties - 40 -Table 3 RATES OF RETURN: M.U.R.B. VERSUS NON-M.U.R.B. APARTMENTS Average Rate of Return Standard Deviation M.U.R.B. 12.8% 5.4 Non-M.U.R.B. 13.2% 8.0 t-Value .13 Number of Observations 14 and 13.2 per cent for the non-M.U.R.B. properties. The following statistical test supports the hypothesis that the means of these two samples are not significantly d i f f e r e n t : 1 5 Let Y = the mean return on M.U.R.B. properties Z = the mean return on non-M.U.R.B. properties Let ( Y - Z ) be an estimator of u^ - U2 = -0.4. Let 2 _ s ( Y - Z ) be the estimator of the variance of the sampling distribution of ( Y - Z*) where: s 2 ( Y - 1) = s 2 1 + I n l + n 2 and where s is the estimator of the common variance: c2 2 s + s 2 s 2 = n l + n 2 " 2 2 Therefore s = 7.763 s 2 ( Y - Z ) = 2.218 - 42-hence Since The hypothesis that u where Therefore, since the condition holds that since s ( Y - Z ) ='1.489 t (.975 ; 12) = 2.179 ( = .05) lu, holds where: A i ^ ( Y - Z ) ^  A 2 A{ = -t (0.975; 12) s ( Y - Z ) A 2 = t (0.975 ; 1 2 ) s ( Y - Z " ) A j = -2.179 (1.489) =-3.24 A 2 = +3.24 A 1 ^ ( Y - Z ) A 2 -3.24 ^ -0.4 =^ 3.24 - 43-These results indicate that M.U.R.B. investors do not necessarily receive a higher rate of return, but rather earn the same returns as are experienced on other apartment investments of similar risk. Hence, the proposition that superior rates of return on M.U.R.B. properties w i l l shift the allocation of resources into the rental housing sector is not supported, since the program does not in fact create superior rates of return for investors. This occurs essentially because the market competes away any special profits expected from M.U.R.B. properties and the future tax benefits associated with M.U.R.B.'s become fully capitalized into higher apartment transactions prices, as supported by the empirical results in Section 5.1. Thus, the apartment valuation and comparable rates of return results yield the same conclusion — M.U.R.B. apartment block investors do not appear to have earned preferential ex ante rates of return as a result of the M.U.R.B. program. There are two groups other than investors who may have benefitted from the M.U.R.B. program - landowners and renters. The next section of this paper tests whether it was landowners who benefitted by estimating the impact of the legislation on multiple family land values. - 4 4 -6.0 ESTIMATION OF MULTIPLE FAMILY LAND PRICE MODEL The objective of this analysis of the determinants of multiple family land value is to find an estimation of the land price model which fully represents those factors which influence land values, so that the estimated impact of the M.U.R.B. variable on land values w i l l be unbiased. To this end, careful selection of variables for inclusion in the regression equation was made, both in terms of the actual measure of specific variables in the theoretical model and in terms of how those variables were represented in empirical terms. The structure of the M.U.R.B. variable as a 0-1 dummy, which is 0.0 during the pre-1975 period and 1.0 thereafter, meant that any time trend existing in other independent variables would have to be eliminated in order to clearly identify the M.U.R.B. impact. Hence, a l l variables are specified in real terms (where applicable). Before discussing the regression results, the following paragraphs describe the 12 variables which have been included in the preferred estimation of the theoretical model. 6.1 DESCRIPTION OF VARIABLES 6.1.1 Location Variables As previously discussed, the two location variables which were significant in estimating multiple family land values (West End and East Vancouver) - 45 -a r e 0-1 d u m m y v a r i a b l e s i n d i c a t i n g w h e t h e r o r n o t t h e l a n d t r a n s a c t i o n t o o k p l a c e i n t h a t s u b - a r e a o f t h e c i t y . ^ S i n c e t h e W e s t E n d d i s t r i c t i s m u c h c l o s e r t o V a n c o u v e r ' s c e n t r a l b u s i n e s s d i s t r i c t , a n d h e n c e i s a m u c h m o r e e s t a b l i s h e d a p a r t m e n t d i s t r i c t , o n e w o u l d e x p e c t s i t e s i n t h i s a r e a t o b e g r e a t e r i n v a l u e t h a n s i t e s i n E a s t V a n c o u v e r . 6.1.2 M.U.R.B. Variable T h i s 0-1 d u m m y v a r i a b l e i s e x p e c t e d t o h a v e a p o s i t i v e e f f e c t o n m u l t i p l e f a m i l y l a n d v a l u e s , s i n c e t h e p r e s e n c e o f M . U . R . B . i n c r e a s e s t h e e x p e c t e d f u t u r e n e t a f t e r - t a x c a s h f l o w s t o t h e d e v e l o p e r o f a n a p a r t m e n t b u i l d i n g . 6.1.3 Vacancy Rates T h e f i r s t m e a s u r e o f v a c a n c y r a t e s u s e d i n t h e f i n a l e s t i m a t i o n i s t h e o v e r a l l v a c a n c y r a t e i n a p a r t m e n t b u i l d i n g s i n t h e C i t y o f V a n c o u v e r w h i c h h a v e b e e n c o m p l e t e d f o r a t l e a s t s i x m o n t h s . A n o t h e r m e a s u r e w h i c h w a s t e s t e d w a s t h e v a c a n c y r a t e i n t h e s u b - a r e a i n w h i c h t h e l a n d s a l e o c c u r r e d , b u t t h i s m e a s u r e d i d n o t p e r f o r m w e l l , L e . t h e c o e f f i c i e n t w a s p o s i t i v e a n d s i g n i f i c a n t r a t h e r t h a n n e g a t i v e i n p r e l i m i n a r y r e g r e s s i o n s . O n e w o u l d e x p e c t t h e v a c a n c y r a t e c o e f f i c i e n t t o h a v e a n e g a t i v e s i g n s i n c e a n i n c r e a s e i n p o t e n t i a l v a c a n c i e s w o u l d r e d u c e e x p e c t e d f u t u r e c a s h f l o w s t o t h e d e v e l o p e r a n d h e n c e r e d u c e t h e a m o u n t h e w o u l d b e w i l l i n g t o p a y f o r a p a r t m e n t z o n e d l a n d . A p o s s i b l e r e a s o n w h y t h i s m e a s u r e d i d n o t p e r f o r m a s e x p e c t e d i s t h e f a c t t h a t t h e v a c a n c y r a t e w a s h i g h e r i n t h e - 46 -West End throughout the study period, but land values were also higher in that area. Some correlation problem may thus have occurred. The second measure of vacancy rates used in the analysis is the vacancy rate in new multiple family dwellings, defined as the stock of newly completed and unoccupied multiple family dwellings in the City of Vancouver divided by multiple family completions over the previous four quarters. An increase in this vacancy rate should have even greater negative impact on developers' expectations regarding future cash flows than the overall vacancy rate in existing apartments, since new apartments w i l l represent developers' strongest competition in the marketplace. 6 A A Income The income measure used in this analysis is real per capita income (indexed by the general CPI for Vancouver) in British Columbia over the study period. Ideally, one would use the average income of non-family house-holds in the Vancouver metropolitan area, since such households are the primary market for multi-unit housing. However, income information at the metropolitan level is severely deficient, particularly as far back as 1971. Although taxation statistics are available at the metropolitan and municipal levels, such statistics do not account for changes in average household income, since they are on an individual taxpayer basis rather than on a household basis. Hence, although the B.C. per capita income measure is not specific to non-family households, it is considered the best - 47 -information available which can represent real changes in income over the required time period. 6.1.5 Interest Rates The interest rate measure employed in this analysis is the real interest rate (adjusted by the general CPI for Vancouver) on NHA approved lender rental properties ( i ). This rate is considered more appropriate than the conventional mortgage rate, which would be more representative of rates on single family dwellings than on apartment properties. 6.1.6 "Excess" Apartment Returns It is reasonable to assume that one inducement for developers to buy multiple family land is the rate of return expected on apartment properties over and above the rate of return on a risk-free asset. This "excess returns" variable is thus defined as the real capitalization rate minus the real interest rate on NHA approved lender rental properties, which in a sense represents the leverage opportunities available to apartment block investors. The measure of capitalization rates is derived from a data fil e containing the universe of arms length apartment block transactions in the City of Vancouver from 1969 to 1981.* 7 Since this data included information on a quarterly basis on the selling price and gross income for each apartment block transaction, a standard representative apartment - 48 -block was selected in each quarter, for which the capitalization rate was used. 6.1.7 Rents One would » expect developers' decisions concerning the price they are willing to pay for multiple family zoned land to reflect current market rents being achieved on new apartment buildings. However, there is no public or private source of such information over the seven-year study period of this paper. Therefore, the measure of rental rates used is the Statistics Canada rent index for Vancouver (adjusted by the general CPI for 18 Vancouver). A second variable which should have an impact on developers' expectations about future rents is the level of apartment dwelling starts in the City of Vancouver. As the number of potential competitive units rises, other things being equal, a developer should expect this competition to reduce future market rents and hence the rents he wi l l be able to achieve in his building. Therefore, this variable is expected to have a negative effect on multiple family land values. 6.1.8 Construction Costs The construction cost variable represents the Statistics Canada construc-tion cost index for British Columbia (adjusted by the general CPI for - 49 -Vancouver). This variable is expected to have a negative impact on multiple family land values, since increases in this variable would decrease expected future cash flows to the developer. 6.1.9 Population The measure used as a proxy for growth in households is the quarterly growth in British Columbia's total population which, although probably too macro a measure to fully represent the effect of increasing numbers of households and decreasing household size in the Vancouver region, is the only measure available on a quarterly basis. Several alternate measures were attempted, one being the change in households in the Ci t y of Vancouver interpolated between census years, and the other the annual 20 change in main residence telephone listings in the City of Vancouver. Neither of these measures performed well in the equation for various reasons. In the case of the census information on households, the interpolation between five-year intervals created time trend problems with the M.U.R.B. variable, since the total change in households in Vancouver between 1976 21 and 1981 was higher than the change between 1971 and 1976; thus, the structure of the variable resulted in high collinearity with the M.U.R.B. variable, preventing efficient estimation of their individual effects on multiple family land values. - 50 -When added to the equation, the regression coefficient for the telephone listings variable was negative, which is contrary to the expected positive effect of growth in households on land values. There are two possible explanations for this result. Firstly, using the C i t y of Vancouver statistics may be too narrowly defining how the housing market operates. Presumably, demand for multiple family housing, and hence pressure on multiple family land values, is coming from migration and undoubling within the entire Vancouver region, rather than just in the City of Vancouver. Secondly, the growth in total households includes family as well as non-family households, hence the effect on non-family housing and land values may not be clearly represented. 6.1.10 The Zoning Issue The underlying assumption throughout this analysis w i l l be that the zoning variable in the theoretical model remains constant. It seems appropriate to address this issue directly and to present evidence that it is indeed a valid assumption. If during the study period of this paper, any major change in the supply of multiple family zoned land occurred, this would clearly bias the represent-ation of the multiple family land market, and hence the M.U.R.B. and other coefficients in the equation. However, discussions with planning officials in the Greater Vancouver region has revealed that the supply of multiple family zoned land on a regional basis was fairly constant through-out the 1972 to 1978 period. Although the West End was downzoned in - 51 -1975, reducing build-out capacity in that area by 5,000 to 10,000 units, other parts of the city were upzoned to increase total capacity, as were other municipalities in the region, most notably Richmond, Burnaby and 2 2 Surrey. Thus, it appears reasonable to assume that the multiple family zoning variable is a constant over the study period of this research. Since zoning is assumed to be constant, both Z and UNITS w i l l drop out of the theoretical model ( equation (11)); the number of units per square foot w i l l be constant for a l l sites because of the constant floor space ratio. E MPIRICAL RESULTS The results of the estimation of the multiple family land value model are shown in Table 4. Each of the regression equations is discussed in turn in the paragraphs which follow. .2.1 Run Number 1 This equation represents the estimation of the theoretical model with all variables measured as expected theoretically. However, there is an extreme collinearity problem with two variables, real rents and real income, whose correlation with the MURB variable are greater than .90, as shown in Table 5 (for RLRENT2 and REALINC). This collinearity prevents an efficient estimation of the true effect of each of these three variables - 52-on land values; the MURB variable consequently shows a negative sign, contrary to what is expected. An examination of the scatter plots of RLRENT2 and REALINC versus Q UARTER included in Appendix "C" provides an explanation for the high collinearity of these two variables with MURB. Essentially, the very small number of data points in the middle of the study period, which was the time when M.U.R.B.'s were introduced, compared to the larger number of data points at the two extreme ends of the v study period, results in high positive and negative correlation between MURB and any time trend variable. This does introduce a bias into the data results, but it is an unresolvable problem in terms of availability of transactions data, due to the paucity of land sales in the C i t y of Vancouver during the 1973 to 1975 period. The objective of this analysis is to find an efficient and unbiased estimate of the significance of the MURB and other variables in determining multiple family land values. The collinearity problem identified above creates an efficiency problem; however, the usual remedies for reducing collinearity, i.e. collecting more data and taking first differences on both sides of the regression equation, are not available in this case. An alternative representation of the rent and income variables is their change from quarter to quarter, which removes the time trend interference with MURB, as can be seen from Table 5 (for GRRLINC and LAGRENT). However, it must be recognized that although some gain in efficiency is - 53-5 4 . Table * THE REGRESSION EQUATIONS FOR MULTIPLE FAMILY LAND VALUES Regression Coefficients of the Independent Variables (t-values in parentheses) Dependent Variable Constant we MURB VR NEWVRATE Rm STARTS CC k.POP ER n F-stat DW SE Real price per square foot of multi-farnily Run Number 1 zoned sites in the City of Vancouver during the 1972 to 1978 period. -252.63 . (-4.12) Run Number 2 1.81 (1.81) -8.66 2.77 -3.26 . (-5.52) -5.6* (-1.44) -3.13 m 8.37 (-1.65) (2.66) (-4.97) (3.41) -1.66 (-1.60) 0.18 (0.11) 0.05 (0.60) 0.14 (1.53) 0.06 . (4.41) ( 0.69* (1.96) -0.35 -0.72) -0.26 (-0.43) 0.84 _ -0.004, ab 0.23 (2.24)' -0.30 (3.53) (-3.90) (-3.89) 1.42 (1.34) -0.002 0.07 . 2.23 . (-1.91) (2.41) (2.00) -0.37 (-2.18) -0.65 . (-2.79) ,592 112 11.98 2.11 2.44 .532 112 9.38 1.88 2.61 Run Number 3 10.36 2.48 -3.20 » 0.65 -1.94 0.33 . 0.12° (1.46) (2.29) (-5.14) (0.20) (-1.23) (3.38) (0.42) 0.99 (1.84) -0.11 -0.004. -0.22" 2.75 , -0.35 (-1.57) (-3.46) (-2.30) (2.42) (-1.51) .540 112 9.70 2.05 2.59 Run Number 4 0.56 3.20 (0.16) (3.12) -3.22 , 5.20 # -2.46 0.35 , 0.20° 0.97 (-5.20) (2.22) (-1.68) (3.76) (0.66) (1.82) 0.18' (1.89) ab -0.004, -0.27, 3.22 -0.44 (-3.23) (-2.98) (2.95) (-1.89) .545 112 9.90 1.97 2.57 Run Number 5 -1.31 3.21 , -3.14 , 4.74 -2.84 0.40 , 0.10° (-0.23) (2.89) (-4.97) (1.89) (-1.93) (4.10) (0.27) 1.33 , -0.29° -0.004, -0.23" 3.16 , -0.42 (2.27) (-0.47) (-3.19) (-2.11) (2.84) (-1.77) .530 112 9.30 2.10 2.61 Run Number 6 9.28 (0.73) 2.17 , (1.96) -3.18 , (-4.95) 1.72 (0.38) -0.67 (-0.42) 0.20 . (2.35) 0.30" (0.95) 0.42 (0.72) -0.13 (-1.31) -0.002, (-2.47) 0.02 (0.44) 2.19 (1.92) -0.47 (-1.88) .517 112 8.82 1.94 2.65 55 Tablet (cont'd) THE REGRESSION EQUATIONS FOR MULTIPLE FAMILY LAND VALUES Regression Coefficients of the Independent Variables (t-values in parentheses) Dependent Variable Constant we MURB VR NEWVRATE Rm STARTS CC /\POP ER. F-stat DW SE Real price per square foot of multi-family zoned sites in the City of Vancouver during the 1972 to 1978 period. Run Number 7 1.52 (0.17) 3.04 Run Number 8 0.73 (0.23) 3.03 -3.21 4.11 -3.17 4.30 -3.10 (3.06) (-5.20) (2.48) (-2.81) 2-81 . (3.02) (-5.08) (2.57) (-2.57) 0.38 , (4.47) 0.38 . (4.50) 1.18 , (2.78) 1.20 . (2.82) 0.16ab -0.004. (1.78) (-3.58) -0.40 , (-3.46) - 0 . 2 8 ° . 3.28 , (-3.06) (3.02) -0.25 b. (-2.80) 3.20 -0.33 , (-1.97) -0.40 (2.93) (-2.42) .543 112 10.82 1.95 2.56 .529 112 11.34 1.93 2.59 Run Number 9 7.79 (9.58) 3.54 , (4.02) .125 112 16.20 1.48 3.35 Average real Run Number 10 price per square foot 23.48 of land sale (1.04) transactions in quarter x. Run Number 11 " 9 3 2 * (6.64) 0.16c (0.20) -5.27 -0.04 (-0.76) (-0.02) 2.52 (1.45) -0.21 (-1.21) 0.13" (0.22) 0.03 (0.30) -0.04c (-0.14) .446 20 1.38 2.75 3.57 ,104 20 2.10 1.68 3.71 . Lagged by one quarter. Change since last quarter. . Location index variable, weighted by sub-area. Expectations variable, defined as the lag over the past six quarters in Vancouver rents. , Real capitalization rate variable. Indicates t-value significant at .05 level. achieved by taking these first differences, there is also some loss in unbiasedness in the results. The following paragraphs describe the data results using these new specifications for rent and income. Run Numbers 2 and 3 Run Number 2 includes Zik R m and in the regression equation, both of which are significant and have the expected positive sign. Other variables in this equation which are significant and have the expected sign are the two location variables (West End and East Vancouver), MURB, population growth ( ^ P O P ), and excess returns on apartment investments ( ER ). Variables which do not have the expected sign are the vacancy rate ( VR ), the vacancy rate in new multiple family dwellings ( NEWVRATE ), and construction costs ( C C * ). Since the specification of the rent variable is in quarterly change terms rather than the actual level, i t would seem more consistent to include construction costs in quarterly change terms as well, particularly since the coefficient for the level of construction costs does not make intuitive -x- -x sense. Run Number 3 replaces C C with «£k CC , but keeps R m rather •x -x-than R m » to see what the effect of £s» C C is in the equation, -X- -x independent of £± R . As Table 4 shows, C C is in fact significant and negative as expected in this equation, but is also negative. The equations in the following paragraphs w i l l specify both £± R m and ^ C C , as this is considered to be most consistent. -56 -6.2.3 Run Number k This equation represents my preferred estimation of the theoretical model, since a l l but two of the variables have the expected sign and the collinearity between independent variables has been minimized (refer to Table 5 ) . According to this equation, the most statistically significant determinants (at the 5 per cent level) of multiple family land values are: location (the West End having a positive effect and East Vancouver a negative effect), MURB, the level of apartment dwelling starts, construction costs, and population growth. Other variables which are not statistically significant, but which do contribute to the explanation of multiple family land values, hence minimizing bias in the estimation of the MURB coefficient, are: vacancy rates, change in real income, the real 23 interest rate, a one quarter lag in the change in rents, and excess returns expected on apartment investments. The NEWVRATE and i variables do not have the expected negative sign in this equation, although these measures are consistent with the theoretical determinants of multiple family land values. Furthermore, neither of these variables is severely collinear with other independent variables in the equation, although the correlation coefficient of . 7 5 between NEWVRATE and MURB, and . 7 9 between REALINT and VACRATE, may be causing statistical problems. - 57 -5 8 . Table 5 CORRELATION MATRIX FULL MODEL VARIABLES Variable Correlation Coefficients 39.NEWREALP 7. WESTEND 8. KITS 9. EASTVAN 1O.MARP0LE 25.MURBSTAT 22.VACRAJE 92 NEWVRATE 42.REAL INC 52.GRRLINC 55.REAL INT 93.RLRENT2 • 97.RLRNTLAG 60.LAGRENT 94.STARTS 95.REALCOST 63.CCOSTBC2 51.POPGRTH 70.RLAPTRTN 12.BCP0P 53.INFLATIO 1 .OOOO .3899 1 .0931 -.3227 .0692 .3592 - . 165S .3794 . 4204 -.2679 - . 1810 -.4081 -.4 105 . 1821 .0273 .2123 - .0439 -.2766 -.1325 .4130 .2539 39. NEWREALP OOOO . 1910 .3675 .0399 .0335 .0725 .0178 . 1252 . 1790 .0147 . 1094 . 1034 .0505 .0563 . 1814 .0861 .0432 .0774 . 1 146 .0251 1 .0000 - . 8035 - .0871 - .4362 .3697 - . 3200 - . 3930 .2359 .2124 . 4340 . 4444 -.0819 -.1136 - .0323 .0269 .4330 . 1 160 - . 4135 -.3353 8. KITS 1 .OOOO - . 1676 .3730 -.3638 .2582 . 2936 -. 1188 - . 1S86 -.3380 - . 3492 .0561 . 1562 -.0682 -.1281 -.371 1 -.0780 .3180 .3030 9: EASTVAN 1.0000 .0570 -.0799 . 1 126 .0130 -.0065 - . 1395 - .0229 -.0298 - .0285 -.0695 - .0096 .2029 - .0333 .0475 .0154 .0880 10. MARPOLE 1 .0000 -.4390 .7542 .9143 - .6092 -.2924 -.9554 - . 9649 . 1991 .4122 . 1827 -.2522 -.8013 - . 1747 . 9482 .5281 25. MURBSTAT 1 .0000 - . 3859 -.3073 . 1562 . 7956 .4469 . 46 1 1 .0976 . 1489 . 2233 - .0496 .450O .2318 - . 3639 -.88 16 22 . VACRATE 1 .0000 .6911 -.2042 -.2820 -.6997 -.7407 . 1557 . 2860 . 1098 . 1285 -.7042 .14 16 .6945 . 4358 92 . NEWVRATE I .OOOO • .6280 • .1436 • .9736 • .9711 . 1578 .5768 .5279 - .337 1 - .6895 -.1811 .9919 .3539 42 . REALINC .0000 . 3289 .6742 .6141 .3394 • .2515 •25 16 .4573 .4488 .7039 •6595 • .3854 52 1 .0000 .3162 .3015 . 1092 .2758 .3523 - .0172 .2004 . 3305 -.2156 - .9273 55 1.0000 .9954 - . 1 107 -.4800 - . 3532 .3578 .7351 .2672 - .9929 - .5347 93. 1 .0000 - . 1036 - . 4576 - . 3346 .3039 .7576 . 1976 - .9901 -.5321 97 . 1.OOOO O80O .0356 .0161 -.2551 -.2041 . 1433 -.0560 60. 1 .OOOO . 4897 -.6018 -. 1030 . 1078 . 5264 - . 1812 94. 1 .0000 - . 0913 -.0779 - .0184 .4309 - . 3548 95. 1 .0000 .0170 .3307 -.3558 -.0998 63 . 1 .0000 .2938 -.7208 -.4498 51 . 1 .0000 - .2190 - . 3687 70. 1.0000 .4378 12. GRRLINC REALINT RLRENT2 RLRNTLAG LAGRENT STARTS REALCOST CC0STBC2 POPGRTH RLAPTRTN BCPOP 53 . INFLATIO It is worthwhile noting that the R-squared of .545 for this equation is quite acceptable for cross-sectional studies of this nature. Although the sample contains transactions which occurred over a seven-year period, the removal of the time trend, and the conversion to real terms changes the data to a cross-sectional sample. One would expect a much higher R-squared in time series studies such as those by Witte and Adams et al. These data results suggest that the introduction of the M.U.R.B. program in 1974 had a significant impact on multiple family land values, and that developers paid a premium of $5.20 per square foot (compared to the average real sales price per square foot of $10.81) to obtain such land over the period of the program. Hence, a developer would pay an extra $52,000 (in 1971 dollars) for a typical 100' x 100' apartment site (this is somewhat smaller than the average apartment block in the RESALES sample). At the 5 per cent level of significance, this represents a confidence interval of $52,000 + $45,891. If one assumes that the developer built a typical (Class 31) 25-unit apartment block on this site, with a marginal tax rate of 55 per cent, a real discount rate of 2 per cent and a seven-year holding period, the present value of the future marginal tax shelter benefits associated with the M.U.R.B. certi f i c a t i o n is $23,180 (in 1971 dollars). Converting to 1980 dollars, the equation estimates that a developer would pay $108,680 to acquire a site with future tax shelter benefits worth $48,446. This estimate is again based on the P V M n R R equation described previously: - 59 -n PV MURB ~ I CCA, MURB Recapture i = 1 ( 1 + r ) l (1 + r )' Thus, the M.U.R.B. premium on land price estimated in these data results represents a significant over-capitalization of future M.U.R.B. tax shelter benefits. Run Number 5 This equation shows the impact of using R m in current rather than lagged form. Although the R-squared is only moderately affected (it is reduced, however), the sign of R m is incorrect, and «^ Y is no longer -x -x-significant. It also reduces slightly the significance of i , ^ \ C C and ^ POP, although it only marginally affects the MURB coefficient. This equation shows that the specification of the rent variable in current terms is not as good a measure as lagged rents in explaining developers' behaviour. This may result from information lags, or it may be that developers are merely slow in reacting to changes in the market. - 60 -6.2.5 Run Number 6 Run Number 6 show the regression results where income is specified as a quarterly change, but rents and construction costs are specified in level terms. Only three variables are statistically significant - WESTEND, EASTVAN, and STARTS, while four variables do not have the correct sign -NEWVRATE, i * , R* , and C C * . Thus, Run Number 4 is s t i l l considered the preferred estimate of the theoretical model, although this run could be considered more theoretically appealing. These two equations show the variables which remain in equation four at the .10 and .05 significance levels, respectively. In the former equation, only A . Y drops out of the equation, while in the latter, A R f f l also drops out. In both cases, NEWVRATE and i s t i l l have the incorrect sign. These results are generally encouraging, in that ten variables remain in the estimated equation even at the 5 per cent level of significance, with an acceptable R-squared of 53 per cent. A run was made including only MURB as the independent variable. It is interesting to note that the MURB coefficient in this equation is 3.54 6.2.6 Run Numbers 7 and 8 6.2.7 Run Number 9 - 61 -(significant at .05 level), and although the R-squared is only .125, the regression is significant at the .05 level (F = 16.20). 6.2.8 Run Number 10 In an attempt to reduce the bias in the regression equation which may result from the large number of land sale observations in some quarters compared to others during the study period, an additional run on the data was made on a quarterly rather than on a transactions basis. This effectively reduced the sample size to 20, since of the 27 quarters over the 1972 to 1978 time period, 7 quarters had no occurrence of land sales transactions. The dependent variable in this equation is the average real price per square foot of a l l land transactions during a quarter. A location index was created, which gave a weighting of 3.0 for sales in the West End, - 3.0 for sales in East Vancouver, and 0.0 for sales occurring in either Kitsilano or Marpole. These weights are based on the earlier regression results, which showed quite stable coefficients for WESTEND and EASTVAN, while KITS and M A RPOLE were never significant in the equations (see Appendix "C" for these regression results). Due to the dramatic reduction in the sample size for this run, the number of variables included in the equation was reduced to seven. Only the existing vacancy rate was included, while an expectations variable, - 62 -NEW RM LAG, which represents a six-quarter moving average of the real growth of rents in Vancouver, replaces A Y , STARTS and A POP. The 1 and E R & variables are collapsed into one rate of return variable, the real capitalization rate. As can be seen from Table 4, the results of this regression are quite disappointing, since not one variable is significant at even the 20 per cent level of significance, nor is the regression as a whole significant, although the R-squared is a surprising 44.6 per cent. An examination of the residual plot and histogram of residuals for this regression (refer to Appendix "D", page 127), reveals a possible outlier in the data, which may be causing high standard errors and thus biasing the results. A regression was run excluding this possible outlier (refer to Appendix "D", page 134); however, the results are very comparable to Run Number 10, although the coefficients of the MURB, REALCOST and V A C R A T E variables switch signs, and the standard error is reduced somewhat and t values improved, 24 as would be expected. A possible explanation for these small sample results is that the number of variables is s t i l l too large for this sample size. However, to remove more independent variables would bias the ful l representation of the multiple family housing market. 6.2.9 Run Number 11 This regression equation shows the small sample results where only MURB is included as the independent variable. Although MURB is not significant, - 63 -its coefficient has a value of 2.52, which is reasonably clsoe to the value in Run 9. The R-squared is again very low (.102), while the F statistic is not significant at the .05 level. - 64 -CONCLUSIONS AND IMPLICATIONS The results of the foregoing analysis provide evidence which contradicts the general case for the operation of the multiple family housing market, where renters should receive the f u l l benefits of the M.U.R.B. program in the form of lower rents. This research has shown that the future tax shelter benefits associated with M.U.R.B. properties are fully capitalized into the market values of completed M.U.R.B. buildings, and that M.U.R.B. investors do not earn rates of return superior to those of investors in non-M.U.R.B. apartment properties. Similarly, these results do not support the widely made argument that adverse tax revisions (such as reductions in tax shelter benefits) cause inferior ex ante rates of 25 return in real estate investment. In competitive capital markets, equilibrium comparative returns among alternative investments are not determined by Government subsidies or differential tax treatments. Expected rates of return among assets of equivalent risk must be equal; otherwise, investors w i l l enter or leave a specific investment market, causing prices to rise or f a l l until the returns among the assets are similar. The only way government programs effect differential returns is through any investment risk created by having a fluctuating or uncertain tax or subsidy policy. This research suggests further that the expected M.U.R.B. tax shelter benefits were over-capitalized into higher land value premiums during the l i f e of the program. Thus, using Tullock's (1975) terminology, a major effect of the program - 65 -was to create transitional gains for existing landowners at the time the program was introduced. The expected favourable tax shelter benefits were thus competed away, resulting in higher multiple family land prices. Although the data results show clearly the impact of the M.U.R.B. on land values, a weakness in the data, i.e. there were very few land sales occurring immediately before and after the introduction of the program, must be recognized, since it may be biasing the results to some extent. The data results nevertheless suggest that one of two cases discussed in Section 3.1 holds. The over-capitalization of M.U.R.B. benefits into land values, combined with the ful l capitalization of M.U.R.B. benefits into the resale values of apartment blocks, would result i f the land supply function were inelastic and the investors demand function were perfectly elastic (Case 4). This would imply that there is substitution in the production function for apartment blocks, i.e. developers w i l l substitute capital for land and incrase the density on existing sites as a result of the increase in demand caused by M.U.R.B. legislation. This is also evidence of semi-strong form efficiency of real estate markets, since the tax shelter benefits were fully capitalized into resale values of M.U.R.B. apartment properties. However, since this research has not tested the speed with which the market reacted to the introduction of the M.U.R.B. program, it does not provide conclusive evidence of real estate market efficiency. The data results also cannot reject the conditions under Case 5, where both the land and apartment supply functions are perfectly inelastic, since the confidence - 66 -interval of the MURB coefficient includes the case where the present value of the M.U.R.B. benefits is equal to the estimated increase in land values which occurred as a result of M.U.R.B. legislation. However, this would imply no substitution in production, which is not very likely. Furthermore, conclusive evidence of this case could only be found by either observing the movement in rents after M.U.R.B.'s were introduced in comparison to what would have occurred in the absence of M.U.R.B.'s., or by deriving structural estimates of the supply and demand curves in the land and apartment markets. Clearly, such a comparison is not possible with these data. A third possible market situation which is supported by the data results is where the demand schedules of both investors and landowners are perfectly elastic, a consequence of both an efficient land and apartment investment market. A definitive answer is not possible, however, without some knowledge of the change in apartment rents which resulted from the M.U.R.B. program. What the results do suggest, however, is that the f u l l capitalization of M.U.R.B. benefits into both land and apartment block values resulted in the f u l l benefits of the M.U.R.B. program not fi l t e r i n g through to renters. Some benefits most likely did reach renters, since it is unrealistic to assume no substitution in production, but the extent of renters' benefits cannot be measured within the scope of this research. If the supply of multiple family land is in fact inelastic and government assistance programs which increase the demand for rental housing or apartment zoned land, - 6 7 -are not accompanied by policies at junior levels of government which concurrently increase the supply of developable land, these assistance programs can become marginally effective tools for increasing the allocation of resources to the housing sector. This research has in fact shown that the M.U.R.B. was a very expensive subsidy policy and that its effectiveness in achieving its objective was limited by the nature of the multiple family housing market. The evidence regarding the slope of the supply and demand curves for landowners and investors suggests that the f u l l impact of the M.U.R.B. tax shelter benefits was split between windfall gains to landowners and decreased rents for renters. However, the distribution of the benefits between these two groups is not clear from these data results. If the introduction of the M.U.R.B. program in 1974 created windfall gains for existing landowners, then it follows that the termination of the program w i l l create windfall losses. It also follows that the "off and on" nature of the program over the past seven years should have created considerable uncertainty for prospective land purchasers and developers, resulting in increased risk of holding real estate. Nevertheless, after termination of the program, once the market has adjusted to the lower costs of production, future market participants should earn "normal" market rates of return on apartment investments. This research has shown that there is s t i l l much to be learned about how housing markets operate. It would be instructive to do a similar study in another metropolitan area, particularly where land sales between 1973 and 1975 were not so scarce, in order to compare market reactions in another local marketplace. - 68 -Before more definitive conclusions can be drawn concerning the behaviour of various market participants, more research needs to be done on rent movements and on the speed with which real estate markets react to changes in information. - 69 -FOOTNOTES Statistics Canada, V i t a l Statistics, Catalogue Number 84-204. See Harris (1979 : 4-14) for a discussion of the tax reform process. See Interpretation Bulletin IT-367R2, September 7, 1981. Af t e r 1978, with few exceptions, a l l new M.U.R.B.-certified buildings came under the 5 per cent C C A asset class (Class 32X There wi l l also be foregone provincial tax revenues, which w i l l vary from province to province. Based on information obtained from Helmut Pastrick at CMHC in Vancouver. Ci t y of Vancouver Planning Department estimates. Stock markets also suffer from some of these deficiencies, such as lack of sophistication, and divergence between expectations and actual accomplishments. The efficiency of stock markets nevertheless has been empirically supported. For additional information on this type of framework for real estate investment analysis, see Gau and Kohlhepp (1976, 1978). The RM-3 zoning classification in the Ci t y of Vancouver allows a maximum floor space ratio (FSR) of 1.5, Le., the ratio of total gross building area to lot size. Comparable holding period in terms of acquisition and sales date. Although the present data f i l e contains 112 transactions, the original data collected comprised some 496 transactions which occurred from 1963 to 1978. However, the pre-1972 data were not useable due to constaints in other data and because of problems which arose with the representation of the 1971 tax reform legislation in the modeL Assuming a typical structure-to-property value ratio of 70 per cent on the average selling price in the sample. In 1980 in British Columbia, a 55 per cent marginal tax rate would apply to investors with a taxable income of $70,000 or more. - 70-For the M.U.R.B. developments, the analysis assumes that 15 per cent of the construction costs are soft; in other words, outlays that could be expensed when incurred as opposed to being capitalized into the depreciable basis of the property. The 15 per cent figure is the average soft cost ratio (after eliminating syndication-type fees) found in a survey of ten registered M.U.R.B. syndicates offered in Western Canada in the third quarter of 1981. Refer to Neter and Wasserman (1974: 12-13) for a discussion of this test. The other two location variables, KITS and MARPOLE, did not have significant coefficients in preliminary regressions. This data was also collected from B.C. Assessment Authority records, under the supervision of Professor George W. Gau. Catalogue Number 62-010. Catalogue Number 62-007. Obtained from the B.C. Telephone Company. Statistics Canada, Census of Canada, for 1971 and 1976, and preliminary census counts for 1981. Based on information obtained from the Planning Departments of the City of Vancouver, the Municipalities of Richmond, Burnaby and Surrey, and the Provincial Land Commission. A l l independent variables were tried with a lag to see if the specification of the model improved, but A R was the only variable which performed better when specified on a lagged basis. This same observation was excluded from a separate run on the large sample (in Runs 1 and 4), and similarly, the regression results changed only marginally. An example of such an argument can be found in Smith (1981). - 71 -BIBLIOGRAPHY Adams, F. Gerard; Milgram, Grace; Green, Edward W.; and Mansfield, Christine, "Undeveloped Land Prices During Urbanization: A Micro-Empirical Study Over Time", Review of Economics and Statistics, Vol. 50, No. 2, May, 1968, pp. 248-258. Bailey, Martin 3., "Progressivity and Investment Yields under U.S. Income Taxation", Journal of Po l i t i c a l Economy, VoL 82, No. 6,1974, pp. 1157-1175. Baxter, Cheryl, "The Impact of Government Policies and Programs on Land Values", The  Real Estate Appraiser and Analyst, Vol. 45, May-June, 1979, pp. 42-45. Brigham, Eugene F., "The Determinants of Residential Land Values", Land Economics, VoL 41, August, 1965, pp. 325-334. Canada Mortgage and Housing Corporation, Canadian Housing Statistics, Ottawa. Clayton Research Associates Ltd., Tax Expenditures-Housing; research paper prepared for C.M.H.C.{ March, 1981, Ottawa. Diamond, Douglas B. Jr., "The Relationship Between Amenities and Urban Land Prices", Land Economics, Vol. 56, No. 1, February, 1980, pp. 21-32. Fama, Eugene F., "Efficient Capital Markets: A Review of Theory and Empirical Work", Journal of Finance, 25 (May) 1970, pp. 383-423. Figlewski, Stephen, "Market 'Efficiency' in a Market with Heterogeneous Information", Journal of Po l i t i c a l Economy, Vol. 86, No. 4, 1978, pp. 581-597. Fisher, Ted L., "Tax Leveraging and Real Estate Tax Shelters", The Appraisal Journal, July, 1980, pp. 414-422. Gau, George W., and Kohlhepp, D.B.£ "Estimation of Equity Yield Rates Based on Capital Market Returns", The Real Estate Appraiser and Analyst, Vol. 44, November-December, 1978, pp. 33-39. Gau, George W., and Kohlhepp, D.B./' "Reinvestment Rates and the Sensitivity of Rates of Return in Real Estate Investment", A R E U E A Journal, Vol. 4, Winter, 1976, pp. 69-83. Goldman, M. Barry, and Sosin, Howard B., "Information Dissemination, Market Efficiency and the Frequency of Transactions", Journal of Financial Economics, Vol. 7,1979, pp. 29-61. Hamilton, Bruce W., "Capitalization of Intrajurisdictional Differences in Local Tax Prices", The American Economic Review, December, 1976, Vol. 66, No. 5, pp. 743-753. Harris, E.C., Canadian Income Taxation, Toronto, 1979. - 72 -Janssen, Christian T.L., and Hoskins, Colin G., "Analysis of ARP and C C A Projects", Appraisal Institute Magazine, May, 1980, pp. 26-32. Krueger, Anne O., "The Poli t i c a l Economy of the Rent-Seeking Society", American  Economic Review, June, 1974. Linnemann, P., "The Demand for Residence Site Characteristics", Journal of Urban  Economics, March, 1981,9(2), pp. 129-148. Mil l s , David E. "The Non-Neutrality of Land Value Taxation", National Tax Journal, Vol. 34, No. 1, March, 1981, pp. 125-129. Needham, Barrie, "A Neo-Classical Supply-Based Approach to Land Prices", Urban  Studies, VoL 18, No. 1, February, 1981, pp. 91-104. Posner, Richard A., "The Social Costs of Monopoly and Regulation", Journal of Po l i t i c a l  Economy, August, 1975, pp. 807-827. Ricks, R. Bruce, "Imputed Equity Returns on Real Estate Financed with Life Insurance Company Loans", The Journal of Finance, December, 1969, pp. 921-937. Roulac, Stephen E.. "Can Real Estate Returns Outperform Common Stocks?', The Journal of Portfolio Management, Winter, 1976, pp. 26-43. Shenkel, William M., "The Valuation of Multiple Family Dwellings by Statistical Inference", The Real Estate Appraiser, January-February, 1975, pp. 25-36. Smith, L.B.J "Federal Housing Programs and the Allocation of Credit and Resources", in Government in Canadian Capital Markets: Selected Cases, edited by J.E.' Pesando and L.B./Smith, C D J H o w e Research Institute, Montreal, 1978. Smith, L.B./ "Canadian Housing Policy in the Seventies", Land Economics, VoL 57, August, 1981, pp. 338-352. Tullock, Gordon, "The Transitional Gains Trap", Bell Journal of Economics, Autumn, 1975, pp. 671-678. Valachi, Donald J. "The Arithmetic of Real Estate Tax Shelter", Journal of Property  Management, Vol.44, July/August, 1979, pp. 209-215. Von Furstenberg, G.M., "The Impact of Government Housing and Credit Programs on the Cost of Housing", in The Cost of Housing, Federal Home Loan Bank of San Francisco, San Francisco, 1977. Wendt, Paul F., and Wong, Sui N., "Investment Performance: Common Stocks Versus Apartment Houses", The Journal of Finance, December, 1965, pp. 633-646. White, Wilbert L., "Price Indexing for Time Adjustments", The Appraisal Journal, VoL 48, January, 1980, pp. 15-23. - 7 3 -Witte, Ann Dryden, "The Determination of Interurban Residential Site P r i c e Differences: A Derived Demand Model with Empirical Testing", The Journal of Regional Science, VoL 15, No. 3,1975, pp. 351-364. Witte, Ann Dryden, "An Examination of Various Elasticities for Residential Sites", Land  Economics, Vol. 53, No. 4, November, 1977, pp. 401-409. Zerbst, Robert H. and Eldred, Gary W., "Improving Multiple Regression Valuation Models Using Location and Housing Quality Variables", Assessors Journal, VoL 12, No. 1, March, 1977, pp. 1-15. - 74-APPENDIX "A" VARIABLE LISTS - 7 5 -Table A - l LIST OF VARIABLES APARTMENT "RESALES" FILE Variable Number Symbol Description 1 F I L E N O l File reference 2 MONTH Quarter of sale: 1 = 01/77 19 = 04/81 3 PRICE Selling price of building 4 FINANCE Total mortgages outstanding 5 FILEN02 File reference 6 INTPMO Interest payable on demand note 7 INTRATE Weighted average interest rate on Total FINANCE. 8 P U R C H T Y P E Type of purchaser: 1 = Individual 2 = 2 or more individuals. 3 = Holding or management co. 4 = Developer or construction co. 5 = Couple 6 = Co-operative 7 = Financial institution 8 = Miscellaneous co. 9 P U R C H L O C Address of purchaser: 1 = Vancouver westside 2 = Vancouver eastside 3 = CBD 4 = West Vancouver 5 = North Vancouver 6 = Richmond 7 = Burnaby 8 = Elsewhere in GVRD 9 = Elsewhere in B.C. 10 = Elsewhere in Canada 10 AGE Year Building was completed. - 76 -Table A - l (cont'd) Variable Number 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Symbol SUITES A REA AVERAGE LOTSIZE BACHS ONES TWOS THREES FOURS CONSTN HEATING STOREYS PARKING L AUNDRY ELEV B A L C POOLREC Description Number of suites in building Total gross floor area of building Average suite size Square footage of site Number of bachelor suites Number of one-bedroom suites Number of two-bedroom suites Number of three-bedroom suites Number of four-bedroom suites Type of construction: 0 = Frame 1 = Concrete Type of heating: 0 = Oil 1 = Electr i c 2 = Gas Number of storeys 0 = None 1 = Above Ground 2 = Underground 3 = Both Dummy variable: 1 = Yes 0 = No Number of elevators in building Dummy variable: 1 = Yes 0 = No Dummy variable: 1 = Yes 0 = No - 77 -Table A - l (cont'd) Variable Number Symbol Description 28 SAUNA Dummy variable: 1 = Yes 0 = No 29 PENTHS Number of PH suites 30 FILEN03 File reference 31 TAXSHELT M.U.R.B. dummy variable 32 GI Gross income of building 33 EXPENSES Operating expenses 34 NOI Net operating income 35 RENTCONT Dummy variable: 1 = Yes 0 = No 36 MTGPMT Annual pmt on FINANCE 37 ARPSUPP Amount of ARP subsidy (if applicable) 38 E CC Estimated construction cost of building (per building permit) 39 R V ALUE Replacement value of building (per B.C. assessment) 40 A C C Actual construction cost (per owner) 41 ARPSTAT Dummy variable: 1 = Yes 0 = No 42 INCDATE Date GI applicable 43 FINDATR Registration date of financing 44 FINDATC Cancellation date of financing 45 FINAMT Financing amount 46 LVRATIO FINANCE/PRICE x 100 47 R E A L A G E No. of years since completion -78 -Table A - l (cont'd) Variable Number 48 49 50 Symbol SPPSF SPPSTE OERATIO Description Selling price per square foot of building area Selling price per suite Operating expense ratio 1 ) Sources of data: B.C. Assessment Authority records, B.C. Land Title O f f i c e , Statistics Canada, Real Estate Board of Greater Vancouver. This f i l e contains M.U.R.B. apartment block resales and a matching sample of non-M.U.R.B. apartment block sales in the same time period. - 79 -Table A-2 LIST OF VARIABLES "LANDSALES" FILE Variable Number 1 2 Symbol FILENOl QUARTER Description Fil e Reference: #5001-6050 Quarter in series: 1 = 1st Qtr, 1963 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 PRICE LOTSIZE FRONTAGE DEPTH WESTEND KITS EASTVAN MARPOLE KERRISDL BCPOP BCPERINC UNEMPLUA UNEMPLSA C O M P L V A N FILEN02 72 - 4th Qtr, 1980 Selling price of lot Total square footage of lot Frontage of lot in feet Depth of lot in feet Dummy variable: 1 = Yes 0 = No as above as above as above as above Estimate of B.C. population in quarter x. Estimate of per capita personal income for B.C. during quarter x. Unadjusted unemployment rate in B.C. during quarter x. Seasonally adjusted unemployment rate in B.C. during quarter x. Total dwelling completions in the C i t y of Vancouver during quarter x. File reference: #5001-6050 - 80 -Table A-2 (cont'd) Symbol COMPLBC C P I A L L CPIHOUSG NONFAMHH V A C R A T E NHARATE CONVRATE MURBSTAT CCASTAT CCANEW CCANEWWP ARPSTAT Description Total dwelling completions in B.C. Consumer Price Index - A l l items; C i t y of Vancouver, during quarter x. Consumer Price Index - Housing Component; Ci t y of Vancouver, during quarter x. Non-family households as a proportion of total households in quarter x; non-family households defined as those in the 15-19, 20-24, and 65+ age groups; extrapolation of census data used to arrive at estimates. Apartment vacancy rate (in buildings completed for at least 6 months) in the C i t y of Vancouver during quarter x. N.H.A. interest rate on approved lender rental properties during quarter x. Conventional mortgage lending rate during quarter x. Dummy variable (0=No; 1+Yes) indicating whether MURB legislation was in effect (or pending) during quarter x. Dummy variable indicating whether C C A . allowances were permitted as tax shelters on a l l rental properties during quarter x. Dummy variable indicating whether C C A . allowances were permitted as tax shelters on new rental properties; this reflects both pre-1971 and post 1974 situations. Same as variable 27, except that allow-ance is made for the White Paper re-leased in the 4th quarter of 1969, which introduced the f i r s t possibility that tax shelters on rental properties might be removed. Dummy variable indicating whether A RP benefits were available during quarter x. - 81 -Table A-2 (cont'd) Variable Number Symbol Description 30 RENTCONT Dummy variable indicating whether rent control legislation (of any form) was in effect in British Columbia during quarter x. 31 HOLDPER Holding period of lot x prior to construction of apartment building (in years). 32 SPPERSF Selling price per square foot of lot x. 33 SPPERFF Selling price per front foot of lot x. 34 SPPERDF Selling price per foot of depth of lot x. 35 DEFLATOR Apartment Sales price index (from Trans-actions File). 36 REALSP PRICE/DEFLATOR 37 R E A L P P S F REALSP/LOTSIZE 38 CPINEW CPIALL/100 39 NEWREALP SPPSF/CPINEW 40 RLINTRTE NHARATE/CPINEW 41 POPGRRTE Growth in B.C. population since 01/71. 42 REALINC BCPERINC/CPINEW. 43 INCGRRTE Growth in real B.C. income per capita since 01/71. 44 NEWQTR Categorical variable for QUARTER. 45 RENTLEVEL Average nominal monthly rents in Vancouver apartments, weighted by local area. 46 GRRTRENT Growth rate in RENTLEVEL since 01/71. 47 CONSTNCOST Construction cost index for Canada. 48 GRRTCOST Growth rate in CONSTNCOST since 01/71. 49 RENTGRTH Growth since last quarter in nominal rent levels. - 82 -Table A-2 (cont'd) Symbol COSTGRTH POPGRTH GRRLINC INFLATION G R R L RENT REALINT R E A L R E N T CCOSTBC RNTGRTH2 RNTGRTH3 LAGRENT LAGCOSTS RNTGRTH4 CGOSTBC2 C A P R A T E Description Growth since last quarter in construction cost index for Canada. Growth since last quarter in B.C. population. Growth since last quarter in B.C. real per capita income. Growth since last quarter in CPIALL, on an annualized basis. Growth since last quarter in real rents in Vancouver apartments. N HARATE - INFLATION Average monthly real rent (RENTLEVEL/ CPINEW) in Vancouver apartments. Growth since last quarter in construction cost index for B.C. Growth since last quarter in rent index for Vancouver (Statistics Canada). Growth since last quarter in rents in a sample of Vancouver apartments less than 5 years old (from Transactions File). One quarter lag in real rent index growth since previous quarter (RNTGRTH2 - INFLATION). One quarter lag in real construction cost index growth since previous quarter (CCOSTBC - INFLATION). Real growth since last quarter in Vancouver rent index (RNTGRTH2 - INFLATION). Real growth since last quarter in B.C. con-struction cost index (CCOSTBC - INFLATION). The real capitalization rate (nominal -INFLATION) being achieved by a standard Vancouver apartment block in quarter x (from Transactions File). - 83 -Table A-2 (cont'd) Variable Number Symbol Description 65 C A P R T L A G One quarter lag in CAPRATE. 66 NOMCAPRT The nominal capitalization rate being achieved by a standard Vancouver apartment block in quarter x (from Transactions File). 67 C APGAIN Real capital gain from a sample of Vancouver apartment blocks since last quarter (from Transactions File). 68 C A P G N L A G One quarter lag in CAPGAIN. 69 POPLAG One quarter lag in POPGRTH. 70 R L A P T R T N Excess returns earned on Vancouver apart-ment blocks ( CAPRATE - REALINT). 71 R L I N C L A G One quarter lag in GRRLINC. 72 V A C R T L A G One quarter lag in VACRATE. 73 RLINTLAG One quarter lag in REALINT. 74 A P R T N L A G One quarter lag in RLAPTRTN. 75 I N F L A L A G One quarter lag in INFLATION. 76 INTCHGE Change since last quarter in NHARATE. 77 APTCOMCH Net change since last quarter in apartment stock in the C i t y of Vancouver (defined as apartment completions minus apartment demolitions). 78 HHCHANGE Quarterly increase in total households in the C i t y of Vancouver (based on interpolation of census data). 79 RLINTCHG Change since last quarter in REALINT. 80 ERCHANGE Change since last quarter in RLAPTRTN. 81 APTSTSCH Change since last quarter in apartment starts in the City of Vancouver. 82 NEW WE Categorical variable for WESTEND. - 84 -Table A-2 (cont'd) Symbol NEWKITS NEWEV NEWMAR NEWKERR SUBVACRT NEWVACCH REZONING VACRTCHG NEWHH NEWVRATE RLRENT2 STARTS REALCOST NEWVRLAG R L R N T L A G Description Categorical variable for KITS. Categorical variable for EASTVAN. Categorical variable for MARPOLE. Categorical variable for KERRISDL. Vacancy rate in apartments 6 months or older in the sub-area and quarter in which the land sale observation occurred. Change since last quarter in the stock of newly completed (in past six months) and unoccupied apartment and row dwellings in the C i t y of Vancouver. Dummy variable reflecting the major down-zoning of the West End enacted in August, 1975. Change since last quarter in VACRATE. Change since the last quarter in the number of main residence telephone listings in the C i t y of Vancouver. Vacancy rate in newly completed multiple family dwellings in the C i t y of Vancouver - defined as the stock of newly completed and unoccupied multiple family dwellings divided by multiple family completions over the previous four quarters. Level of the Statistics Canada Rent Index for Vancouver (in real terms). The number of apartment dwellings starts in the C i t y of Vancouver in quarter x. Level of the Statistics Canada Construction Cost Index for B.C. (in real terms). A one quarter lag in NEWVRATE. A one quarter lag in RLRENT2. - 85 -Table A-2 (cont'd) Variable Number Symbol Description 98 R L C S T L A G A one quarter lag in REALCOST. 99 NEWVACMF The number of newly completed and unoccupied multiple family dwellings in the Ci t y of Vancouver in quarter x. 1) Sources of data: B.C. Assessment Authority records, B.C. Land Title Office, Statistics Canada, Real Estate Board of Greater Vancouver. - 86 A P P E N D I X " B " D E S C R I P T I V E S T A T I S T I C S - 87 -Table B-l DESCRIPTIVE STATISTICS "RESALES" FILE Standard Variable N Minimum Maximum Mean Deviation 1 . FILEN01 2 . MONTH 3. PRICE 4. FINANCE 5 . FILEN02 6.INTPMO 7.INTRATE 8. PURCHTYP 9. PURCHLOC 10.AGE 11.SUITES 12. AREA 13. AVERAGE 14. LOTSIZE 15. BACHS 16 . ONES 17. TWOS 18. THREES 19. FOURS 20. CONSTN 21. HEATING 22.STOREYS 23. PARKING 24. LAUNDRY 25. ELEV 26 . BALC 27 . POOLREC 59 59 59 58 59 37 58 57 44 59 59 59 59 58 54 54 54 54 54 56 58 59 59 50 59 55 58 103.00 4 . OOOO 66666. 0 . 103.00 0. 0. 0. 1.0000 5.OOOO 5.OOOO 4200.0 196.00 3050.0 0. 0. 0. 0. 0. . 0. 0. 1 . OOOO 0. 0. 0. 0. 0. 1112.0 16 .000 .30000 +7 .75000 +7 1112.0 26250. 17.200 48.OOOO 10.000 79.000 93.000 57229. 124 1 .0 35000. 60.000 68.000 21.000 7.OOOO 1.OOOO 1.OOOO 2.OOOO 17.000 3.OOOO 1.OOOO 2.OOOO 1.OOOO 1 . OOOO 816.19 13 . 458 .78522 +6 .60342 +6 816.19 2404 .4 10. 993 2.4561 2.9091 53.915 27.220 18760. 674.41 10566. 7 . 2593 17.463 2. 1852 .27778 .18519 - 1 . 19643 1 .3276 3 . 5763 1 .4746 .92000 .49153 .50909 .51724 -1 344.92 2 .5415 .70338 +6 .10686 +7 344.92 5248 . 5 3 . 5687 1 .5592 2 . 2805 24.883 19.111 13480. 169 . 16 6184.2 12.189 • 14.457 4 . 2563 1 . 2 196 .13608 .40089 .80324 2.6209 1 .0061 .27405 .59807 .50452 . 22340 - 88 -Table B-l (Cont'd) DESCRIPTIVE STATISTICS "RESALES" FILE Variable N Minimum Maximum Mean Standard Deviation 28.SAUNA 29.PENTHS .30.FILEN03 31 . TAXSHEI.T 32. GI 33. EXPENSES 34. N0I 35. RENTCONT 36. MTGPMT 37. ARPSUPP 38. ECC 39. RVALUE 40. ACC 41. ARPSTAT 42.INCDATE 43. FINDATR 44. FINDATC 45. FINAMT 46. FILEN04 47 . S0LD77 48.S0LD78 49.S0LD79-50.S0LD80 51 .REALAGE 52.LVRATIO 53.SPPSF 54.SPPSTE 55 . OERATIO 56.GIPERSTE 58 58 59 59 55 28 27 58 56 1 1 • 12 49 5 59 55 51 5 50 59 59 59 59 59 59 58 59 59 28 55 0. 0. 103.00 b. . 25000 2904 .0 9697 .0 0. I o. o. .10000 +6 74150. .25250 +6 0. 0. 1 .0000 42.000 21000. 103.00 0. 0. O. 0. 0. 0. 3.1503 3072 . 7 . 13158 .71429 -2 1.0000 2 .0000 1112.0 1O.OOO .25348 +6 56240. .14212 +6 1 .0000 .32562 +6 76263 . .43600 +7 .20690 +7 .17800 +7 1 .0000 127.00 193.00 131.00 .23100 +7 1112.0 1.0000 1.0000 1.0000 1.0000 75.000 1 12.50 93.329 61O00. .21638 +6 6231 . 3 .51724- - 1 . 12069 816.19 .45763 72979. 21305. 39329. .74138 60456. 19802. . .85451 +6 .51253 +6 .99806 +6 .13559 49.436 98.275 104.60 .38676 +6 815.83 . 16949 - 1 . 16949 - 1 .32203 .64407 26.492 2 . 5335 40.343 27606. 7728.3 2766.9 . 22340 . 37825 344.92 1 . 3432 59494 .' 18268. 30589. .44170 824 1 1 . 254 19 . .11690 +7 .41474 +6 .59411 +6 .34529 23.899 33.404 37.753 .42146 +6 344.62 .13019 .13019 .47 127 .48290 25.549 14.'698 . 17.129 10766. 40893. 1101.6 - 89 -Table B-2 DESCRIPTIVE STATISTICS "LANDSALES" FILE Variable N Minimum Maximum Mean Standard Deviation 1 . FILENO1 2. QUARTER 3. PRICE 4. LOTSIZE 5. FRONTAGE 6. DEPTH 7. WESTEND 8. KITS 9 . EASTVAN 10. MARPOLE 11. KERRISDL 12. BCPOP 13. BCPERINC 14. UNEMPLUA 15. UNEMPLSA 16. COMPLVAN 17. FILEN02 18 . COMPLBC 19. CPIALL 20. CPIHOUSG 21 .NONFAMHH 22. VACRATE 23. NHARATE 24. CONVRATE 25. MURBSTAT 26. CCASTAT 27. CCANEW 28. CCANEWWP 29. ARPSTAT 30. RENTCONT 31. HOLDPER 1 15 115 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 115 102 1001.0 .37 .000 18000. 2950.0 25.000 100.OO O. 0. 0. 0. 0. 2223.6 3859 . 3 6.OOOO 5.5300 104.00 1001 .0 5846 .0 102.70 101.33 26.640 .10000 8 . 8900 8 .9800 0. O. 0. O. O. 0. O. 6025.0 63 .OOO .15000 +7 67054 . 400.00 168.OO 1.OOOO 1.OOOO 1.OOOO I. OOOO 0. 2533 . 2 8677 . 8 9.6300 9 . 0700 1353.0 6025.0 12091. 176.27 170.50 28.870 2 . OOOO 1 1 . 880 II. 980 1.OOOO 1 . OOOO 1 . OOOO 1 . OOOO 1 . OOOO 1 . OOOO 5^ . OOOO 2220.5 54 .652 .15293 +6 9285 . 1 72.817 123.06 .86957 -1 .28696 .60870 . 17391 -1 0. 2451 .8 7094 . 3 8.1999 8.3520 755.77 2220. 5 8187 . 6 150.83 147 . 17 28.297 .84000 10.620 10.583 .85217 .34783 -1 .86087 .85217 .85217 .86957 1 . 2255 : 1992 . 2 7 . 1390 .20603 +6 1 1446. 75.698 9 . 0934 .28300 .45432 .49018 .13130 86.515 1360.9 .6271 1 .52081 219.22 1992.2 1201 . 5 20.648 21.184 .60357 .49187 . 83352 .82093 . 35648 .18403 .34760 .35648 •. 35648 .33826 .70229 -90 Table B-2 (Cont'd) DESCRIPTIVE STATISTICS "LANDSALES" FILE Variable N Minimum Maximum Mean Standard Deviation 32 . SPPERSF 33.SPPERFF 34.SPPERDF 35. DEFLATOR 36. REALSP 37. REALPPSF 38. CPINEW 39. NEWREALP 40. RLINTRTE 4 1 . POPGRRTE 42.REALINIC 43.INCGRRTE 44. NEWQTR 45. RENTLEVE 46. GRRTRENT '4 7 .CONSTNCO 48. GRRTCOST 49. RENTGRTH 50. COSTGRTH 51. POPGRTH 52. GRRLINC 53.INF LAT 10 54 .GRRLRNT 55.REALINT 56 . RE ALRENIT 57. CCOSTBC 58. RNTGRTH2 59. RNTGRTH3 60. LAGRENT 61. LAGCOSTS 1 15, 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 112 1 12 4 . 2853 539 . 77 150.00 1 . 2470 14320. 2 . 1200 1 .0270 2 . 7578 5.9454 1 .0084 3757 . 8 1 .0168 37.000 168.80 1 .6880 105.10 1 .0510 0. 2 .0000 .77000 - 1 . 8000 3.8500 -8.0200 - 1 . 6 100 157.7 1 3.2600 1 . 1900 -14.890 -9.9900 -7.8800 33.898 4242.4 8928 . 6 2 .6520 .70588 +6 15.863 1.7627 21 .541 8 . 7537 1.1488 4923.0 1 . 3320 63.000 . 278.OO 2 . 7800 194.50 1 . 9450 14.900 i20.100 4 .0100 9 .0400 12.230 1 1 .840 5 . 2900 ' 182 .02 21 . 320 7 . 9500 17.410 1 . 7700 7.6400 16 . 585 2039.7 1 198 .0 2 .0897 75246. 7 .9269 1 . 5083 10.807 7.1474 1.1119 4658 . 8 1.2605 54.652 251.02 2.5102 162.67 1 .6267 5.6250 8.3714 1.5454 3.5627 7.5704 - 1 .8899 3 .0391 166.31 9.1174 4.91 19 7.6050 --2.0659 3.4312 . 6.2763 794.80 ' 1399.7 .45541 .10029 +6 2.7262 .20648 : 3.5675 .87049 ' .39234 -1 i ! 336.06' . .90929 -1 7.1390 32.821 .3282 1 ; 24.040 ' .24040 2.8106 5.2952 .63257 2 .6694 1 .9916 3 . 2739 1 . 4552 3. 1433 4 . 9600 1 . 9262 7.2952 2.9628 4.6865 91 Table B-2 (Cont'd) DESCRIPTIVE STATISTICS "LANDSALES" FIL E Variable N Minimum Maximum Mean Standard Deviation 62. RNTGRTH4 63. CC0STBC2 64. CAPRATE 65. CAPRTLAG 66. NOMCAPRT 67. CAPGAIN 68. CAPGNLAG 69. POPLAG 70. RLAPTRTN 71. RLINCLAG 72 . VACRTLAG 73.RLINTLAG 74 . APRTNLAG 75.INFLALAG 76.INTCHGE 77 . APTCOMCH 78. HHCHANGE 79. RLINTCHG 80. ERCHANGE 8 1 .APT5TSCH 82. NEWWE 83. NEWKITS 84. NEWEV 85 . NEWMA.R 86 . NEWKERR 87.SUBVACRT 88. NEWVACCH 89. REZONING 90. VACRTCHG 1 12 1 12 1 12 112 112 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 112.' 1 15 1 12 1 12 1 12 10 33 70 2 O 1 12 1 12 1 15 1 12 -5.8300 -3 . 8 100 -4.9000 -5.1000 1 1 .000 - 5 . 9000 -6.9400 . 77000 -5.4300 - 1 . 8000 . 10000 -5.8900 -.88000 2 . 7300 -.65000 -908.00 341.00 -8 . 8200 - 2 . 3 100 -737 .00 1 . OOOO 1 . OOOO 1 . OOOO 1 . OOOO - . 70000 -221.00 O. - . 7 5000 - 1 . 1800 12.370 10.520 10.410 13.780 13.030 13.030 3 . 4000 5 . 2300 9 . 6900 2 . 1000 6 . 3800 5 . 1400 15.900 .83000 6 1 3 . 00 663.00 10.010 2 . 1300 698.00 1 . OOOO 1 . OOOO 1 . OOOO 1.OOOO .55000 156.00 1.OOOO .30000 -2.6585 1 .5471 5.0375 5 . 1224 12.735 5.7 133 3.2793 1 .537 1 1 .9984 3.9503 .84241 3.4554 1.6670 7.2872 -. 13321 19.491 559.40 -.54357 , .45866 243.66 ; 1.OOOO 1.OOOO i 1.OOOO 1.OOOO .15670 -13.911 . 77391 . 174 1 1 - 1 1.1913 4.7458 3.1156 3.3439 .73109 6.1479 5.0261 .77142 2 . 3157 2.471 1 . 55905 2 . 5880 1 . 4522 2 . 8396 .27534 258.36 151.08 3.7617 1 . 2049 427.35 .22546 80.628 .42013 .19759 92 Table B-2 (Cont'd) DESCRIPTIVE STATISTICS "LANDSALES" FIL E Variable N Minimum Maximum Mean Standard Deviation 91. NEWHH 92. NEWVRATE 93. RLRENT2 94.STARTS 95. REALCOST 96. NEWVRLAG 97. RLRNTLAG 98 . RLCSTLAG 99.NEWVACMF 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 1 12 -418.00 1 . 1 200 34.070 32.000 1 12 . 24 1 . 1200 35.450 103.11 3 1 .000 2133.O 29.200 91 .020 1385 .0 153.67 29.200 95.160 151 .46 553.00 19.2 .93 16.625 48.012 822 . 13 131.27 17.184 49.755 129.91 349.99 760.19 7 . 1638 16.272 437.97 1 1 . 740 7 . 8095 16.754 14.404 137.33 - 93 -APPENDIX "C" SCATTER PLOTS - 94-N = 115 OUT OF 115 42.REALINC VS. 2.QUARTER REALINC ^ ^ * * * 4923.0 + 9 X X '• + 6 • 6 4690.O + 8 4 7 + 6 3 4456.9 + 4223.9 3990.9 + 3 + 3 3757.8 +6 + + + ---- + + + + + + + + 3 7 OOO 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7SCATTER V=93,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 93.RLRENT2 VS. 2.QUARTER RLRENT2 9 1.020 +6 3 3 79.630 68.240 + * O N + 56.850 + + 6 45.460 + 4 66 7 8 X 9 X 34.070 + + -- + + . 37.OOO 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7SCATTER V=93,25 CASES=380~388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 93.RLRENT2 VS. 25.MURBSTAT RLRENT2 91 .020 +6 79.630 + 2 68.240 + 56.850 + 45.460 + 34.070 • + + -o. .40000 .80000 MURBSTAT 20000 •60000 1•0000 COMMAND 7SCATTER V=22,92 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT "OF 115 22.VACRATE VS. 92.NEWVRATE VACRATE 2 .0000 +6 1.6200 + 1.2400 + . 86000 + . 48000 + 10000 + 4 1 . 1200 - + 6 . + + + + y V + + 12.352 23.584 NEWVRATE 6.7360 17.968 29.200 COMMAND 7SCATTER V=12,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 115 OUT OF 115 12.BCP0P VS. 2.QUARTER BCPOP 2533.2 + X 9 6 I O N I 2471.3 + 8 6 4 7 + 3 6 2409.4 + 2347 . 4 2285 . 5 + 3 3 2223.6 +6 + - - + 37.000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7SCATTER V=51,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE/5': 380-388 , 390-396 , 398-496 N= 112 OUT OF 115 51.POPGRTH VS. 2.QUARTER POPGRTH 4.0100 + * 3.3620 +6 2.7140 + 2.0660 + 3 2 3 6 X I 00 O N I 1.4180 + 66 X .77000 + 7 + + + + + + + + + + + 37 000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7SCATTER V=12,25 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 115 OUT OF 115 12.BCP0P VS. 25.MURBSTAT BCPOP 2533.2 + 247 1 . 3 2409.4 + 2347.4 +* 2 2285.5 + + 3 3 2223.6 +6 - + -.40000 .80000 MURBSTAT . 20000 •60000 1•0000 COMMAND 7SCATTER V = 51,25 CASES = 380-388 , 390-396 ,'398-496 I O N O N I APPENDIX "D" RESIDUAL PLOTS - 100 -SCATTER PLOT CASES=CASE# : 380-388,390-396,398-496 N = 112 OUT OF 115 51.POPGRTH VS. 25.MURBSTAT POPGRTH 4.0100 +* + 3.3620 +6 + * 2.7 140 + + 2.0660 +5 3 X 4 1.4180 + * 8 .77000 + 7  + + + + + + + + + + + 0 .40000 .80000 MURBSTAT .20000 •60000 1•OOOO COMMAND ?REG V = 39,7,9.25,22,92,42,55,93,94,95,51,70 CASES = 380-388 , 390-396 , 398-4.96-LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 F-STAT SIGNIF 1 1 . 984 . OOOO OURCE DF SUM SQRS MEAN SQRREGRESSION 12 852.31 71.026 ERROR 99 586.76 5.9268 TOTAL 1 1 1 1439 . 1 MULT R= .76959 R-SQR= .59227 SE= 2.4345 VARIABLE PARTIAL CONSTANT COEFF STD ERROR -252.63 61.277 T-STAT -4.1228 SIGNIF .0001 I —< O I Run Number 1 7 . WESTEND .17877 1.8095 9 . EASTVAN -.48526 -3.2618 25 . MURBSTAT -.14320 -5.6441 22 . .VACRATE -.15886 - 1.6637 92 . NEWVRATE .06005 .4994 1 42 .REALINC .40488 .58387 55 .REALINT -.07 194 -.34626 93 .RLRENT2 .33421 .84497 94 .STARTS -.36522 -.35193 95 .REALCOST -.36422 -.30203 51 .POPGRTH .13345 1.4186 70 .RLAPTRTN -.21386 -.37337 1.0009 1.8078 .0737 .59069 -5.5220 .0000 3.9203 -1.4397 .1531 1.0392 -1.6010 .1126 -1 .83433 -1 .59857 .5508 -1 .13252 -1 4.4057 .0000 .48247 -.71767 .4746 .23949 3.5282 .0006 -2 .90157 -3 -3.9035 .0002 .77618 -1 -3.8912 .0002 1.0589 1.3398 .1834 .17140 -2.1783 .0318 COMMAND ? SAVE V100=RESIDUAL LABEL FOR THE RESULT VARIABLE(S) = RESI DUAL CASES TO SELECT =380-388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396.398-496 VARIABLE TOTAL VALID MISS 100.RESIDUAL 115 112 3 COMMAND 7SCATTER V=100,39 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 39.NEWREALP RESIDUAL 6 . 2029 * * * 2 3.2202 + 2 + * * * 2 * * * * 2 * 2522* * 3 .23750 + * 22 * 2 * 3 * 53 * *2 *2*** 2 *2 + * * * * 2 * * * * * * 2 * * * * 2 * -2.7452 + * I O -5.7279 + -8.7106 +* + + + + + + + + + + + 2 7 5 7 8 10.271 17.784 NEWREALP 6.5144 14.027 21.541 COMMAND 7SCATTER V=100,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 2.QUARTER RESIDUAL 6.2029 + * .3.2202 + .23750 + * 2 * * * * * * * * * 2 2 4 * * * 2 3 2 4 * * 4 3 2 * 3 5 2 * * . *2 * 5 * 2 2 * * * 3 3 * * * * 2 -2.7452 + -5.7279 + + -8.7106 + + + + + + + + + + -' + + 3 7 000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND ?HISTOGRAM V=100 INT=10 OP=HIST% CASES TO SELECT =380-388,390-396,398-496 I CO O HISTOGRAM CASES=CASE#:380-388,390-396,398-496 MIDPOINT HIST% COUNT FOR 100.RESIDUAL (EACH X= 1) -8.7106 9 1 + X -7.0535 0. 0 + -5 . 3965 3 . .6 4 + XXXX -3 . 7394 2 . . 7 3 + XXX -2 .0824 16 . . 1 18 +XXXXXXXXXXXXXXXXXX - . 42532 34 . 8 39 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX. 1 . 2317 26 .8 30 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX 2.8888 9 .8 1 1 +XXXXXXXXXXX 4.5458 4 . 5 5 +XXXXX 6.2029 . 9- 1 + X MISSING 3 (INTERVAL WIDTH= 1.6571) TOTAL 1 15 COMMAND 7TRANS V101=V100/2.4345 LABEL FOR THE RESULT VARIABLE(S) =STANDRES CASES TO SELECT =380-388,390-396,398-496 DIVIDE TRANSFORMATION CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS 101.STANDRES 115 112 3 COMMAND 7SCATTER V=101',2 CASES = 380-388 , 390-396 , 398-496 SCATTER PLOT CASES = CASE/f : 380-388,390-396,398-496 N= 112 OUT OF 115 101.STANDRES VS. 2.QUARTER STANDRES 2.5479 + * 1.3227 + .97556 -1+ * 3 2 2 * * 2 2 4 * * * 2 3 2 4 * * 4 3 5 *' *2 * 5 * 2 2 * * * 3 3 * * * * 2 •3-O • 1 . 1276 + -2.3528 + -3.5780 + + + 4- + + + + + + + + 37.OOO 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND ,„„ ?REG V = 39,7,9,25,22,92,52, 55,60,94,95,51 ,70 CASES=380-388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F -STAT SIGNIF REGRESSION 12 765 .63 63.803 9 . 3794 .0000 ERROR 99 673 . 44 6.8024 TOTAL 1 1 1 1439 . 1 MULT R= .72941 R-SQR= .53203 SE= 2.6081 VARIABLE PARTIAL COEFF STD ERROR T -STAT SIGNIF CONSTANT -8.6634 5.2630 -1 .6461 . 1029 7 .WESTEND .25848 2 .7661 1.0390 2 .6623 .0091 9 . EASTVAN - .44710 -3.13 17 .62970 -4 .9733 .0000 25 .MURBSTAT .32397 8.3651 2.4551 3 .4072 .0010 22 .VACRATE .01123 .17959 1.6069 1 1 177 .9112 92 .NEWVRATE .15198 .13919 .90979 -1 1 . 5299 . 1292 52 .GRRLINC .19347 .68528 . 34927 1 .9621 .0526 55 .REALINT -.04331 -.26336 .61060 -.43131 .6672 60 .LAGRENT -.21939 .23084 .10317 2 . 2374 .0275 94 .STARTS -.18856 -.17540 -2 .91811 -3 - 1 .9104 .0590 95 .REALCOST .23555 .74282 -1 .30802 -1 2 .4116 .0177 5 1 .POPGRTH .19694 2.2256 1.1136 1 .9986 .0484 70 . RLAPTRTN -.27027 -.65161 .23329 -2 . 7931 .0063 COMMAND 7SAVE V100=RESIDUAL LABEL=RESIDUAL CASES=380-388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS I O Run Number 2 100.RESIDUAL 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND 7SCATTER V=100,39 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 39.NEWREALP RESIDUAL 7.0373 + 4.0374 + 1.0375 + -1.9625 + 2 * 2 * * * * * 4 2 *3 * 2 53 * * * 2 * 3 * 2* *3 3 3 2 3 * * * * * * ) * * * * 2 * 2 -4.9624 + -7.9623 + * + 2.7578 10.271 6 . 5144 14.027 17.784 NEWREALP 21 . 541 COMMAND 7SCATTER V=100,2 CASES = 380~388,390-396 , 398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 2.QUARTER RESIDUAL 7 .0373 + * + N O o I 4.0374 + * + * * * * 2 * * * 4 1 .0375 + ** * .* 2 * 4 * 2 3*4 * 3 2 5 + * * 2 3 * * 2 3* 4 5 3 * 2 * * * -1.9G25 +2 * * * * 2 * * * * * + * * * -4.9G24 + -7.9623 + * + + + + + + + + + + + 37.000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND ?HISTOGRAM V=100 INT=10 OP=HIST% CASES TO SELECT =380-388,390-396,398-496 HISTOGRAM CASES = CASE# : 380-388.390-396,398-496 MIDPOINT HIST% COUNT FOR 100.RESIDUAL (EACH X= 1) -7.9623 9 1 +X -6.2957 1 . 8 2 + XX -4.6290 2 . . 7 3 + XXX -2.9624 7 . . 1 8 +XXXXXXXX - 1 .2958 33 .0 37 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX .37081 31 . 3 35 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX 2.0374 13 . 4 15 +XXXXXXXXXXXXXXX 3.7040 4 . 5 5 +XXXXX 5.3707 2 .7 3 + XXX 7.0373 2 .7 3 +XXX MISSING 3 TOTAL 115 (INTERVAL WIDTH= 1.6666) COMMAND 7TRANS V101=V100/2.6081 CASES=380-388,390-396,398-496 LABEL FOR THE RESULT VARIABLE(S) i o =STANDRES DIVIDE TRANSFORMATION CASES=CASE#:380-388,330-396,398-496 VARIABLE TOTAL VALID MISS 101.STANDRES 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND 7SCATTER V=101.2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 101.STANDRES VS. 2.QUARTER STANDRES 2.6982 + * 1.5480 2 00 .39778 + * * 3 .75245 +2 * * 4 * * 2 * 4 2 3*4 3 2 5 * 2 3 * 2 3* 4 5 O 1.9027 -3.0529 + + -37 000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7REG V=39,7,9,25,22,92,52,55,93,94,63,51,70 CASES=380-388.390-396,398-496 LEAST SQUARES REGRESSION CASES = CASE/S': 380-388 , 390-396 , 398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SOR F--STAT SIGNIF REGRESSION 12 777 . 58 64.799 9 .6980 .0000 ERROR 99 66 1 . 48 6.6816 TOTAL 1 1 1 1439 . 1 MULT R= .73508 R-SQR= .54034 SE= .2.5849 VARIABLE PARTIAL COEFF STD ERROR T -STAT SIGNIF CONSTANT 10.362 7.1117 1 .457 1 . 1483 7 . WESTEND .22442 2.4837 1.0839 2 .2914 .024 1 .9 . EASTVAN -.45866 -3.1962 .62236 -5 . 1356 .0000 25 . MURBSTAT .01987 .64773 3.2757 19774 .8437 22 .VACRATE -.12310 -1.9362 1.5687 -1 . 2342 . 2200 92 .NEWVRATE .32202 . 33336 .98500 -1 3 . 3843 .0010 52 .GRRLINC .04208 .12366 .29512 41901 .6761 55 .REALINT . 1822 1 .99055 .53722 1 .8438 .0682 93 .RLRENT2 -.15570 -.11392 .72638 -1 -1 .5683 . 1200 94 .STARTS -.32828 -.41391 -2 .11970 -2 -3 .4580 .0008 63 .CC0STBC2 -.22526 - .21,603 .93908 -1 -2 . 3004 .0235 51 .POPGRTH .23632 2.7463 1.1349 2 .4198 .0174 70 .RLAPTRTN -.15033 -.35266 .23309 - 1 .5 129 . 1335 COMMAND 7SAVE V100=RESIDUAL LABEL = RESIDUAL CASES=380~388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS 100.RESIDUAL 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND 7SCATTER V=100,39 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 39.NEWREALP RESIDUAL 8.2391 + + * 5.1610 + * 2 * * + Run Number 3 i O N o 2.0830 + * 3 * * * * * * * * 3 * * 4 * * * * + * * **2 *** * * * *622* * *2 -.99504 + ** 4 * * * 2 3 ** * 2 2 * 32* * 4- * * * -4.0731 + -7.1511 2 7578 10.271 17.784 NEWREALP 6.5144 14.027 21.541 COMMAND 7SCATTER V=100,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 2.QUARTER RESIDUAL 8.2391 + * + 5 . 1610 + 2.0830 + * * * * * -.99504 + 3 2 + * -4.0731 + * * 2 * * * * 2 * 3*2 * 2 6 2 * 2 2 * * * 22 3 7 * * * * 4 * * 5 ** 3 * 2 * 2 * * -7.1511 + + H 1 + + + + + + + r 37.OOO 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND ?HISTOGRAM V=100 INT=10 OP=HIST% CASES TO SELECT =380-388,390-396,398-496 HISTOGRAM CASES=CASE#:380-388.390-396,398-496 MIDPOINT HIST°/„ COUNT FOR 100.RESIDUAL (EACH X= 1) -7.1511 .9 i + X -5 .44 1 1 3 . 6 4 + XXXX -3.7311 4 . 5 5 +XXXXX -2 .0210 18 . 8 21 +XXXXXXXXXXXXXXXXXXXXX - .31103 35 . 7 40 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX 1 . 3990 25 .0 28 +XXXXXXXXXXXXXXXXXXXXXXXXXXXX 3 . 1090 3 .6 4 +XXXX 4 .8190 6 . 3 7 +XXXXXXX 6.5291 .9 1 + X 8.2391 . 9 1 +x PASSING 3 (INTERVAL WIDTH= 1.7100) TOTAL 1 15 COMMAND 7TRANS V101=V100/2.5849 LABEL=STANDRES CASES=380-388,390-396,398-496 DIVIDE TRANSFORMATION CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS 101.STANDRE S 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND 7SCATTER V=101,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 101.STANDRES VS. 2.QUARTER STANDRES 3.1874 + * 1.9966 + * * * 2 * .80583 + * * * * * 2 * * 3*2 * * 2 6 + * * 2 * 2 2 * * * * 22 3 7 ^ * * * * -.38494 + 4 * * 5 3 * * 3 2 * 2 * 2 + * * * •1.5757 + -2.7665 + * + ___._ + + + + + + + + + + 37 000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND „ „„„ 7REG V = 39.7,9,25,22,92.52. 55,60,94,63.51.70 CASES = 380-388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F -STAT SIGNIF REGRESSION 12 784 . 78 65.398 9 . 8953 .0000 ERROR 99 654.29 6.6090 TOTAL 1 1 1 1439. 1 MULT R= .73847 R-SQR= .54534 SE = 2.5708 VARIABLE PARTIAL COEFF STD ERROR T -STAT SIGNIF CONSTANT .56185 3.5761 1571 1 .8755 7 .WESTEND . 29935 3.2022 1.0258 •3 .1216 .0024 9 .EASTVAN -.46335 -3.2222 .61937 -5 . 2024 .OOOO 25 .MURBSTAT .21785 5.2002 2.34 14 2 . 2210 .0286 22 .VACRATE -.16632 -2.4589 1 .4652 - 1 .6783 .0965 92 .NEWVRATE .35359 .35300 .93856 -1 3 . 76 1 1 .0003 52 .GRRLINC .066 19 .19922 .30184 .65999 .5108 55 .REALINT .17967 .96650 .53185 1 .8172 .0722 60 .LAGRENT .18669 . 18379 .97205 -1 1 .8908 .0616 94 .STARTS -.30850 -.38300 -2 . 1 1869 -2 -3. 2270 .0017 I Run Number 4 63.CC0STBC2 - .28695 -.27091 .90895 -1 -2.9804 .0036 51.POPGRTH .28434 3.2185 1.0907 2.9509 .0040 70.RLAPTRTN - .18637 - .43530 .23063 -1.8875 .0620 COMMAND 7SAVE V100=RESIDUAL LABEL = RESIDUAL CASES = 380"388,390-396 . 398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS 100.RESIDUAL 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND 7SCATTER V=100,39 CASES=380~388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 39.NEWREALP RESIDUAL 9..2064 + 5.9503 + 2.6942 + -3.8180 + 2 * * * * * * * 2 * * + * 4 * * * * * * * 23 * 2 * * 72 * .56190 + * 2 2 * * * * *2 ** * 3 2 * * 4 2 + ** 2 * 24 * * * * * * * * * * -7 .0741 + - -+ ,7578 10.271 17.784 NEWREALP 6 .5144 14.027 21.541 I I COMMAND 7SCATTER V=100,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 100.RESIDUAL VS. 2.QUARTER RESIDUAL 9.2064 + * 5.9503 + 2.694 2 + * + * * * * * .56190 + 5 -3.8180 + * * * * 2 * * * 2 2 2 * 2 * * 3 6 2 * 2 4 2 3 5 * 2 2**3 * 3 * 3 * 4 3 2 * 2 + -7.0741 37.000 47.400 57.800 42.200 52.600 QUARTER 63.000 COMMAND ?HISTOGRAM V=100 INT=10 OP=HIST% CASES TO SELECT =380-388,390-396.398-496 HISTOGRAM CASES=CASE#:380-388,390-396.398-496 MIDPOINT HIST% COUNT FOR 100.RESIDUAL (EACH X= 1) -7.074 1 -5.2652 -3.4562 -1 . 6473 . 16168 1 .9706 14 20 35 17 1 1 16 23 +X + X +XXXXXXXXXXXXXXXX +XXXXXXXXXXXXXXXXXXXXXXX 40 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX 19 +XXXXXXXXXXXXXXXXXXX 3 . 7796 8 . .0 9 +XXXXXXXXX 5.5885 1 . 8 2 + XX 7 . 3975 0 0 + 9 . 2064 .9 1 +x MISSING 3 TOTAL 1 15 (INTERVAL COMMAND 7TRANS V101=V100/2.5708 LABEL=STANDRES CASES=380-388,390-396,398-496 DIVIDE TRANSFORMATION CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS 101 . ST ANDRES 115 112 3* * CASES CHANGED IN EXISTING VARIABLE COMMAND ?HISTOGRAM V=101 INT=10 CASES=380-388,390-396,398-496 OP=HIST% HISTOGRAM CASES=CASE#:380-388,390-396,398-496 MIDPOINT HIST% COUNT FOR 101.STANDRES (EACH X= 1) -2 . 7517 .9 1 + X -2.0481 .9 1 + X - 1 . 3444 14 . . 3 16 +XXXXXXXXXXXXXXXX -.64076 20 . 5 23 +XXXXXXXXXXXXXXXXXXXXXXX .62893 -1 35 . 7 40 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX . 76655 17 .0 19 +XXXXXXXXXXXXXXXXXXX 1 . 4702 8 .O 9 +XXXXXXXXX 2.1739 1 .8 2 + XX 2.8775 0 0 + 3.5812 .9 1 + X MISSING 3 (INTERVAL WIDTH= .70365) TOTAL 1 15 COMMAND . 7SCATTER V=101,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 101.STANDRES VS. 2.QUARTER STANDRES 3.5812 + * 2.3146 + I 1.0480 + * * * .21857 + 2 2 2 * 2 * * 3 6 2 * 2 4 2 3 5 * 2 2 * * 3 * 3 * 3 * 4 3 2 * 2 -1.4851 + -2.7517 + 37.000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND 7REG V=39,25 CASES=380-388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 I ANALYSIS OF VARIANCE OF 39 .NEWREALP N = 115 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F-STAT SIGNIF REGRESSION 1 181.88 181.88 16.195 .0001 ERROR 113 1269 .0 1 1 .230 TOTAL 1 14 1450.9 MULT R= .35405 R-SQR: = .12535 SE= 3.3512 VARIABLE PARTIAL COEFF STD ERROR T-STAT SIGNIF CONSTANT 7.7878 .81278 9.5817 .0000 25.MURBSTAT 35405 3.5432 .88046 4.0243 .0001 COMMAND „„_ 7REG V=39,7,9,25,22,92,52,55,60,94,63,51.70,38 CASES=380-388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N = 112 OUT OF 115 * CASES CHANGED IN EXISTING VARIABLE VARIABLE TRANSFORMATION STRAT=NEWQTR:51 VARIABLE TOTAL VALID MISS 98.RLCSTLAG 3 3 0* * CASES CHANGED IN EXISTING VARIABLE End of command f i l e "*SOURCE*" at l i n e 999 (} COMMAND ?REG V=39,25 CASES=380~388,390-396,398-496 STRATA=NONE LEAST SQUARES' REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 115 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F-STAT SIGNIF REGRESSION 1 181.88 181.88 16.195 .0001 ERROR 113 1269.O 11.230 TOTAL 114 1450.9 MULt R= .35405 R-SQR= .12535 SE= 3.3512 VARIABLE PARTIAL COEFF STD ERROR T-STAT SIGNIF CONSTANT 7.7878 .81278 9.5817 .0000 25.MURBSTAT .35405 3.5432 .88046 4.0243 .0001 COMMAND 7SAVE V200=RESIDUAL OPTION=TEST LABEL=RESIDUAL CASES=380-388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 115 115 O 1.4775 1 COMMAND ?HISTOGRAM V=200 INT=20 OP=HIST% CASES=380-388,390-396,398-496 . HISTOGRAM CASES=CASE#:380-388,390-396,398-496 MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) -8 .5732 .9 i +X -7 .4127 O. 0 + Run Number 9 i -6 .2522 . 9 1 +x -5 .0918 1 . 7 2 + XX -3 .9313 3 . 5 4 + XXXX -2 .7708 13 . 9 16 +XXXXXXXXXXXXXXXX - 1 .6103 28 . 7 33 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX - .44979 16 . 5 19 +XXXXXXXXXXXXXXXXXXX .71070 7 .0 8 +XXXXXXXX 1 .8712 7 .8 9 +XXXXXXXXX 3.0317 5 . 2 6 +XXXXXX 4 . 1922 2 . 6 3 + XXX 5.3527 3 .5 4 + XXXX 6 .5132 4 . 3 5 +XXXXX 7.6737 .9 1 +x 8.8341 .9 1 +x 9 .9946 .9 1 +x 11.155 0 0 + 12.316 0 0 + 13 .476 .9 1 +x TOTAL 115 (INTERVAL WIDTH= 1.1605) COMMAND SCATTER V=200,2 CASES= 380-388,390-396.398-496 SCATTER PLOT CASES=CASE# : 380-388 , 390-396 , 398-496 N = 115 OUT OF 115 200.RESIDUAL VS. 2.QUARTER RESIDUAL 13.476 + * 9 .0662 + * • * 4.6564 + 2 3 2 * .24651 + 3 * + 2 * * * 5 * 2 * * * * 2 2 * * * 3 4 4 * 4 7 * * * 7 2 * 3 * 2 * * 3 -4.1634 + -8.5732 + I 0 0 + + + + + + + + + + + 37 .000 47 .400 57 .800 QUARTER 4 2 . 2 0 0 52 .600 63 .000 COMMAND ?REG V = 3 9 , 7 , 9 , 2 5 , 2 2 , 9 2 , 5 2 , 5 5 , 6 0 , 9 4 , 6 3 , 5 1 , 7 0 , 5 3 CASES=380~388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#: 380-388 , 390-396 , 398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F- STAT SIGNIF REGRESSION 13 844.46 64 .958 1C i. 706 .0000 ERROR 98 594.61 6.0675 TOTAL 111 1439 . 1 MULT R= .76603 R-SQR= .58681 SE= 2 .4632 VARIABLE PARTIAL COEFF STD ERROR T- STAT SIGNIF CONSTANT 33.083 10.921 3 . 0293 .0031 7 . WESTEND .37307 4.0617 1.0204 3 . 9806 .0001 9 . EASTVAN - .44450 -2.9469 .5999 1 -4 . 9123 .0000 25. .MURBSTAT .36552 13.287 3.4179 3 . 8875 .0002 22 . VACRATE -.30921 -5.4805 1.7027 -3 . 2188 .0017 92 .NEWVRATE .43885 .47177 .97577 -1 4 . 8348 .0000 52 . GRRLINC . 23838 .87753 .361 14 2 . 4299 .0169 55 . REAL INT - .19115 -2.1565 1.1186 -1 . 9278 .0568 60 .LAGRENT .26034 .25613 .95951 -1 2 . 6693 .0089 94 . STARTS - .41933 - .79959 -2 .17486 -2 -4 . 5726 .0000 63 . CC0STBC2 - .40256 -.66067 .15176 -4 . 3535 .0000 51 .POPGRTH . 36235 4. 1977 1.0907 3 . 8486 .0002 70 .RLAPTRTN - .32428 - .90736 .26737 -3 . 3936 .0010 53 . INFLATIO -.30201 -3.7397 1 . 1924 -3 . 1362 .0023 COMMAND 7SAVE V200=RESIDUAL OPTION=TEST LABEL=RESIDUAL CASES=380-388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 115 112 3* 2 .0430 13 * CASES- CHANGED IN EXISTING VARIABLE COMMAND • ?HISTOGRAM V = 200 INT = 20 OP=HIST°/„ CASES = 380~388 , 390-396 , 398-496 HISTOGRAM CASES=CASE#:380-388,390-396,398-496 With INFLATION v a r i a b l e MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) - 6 . 7 2 6 5 9 1 +X - 5 . 9 5 2 2 0 . 0 + - 5 . 1 7 7 9 0 . O + - 4 . 4 0 3 5 1 . 8 2 +XX - 3 . 6 2 9 2 4 . 5 5 +XXXXX - 2 . 8 5 4 9 6 . 3 7 +XXXXXXX - 2 . 0 8 0 5 8 . 9 10 +XXXXXXXXXX - 1 . 3 0 6 2 10 . 7 12 +XXXXXXXXXXXX - . 5 3 1 8 9 12. .5 14 +XXXXXXXXXXXXXX . 2 4 2 4 3 17 . 9 2 0 +XXXXXXXXXXXXXXXXXXXX 1 . o i ' 6 8 13 .  4 15 +XXXXXXXXXXXXXXX 1 . 7 9 1 1 7 . . 1 8 +XXXXXXXX 2 . 5 6 5 4 4 , 5 5 +XXXXX 3 . 3 3 9 7 6 . 3 7 +XXXXXXX 4 . 1 1 4 1 3 . 6 4 +XXXX 4 . 8 8 8 4 0 0 + 5 . 6 6 2 7 0 d + 6 . 4 3 7 1 .9 1 7 . 2.1 14 0 o + 7 . 9 8 5 7 .9 i +x MISSING 3 (INTERVAL WIDTH= . 7 7 4 3 3 ) TOTAL 1 15 COMMAND 7SCATTER V=200,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES = CASE/? :380-388,390-396,398-496 N= 112 OUT OF 115 200.RESIDUAL VS. 2.QUARTER RESIDUAL 7.9857 + 5 .0433 2 . 1008 - .84162 -3.784 1 + 3 2 * * * * * 2 2 * 5 * * 2 * 3 5 6 2 2 * 6 2 * * * * * * * 4 * 3 2 * 2 3 2 * 2 * 2 * O CM + -6.7 265 + 37.000 47.400 57.800 QUARTER 42.200 52.600 63.000 COMMAND ?REG V = 39,7,9,8,25,22,92.52,55,60,94,63,51 .70 CASES = 380-388.390-396,398-496 LEAST SQUARES REGRESSION CASES^ CASE*:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F -STAT SIGNIF REGRESSION 13 784.79 60.368 9 .0421 .0000 ERROR ,98 654.28 6.6763 TOTAL i 1 1 1439 . 1 MULT R= .73847 R-SQR= .54534 SE= 2.5839 VARIABLE PARTIAL COEFF STD ERROR T -STAT SIGNIF CONSTANT .62439 4.0269 15505 .8771 7 .WESTEND .14929 3.1392 2.1004 1 .4946 . 1382 9 .EASTVAN - . 16813 -3.2857 1.9460 - 1 .6884 .0945 8 .KITS -.00348 -.68919 -1 2.0010 34441 -1 .9726 25 .MURBSTAT .21712 5.1946 2.3591 2 . 2019 .0300 22 .VACRATE - . 16621 -2.4621 1 .4756 -1 .6686 .0984 92 .NEWVRATE . 35253 .35330 .94738 -1 3 .7293 .0003 52 .GRRLINC .06616 .19913 .30339 65635 .5131 55 .REALINT .17873 .96881 .53873 1 . 7983 .0752 60 .LAGRENT .18669 . 1839 1 .97763 -1 1 .8812 .0629 94 .STARTS -.30657 -.38353 -2 .12029 -2 -3 . 1884 .0019 63 .CC0STBC2 -.27979 -.27169 .94174 -1 -2 .8850 .0048 51 .POPGRTH .28410 3.2206 1.0979 2 .9333 .0042 70 .RLAPTRTN -.18640 -.43538 .23181 -1 .8782 .0633 7SAVE V200=RESIDUAL OPTION=TEST LABEL=RESIDUAL CASES=380~388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 115 112 3* 1.9642 13 * CASES CHANGED IN EXISTING VARIABLE COMMAND With KITS v a r i a b l e ?HISTOGRAM V = 200 INT=20 OP=HIST% CASES=380-388,390-396,398-496 HISTOGRAM CASES=CASE#:380-388,390-396,398-496 MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) -7 .0724 9 1 +X -6 .2154 0. 0 + -5 .3585 0. 0 + -4 .5015 3 . 6 4 + XXXX -3 . 6446 2 . 7 3 + XXX -2 . 7876 10. 7 12 +XXXXXXXXXXXX - 1 .9306 8 . 0 9 +XXXXXXXXX - 1 .0737 14 . 3 16 +XXXXXXXXXXXXXXXX - .21672 15 . 2 17 +XXXXXXXXXXXXXXXXX .64024 17 . O 19 +XXXXXXXXXXXXXXXXXXX 1 . 4972 9 . 8 1 1 +XXXXXXXXXXX 2.3542 7 . 1 8 +XXXXXXXX 3.2111 1 . .8 2 +XX 4.0681 6 . 3 7 +XXXXXXX 4 .9250 .9 1 + X 5 . 7820 0 0 + 6 . 6390 .9 1 +x 7 . 4959 0 O + 8.3529 0 0 + 9.2098 .9 1 +x MISSING 3 (INTERVAL WIDTH= .85696) TOTAL 1 15 COMMAND 7SCATTER V=200,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 200.RESIDUAL VS. 2.QUARTER RESIDUAL 9 .2098 + * 5.9534 + 2 .6969 + * .55950 + 2 * 2 2 2 * 2 * * 3 6 2 * 2 3 2 3 6 * 2 2 * * 3 * * 3 * 3 * 4 3 CN -3.8159 -7 .0724 + - - + 37 .000 47 .400 57 .800 QUARTER 4 2 . 2 0 0 52.GOO 63 .000 COMMAND 7REG V = 3 9 , 7 , 9 , 1 0 , 2 5 . 2 2 , 9 2 , 5 2 , 5 5 , 6 0 . 9 4 , 6 3 , 5 1 , 7 0 CASES=380-388,390-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F--STAT SIGNIF REGRESSION 13 784.79 60.368 9 .0421 .0000 ERROR 98 654 .28 6.6763 TOTAL 1 1 1 1439 . 1 MULT R= .73847 R-SQR= .54534 SE= 2.5839 VARIABLE PARTIAL COEFF STD ERROR T -STAT SIGNIF CONSTANT .55547 3.5990 15434 .8777 7 . WESTEND .29616 3.2081 1.0451 3 .0696 .0028 9 .EASTVAN - . 45 155 -3.2168 .64207 -5 .0100 .0000 10 .MARPOLE .00348 .68919 -1 2.0010 3444 1 -1 .9726 25 .MURBSTAT .21712 5.1946 2.3591 2 . 2019 .0300 22 .VACRATE - . 1662 1 -2.4621 1.4756 - 1 . 6686 .0984 92 .NEWVRATE .35253 .35330 .94738 -1 3 . 7293 .0003 52 .GRRLINC .06616 .19913 .30339 65635 .5131 55 .REALINT .17873 .96881 .53873 1 . 7983 .0752 60 .LAGRENT .18669 . 18391 .97763 -1 1 .8812 .0629 94 .STARTS - .30657 - .38353 -2 .12029 -2 -3 . 1884 .0019 63 .CC0STBC2 - .27979 - .27169 .94174 -1 -2 . 8850 .0048 51 .POPGRTH .284 10 3.2206 1.0979 2 .9333 .0042 70 . RLAPTRTN - .18640 - .43538 .23181 - 1 .8782 .0633 7SAVE V200=RESIDUAL OPTION=TEST LABEL=RESIDUAL CASES=380-388,390-396,398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 115 112 3* 1.9642 13 With MARPOLE v a r i a b l e * CASES CHANGED IN EXISTING VARIABLE COMMAND ?HISTOGRAM V=200 INT=20 OP=HIST% CASES=380-388,390-396.398-496 HISTOGRAM CASES=CASE#:380-388,390-396,398-496 HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) MIDPOINT 0724 2154 3585 5015 6446 7876 1 . 9306 1.0737 .21672 .64024 1 . 497 2 3542 2 111 068 1 9250 7820 6390 4959 8.3529 9.2098 O. 0. 3 . 2 10. 8 14 15 17 9 7 1 .8 6 . 3 O. O. 1 +X 0 + O + 4 3 + XXXX + XXX 12 +XXXXXXXXXXXX 9 +XXXXXXXXX 16 +XXXXXXXXXXXXXXXX 17 +XXXXXXXXXXXXXXXXX 19 +XXXXXXXXXXXXXXXXXXX 11 +XXXXXXXXXXX 8 +XXXXXXXX 2 +XX 7 +XXXXXXX 1 +x 0 + 1 +x 0 + d + 1 +x MISSING TOTAL 3 1 15 (INTERVAL WIDTH= .85696) COMMAND 7SCATTER V=200,2 CASES=380-388,390-396,398-496 SCATTER PLOT CASES=CASE#:380-388,390-396,398-496 N= 112 OUT OF 115 200.RESIDUAL VS. 2.QUARTER RESIDUAL 9.2098 + * 5.9534 + 2.6969 + * * * * * 2 * * * 2 2 2 * 2 * * 3 6 •a-CM - .55950 -3.8159 + 2 * 2 . 3 2 3 6 * 2 2 * * 3 * * 3 * 3 * 4 3 2 * 2 2 * -7.0724 + + + + +----+ + + + + + 3 7 . O O O 47 .400 57 .800 QUARTER 42 .200 52 .600 63 .000 COMMAND 7REG V = 3 9 . 7 , 9 , 2 5 , 2 2 , 9 2 , 5 2 , 5 5 . 9 3 . 9 4 , 6 3 , 5 1 , 7 0 CASES=380-388,39Q-396,398-496 LEAST SQUARES REGRESSION CASES=CASE#:380-388,390-396.398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE REGRESSION ERROR TOTAL DF SUM SQRS MEAN SQR 12 777.58 99 661.48 1 11 1439 . 1 64 .799 6.6816 F-STAT 9.6980 SIGNIF .0000 MULT R= .73508 R-SQR= .54034 SE= 2.5849 VARIABLE PARTIAL COEFF CONSTANT 10.362 7 . ,WESTEND . 22442 2 . 4837 9 . .EASTVAN - .45866 -3.1962 25 . MURBSTAT .01987 .64773 22 .VACRATE - . 12310 - 1.9362 92 . NEWVRATE .32202 .33336 52 .GRRLINC .04 208 .12366 55 .REALINT . 1822 1 .99055 93 .RLRENT2 - . 1557.0 -.11392 94 .STARTS - . 32828 -.41391 63 .CC0STBC2 - . 22526 - .21603 5 1 .POPGRTH .23632 2.7463 70 . RLAPTRTN - .15033 - .35266 STD ERROR T-STAT SIGNIF 7.1117 1 .4571 . 1483 1.0839 2 .2914 .0241 .62236 -5 . 1356 .0000 3.2757 19774 .8437 1.5687 - 1 . 2342 . 2200 .98500 -1 3 . 3843 .0010 . 29512 .41901 .6761 .53722 1 .8438 .0682 .72638 -1 -1 .5683 . 1200 .11970 -2 -3 . 4580 .0008 .93908 - 1 -2 . 3004 .0235 1.1349 2 .4198 .0174 .23309 - 1 .5129 . 1335 COMMAND 7SAVE V200=RESIDUAL OPTION = TEST LABEL = RESIDUAL CASES = 380-388,390-396 , 398-496 RESIDUAL USING: REGRESS CASES=CASE#:380-388,390-396,398-496 (N Run Number 3 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 115 112 3* 2.0508 12 * CASES CHANGED IN EXISTING VARIABLE COMMAND ?HISTOGRAM V=200 INT=20 OP=HIST% CASES=380-388,390-396,398-496 HISTOGRAM CASES= CASE#: 380-388,390-396.398-496 MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH I -7.1511 9 1 + X -6.34 1 1 . 0. 0 + -5 . 531 1 2 . 7 3 +XXX -4.7211 1 . 8 2 + XX -3.9111 1 . 8 2 + XX -3.1011 2 . 7 3 + XXX -2.291 1 8 . 9 10 +XXXXXXXXXX -1.4810 13 . . 4 15 +XXXXXXXXXXXXXXX - .67103 9 . . 8 1 1 +XXXXXXXXXXX .13898 21 . 4 24 +XXXXXXXXXXXXXXXXXXXXXXXX .94899 13. .4 15 +XXXXXXXXXXXXXXX 1.7590 1 1 .6 13 +XXXXXXXXXXXXX 2 . 5690 1 .8 2 +XX 3.3790 1 . 8 2 + XX 4.1890 4 .5 5 +XXXXX 4 . 9990 1 .8 2 + XX 5.8090 0 0 + 6.619 1 . 9 1 +x 7.4291 0 0 + 8.2391 .9 1 +x MISSING 3 (INTERVAL WIDTH= .81001) TOTAL 115 COMMAND 7SCATTER V=200,2 CASES=380"388,390-396,398-496 SCATTER PLOT CASES=CASE# : 380-388,390-396,398-496 N= 112 OUT OF 115 200.RESIDUAL VS. 2.QUARTER RESIDUAL 8.2391 + * * 5.1610+ * * 2 * * 2 .0830 + * .99504 * * * * 2 3 * 2 2 6 * 2 2 * * 22 3 7 * * * * 4 * * 5 * * 3 2 * 2 -4.0731 -7.1511 •i 37 .000 + + + + + + + + + 47 .400 57 .800 QUARTER 4 2 . 2 0 0 52 .600 63 .000 COMMAND , „ „ 7REG V = 3 9 , 7 , 9 , 2 5 , 2 2 , 9 2 , 5 2 , 5 5 , 9 3 , 9 4 , 9 5 , 5 1 , 7 0 CASES=380-388,390-396,398-496 LEAST SQUARES REGRESSION. CASES=CASE#:380-388,390-396,398-496 ANALYSIS OF VARIANCE OF 39.NEWREALP N= 112 OUT OF 115 SOURCE DF SUM SQRS MEAN SQR F REGRESSION 12 743.57 61.964 8 ERROR 99 695 .50 7.0252 TOTAL 1 1 1 439 . 1 MULT R= .71882 R-SQR= .51670 SE= 2.6505 .8202 SIGNIF .0000 VARIABLE CONSTANT 7.WESTEND 9.EASTVAN 25.MURBSTAT 22.VACRATE 9 2 . NEWVRATE 52.GRRLINC 55.REALINT 9 3 . RLRENT2 94.STARTS 95.REALCOST 51.POPGRTH 70.RLAPTRTN PARTIAL .19305 - .44551 .03837 - .04253 .23020 .09476 .07257 - .13018 - .24088 .04391 . 18965 - . 18555 COEFF 9 . 2826 2 . 1747 -3 . 1841 1 .7167 - .66655 .20433 . 30075 . 422 19 - . 12725 - . 24046 . 17583 2 . 1902 - .46718 STD ERROR 12.666 1 . 1 109 . 64309 4 . 4936 1 . 5736 .86815 -1 .31753 . 58313 .97400 -1 .97377 -3 .40203 -1 1 . 1396 . 24866 T-STAT . 73290 1 .9577 -4 .9513 .38204 - . 42358 2.3537 .947 14 . 72399 -1 .3064 -2.4694 .43735 1 .9218 -1 .8788 SIGNIF .4654 .0531 .0000 .7033 .6728 .0206 . 3459 . 4708 . 1944 .0152 .6628 .0575 .0632 COMMAND Run Number 6 i 7 S A V E V 2 0 0 = R E S I D U A L O P T I O N = T E S T L A B E L = R E S I D U A L C A S E S = 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 R E S I D U A L U S I N G : R E G R E S S C A S E S = C A S E # : 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 V A R I A B L E T O T A L V A L I D M I S S D W # V A R 2 0 0 . R E S I D U A L 115 112 3* 1.9386 12 * C A S E S C H A N G E D I N E X I S T I N G V A R I A B L E C O M M A N D ? H I S T O G R A M V = 2 0 0 I N T = 2 0 O P = H I S T % C A S E S = 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 H I S T O G R A M C A S E S = C A S E # : 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 M I D P O I N T H I S T % C O U N T F O R 2 0 0 . R E S I D U A L ( E A C H X = 1) - 7 . 8 2 7 7 9 1 + X - 7 . 0 1 8 1 0 . 0 + - 6 . 2 0 8 4 9 1 + x - 5 . 3 9 8 8 9 1 + x - 4 . 5 8 9 2 2 . . 7 3 + XXX - 3 . 7 7 9 6 . 9 1 + x - 2 . 9 7 0 0 5 . . 4 6 +XXXXXX - 2 . 1 6 0 3 5 . . 4 6 +XXXXXX - 1 . 3 5 0 7 1 3 . 4 1 5 +XXXXXXXXXXXXXXX - . 5 4 1 0 9 1 7 . O 1 9 +XXXXXXXXXXXXXXXXXXX . . 2 6 8 5 3 1 9 . 6 2 2 +XXXXXXXXXXXXXXXXXXXXXX 1 . 0 7 8 2 1 4 . 3 1 6 +XXXXXXXXXXXXXXXX 1 . 8 8 7 8 6 . 3 7 +XXXXXXX 2 . 6 9 7 4 3 . 6 4 +XXXX 3 . 5 0 7 0 . 9 1 + x 4 . 3 1 6 6 2 . 7 3 + XXX 5 . 1 2 6 3 . 9 1 + x 5 . 9 3 5 9 1 . 8 2 + XX 6 . 7 4 5 5 1 . 8 2 +XX 7 . 5 5 5 1 . 9 1 + x M I S S I N G 3 T O T A L 1 1 5 ( I N T E R V A L W I D T H = . 8 0 9 6 2 ) C O M M A N D 7 S C A T T E R V = 2 0 0 , 2 C A S E S = 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 S C A T T E R P L O T C A S E S ^ C A S E * : 3 8 0 - 3 8 8 , 3 9 0 - 3 9 6 , 3 9 8 - 4 9 6 N= 1 1 2 O U T O F 1 1 5 2 0 0 . R E S I D U A L V S . 2 . Q U A R T E R R E S I D U A L 7 . 5 5 5 1 + * 4.4786 * + 2 1 .4020 + * 2 3 4 * • * * 2 5 * * 2 8 + * * + 3 * 3 3 2 * * * * * 2 5 3 * 2 * * 3 • 1 .674G +2 -4 . 751 1 * * * 2 -7 .8277 + 3 7 . 0 0 0 47 .400 57 .800 4 2 . 2 0 0 52 .600 QUARTER 6 3 . 0 0 0 COMMAND CORRELATE V = 3 9 , 7 , 8 . 9 , 1 0 , 2 5 , 2 2 , 9 2 , 4 2 , 5 2 , 5 5 , 9 3 , 9 7 , 6 0 , 9 4 , 9 5 , 6 3 , 5 1 , 7 0 , 12, CORRELATION MATRIX CASES = CASE#:380-388,390-396 , 398-496 N= 112 DF = 110 R@ .0500= .1857 R<a .0100= .2425 VARIABLE 39.NEWREALP 7.WESTEND 8 . KITS 9.EASTVAN 10.MARPOLE 25.MURBSTAT 22 . VACRATE 92.NEWVRATE 42.REAL INC 52 GRRLINC 55.REAL INT 1.OOOO . 3899 .0931 - . 3227 .0692 . 3592 - . 1656 . 3794 . 4204 - . 2679 - .1810 1.0000 -. 1910 - . 3675 - .0399 .0335 .0725 .0178 . 1252 - . 1790 .0147 1.0000 - .8035 -.0871 -.4362 . 3697 - .3200 - .3930 . 2359 .2124 1.0000 - .1676 . 3730 - . 3638 . 2582 . 2936 - . 1 188 - . 1686 1.0000 .0570 - .0799 . 1 126 .0130 - .0065 - . 1395 1.0000 - .4390 . 7542 .9143 - .6092 - . 2924 CASES = 380-38'8 ,390-396,398-496 ON CM + X 5 . 5260 6 3 3 .8500 + 3 37 ..000 47 .400 42 .200 52 .600 + + + 57.800 QUARTER 63 .000 ? R E G M ^ 1 0 1 . 1 0 2 , 2 5 , 2 2 , 6 4 , 9 3 , 1 0 3 , 9 5 C A S E S = 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 . 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 . 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 . 4 3 3 . 4 3 9 . 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 LEAST SQUARES REGRESSION CASES = CASE#: 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 12,4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 ANALYSIS OF VARIANCE OF 101.RLAVGSP N= 20 OUT OF 20 SOURCE DF SUM SQRS MEAN SQR F-STAT SIGNIF REGRESSION 7 123.60 17.658 1.3824 . 2966 ERROR 12 153.28 12.773 TOTAL 19 276.88 MULT R= .66814 R-SQR= .44642 SE= 3.5739 VARIABLE PARTIAL COEFF STD ERROR T-STAT SIGNIF CONSTANT 23.479 22.602 1.0388 .3194 102 .LOCINDEX .05842 .16037 .79108 .20272 .8428 25 .MURBSTAT - .21313 -5.2688 6.9723 -.75567 . 4644 22 .VACRATE - .00503 - .42969 -1 2.4660 -.17424 -1 .9864 64 .CAPRATE - .04032 - .41806 - 1 .29907 -.13979 .8911 93 .RLRENT2 - .33074 - .21299 .17544 -1.2140 . 2481 103 .NEWRMLAG .06222 .13219 .61214 .21595 .8327 95 .REALCOST .08560 .25976 -1 .87283 -1 .29760 .7711 o Run Number 10 7SAVE A V200=RESIDUAL OPTION=TEST LABEL = RESIDUAL CASES = 3 8 0 , 3 8 6 . 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 . 4 1 2 , 4 1 9 , 4 2 7 . 4 3 3 , 4 3 9 . 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 . 496 RESIDUAL USING: REGRESS CASES = C A S E # : 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 . 399 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 VARIABLE TOTAL VALID MISS DW . #VAR 200.RESIDUAL 20 20 O* 2.7524 7 * CASES CHANGED IN EXISTING VARIABLE 'HISTOGRAM V=200 INT=20 OP=HIST% C A S E S = 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 HISTOGRAM CASES=CASE# : 380, 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) -4 .2056 5 . 0 1 +X -3 .5245 0. 0 + -2 . 8433 5 . 0 1 +x -2 . 1622 15 . 0 3 +XXX - 1 . 48 1 1 0. 0 + - . 79993 35 . 0 7 +XXXXXXX - . 1 1880 0. 0 + .56234 25 . 0 5 +XXXXX 1 .2435 0, 0 + 1 . 9246 0. 0 + 2.6057 5 .0 1 +x 3 . 2869 0 0 + 3 . 9680 0 0 + 4.6491 0 0 + 5 . 3303 5 .0 1 +x 6.0114 0 0 + 6 . 6925 0 0 + 7.3737 0 0 + 8 .0548 O 0 + 8 . 7359 5 .0 i +x TOTAL 20 (INTERV .681 13) COMMAND 7SCATTER V=200,2 C A S E S = 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 . 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 I l SCATTER PLOT CASES = C A S E # : 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 . 4 9 6 N= 20 OUT OF 20 200.RESIDUAL VS. 2.QUARTER RESIDUAL 8 .7359 + * + 6 . 1476 3.5593 + 97 102 +* •1.6173 + * * * -4.2056 + H 37 .000 47 .400 57.80O 42 .200 52 .600 QUARTER 63 .000 ?REG M V=101, 1 0 2 , 2 5 , 9 2 , 6 4 . 9 3 , 1 0 3 . 9 5 CASES = 3 8 0 , 3 8 6 . 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 . 405 , 4 0 8 , 4 1 2 . 4 1 9 . 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 496 LEAST SQUARES REGRESSION CASES=CASE# :380 ,386 ,390 ,393 ,394 ,396 .398 ,399 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 ANALYSIS OF VARIANCE OF 101.RLAVGSP N= 20 OUT OF 20 SOURCE DF SUM SQRS MEAN SQR F-STAT SIGNIF REGRESSION 7 124 . 13 17 .733 1.3932 . 2927 ERROR 12 152.75 12.729 TOTAL 19 276.88 MULT R= .66957 R-SQR= .44833 SE= 3.5678 VARIABLE PARTIAL COEFF STD ERROR T-STAT SIGNIF CONSTANT 22.467 22.865 .98259 . 3452 102 . LOCINDEX .08121 .18308 .64868 .28224 . 7826 25 . MURBSTAT - . 221 12 -5.4127 6.8914 -.78544 .4474 92 .NEWVRATE .05898 .34752 -1 .16978 .20469 .8412 64 .CAPRATE - .06024 - .62205 -1 .29756 -.20905 .8379 93 .RLRENT2 - .31196 - .20337 .17880 -1.1374 . 2776 103 .NEWRMLAG .08587 .14289 .47860 .29855 .7704 95 .REALCOST .09215 .27510 -1 .85813 -1 .32058 .7540 CM With NEWVRATE v a r i a b l e 7SAVE A V200 = RESIDUAL OPTION = TEST LABEL = RESIDUAL CASES = 380 ,386 ,390 ,393 ,394 , 396,398 . 399 , 4 0 5 . 4 0 8 , 4 1 2 , 4 1 9 . 4 2 7 . 4 3 3 , 4 3 9 . 4 5 0 , 4 5 9 . 4 9 4 , 4 9 5 . 4 9 6 RESIDUAL USING: REGRESS CASES=CASE# :380 ,386 ,390 ,393 ,394 ,396 ,398 ,399 , 405 . 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 20 20 0* 2.7901 7 * CASES CHANGED IN EXISTING VARIABLE ?H?STOGRAM V=200 INT=20 OP=HIST% CASES=380,386,390,393,394,396,398,399,405.408.412,419,427,433,439,450.459,494,495,496 HISTOGRAM CASES=CASE#:380.386,390,393,394,396,398,399,405,408.412, 419.427,433,439,450,459,494,495,496 MIDPOINT HIST% COUNT FOR 200 -4.3017 • •5 . 0 1 +X -3.6085 0. 0 + -2.9152 5 . 0 1 + X -2.2220 10. 0 2 + XX -1.5287 5 . 0 1 +x -.83546 35 . 0 7 +XXXXXXX - . 14221 0. 0 + .55104 25 . 0 5 +XXXXX 1 .2443 0. 0 + 1 . 9375 0. 0 + 2.6308 5 . 0 1 +x 3 . 3240 0. 0 + 4 .0173 0 0 + 4.7105 5 .0 1 +x 5.4038 0. 0 + 6 .0970 0 0 + 6 . 7903 0 0 + 7.4835 0 O + 8.1768 0 0 + 8 . 8700 5 .0 1 +x TOTAL 20 (INTERV .69325) ro COMMAND 7SCATTER V = 200,2 CASES=380,386,390,393.394,396,398.399,405,408,412,419,427,433,439,450,459,494,495,496 SCATTER PLOT CASES = CASE# : 380,386,390,393,394,396,398,399,405,408 , 412 , 419.427,433,439,450,459,494,495,496 N= 20 OUT OF 20 200.RESIDUAL VS. 2.QUARTER RESIDUAL 8.8700 + * 6 . 2357 3 .6013 .96699 +* •1.6674 + -4.3017 37 .000 47 .400 57 .800 4 2 . 2 0 0 52 .600 y QUARTER 63 .000 COMMAND 7C0R RELATE V = 1 0 1 , 1 0 2 , 2 5 , 2 2 , 9 2 , 6 4 , 9 3 , 1 0 3 , 9 5 C A S E S = 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 . 4 3 9 , 4 5 0 . 4 5 9 , 4 9 4 . 4 9 5 . 4 9 6 CORRELATION MATRIX CASES = CASE# :380 ,386 ,390 ,393 ,394 ,396 .398 , 399 , 405 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 = 2C i DF = 18 VARIABLE R@ .0500= .4438 R@ .0100= .5614 101 . RLAVGSP 1.OOOO 102 . LOCINDEX . 1777 1.OOOO 25 . MURBSTAT . 3230 - .3980 1 .0000 22 . VACRATE - .1968 .1987 . 2010 1.OOOO 92 . NEWVRATE . 3067 - .3673 . 8094 -. 1610 1.OOOO 64 . CAPRATE - .3466 -.1202 .1811 . 5806 -.0774 1 .0000 93 . RLRENT2 - .5363 .1566 .9047 . 3221 - .7573 . 3989 103 . NEWRMLAG - .0149 - .3542 . 1849 .5312 . 1092 .4183 95 . REALCOST .3561 .3531 . 1082 .0703 - .0613 .0563 101 . RLAVGSP 102. LOCINDEX 25. 22. MURBSTAT VACRATE 92 . NEWVRATE 64 . CAPRATE 93 .RLRENT2 1.OOOO 103 .NEWRMLAG - .057 1 1.OOOO 95 .REALCOST - .1337 .1925 1 . OOOO CO C o r r e l a t i o n Matrix Small Sample Variables 93 . 103 . 95 . RLRENT2 NEWRMLAG REALCOST TREITV^IOI^S CASES = 380,386,390,393.394,396,398,399,405,408,412,419,427,433, 439.450.459.494,495.496 LEAST SQUARES REGRESSION CASES = CASE#:380,386,390,393,394,396,398 , 399 , 405,408,412,419,427,433,439,450,459,494,495,496 ANALYSIS OF VARIANCE OF 101.RLAVGSP N= 20 OUT OF 20 SOURCE DF SUM SQRS MEAN SQR F-STAT 2.0973 REGRESSION ERROR TOTAL 1 18 19 28.895 247.99 276 . 88 28.895 13.777 MULT R= .32304 R-SQR= .10436 SE= 3.7117 STD ERROR T-STAT VARIABLE CONSTANT 25.MURBSTAT PARTIAL .32304 COEFF 9. 3184 2.5200 1 .4029 1.7401 6 .6422 1 .4482 SIGNIF . 1648' Run Number 11 SIGNIF .0000 . 1648 7SAVEAV200=RESIDUAL OPTION=TEST LABEL=RESIDUAL CASES=380,386.390,393,394,396,398,399,405,408.412.419,427,433,439,450,459,494,495.496 RESIDUAL USING: REGRESS CASES = CASE# : 380,386,390,393.394.396,398,399 , 405,408,412,419,427,433,439,450,459,494,495,496 VARIABLE TOTAL VALID MISS DW 0VAR 200.RESIDUAL 20 20 0* 1.6831 1 * CASES CHANGED IN EXISTING VARIABLE 7HIST0GRAM V=200 INT=20 OP=HIST% CASES=380,386,390,393.394,396,398,399.405,408,412,419,427.433,439,450,459,494,495,496 HI STOGRAM CASES = CASE/5': 380, 386 , 390, 393 , 394 , 396 , 398 , 399 , 405 , 408 , 4 12 , 419.427,433,439,450,459,494,495,496 MIDPOINT HIST% COUNT FOR 200 -3 . 665 1 10.0 2 +XX -2.8435 0. 0 + -2.0219 30.0 6 +XXXXXX - 1 .2003 20.0 4 +XXXX -.37866 10.0 2 +XX .44295 O. 0 + 1 .2646 10.0 2 +XX 2.0862 5.0 1 +X 2.9078 0. 0 + 3.7294 0. 0 + 4.5510 10.0 2 + XX 5.3726 0. 0 + 6.1943 0. 0 + 7.0159 0. 0 + 7.8375 0. 0 + 8 . 659 1 0. 0 + 9.4807 0. 0 + 10.302 O. 0 + 1 1 . 124 0. 0 + 11.946 5.0 1 +x TOTAL 20 (I (INTERVAL WIDTH= .82161) COMMAND 7SCATTER V = 200,2 CASES = 380, 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 SCATTER PLOT C A S E S = C A S E # : 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 6 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 N= 20 OUT OF 20 200.RESIDUAL VS. 2.QUARTER RESIDUAL 11.946 + * 8 .8234 + VD 5.7013 + 2.5791 + - .54299 + -3.6651 + H 3 7 . 0 0 0 4 2 . 2 0 0 47 .400 57 .800 QUARTER 52 .600 63 .000 ANALYSIS OF VARIANCE OF 101.RLAVGSP N = 19 OUT OF 19 SOURCE DF SUM SORS MEAN SOR F-STAT SIGNIF REGRESSION 7 125.89 17.984 5.0520 .0088 ERROR 1 1 39.157 3.5597 TOTAL 18 165.04 MULT R= .87335 R-SQR= .76275 SE = 1.8867 VARIABLE PARTIAL COEFF STD ERROR T-STAT SIGNIF CONSTANT 16.14 1 12.002 1 .3448 . 2058 102 .LOCINDEX .38000 . 57781 .42408 1.3625 . 2003 25 .MURBSTAT . 1 1942 1 .5448 3.8725 . 39892 .6976 22 .VACRATE . 1 1670 .50876 1.3055 .38971 . 7042 64 .CAPRATE - .07805 -.40996 -1 .15788 -.25966 . 7999 ,.93 .RLRENT2 - .28716 -.944 11 - 1 .94955 -1 - .99427 .3415 103 .NEWRMLAG .22198 .24446 .32376 .75505 . 4661 95 .REALCOST - .01928 -.29651 -2 .46360 -1 -.63958 -1 .9502 Run Number 10 (excluding o u t l i e r ) ?SAVE A V200=RESIDUAL 0PTI0N=TEST LABEL=RESIDUAL C A S E S = 3 8 0 . 3 8 6 . 3 9 0 , 3 9 3 , 3 9 4 . 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 . 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 . 4 9 5 , 4 9 6 STR RESIDUAL USING: REGRESS CASES = C A S E # : 3 8 0 , 3 8 6 . 3 9 0 , 3 9 3 , 3 9 4 , 3 9 8 , 3 9 9 , 405 , 4 0 8 . 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 . 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 VARIABLE TOTAL VALID MISS DW #VAR 200.RESIDUAL 19 19 0 2.2702 7 7HIST0GRAM V = 200 INT=20 OP = HIST% CASES = 3 8 0 . 3 8 6 , 3 9 0 . 3 9 3 , 3 9 4 , 3 9 8 , 3 9 9 . 4 0 5 , 4 0 8 , 4 1 2 , 4 1 9 , 4 2 7 , 4 3 3 , 4 3 9 . 4 5 0 , 4 5 . 9 , 4 9 4 , 4 9 5 , 4 9 6 HISTOGRAM CASES = C A S E * : 3 8 0 , 3 8 6 , 3 9 0 , 3 9 3 , 3 9 4 , 3 9 8 , 3 9 9 , 4 0 5 , 4 0 8 , 4 1 2 , 4 19 , 4 2 7 , 4 3 3 , 4 3 9 , 4 5 0 , 4 5 9 , 4 9 4 , 4 9 5 , 4 9 6 MIDPOINT HIST% COUNT FOR 200.RESIDUAL (EACH X= 1) -2 .0720 5 . 3 1 +x - 1 .7236 0. 0 + - 1 .3753 5 . 3 1 +x - i.. 0269 15 . 8 3 + XXX - .67858 10. 5 2 + XX - .33022 21 . 1 4 + XXXX . .18 134 - 1 ' 15 . 8 3 + XXX .36649 IO. 5 2 + XX .71484 5 . 3 1 +x 1.0632 0. 0 + 1 . 4.1 16 ' 0. 0 + 1.7599 O. 0 + 2.1083 O. 0 + 2.4566 0. 0 + 2.8050 5 . 3 1 + X 3 . 1533 0. 0  3 . 501 7 0. 0 + 3.8500 0. 0 + 4 . 1984 0. 0 + 4.5467 5 . 3 1 +x TOTAL 19 ( 19 (INTERVAL WIDTH= .34836) COMAND 7SCATTER V=200,2 CASES=380,386,390.393.394.398,399.405,408.412,419.427,433,439,450,459,494,495,496 SCATTER PLOT CASES=CASE#:380,386,390,393,394,398,399,405,408,412,419, 427,433,439,450,459,494,495,496 ., N= 19 OUT OF 19 200.RESIDUAL VS. 2.QUARTER RESIDUAL 4.5467 • + * 3.2230 1 .8993 + . 57550 00 CO * • * * * * * .74825 + 37.OOO -2.0720 + + + + + + + + + + + + 47.400 57.800 QUARTER 42.200 52.600 63.000 ?R'EGT'101 . 102 , 25 . 22 , 64 , 93 , 103 , 95 C ASES = 380, 386 , 390, 393 . 394 . 398 ,399 , 405 , 408 , 4 12 . 4 19 , 427 , 439 , 450, 459 , 494 , 495 , 496 LEAST SQUARES REGRESSION CASES = CASE#:380,386,390,393,394,398,399,405 , 408,412,419,427,439,450,459,494,495,496 APPENDIX "E" DATA FILE LISTINGS 139 NITS (DH4A/ANNA/10267 ) #SIG GAU #Enter u s e r p a s s w o r d . ? #**Las t s i g n o n was: 14 : 1 4 :37 H Use r " G A U . " s i g n e d on at 14 :19 :06 on Tue Apr 20/82 NO MESSAGES CTL -P -• *PRINT* CTL-F - *FTN CTL-0 - %P AGE CTL -T -- FORT.TABS CTL-R - R MIDAS CTL-G - %WF=36 CTL -w -- *STATUS CTL-0 - PORTRAT CTL-Y - %UC CTL -u -- %DUPLEX CTL-L - *LISTER CTL-Z - %LC CTL - s -- SIG $ CTL-X - CANCEL CTL-V - S $ = 0N - - %WF a - %WB=36 < - %WL > PROUTE - %WR=60 = ANGS CTL -D • - DEL LINE CTL-B - PAUSE CTL-H - LEFT CTL -E - DEL END CTL-M - RETURN CTL-I - RIGHT CTL -C - EOF CTL-K - HOME CTL-N - UP CTL -A - INSERT CTL-J - DOWN #SET PROUTE=CNTR tt $ . 0 4 , $.07T ^CONTROL *PRINT* LANDSCAPE ONESIDED C0PIES=3 #*PRINT* a s s i g n e d j o b number 523752 #*PRINT* RM523752 h e l d H $ . 0 9 , $.15T /fLIST RESALES > > 1 2 3 3 . 4 5 6 6 . 7 8 9 9. 10 1 1 12 12 . 13 14 15 15 . 16 17 18 18 . 19 20 21 21 . 22 23 24 100432464621205825 EAST 7TH 1004 975913.7500 3 277 36 1004 1111900 1 1004 00 00 00 01 03 1011317607234501556 CHARLES 101 1 .1.0. 7500 2 277 47 1011 1151620 0 1011 00 00 00 01 03 1016321234633011925 WOODLAND 24 1 17 147548 33792 211597 0 .0000 4 277 30 0 21 152 123662 26698 188549 1016 1016 1 89220 1016 00 00 00 01 03 1034317631234431545 E 2ND 1034 11.7500 2 276 48 1034 1134940 0 1034 00 00 00 01 04 1037263 144832998777 HUDSON ST 1037 0 .0000 2 278 75 52022 1037 1251880 O 320475 1037 00 00 00 01 02 1042337770235701574-78KINGSWAY 1042 10.6666 4 278 10 6536 1042 1 24000 O 1042 00 00 00 01 02 1046606606116651331 NELSON 1046 61215.0000 4 178 17 1046 1 75120 O 1046 00 00 00 01 02 1048323644 19454334 E 1048 97 1912.5000 2 1048 1102282 LA W53'B98,DL264A,P5738 670 6466 35489 600000 804550 L 5-12 B49,DL264A.P430 719 25254 0000005850001155100 L17-20.B74,DL264A,P442 705 16104 32844360000 5TH 276 32 O 44923 21 162 19058 23752 18948 161 1785821000000 1 4 2 1 1 1 0 0 0 1 44101 369148 161876000 963287 0 2 4 2 1 1 1 1 0 0 1 34184 328248 1511380000000000 0 2 4 2 1 1 1 0 0 0 1 29193 901246 L ' A ' ,B65,DL264A,PL16291 1613900001257988 556 20130 29 19 0 0 0 0 1 3 2 1 1 1 0 0 0 52775 757000 921895 1 24 95 308900 L ' D' ,B9 ,DL318,P1749 & 16599 1630000000000000 694 35000 3 68 4 0 0 1 2 4 2. 1 1 1 0 O 0 762631500000 1780000 1 40 24 422310018 L' 1&2' ,B7 ,9&11,DL352,PL2170 15 327000 322052 654 4925 0 8 0 0 0 0 1 3 3 1 0 1 0 0 0 8883 100000 1 44 103 L' 17' ,B34,DL185,P92 715 8646 260000 15 666667500000 0 1 3 2 1 1 1 0 0 0 0 46 L 'G ' , B28 ,DL200A ,P15786 13 985000 130900 742 18117 3 27 2 0 0 0 2 4 2 1 1 1 0 0 0 320OO0 673000 0 37 96 21000 > 24 . 5 > 25 > 26 > 27 > 27 . 5 > 28 > 29 > 30 > . 30 . 5 > 31 > 32 > 33 > 33 . 5 > 34 > 35 > 36 > 36 . 5 > 37 > 38 > 39 > 39 . 5 > 40 > 41 > 42 > 42 . 5 > 43 > 44 > 45 > 45 . 5 > 46 > 47 > 48 > 48 . . 5 > 49 > 50 > 51 > 51 . 5 > 52 > 53 > 54 > 54 . 5 > 55 > 56 > 57 > 57 . 5 > 58 > 59 > 60 > 60 . 5 > 61 > 62 > 63 > 63 . 5 > 64 > 65 > 66 > 66 . 5 > 67 > 68 > 69 1048 00 00 00 01 04 1050207648095951905 W 8TH 1050 160512.2356 1 278 5 6092 1050 1 30300 0 27228 1050 01 00 00 00 00 1060212683146972885 SPRUCE 1060 797410.7500 4 277 40 26878 1060 1 0 183755 1060 00 01 00 00 01 106512969003853 3663 W 16TH 1065 010.6250030378 30 18060 1065 0186940 4482014212000 0 1065 00 00 00 01 02 041531763123205 1421 E 2ND 04 15 10.2066010677 33 18022 041501100848 00 100764 04 15 00 00 01 00 02 042132164123416 1602-06 E 6TH 0421 11.0000010179 12 7356 042101 36000 7269 28731 0 21368 04 21 00 00 01 00 00 014521165412095 1705 W 10TH 0145 0.0000020125 5 4739 014501 15600 3000 12600 1 O 0145 00 00 01 00 54 0123212 14665492 1195 W 11TH 0123 10.4561010178 18 14878 012301 75372 65892 0123 00 OO 01 00 01 010321213465093 2555 HEMLOCK 0103 10.5000010279 24 15267 010301 0 68187 0103 00 00 01 00 00 041231723460605 1209 WOODLAND 0412 012.7500010178 5 4780 0412 1 22800 3000 19800 0 0 0412 00 00 01 00 01 012221168312467 1535 W 13TH 0122 0 9.7617010441 17 10891 0122 O 37878 1 17172 0122 00 00 01 00 38 013621568612470 1536 W 14TH 0136 010.2500020128 21 13632 0136 0 51084 14727 36357 1 0136 00 00 01 00 51 030526014483004 8606-20 HUDSON 0305 0 0.0000010144 6 24167 0305 0 8820 1 0 0305 00 00 01 00 35 044232767023483 1657 E 12TH 0442 010.9768010412 11 6327 0442 O 29000 1 1626 0442 00 00 01 00 67 043032465021438 938 E BROADWAY 0430 0013.4762010255 10 8200 0430 O 26328 5809 20518 1 0430 00 00 01 00 24 041431763023026 1344 E 1ST 0414 010.6749010270 30 19833 04 14 0 73980 1 90958 L ' 1 1 ' , B 3 0 6 . D L 5 2 6 , P 5 9 0 04 80000 27228 1218 6000 0 0 2 3 0 1 3 2 1 0 1 0 1 0 260000 252496 0036 L 'A ' ,DL526 ,B414 ,VR542 ,P17065 07 19910001697994 672 18750 0 39 1 0 0 0 1 4 2 1 1 1 0 0 0 1362920 O L ' A ' B112 DL540 P17099 602 0 30 0 0 27000 885510 L21&22&24 B66 DL264A P448 13 4 180001131135 302 01 OOOO 0 01 42 97 1131135 1211730001170000 546 16104 6 27 0 0 656400 888950 L13 B154 DL264A P1 141 613 9863 6 6 0 0 339700 L11 B348 DL526 P1949 947 6250 142350 00001 30201 101000000 00 34 92 961066618 12 275000 184250 00001 302010001000000 00 64 94 185000 12 155000 0 0002 200000000000000 00 5812 1 600000 LA-C 19S20 B374 DL526 P2014 11 800000 621382 827 12400 0 14 4 O 000010302010101000000 755775 775750 00 58 97 623295 LA 17&18 B351 DL526 P2334 121060000 643707 636 12500 3 20 1 0 00001 40201 101000000 851600 00 106 645000 L5 B 41 DL264A P399&1771 11 197000 128000 956 6250 0 0 5 0 00001 201010001000000 191600 00 52116 128000 L19&20 B410 DL526 P1949 640 9375 1 16 0 0 334400 L7&8 B450 DL526 P11949 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1 4908 5176 6072 4200 928 5180 1640 4765 10216 040910.2500 54096 0409 00 00 01 00 10 060321917070205 3707 CAMBIE 0603 9.5000 000149 8 0603 0 15852 6154 9697 1 0603 OO 00 01 00 30 043733918872899 4899 QUEBEC 0437 011.555901 10 6 0437 O 15900 1 0437. 00 00 01 00 69 041832163423411 1515 E 4TH 0418 011.7243010955 7 0418 O 14880 3030 11849 1 04 18 00 00 01 00 24 040221469018667 137 E 16TH 0402 012.0000030164 8 0402 O 17472 3656 13816 1 0402 00 00 01 00 15 031226313883350 8860 MONTCALM 0312 0 1.0000010264 24 17917 0312 0 3 1980 1 0312 00 00 01 00 15 030726014583046 8650 SELKIRK 0307 011.2590010859 21 20952 0307 O 49936 13004 36932 1 32304 0307 00 00 01 00 20 104221266413425 1373 W 11TH 104 2 15.5000080307 8 1042 0 28400 5153 21297 1 1042 00 00 00 01 7 1 105521265414965 1035 W 10TH 1055 011.5000051060 10 1055 O 17856 1 1055 00 00 00 01 20 102460260611357 1655 NELSON 1024 1312512.6697030372 75 53507 1024 0253476 1 325620 1024 00 00 OO 01 08 103660661511805 1320 BUTE 1036 10.143903 67 93 57229 1036 0179276 1 63645 1036 00 00 00 01 13 103760260611063 1735 NELSON 1037 281311.0000020269 62 38114 1037 0108822 4 1740 67082 1 160424 1037 00 OO 00 01 11 108030757919862 662 ALEXANDER 1080 014.7768011012 12 4276 1080 O 14280 2904 11376 1 0 1080 00 00 00 01 68 102760360711596 1091 BROUGHTON 1027 477311.5000030312 40 49657 1027 0174763 1 61476 1027 00 00 00 01 68 107331159619834 634 E GEORGIA 1073 013.864201 05 55 10800 1073 0 49200 15277 33923 1 13793 4384 13836 7645 10572 L1-3 B24 DL184 P178 640 18117 6 28 1 0 642390 L2 B600 DL526 P2976 647 3757 2 6 0 0 143500 L8 B4 DL634 P1426 700 3848 0 5 1 0 1500 105000 L33 B145 DL264A P222 740 6100 1 5 i 0 0 111500 L12 B55 DL 302 P198 595 5440 2 5 1 0 142850 L13&14 B6 DL318 P1749 630 14000 9 14 1 0 464200 L8S9 B'P' DL318 P1903 680 10996 2 18 1 0 398300 L18 B372 DL526 P991 548 6250 2 2 4 0 164150 L14 B355 DL526 P991 764 6250 1 8 1 0 232200 L24-28 B58 DL185 P92 713 26959 24 43 8 0 1629650 L18 E HLF&19 B58 DL185 615 17292 60 33 0 0 2068950 L11&12 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18 1070 15732 35516 9936 35988 59 13 1 8920 13860 114.5 1073 00 OO 00 01 75 115 101060661311647 1345 BURNABY 116 1010 011.250005 60 15 9133 117 1010 O 36448 8153 28295 1 23580 117.5 1010 OO 00 00 01 20 118 101460360511765 1231 BARCLAY 119 1014 O 8.000005 62 21 13149 120 1014 O 61584 23402 38182 1 23100 120.5 1014 OO 00 00 01 .18 121 101560260511425 1549 BARCLAY 122 1015 29 1614.0000030358 21 12077 123 1015 0 56280 24200 32080 1 0 123.5 1015 00 00 00 01 22 124 110030923558826 322S326 WOODLAND 125 1100 03 10 32 11880 126 1100 O 32520 14756 17764 1 126.2 1100 00 00 00 01 70 127 111232568319404 310 E 128 1112 .12.000001 129 1112 0 70800 129.5 1112 00 00 00 01 20 130 107820964816318 686 W 8TH 131 1078 13.000001 132 1078 0 48384 15240 33144 1 132.5 1078 OO 00 00 01 54 133 111121468718604 3122 QUEBEC 134 1111 01.1.500001 135 1 1 1 1 0 33600 135.5 1090 00 00 00 01 70 136 109031058825536 2026 FRANKLIN 137 1090 011.255205 138 1090 O 20904 3842 138.5 1090 00 00 00 01 70 139 1007603607 1 1796 10658.1085 BUTE 140 1007 13.6229030339 26 14088 141 1007 0 62145 26722 35423 1 14 1.5 1007 OO 0 0 . 0 0 01 41 142 101660260711317 1675 COMOX 143 1016 14.000002 61 21 144 1016 O 58884 25320 33564 1 144.5 1016 00 00.OO 01 19 145 1077208648 13045 1455 W 8TH 146 1077 2625012.4483040312 25 147 1077 O 51220 1 147.5 1077 OO 00 00 01 68 148 103460660911784 1222 PENDRELL 149 1034 10.2879030365 43 25653 150 1034 0119709 1 83131 150.5 1034 OO 00 00 01.15 151 103560360311825 1155. HARO 152 1035 12.3988040368 50 25240 153 1035 0148000 56240 91760 1 153.5 1035 00 00 00 01 12 154 106012064208485 2211 W 5TH 155 1060 0 7.750003 67 35 156 1060 0131940 52776 79164 1 156.5 1060 OO 00 00 01 13 157 106112064808727 2185 W 8TH 158 106 1 014.000005 66 20 159 1061 O 72162 28865 43297 1 L16 B38 DL185 P92 608 8646 0 15 0 0 247500 L24 B33 DL185 P92 625 8646 2 19 O 0 383500 L12 B45 DL185 P92 575 8646 2 18 1 0 339500 15 394000 148055 00002 201010001000001 00 36 91 152000 15 625000 521000 OOOOO 301010000000000 00127 107 200000 16 460000 250000 00002 301010000000000 00 72130 250000 LB B15 S U B ' C DL183 P5443 08 170000 114361 383 4455 32 0 0 0 OOOOO 300 0000000000 156500 00 58 95 80000 L1&2 B112 DL301 P187 605 12078 2 24 0 0 439800 L2 B339 DL526 P7916 552 5850 0 18 0 0 286650 16 735000 605000 00002 2010100 000000 00 71107 285000 14 368000 257500 00002 300 0000000000 00 66122 189500 LD OF SUB1&2 B55 DL302 P6105 15 365000 228000 685 7663 1 12 0 0 263700 OOOOO 2010100 00 69107 000000 120000 10 17062 8 4484 1 14832 47292 13250 37008 1761 1 26412 L3 B39 DL184 P178 560 6034 0 8 0 0 128600 L1 B36 DL185 P92 542 8646 21 5 0 0 372900 L23 B59 DL185 P92 630 8646 O 21 0 6 377300 L11 B311 DL526 P590 653 6000 5 16 4 0 332150 L2 B37 DL185 P92 596 8646 1 40 2 0 884500 L14 B19 DL185 P 92 505 8646 34 15 1 0 313904 23242 21972 12696 24620 L23-26 B243 DL526 P590 664 16800 7 27 1 0 657550 L18&19 B304 DL526 P590 633 12000 5 13 2 0 389700 15 164000 123218 00101 201010000000000 00 72 96 126000 16 585000 407000 00002 200010000000000 00 67 129 307000 16 660000 65000 00002 201010000000000 00 77122 263000 14 400000 291756 OOOOO 300010000000000 00 17 7 1131 203000 151440000 769069 00102 90301 101000001 00 56101 600000 1618000001254882 00100 803010100 01 00 75101 281972 131060000 190564 00002 202010101000000 00 74 14 600000 350000 00002 203010001000001 00 75 65125 213150 r*N 159.5 1061 00 00 00 01 14 160 102960360711955 1041 C0M0X 161 1029 12.6600030311 34 162 1029 0103884 1 162.5 1029 OO 00 00 01 69 163 103160260610920 1872 NELSON 164 1031 O 9.0000030359 35 165 1031 0105564 41170 64394 1 165.5 1031 00 00 00 01 21 166 1030603607 11697 1075 JERVIS 167 1030 620817.2000040358 37 168 1030 O 57924 1 168.5 1030 OO OO 00 01 22 169 1032602605 10796 2010 BARCLAY 170 1032 015.0000 52 39 171 1032 0133884 52215 81669 1 17 1.5 1032 00 00 00 01 28 172 102851659711704 610 JERVIS 173 1028 3208 14.0748030310 51 174 1028 0 1 > 174.5 1028 OO 00 00 01 70 > 175 1042 > 176 1042 10.7500 78 10 > 177 1042 1 0 > 178 1042 00 00 00 01 02 #End o f F i l e H $ . 0 9 , $ .25T #$C *MSOURCE*@SP *PRINT* 32768 10548 25176 28814 28663 74496 34801 47149 167304 L14 B8 DL185 P92 963 8646 7 6 21 O 689400 L6 B69 DL185 P 92 716 8646 14 21 0 0 667050 1610800000785809 00100 400010100000000 00 58106 470490 15 930000 24924 1 00102 70301 101000000 00 7 1 L19 B35 DL185 P92 151075000 750000 772 8646 0 30 7 0 00100 803 0100000000 698800 00 00117 129 650000 LB 14-16 B68 DL185 P8501 161070000 350000 892 12965 18 15 6 O 00102 403010100000001 755150 00 72130 370000 LC B30 DL185 P92 922 9108 0 25 19 7 607100 161550000 955088 00100 600 0200000000 00 12 1 1 1 815000 6536 44923 654 4925 O 8883 100000 16 610000 268000 O 0 0 1 3 3 1 0 1 0 0 0 1 U n i v e r s i t y o f B r i t i s h Co lumbia Comput ing Cen t r e - D e v i c e : DSE7 Task : H THE SYSTEM WILL BE IN UNATTENDED MODE FROM MIDNIGHT TO 4 AM TONITE*** H s i g gau H E n t e r u s e r p a s s w o r d . ? . . U * * L a s t s i g n o n was: 18 :37 :27 H ..User " G A U . 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919 1029 060 > 9 2 0 1029 08198 > 92 1 1029 060 > 922 1029 08198 69500 155.23 94800 157.37 0150000 157.37 0150000 157.37 0200000 157.37 550000 157.37 550000 157.37 126667 160.43 120000 160.4 3 120000 160.43 1 10000 160.43 140000 160.4 3 120000 160.43 95000 160.43 60000 160.43 49500 160.43 48000 160.4 3 135000 160.43 320000 163.13 95000 163 . 13 465000 163.13 5 14000 163. 13 36000 163. 13 1500000 163.13 55000 163.13 350000 163.13 0080400 163.13 800O0 166.20 125000 166.20 76000 166.20 4191 33 151.07 28.71 5368 44 154.27 28 .63 005900 050 154.27 28 .63 005900 050 154.27 28 .63 005900 050 154.27 28 .63 20130 165 154.27 28.63 20130 165 154.27 28 .63 8052 66 158.33 28.55 4323 33 158.33 28.55 4323 33 158.33 28.55 4323 33 158.33 28.55 4323 33 158.33 28.55 4323 33 158.33 28.55 21472 176 158.33 28.55 3660 30 158.33 28.55 3113 25 158.33 28.55 3113 25 158.33 28.55 8052 66 158.33 28.55 16104 132 161.17 28 .48 4026 33 161.17 28.48 23909 196 161.17 28 .48 27765 228 16 1.17 28.48 4026 33 161.17 28 .48 67054 400 161 . 17 28 .48 4026 33 16 1.17 28.48 13988 112 161 . 17 28 .48 006000 O50 161 . 17 28 .48 6000 50 164 .17 28 .40 6039 50 164.17 28 .40 5319 44 164.17 28 .40 127 00 00 01 00 00 0 .50 11.76 11.48 1 122 00 00 01 00 00 0 .80 11. 118 00 01 0 .80 11. 118 00 01 0 .80 11. 118 00 01 0 .80 11. 122 00 00 0 .80 11. 122 00 00 0 .80 11. 1 10.42 1 00 00 00 1 10.42 1 00 00 00 1 10.42 1 00 00 00 1 10.42 1 01 OO 00 1 10.42 1 01 00 00 1 10.42 1 122 00 00 01 00 00 1.10 10.50 10.33 1 131 01 00 OO 00 00 1.10 10,50 10.33 1 1 3 1 0 1 00 00 00 00 1.10 10.50 10.33 1 131 01 00 00 00 00 1.10 10.50 10.33 1 131 01 00 00 00 00 1.10 10.50 10.33 1 131 01 00 00 00 OO 1.10 10.50 10.33 1 122 00 00 01 00 00 1.10 10.50 10.33 1 122 00 00 01 00 00 1.10 10.50 10.33 1 125 00 00 01 00 OO 1.10 10.50 10.33 1 125 00 00 01 00 00 1.10 10.50 10.33 1 122 00 00 01 00 00 1.10 10.50 10.33 1 122 00 01 00 00 00 1.05 10.51 10.35 1 122 00 01 00 00 00 1.05 10.51 10.35 1 122 00 00 01 00 00 1.05 10.51 10.35 1 120 00 00 01 00 00 1.05 10.51 10.35 1 122 00 00 01 00 00 1.05 10.51 10.35 1 168 00 00 01 00 00 1.05 10.51 10.35 1 122 00 00 01 00 00 1.05 10.51 10.35 1 125 00 OO 00 01 00 1.05 10.51 10.35 1 120 00 01 OO 00 OO 1.05 10.51 10.35 1 120 00 01 00 00 OO 1.00 10.51 10.34 1 122 OO OO 01 00 00 1.00 10.51 10.34 1 122 00 00 01 00 00 1.00 10.51 10.34 1 2476 .0 0 2482 .0 0 2482 .O 0 2482 .0 0 2482.6 .0 0 . 0 2482 .0 0 2482 .0 0 2489 .0 0 2489 .0 0 2489 .0 0 2489 .0 O 2489 .0 0 2489 .0 0 2489 .0 0 2489 .0 0 2489 .0 0 2489 .0 0 2489 .0 0 2496 .0 0 2496 .0 0 2496 .0 0 2496 .0 0 . 0 2496 . 5 .0 0 2496 .0 0 2496 .0 O 2496 .0 0 . 0 2496.5 .0 0 . 0 2506.4 .0 0 . 0 2506.4 .0 0 . 0 2506.4 .0 0 . 0 . 1 .0 .6 .0 . 6 .0 .6 .0 7372 .0 7 .70 1.0 1.0 1.0 7561.0 9.53 1.0 1.0 1.0 7561.0 9 .53 1.0 1.0 1.0 7561.0 9 .53 1.0 1.0 1.0 7561.0 9.53 1.0 1.O 1.0 7561.0 9 .53 1.0 1.0 1.0 7561.O 9.53 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.O 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.O 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7750.0 8.33 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.0 8.07 1.0 1.0 1.0 7939.O 8.07 1.0 1.0 1.0 8128.0 8. 10 1.0 1.0 1.0 8128 .0 8 .10 1.0 1.0 1.0 8128.0 8 . 10 1.0 1.0 1.0 8 .00 0938 1.0 01 8.53 1034 1.0 01 8.53 1034 1.0 01 8.53 1034 1 .O 01 8.53 1034 1.0 01 8.53 1034 1.0 01 8.53 1034 1.0 01 8.33 0972 1.0 01 8.33 0972 1.0 01 8.33 0972 1.0 01 8.33 0972 1.0 01 8.33 0972 0 01 33 0972 0 01 33 0972 0 01 33 0972 0 01 33 0972 0 01 33 0972 0 01 33 0972 O 01 60 0791 0 01 60 0791 0 01 8 .60 0791 1.0 01 8 .60 0791 1 .0 01 8 .60 0791 1 .0 01 8 .60 0791 1.0 01 % 8 .60 0791 1 .0 01 8 .60 0791 1.0 01 8 .60 0791 1 .0 02 8.53 0751 1.0 01 8.53 0751 1 .0 01 8.53 0751 1.0 01 > •923 1029 060 > 924 1029 08198 > 925 1019 060 > 926 1019 08198 > 927 1064 060 > 928 1064 08 198 > 929 1064 060 > 9.30 1064 08198 > 931 1005 060 > 932 1005 08198 > 933 1005 060 > 934 1005 08 198 > 935 1005 060. > 936 1005 08198 > 937 1005 060 . > 938 1005 08198 > 939 1063 060 . > 940 1063 08 198 > 94 1 104O 060 , > 942 1040 08 198 > 943 1040 060 > 944 1040 08 198 > 945 1040 060 > 946 1040 08 198 > 947 1031 060 . > 948 1031 08 198 > 949 1031 060 . > 950 1031 08 198 > 951 1031 060 -> 952 1031 08 198 > 953 1031 060 > 954 103 1 08 198 > 955 1031 060 > 956 1031 08 198 > . 957 1031 060 > 958 1031 08198 > 959 1024 060 . > 960 . 1024 08 198* > 961 1024 060 > 962 1024 08 198 > 963 1024 060 > 964 1024 08 198 > 965 1024 060 > 966 1024 08 198 > 967 1024 060 > 968 . 1024 08198 > 969 1024 060 . > 970 1024 08 198 > 971 1021 060 . > 972 1021 08 198 > 973 1019 060 > 974 1019 08198 > 975 1019 060 > 976 1019 08 198 > 977 5092 060 .. > 978 5092 08198 > 979 5025 060 > 980 5025 08 198 > 981 5025 060 . > 982 5025 08198 80000 6039 50 122 00 00 01 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 57000 4026 33 122 00 00 01 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 200000 8646 66 131 01 00 00 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 200000 8646 66 131 01 00 00 00 00 2506. 166.20 164.17 2 8 . 4 0 1.00 10.51 10.34 1.0 0 . 63500 4026 33 122 00 00 01 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 63000 4026 33 122 00 00 01 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 58000 4026 33 122 00 00 01 00 00 2506. 166.20 1 6 4 . 1 7 . 2 8 . 4 0 1.00 10.51 10.34 1.0 0. 90000 4026 33 122 00 00 01 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 . 215000 12480 125 100 00 01 00 00 00 2506. 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 68500 3000 25 120 00 01 00 00 00 2506 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0. 64000 3000 25 120 00 01 00 00 OO 2506 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 112000 6000 50 120 00 01 00 00 00 2506 166.20 164.17 2 8 . 4 0 1.00 10.51 10.34 1.0 0 75000 4026 33 122 00 00 01 00 00 2506 166.20 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164.17 28 .40 1.00 10.51 10.34 1.0 0 52000 4026 .33 122 00 00 01 00 00 2506 166.20 164.1.7 28 .40 1.00 10.51 10.34 1.0 O 68500 4026 33 122 00 00 01 OO OO 2506 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 0090000 006000 050 120 OO 01 00 00 00 2506 166.20 164.17 2 8 . 4 0 1.00 10.51 10.34 1.0 0 0068500 002950 025 118 00 01 00 00 00 2506 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 0064000 002950 025 118 00 01 00 00 00 2506 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 4 8128 .0 8 .10 8. 0 1.0 I . O 1.0 1. 4 8128 .0 8 .10 8. 0 1.0 1.O 1.0 1. 4 8128 .0 8 .10 8. 1.0 1.0 1.0 1. 8128 .0 8 .10 8. 1.0 1.O 1.0 1. 8128 .0 8 .10 8. 1.0 1.0 1.0 1. 8128 .0 8 .10 8. 1.0 1.O 1.0 1. 8128 .0 8 .10 8. 1.0 1.0 1.0 1 . 8128 .0 8 .10 8. 1.0 1.0 1.0 1. 8128 .0 8 .10 8. 1.0 1 .O 1.0 1 . 8128 .0 8 .10 8. 1.0 1.0 1.0 1 . 8128 .0 8 .10 8. 0 1.0 1.0 1.0 1. 4 8128 .0 8 .10 8. 1 . 0 1 . 0 1.0 1. 8128 .0 8 .10 8. 1.0 1 O 1.0 1 8128 .0 8 .10 8 1.0 1.0 1.0 1. 8128 .0 8 .10 8 1.0 1.0 1.0 1 8128 .0 8 .10 8 1.0 1.Q 1.0 1 8128 .0 8 .10 8 1.0 1 O 1.0 1 8128 .0 8 .10 8 1.0 1.0 1.0 1 8128 .0 8 .10 8 .0 1.0 1.O 1.0 1 .4 8128 .0 8 .10 8 1.0 1.O 1.0 1 8128 .0 8 .10 8 1.0 1.0 1.0 1 8128 .O 8 .10 8 1.0 1.0 1.0 1 8128 .0 8 .10 8 1.0 1.0 1.0 1 .4 8128 .0 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128 .0 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128 .0 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128.O 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128 .0 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128.O 8 .10 8 .0 1.0 1.0 1.0 1 .4 8128.O 8 .10 8 .0 1.0 1.0 1.0 1 .0 . 4 .0 .4 .0 . 4 .0 53 0751 0 01 53 0751 0 01 53 0751 0 02 53 0751 0 02 53 0751 0 01 53 0751 .0 01 .53 0751 .0 01 .53 0751 O 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 075 1 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .O 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 .53 0751 .0 01 53 0751 0 01 53 0751 O 01 53 0751 O 01 0 0 •> 984 5025 08198 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 . 0 1.0 1.0 1.0 1.0 01 > 985 6019 060 0215000 012480 125 100 00 01 00 00 00 2506.4 8128.0 8 .10 8.53 0751 > 986 6019 08198 166.20 164.17 28 .40 1.00 10.51 10.34 1.0 0 .0 1.0 1.0 1.0 1.0 > 987 6023 061 0337000 018649 173 108 00 00 01 00 00 2517.6 8311.3 9 .43 8 .40 1353 > 988 6023 06708 169.10 166.33 28.32 1.10 10.34 10.32 1.0 0 . 0 1.0 1.0 1.0 1.0 > 989 6017 062 0510000 018000 150 120 00 01 00 00 00 2524.1 8494.5 7.73 7.80 1003 > 99.0 6017 08105 173.03 168.37 28.24 1.20 10.45 10.39 1.0 0 . 0 1.0 1.0 1.0 1.0 > 991 6024 063 0150000 006288 048 131 01 00 00 00 00 2533.2 8677.8 7.67 8.27 1057 > 992 6024 07950 176.27 170.50 28 .16 1.15 10.48 10.43 1.0 0 . 0 1.0 1.0 1.0 1.0 > 993 6022 063 0335000 020130 165 122 00 00 01 00 00 2533.2 8677.8 7.67 8.27 1057 > - 994 6022 07950 176.27 170.50 28.16 1.15 10.48 10.43 1.0 0 .0 1.0 1.0 1.0 1.0 #End of F i l e H i $ . 0 7 , $ .17T #LIST LAND.MIDAS.2 > 1 $RUN M:MIDAS > 2 READ VAR=1-31 CASES=1-496 FILE=LANDSALES FORMAT=(F4 .0 ,2X , F3 .0 ,3X , F7 .O ,& > 3 1 X , F 6 . 0 . 1 X , F 3 . 0 , 1 X , F 3 . O . 5 ( 1 X . F 2 . 0 ) , 2 ( 1 X , F 6 . 1 ) . 1 X . F 4 . 2 , 1 X , F 4 . 2 , 1 X , F 4 . 0 , & > 4 2 X . / . F 4 . 0 . 2 X . F 5 . 0 . 2 ( 1 X . F 6 . 2 ) . 1 X . F 5 . 2 , 1 X . F 4 . 2 . 1X ,F5 .2 1 X . F 5 . 2 . 1X .F3 . 1,& > 5 5( 1X . F3 . 1 ) , 1X, F2 .0 ) LABELS = FILENO1,QUARTER,PRICE,LOTS IZE.FRONTAGE,DEPTH,& > 6 WESTEND,KITS . EASTVAN,MARPOLE,KERRI SDL,BCPOP,BCPERINC,UNEMPLUA,UNEMPLSA,& > 7 COMPLVAN,FILEN02,COMPLBC,CPIALL.CP IHOUSG.NONFAMHH,VACRATE.NHARATE,S > 8 CONVRATE.MURBSTAT.CCASTAT.CCANEW.CCANEWWP,ARPSTAT,RENTCONT.HOLDPER > 9 TRANS V32=V3/V4 LABEL=SPPERSF > IO TRANS V33=V3/V5 LABEL=SPPERFF > 11 TRANS V34=V3/V6 LABEL=SPPERDF > 12 TRANS V35=1.000 CASES=287-320 LABEL=DEFLATOR > 13 TRANS V35=1.137 CASES = 32 1-333 LABEL=DEFLATOR . > 14 TRANS V35=1.171 CASES=334-344 LABEL=DEFLATOR > 15 TRANS V35= 1 . 160 CASES = 345~348 LABEL=OEFLATOR > 16 TRANS V35=1.142 CASES=349-352 LABEL=DEFLATOR > 17 TRANS V35=1.231 CASES=353-355 LABEL=DEFLATOR > 18 TRANS V35=1.170 CASES=356 LABEL=DEFLATOR > 19 TRANS V35=1.142 CASES=357 LABEL=DEFLATOR > 20 TRANS V35=1.077 CASES=358-372 LABEL=DEFLATOR > 21 TRANS V35=1.104 CASES=373-374 LABEL=DEFLATOR > 22 TRANS V35=1.193 CASES=375-377 LABEL = DEFLA TOR > 23 TRANS V35=1.101 CASES = 378-379 LABEL=DEFLATOR > 24 TRANS V35=1.247 CASES=380~385 LABEL=DEFLATOR > 25 TRANS V35=1.257 CASES=386-389 LABEL=OEFLATOR > 26 TRANS V35=1.310 CASES=390-392 LABEL=DEFLATOR > 27 TRANS V35=1.293 CASES=393 LABEL=DEFLATOR > 28 TRANS V35=1.382 CASES=394-395 LABEL=DEFLATOR > 29 TRANS V35=1.576 CASES=396-397 LABEL=DEFLATOR > 30 TRANS V35=1.681 CASES=398 LABEL=DEFLATOR > 31 TRANS V35=1.662 CASES=399-404 LABEL=DEFLATOR > 32 TRANS V35=1.803 CASES=405-407 LABEL=DEFLATOR > 33 TRANS V35=1.752 CASES=408-411 LABEL=DEFLATOR > 34 TRANS V35=1.944 CASES=412-418 LABEL=DEFLATOR > 35 TRANS V35=1.887 CASES=419-426 LABEL=DEFLATOR > 36 TRANS V35=2.063 CASES=427-432 LABEL=DEFLATOR > 37 TRANS V35=2.152 CASES=433-438 LABEL=DEFLATOR > 38 TRANS V35=2.087 CASES=439-449 LABEL=DEFLATOR > 39 TRANS V35=2.125 CASES=450-458 LABEL=DEFLATOR > 40 TRANS V35=2.652 CASES=459-493 LABEL=DEFLATOR > 41 TRANS V35=2.196 CASES=494 LABEL=DEFLATOR > 42 TRANS V35=2.118 CASES=495 LABEL=DEFLATOR > 43 TRANS V35=2.218 CASES=496 LABEL=DEFLATOR > 44 TRANS V36=V3/V35 CASES=ALL LABEL=REALSP > 45 TRANS V37=V36/V4 LABEL=REALPPSF > 46 TRANS V38=V19/100.0 LABEL=CPINEW '> 47 TRANS V39=V32/V38 LABEL=NEWREALP > 48 .TRANS V40=V23/V38 LABEL=RLINTRTE > 49 TRANS V41=V12/2205.1 LABEL=POPGRRTE > 50 TRANS V42=V13/V38 LABEL=REALINC > 51 TRANS V43=V42/3695.85 LABEL=INCGRRTE > 52 CODE V44=V2 LABEL=NEWOTR > 53 TRANS V45=1G7.5 STRATA= V44:36 LABEL=RENTLEVEL > 54 TRANS V45=168.8 STRATA=V44:37 LABEL=RENTLEVEL > 55 TRANS V45=170.0 STRATA=V44:38 LABEL=RENTLEVEL > 56 TRANS V45=176.0 STRATA=V44:39 LABEL=RENTLEVEL > 57 TRANS V45=182.0 STRATA=V44:40 LABEL=RENTLEVEL > 58 TRANS V45=194.0 STRATA 3 V44:42 LABEL=RENTLEVEL > 59 TRANS V45=214.0 STRATA=V44:45 LABEL=RENTLEVEL > 60 TRANS V45=220.0 STRATA=V44:47 LABEL=RENTLEVEL > 61 TRANS V45=229.0 STRATA=V44:50 LABEL-RENTLEVEL > 62 TRANS V45=247.0 STRATA=V44:53 LABEL=RENTLEVEL > 63 TRANS V45=253.0 STRATA=V44:54 LABEL=RENTLEVEL > 64 TRANS V45=256.5 STRATA=V44:55 LABEL=RENTLEVEL > 65 TRANS V45=260.0 STRATA=V44:56 LABEL=RENTLEVEL > 66 TRANS V45=263.5 STRATA=V44:57 LABEL=RENTLEVEL > 67 TRANS V45=267.0 STRATA=V44:58 LABEL=RENTLEVEL > 68 TRANS V45=269.8 STRATA=V44:59 LABEL=RENTLEVEL > 69 TRANS V45=272.5 STRATA=V44:60 LABEL=RENTLEVEL > 70 TRANS V45=275.3 STRATA=V44:61 LABEL^RENTLEVEL > 71 TRANS V45=278.0 STRATA=V44:62 LABEL 3 RENTLEVEL > 72 TRANS V45=278.0 STRATA=V44:63 LABEL=RENTLEVEL > 73 TRANS V46 = V45/10O.O STRATA = NONE LABEL = GRRTRENT > 74 TRANS V47=103.5 STRATA=V44:36 LABEL=CONSTNCOST > 75 TRANS V47=105.1 STRATA=V44:37 LABEL=CONSTNCOST > 76 TRANS V47=108.2 STRATA=V44:38 LABEL=CONSTNCOST > 77 TRANS V47=111.1 STRATA=V44:39 LABEL=CONSTNCOST > 78 TRANS V47=116.3 STRATA = V44 :40 LABEL = CONSTNCOST > 79 TRANS V47=123.6 STRATA=V44:42 LABEL=CONSTNCOST > 80 TRANS V47=130.3 STRATA=V44:45 LABEL=CONSTNCOST > .81 TRANS V47=137.0 STRATA=V44:47 LABEL=CONSTNCOST > 82 TRANS V47=141.5 STRATA = V44:50 LABEL=CONSTNCOST > 83 TRANS V47=154.5 STRATA=V44:53 LABEL=CONSTNCOST > 84 TRANS V47=159.3 STRATA=V44:54 LABE L = C0NSTNC0ST > 85 TRANS V47= 162.6 STRATA = V44:55 LABEL =CONSTNCOST > 86 . TRANS V47=165.6 STRATA=V44:56 LABEL = CONSTNCOST > 87 ' TRANS V47=168.5 STRATA=V44:57 LABEL=CONSTNCOST > 88 TRANS V47=174.0 STRATA=V44:58 LABEL=CONSTNCOST > 89 TRANS V47=179.5 STRATA=V44:59 LABEL=CONSTNCOST > 90 TRANS V47=180.4 STRATA=V44:60 LABE.L=CONSTNCOST > 91 TRANS V47=184.2 STRATA = V44:61 LABEL = CONSTNC0ST > 92 TRANS V47=189.9 STRATA=V44:62 LABEL=C0NSTNC0ST > 93 TRANS V47=194.5 STRATA=V44:63 LABEL=CONSTNCOST > 94 TRANS V48=V47/100.0 STRATA=NONE LABEL=GRRTCOST > 95 TRANS V49=2.9 STRATA=V44:36 LABEL=RENTGRTH > 96 TRANS V49=3.1 STRATA=V44:37 LABEL=RENTGRTH > 97 TRANS V49=2.9 STRATA=V44:38 LABEL=RENTGRTH > 98 TRANS V49=14.9 STRATA=V44:39 LABEL=RENTGRTH > 99 TRANS V49=14.3 STRATA=V44:40 LABEL=RENTGRTH > 100 TRANS V 4 9 M 3 . 4 STRATA = V44 : 42 LABEL=RENTGRTH > 101 TRANS V49=5.8 STRATA=V44:45 LABEL=RENTGRTH > 102 TRANS V49 = 5.6 STRATA = V44:47 LABEL = RENTGRTH > 103 TRANS V49=5.4 STRATA=V44:50 LABEL=RENTGRTH > 104 TRANS V49=10.3 STRATA=V44:53 LABEL=RENTGRTH > 105 TRANS V49=10.1 STRATA=V44:54 LABEL=RENTGRTH > 106 TRANS V49 = 5.6 STRATA = V44 : 55 LABEL = RENTGRTH O > 107 TRANS V49-= 5 . 6 STRATA=V44:56 LABEL=RENTGRTH > 108 TRANS V49-= 5 . 5 STRATA=V44:57 LABEL=RENTGRTH > 109 TRANS V49 = 5 . 4 STRATA=V44:58 LABEL=RENTGRTH > 1 10 TRANS V49 = 4 . 3 STRATA=V44:59 LABEL=RENTGRTH > 1 1 1 TRANS V49 = 4 . 1 STRATA=V44:60 LABEL=RENTGRTH > 1 12 TRANS V49 = 4 . 2 STRATA=V44:61 LABEL=RENTGRTH > 1 13 TRANS V49 = 4 . 0 STRATA=V44:62 LABEL=RENTGRTH > 114 TRANS V49 =0. 0 STRATA=V44:63 LABEL=RENTGRTH > 1.15 TRANS V50 = 10 . 7 STRATA=V44 36 LABEL=COSTGRTH > 1 '1.6 TRANS V50 = 6 . 3 STRATA=V44:37 LABEL=COSTGRTH > 1 I? TRANS V50 = 1 1 .5 STRATA=V44 38 LABEL=COSTGRTH > 118 TRANS V50 = 1 1 . 2 STRATA=V44 39 LABEL=COSTGRTH > 1 19 TRANS V50 = 20 . 1 STRATA=V44 40 LABEL=COSTGRTH > 120. TRANS V50 = 17 . 2 STRATA=V44 42 LABEL=COSTGRTH > 121 TRANS V50 = 6 . 4 STRATA=V44:45 LABEL=COSTGRTH > 122 TRANS V50 = 4 . 5 STRATA=V44:47 LABEL=COSTGRTH > 123 TRANS V50 = 18 . 2 STRATA=V44 50 LABEL=COSTGRTH > 124 TRANS V50 = 9 . 3 STRATA=V44:53 LABEL=COSTGRTH > 125 TRANS V50 = 13 .0' STRATA=V44 54 LABEL=COSTGRTH > 126 TRANS V50 = 8 . 5 STRATA=V44:55 LABEL=COSTGRTH > 127 TRANS V50 = 7 . 6 STRATA=V44:56 LABEL=COSTGRTH > 128 TRANS V50 = 7 . 2 STRATA=V44:57 LABEL=COSTGRTH > 129 TRANS V50 = 13 . 7 STRATA=V44 58 LABE L = C0STGRTH > 130 TRANS V50 = 13 . 3 STRATA=V44 59 LABE L = C0STGRTH > 131 TRANS V50 = 2 . 0 STRATA=V44:60 LABEL=COSTGRTH > 132 TRANS V50 = 8 . 7 STRATA=V44:61 LABEL=C0STGRTH > 133 TRANS V50 = 13 .0 STRATA=V44 62 LABEL=COSTGRTH > 134 TRANS V50 = 10.0 STRATA=V44 63 LABEL=COSTGRTH > 136 TRANS V51 = 3 . 13 STRATA=V44 36 CASES=ALL LABEL=P0PGRTH > 137 TRANS V51 = 3 . 40 STRATA=V44 37 LABEL=POPGRTH > 138 TRANS V51 = 2 . 12 STRATA=V44 38 LABEL=POPGRTH > 139 TRANS V5 1 = 1 . 91 STRATA=V44 39 LABEL=POPGRTH > 140 TRANS V51 = 2 . 77 STRATA=V44 40 LABEL=POPGRTH > 14 1 TRANS V51 = 2 . 10 STRATA=V44 42 LABEL=POPGRTH > 142 TRANS V51 = 4 . 01 STRATA=V44 45 LABEL=POPGRTH > 143 TRANS V51 = 3 . 08 STRATA=V44 47 LABEL=POPGRTH > 144 TRANS V51 = 1 . 60 STRATA=V44 50 LABEL=POPGRTH > 145 TRANS V51 = 1 . 51 STRATA=V44 53 LABE L = POPGRTH > 146 TRANS V5 1 =0. 77 STRATA=V44 54 LABEL=POPGRTH > 147 TRANS V5 1 = 1 27 STRATA=V44 55 LABEL=POPGRTH > 148 TRANS V5 1 = 1 06 STRATA=V44 56 LABEL=POPGRTH > 149 TRANS V51 = i 05 STRATA=V44 57 LABEL=POPGRTH > 150 TRANS V5 1 = 1 07 STRATA=V44 58 LABEL=POPGRTH > 151 TRANS V51 = 1 18 STRATA=V44 59 LABEL=POPGRTH > 152 TRANS V51 = 1 60 STRATA=V44 •60 LABEL=POPGRTH > 153 TRANS V51 = 1 80 STRATA=V44 •61 LABEL=POPGRTH > 154 TRANS V51 = 1 04 STRATA=V44 :62 LABEL=POPGRTH > 155 TRANS V51 = 1 45 STRATA=V44 :63 LABEL=POPGRTH > 156 TRANS V52 = 6 20 STRATA=V44 : 36 LABEL=GRRLINC > 157 TRANS V52 = 6 88 STRATA=V44 : 37 LABE L = GRRLINC > 158 TRANS V52 = 8 10 STRATA=V44 : 38 LABEL=GRRLINC > 159 TRANS V52 = 9 04 STRATA=V44 : 39 LABEL=GRRLINC > 160 TRANS V52 = 8 17 STRATA=V44 : 40 LABE L = GRRLINC > 161 TRANS V52 = 8 20 STRATA=V44 :42 LABEL=GRRLINC > 162 TRANS V52 = 6 84 STRATA=V44 :45 LABEL = GRRLINC > 163 TRANS V52 = 1 51 STRATA=V44 :47 LABEL=GRRLINC > 164 TRANS V52 = 3 86 STRATA=V44 : 50 LABEL=GRRLINC > 165 TRANS V52 = 4 21 STRATA=V44 : 53 LABEL=GRRLINC > 166 TRANS V52 .80 STRATA=V44:54 LABEL=GRRLINC > 167 TRANS V52 = 7 15 STRATA=V44 : 55 LABEL=GRRLINC I —« I > 168 TRANS V52=6.22 STRATA=V44:56 LABEL=GRRLINC > 169 TRANS V52 = 4 .76 STRATA = V44:57 LABEL = GRRLINC > 170 TRANS V52=2.20 STRATA=V44:58 LABEL=GRRLINC > 171 TRANS V52=3.01 STRATA=V44:59 LABEL=GRRLINC > 172 TRANS V52=1.97 STRATA=V44:60 LABEL=GRRLINC > 173 TRANS V52=2.02 STRATA=V44:61 LABEL=GRRLINC > 174 TRANS V52=-0.47 STRATA=V44:62 LABEL=GRRLINC > 175 TRANS V52=1.13 STRATA=V44:63 LABEL=GRRLINC > 176 TRANS V53=3.96 STRATA=V44:36 LABEL=INFLATION > 177 TRANS V53=4.16 STRATA = V44:37 LABEL = INFLATI ON > 178 TRANS V53=4.19 STRATA=V44:38 LABEL=INFLATION > 179 TRANS V53 = 3.85 STRATA = V44:39 LABEL=INFLAT ION > 180 TRANS V53=3.85. STRATA=V44:40 LABEL=INFLATION > 181 TRANS V53 = 5.91 STRATA = V44:42 LABEL=INFLAT I ON > 182 TRANS V53 = 9.64 STRATA = V44:45 LABEL = INFLAT ION > 183 TRANS V53=12.23 STRATA = V44:47 LABEL = INFLATI ON > 184 TRANS V53=1 1.02 STRATA = V44:50 LABEL = INFLATI ON > 185 TRANS V53 = 9 .78 STRATA = V44:53 LABEL=INFLAT ION > 186 TRANS V 5 3 =n . 3 5 STRATA = V44 : 51 LABEL = INFLATION > 187 TRANS V53=9.06 STRATA=V44:55 LABEL=INFLATION > 188 TRANS V53=8.68 STRATA=V44:56 LABEL=INFLATION > 189 TRANS V53=8.33 STRATA = V44:57 LABEL=INFLAT ION > 190 TRANS V53 = 6.44 STRATA = V44:58 LABEL = INFLAT I ON > 191 TRANS V53=6.71 STRATA=V44:59 LABEL=INFLATION > 192 TRANS V53=7.07 STRATA = V44:60 LABEL = I NFLAT I ON > 193 TRANS V53 = 7.45 STRATA = V44:61 LABEL = INFLAT I ON . > 194 TRANS V53 = 7.85 STRATA = V44:62 LABEL = INFLAT I ON > 195 TRANS V53 = 8 .05 STRATA=V44:63 LABEL=INFLAT ION > 196 TRANS V54=-0.17 STRATA=V44:36 LABEL=GRRLRNT > 197 TRANS V54 = -2 .37 STRATA = V4"4 : 37 LABEL=GRRLRNT > 198 TRANS V54=-1.04 STRATA=V44:38 LABEL=GRRLRNT > 199 TRANS V54=11.84 STRATA=V44:39 LABEL=GRRLRNT > 200 TRANS V54=10.78 STRATA=V44:40 LABEL=GRRLRNT > 201 TRANS V54=3.05 STRATA=V44:42 LABEL=GRRLRNT > 202 TRANS V54=-4.38 STRATA=V44:45 LABEL=GRRLRNT > 203 TRANS V54 = -8.02 STRATA = V44 :47 LABEL=GRRLRNT > 204 TRANS V54=-3.74 STRATA=V44:50 LABEL=GRRLRNT > 205 TRANS V54 = 3.12 STRATA = V44 :53 LABEL = GRRLRNT > 206 TRANS V54=-5.03 STRATA=V44:54 LABEL=GRRLRNT > 207 TRANS V54=-0.14 STRATA=V44:55 LABEL=GRRLRNT > 208 TRANS V54=-0.71 STRATA=V44:56 LABEL=GRRLRNT > 209 TRANS V54=-0.12 STRATA=V44:57 LABEL=GRRLRNT > 210 TRANS V54=-2.39 STRATA=V44:58 LABEL=GRRLRNT > 211 TRANS V54=-2.48 STRATA=V44:59 LABEL=GRRLRNT > 212 TRANS V54=-3.41 STRATA=V44:60 LABEL=GRRLRNT > 213 TRANS V54=-2.80 STRATA=V44:6 1 LABEL=GRRLRNT > 214 TRANS V54 = -5 .13 STRATA = V44 :62 LABEL=GRRLRNT > 215 • TRANS V54=-7.17 STRATA=V44:63 LABEL=GRRLRNT > 216 TRANS V55=V23-V53 STRATA=NONE LABEL=REALINT > 217 TRANS V56=V45/V38 STRATA=NONE CASES=378-496 LABEL=RE > 218 TRANS V57=8.17 STRATA=V44:36 CASES=ALL LABEL=CCOSTBC > 219 TRANS V57=6.06 STRATA=V44:37 LABEL=CCOSTBC > 220 TRANS V57=9.44 STRATA=V44:38 LABEL=CCOSTBC > 221 TRANS V57=10.37 STRATA=V44:39 LABEL=CCOSTBC > 222 TRANS V57=16.22 STRATA=V44:40 LABEL=CCOSTBC > 223 TRANS V57=11.52 STRATA=V44:42 LABEL=CCOSTBC > 224 TRANS V57=13.92 STRATA=V44:45 LABEL=CCOSTBC > 225 TRANS V57=11.84 STRATA=V44:47 LABEL=CCOSTBC > 226 TRANS V57=2 1.32 STRATA=V44:50 LABEL=CCOSTBC > 227 TRANS V57=11.58 STRATA=V44:53 LABEL=CCOSTBC > 228 TRANS V57 = 8 .02 STRATA=V44: 54 LABEL=CCOSTBC > 229 TRANS V57 = 10. 77 STRATA=V44 : 55 LABEL=CCOSTBC > 230 TRANS V57 = 1 1 . 52 STRATA=V44 : 56 LABEL=CCOSTBC > 23 1 TRANS V57 = 9 . 94 STRATA = V44 : 57 LABEL=CCOSTBC > 232 TRANS V57 = 13.17 STRATA=V44 :58 LABEL=CCOSTBC > 233 TRANS V57 = 13 . 72 STRATA=V44 : 59 LABEL=CCOSTBC > 234 TRANS V57 = 3 . 26 STRATA=V44: 60 LABEL=CCOSTBC > 235 TRANS V57 = 10.84 STRATA=V44 :61 LABEL=CCOSTBC > 236 TRANS V57 = 13 .03 STRATA=V44 :62 LABEL=CCOSTBC > 237 TRANS V57 = 8 .72 STRATA=V44: 63 LABEL=CCOSTBC > 238 TRANS V58 = 1 . 20 STRATA=V44: 36 LABEL=RNTGRTH2 > 2 39 TRANS V58 = 1 . 19 STRATA=V44: 37 LABEL=RNTGRTH2 > 240 TRANS V58 = 1 . 59 STRATA=V44: 38 LABEL=RNTGRTH2 > 24 1 TRANS V58 = 1 .98 STRATA=V44: 39 LABEL=RNTGRTH2 > 242 TRANS V58 = 1 . 97 STRATA=V44: 40 LABEL=RNTGRTH2 > 243 TRANS V58 = 3 . 53 STRATA=V44: 42 LABEL=RNTGRTH2 > 244 TRANS V58 = 3 .81 STRATA=V44: 45 LABEL=RNTGRTH2 > 245 TRANS V58 = 7 . 15 STRATA=V44: 47 LABEL=RNTGRTH2 > 246 TRANS V58 = 7 . 95 STRATA=V44: 50 LABEL=RNTGRTH2 > 247 TRANS V58 = 7 . 12 STRATA=V44: 53 LABEL=RNTGRTH2 > 248 TRANS V58 = 5 .97 STRATA=V44: 54 LABEL=RNTGRTH2 249 TRANS V58 = 7 . 57 STRATA=V44: 55 LABEL=RNTGRTH2 > 250 TRANS V58 = 7 . 43 STRATA = V44 : 56 LABEL=RNTGRTH2 > 25 1 TRANS V58 = 6 . 96 STRATA=V44: 57 LABEL=RNTGRTH2 > 252 TRANS V58 = 5 . 26 STRATA=V44: 58 LABEL=RNTGRTH2 > 253 TRANS V58 = 4 . 88 STRATA=V44: 59 LABEL=RNTGRTH2 > 254 TRANS V58 = 3 . 90 STRATA=V44: 60 LABEL=RNTGRTH2 > 255 TRANS V58 = 2 . 37 STRATA=V44: 61 LABEL==RNTGRTH2 > 256 TRANS V58 = 2 . 95 STRATA=V44: 62 LABEL=RNTGRTH2 > 257 TRANS V58 = 3 . 82 STRATA=V44: 63 LABEL=RNTGRTH2 > 258 TRANS V59 = 1 .31 STRATA=V44: 36 LABEL=RNTGRTH3 > 259 TRANS V59 = : —I 0.94 i STRATA=V44 l : 37 '' LABEL = RNTGRTH3 > 260 TRANS V59 = 0 . 50 STRATA=V44: 38 LABEL=RNTGRTH3 > 26 1 TRANS V59 = ••-7.62 STRATA=V44:32 I LABEL=RNTGRTH3 > 262 TRANS V59 = 8.12 STRATA=V44:40 LABEL=RNTGRTH3 > 263 TRANS V59 = = - 13.96 STRATA=V44:42 LABEL=RNTGRTH3 > 264 . TRANS V59 = = 10.27 STRATA=V44:45 LABEL=RNTGRTH3 > 265 TRANS V59 = 6.21 I STRATA=V44:47 ' LABEL=RNTGRTH3 > 266 TRANS V59 = = -2.00 STRATA=V44:50 LABEL=RNTGRTH3 > 267 TRANS V59 = MO.20 STRATA=V44:53 LABEL=RNTGRTH3 > 268 TRANS V59 = = 1 .08 STRATA=V44: 54 LABEL=RNTGRTH3 > 269 TRANS V59 = =17.41 I STRATA=V44:55 LABEL=RNTGRTH3 > 270 TRANS V59 = =15.54 STRATA=V44:56 LABEL=RNTGRTH3 > 27 1 TRANS V59 = =15.13 STRATA=V44:57 LABEL=RNTGRTH3 > 272 TRANS V59 = =11.57 STRATA=V44:58 LABEL=RNTGRTH3 > 273 TRANS V59 = =10.92 STRATA=V44:59 LABEL=RNTGRTH3 > 274 TRANS V59 = = 9 . 29 STRATA=V44: :60 LABEL=RNTGRTH3 > 275 TRANS V59 = = 9 . 18 STRATA=V44: :61 LABEL=RNTGRTH3 > 276 TRANS V59 = = 6 .09 STRATA=V44; :62 LABEL=RNTGRTH3 > 277 TRANS V59 = = -14.89 STRATA=V44:63 LABEL=RNTGRTH3 > 278 TRANS V60= 2.88 STRATA=V44:36 LABEL=LAGRENT > 279 TRANS V60= = -2.02 STRATA=V44:37 LABEL=LAGRENT > 280 TRANS V60= ---4.33 STRATA=V44:38 LABEL=LAGRENT > 28 1 TRANS V60 = --- 2.36 STRATA=V44:39 LABEL=LAGRENT > 282 TRANS V60= ---0.75 STRATA=V44:40 LABEL=LAGRENT > 283 284 TRANS V60= --- 5.86 STRATA=V44:42 LABEL=LAGRENT > TRANS V60= ---4.07 STRATA=V44:45 LABEL=LAGRENT > 285 TRANS V60= ---9.99 STRATA=V44:47 LABEL=LAGRENT > 286 TRANS V60= - - 2.63 STRATA=V44:50 LABEL=LAGRENT > 287 TRANS V60= =G 1 .16 STRATA=V44 : 53 LABEL=LAGRENT CO > 288 TRANS V60= 0.11 STRATA=V44:54 LABEL=LAGRENT > 289 TRANS V60 = -9 .93 STRATA=V44:55 LABEL=LAGRENT > 290 TRANS V60 = 1.77 STRATA=V44:56 LABEL=LAGRENT > 29 1 TRANS V60= 1.11 STRATA = V44 :57 LABEL = LAGRENT > 292 TRANS V60 = 1.33 STRATA=V44:58 LABEL=LAGRENT > 293 TRANS V60 = -2 .75 STRATA=V44:59 LABEL=LAGRENT > 294 TRANS V60 = -2 .02 STRATA=V44:60 LABEL=LAGRENT > 295 TRANS V60= -3 .84 STRATA=V44:61 LABEL=LAGRENT > 296 TRANS V60= -4 .79 STRATA=V44:62 LABEL=LAGRENT > 297 TRANS V60= -6 .68 STRATA=V44:63 LABEL=LAGRENT > 298 TRANS V6 1 = 6 .37 STRATA=V44:36 LABEL=LAGCOSTS > 299 TRANS V6 1 = 4 .95 STRATA=V44:37 LABEL=LAGCOSTS > 300 TRANS V6 1 = 0 .54 STRATA=V44:38 LABEL=LAGCOSTS > 301 TRANS V6 1 = 5.49 STRATA=V44:39 LABEL=LAGCOSTS > 302 TRANS V6 1 = 7.64 STRATA=V44:40 LABEL=LAGCOSTS > 303 TRANS V6 1 = 5.17 STRATA=V44:42 LABEL=LAGCOSTS > 304 TRANS V6 1 = 2.24 STRATA=V44:45 LABEL=LAGCOSTS > 305 TRANS V61 = -5 .15 STRATA=V44:47 LABEL=LAGCOSTS > 306 TRANS V6 1 = -7.12 STRATA=V44:50 LABEL=LAGCOSTS > 307 TRANS V6 1 = -0 .24 STRATA=V44:53 LABEL=LAGCOSTS > 308 TRANS V6 1 = 4 .57 STRATA = V44:54 LABEL = LAGCOSTS > 309 TRANS V6 1 = -7 .88 STRATA=V44:55 LABEL=LAGCOSTS > 310 TRANS V6 1 = 4 .97 STRATA=V44:56 LABEL=LAGCOSTS > 31 1 TRANS V6 1 = 5 .20 STRATA=V44:57 LABEL=LAGCOSTS > 312 TRANS V6 1 = 4.31 STRATA=V44:58 LABEL=LAGCOSTS > 313 TRANS V6 1 = 5.16 STRATA=V44:59 LABEL=LAGCOSTS > 314 TRANS V6 1 = 6 .82 STRATA=V44:60 LABEL=LAGCOSTS > 315 TRANS V61 = -4 .48 STRATA=V44:61 LABEL=LAGCOSTS > 3 16 TRANS V6 1 = 3.68 STRATA=V44:62 LABEL=LAGCOSTS > 317 TRANS V61 = 3 .40 STRATA=V44:63 LABEL=LAGCOSTS > 3 18 TRANS V62 = V58-V53 LABEL = RNTGRTH4 STRATA = NONE > 3 1.9 TRANS V63 = V57-V53 LABEL = CC0STBC2 STRATA = NONE > 320 TRANS V64 = 10.41 STRATA=V44:36 LABEL=CAPRATE > 321 TRANS V64 = 7 . 72 -STRATA = V44:37 LABEL = CAPRATE > 322 TRANS V64 = 9 .83 STRATA = V44 : 38 LABEL = CAPRATE > 323 TRANS V64 = 10.20 STRATA=V44:39 LABEL=CAPRATE > 324 TRANS V64 = 10.52 STRATA=V44:40 LABEL=CAPRATE > 325 TRANS V64 = 1.74 STRATA=V44:42 LABEL=CAPRATE > 326 TRANS V64 = 1.20 STRATA=V44:45 LABEL=CAPRATE > 327 TRANS V64 = -2 .76 STRATA=V44:47 LABEL=CAPRATE > 328 TRANS V64 = 3.64 STRATA=V44:50 LABEL=CAPRATE > 329 TRANS V64 = 4.81 STRATA=V44:53 LABEL=CAPRATE > 330 TRANS V64 = - 4 . 9 0 STRATA=V44:54 LABEL=CAPRATE > 331 TRANS V64 = 6 .48 STRATA=V44:55 LABEL=CAPRATE > 332 TRANS V64 = 6 .63 STRATA=V44:56 LABEL=CAPRATE > 333 TRANS V64 = 6 . 2 0 STRATA=V44:57 LABEL=CAPRATE > 334 TRANS V64 = 5.34 STRATA=V44:58 LABEL=CAPRATE > 335 TRANS V64 = 5.06 STRATA=V44:59 LABEL=CAPRATE > 336 TRANS V64 = 5.44 STRATA=V44:60 LABEL=CAPRATE > 337 TRANS V64 = 6.61 STRATA=V44:61 LABEL=CAPRATE > 338 TRANS V64 = 2 .73 STRATA=V44:62 LABEL=CAPRATE > 339 TRANS V64 = 5.73 STRATA=V44:63 LABEL=CAPRATE > 340 TRANS V65 = 9 .84 STRATA=V44:36 LABEL=CAPRTLAG > 341 TRANS V65 = 10.41 STRATA=V44:37 LABEL=CAPRTLAG > 342 TRANS V65 = 7.72 STRATA=V44:38 LABEL=CAPRTLAG > 343 TRANS V65 = 9 .83 STRATA=V44:39 LABEL=CAPRTLAG > 344 TRANS V65 = 10 .20 STRATA=V44:40 LABEL=CAPRTLAG > 345 TRANS V65 = 6 .34 STRATA=V44:42 LABEL=CAPRTLAG > 346 TRANS V65 = 4 .43 STRATA=V44:45 LABEL=CAPRTLAG > 347 TRANS V65 = - 5 . 1 0 STRATA=V44:47 LABEL=CAPRTLAG v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v t i Ju ^ ^ A ft U C J t J U C J U C J Q U U U . 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TJ TJ 73 TJ TJ TJ T l TJ TJ 73 73 73 T3 > > > > > > > > 73 > > > > > > > > > > > > >• > > > > > > > > > > > > -1 -1 —1 H —i > -i -1 —i H —i —1 H H —i -1 -1 —1 -1 > > > > > > > > > > > > > > > J> > > t> > > > > > > > > > > > > •> II II II ll II II II II > I I 11 II I I 11 II I I II I I ll II I I I I I I I I II II n II II II II ll ll 11 < < < < < < < < II < < < < < < < < < < < < < < < < < < < < < < < < < ft ft ft ft ft ft ft ft < ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft ft • ft ft ft ft ft ft ft ft ft ft ft cn cn cn cn Ul Ul U l Ul U l Ul U l CJ CJ cn cn cn cn Ul U l Ul Ul Ul Ul U l U l ft ft ft ft CO CO CJ CO CO ro O CO CO cn Ul ft CJ O cn CO IO . O CO 00 cn Ul ft CO O Ul ro o CO CO -1 cn Ul i~ \— r- t- f~ r- |— |— I-> > 03 00 m m i— r-ti n o o > > TJ "0 CD CD > > & CO CO rn m |— II O n > > 73 TJ CD CD CO CO m m Z Z Z 2 - « 2 Z Z 2 - < 2 2 Z CD CD > > 2 Z > > CO CO tn m t r-ti n z z a a 2 2 CD CD > > T3 TJ 73 73 I— I- I-> > t> CO CO 03 m m m > i> > CO 03 CO m tn m CO 03 rn m i— l— r -> > co co m m I- r-n II II ti II II II II II n ti 2 Z Z O O O 2 S 2 O CD CD > > > TJ TJ TJ 73 TJ 73 _ Z z O O O 2 2 2 CD CD CD > > > TJ TJ U 73 73 73 z z o o 3 2 O CD > > TJ "0 73 73 2 Z o o 3 3 CD O > > T3 TJ 73 73 > > CO CO m m r - i— II II z z o o 2 2 CD CD > > 73 TJ T! TJ —4 H 03 00 m m Z Z o o 2 3 O CD > > TJ TJ 73 73 |— I - f > > > > 00 CO CO 03 m tn m m r~ it ti ti n z z z > O O O 73 3 2 2 73 CD CD CD —I > > > I -T l 73 TJ > 73 73 73 CD H —4 H > > CO CO m m i — i -> > > > I -03 CO tn tn CO 00 m m t — r- i — i — 3> » > > CO CO CO 00 m m m m r r CD CD CD CD CD CD 11 > > 73 T> 73 T l II II II > > > > TJ "0 TJ TJ TJ TJ 73 TJ CD CD CD > > > T l 73 73 73 73 73 > i > > > j > > r - > > > C D C D C D C D C D C D » C D C D C D CD - 155 -' > 408 TRANS V68=7.69 STRATA=V44:50 LABEL=CAPGNLAG > 409 TRANS V68=-1.00 STRATA=V44:53 LA8EL=CAPGNLAG > 410 TRANS V68=-1.41 STRATA=V44:54 LABEL=CAPGNLAG > 411 TRANS V68=-5.90 STRATA=V44:55 LABEL=CAPGNLAG > 412 TRANS V68=2.72 STRATA=V44:56 LABEL=CAPGNLAG > 413 TRANS V68=3.84 STRATA=V44:57 LABEL=CAPGNLAG > 414 TRANS V68=9.21 STRATA=V44:58 LABEL=CAPGNLAG > 415 TRANS V68=3.87 STRATA=V44:59 LABEL=CAPGNLAG > 416 TRANS V68=6.49 STRATA=V44:60 LABEL=CAPGNLAG > 417 TRANS V68=13.03 STRATA=V44:61 LABEL=CAPGNLAG > 4 18 TRANS V68=7.73 STRATA=V44:62 LABEL=CAPGNLAG > 419 TRANS V68=2.44 STRATA=V44:63 LABEL=CAPGNLAG > 420 TRANS V69=1.89 STRATA =V44:36 LABEL = P0PLAG > 421 TRANS V69=3.13 STRATA=V44:37 LABEL=P0PLAG > 422 TRANS V69=3.40 STRATA=V44:38 LABEL=P0PLAG > 423 TRANS V69=2.12 STRATA=V44:39 LABEL=P0PLAG > 424 TRANS V69=1.91 STRATA=V44:40 LABEL=P0PLAG > 425 TRANS V69 = 3.39 STRATA = V44:42 LABEL = P0PLAG > 426 TRANS V69=3.39 STRATA=V44 : 45 LABEL=P0PLAG > 427 TRANS V69=2.53 STRATA=V44:47 LABEL=P0PLAG > 4 2 8 ' TRANS V69=2.95 STRATA=V44:50 LABEL=P0PLAG > 429 TRANS V69=1.72 STRATA=V44:53 LABEL=POPLAG > 430 TRANS V69=1.51 STRATA=V44:54 LABEL=POPLAG > 431 TRANS V69=0.77 STRATA=V44:55 LABEL=P0PLAG > 432 TRANS V69=1.27 STRATA=V44:56 LABEL=P0PLAG > 433 TRANS V69=1.06 STRATA = V44:57 LABEL = POPLAG > 434 TRANS V69=1.05 STRATA = V44 : 58 LABEL=POPLAG > 435 TRANS V69=1.07 STRATA = V44:59 LABE L = POPLAG > 436 TRANS V69=1.18 STRATA=V44:60 LABEL=POPLAG > 437 TRANS V69=1.60 STRATA=V44:61 LABEL=POPLAG > 438 TRANS V69= 1 . 80 STRATA = V44:62 LABEL = POPLAG > 439 TRANS V69=1.04 STRATA=V44:63 LABEL = POPLAG > 440 TRANS V70=V64-V55 STRATA=NONE CASES=378-496 LABEL=RLA > 441 TRANS V71=5.55 STRATA=V44:36 LABEL=RLINCLAG CASES=ALL > 442 TRANS V71=6.20 STRATA=V44:37 LABEL=RLINCLAG > 443 TRANS V71=6.88 STRATA=V44:38 LABEL=RLINCLAG > 444 TRANS V71=8.10 STRATA = V44:39 LABEL = RLINCLAG > 445 TRANS V71=9.04 STRATA=V44:40 LABEL=RLINCLAG > 446 TRANS V71=9.69 STRATA=V44:42 LABEL=RLINCLAG > 447 TRANS V71=7.56 STRATA=V44:45 LABEL=RLINCLAG > 448 TRANS V71=1.47 STRATA=V44:47 LABEL=RLINCLAG >• 449 TRANS V71=5.16 STRATA=V44:50 LABEL=RLINCLAG > 450 TRANS V71=3.89 STRATA=V44:53 LABEL=RLINCLAG > 451 TRANS V71=4.21 STRATA=V44:54 LABEL=RLINCLAG > 452 TRANS V71=-1.80 STRATA=V44:55 LABEL=RLINCLAG > 453 TRANS V71=7.15 STRATA=V44:56 LABEL=RLINCLAG > 454 TRANS V71=6.22 STRATA=V44:57 LABEL=RLINCLAG > 455 TRANS V71=4.76 STRATA=V44:58 LABEL=RLINCLAG > 456 TRANS V71=2.20 STRATA=V44:59 LABEL=RLINCLAG > 457 TRANS V71=3.01 STRATA=V44:60 LABEL=RLINCLAG > 458 TRANS V71 = 1 . 97 STRATA = V44:61 LABEL = RLINCLAG > 459 TRANS V71=2.02 STRATA=V44:62 LABEL=RLINCLAG > 460 TRANS V71=-0.47 STRATA=V44:63 LABEL=RLINCLAG > 461 TRANS V72=2.90 STRATA=V44:36 LABEL=VACRTLAG > 462 TRANS V72=2.10 STRATA=V44:37 LABEL=VACRTLAG > 463 TRANS V72=2.00 STRATA=V44:38 LABEL=VACRTLAG > 464 TRANS V72=1.90 STRATA=V44:39 LABEL=VACRTLAG > 465 TRANS V72=1.15 STRATA=V44:40 LABEL=VACRTLAG > 466 TRANS V72=0.50 STRATA=V44:42 LABEL=VACRTLAG > 467 TRANS V72=0.20 STRATA=V44:45 LABEL=VACRTLAG VD > 468 TRANS V72 =0. 20 STRATA = V44 : 47 LABEL= VACRTLAG > 469 TRANS V72 =0. 10 STRATA = V44 : 50 LABEL= VACRTLAG > 470 TRANS V72 =0. 10 STRATA = V44 : 53 LABEL= VACRTLAG > 47 1 TRANS V72 =0. 15 STRATA = V44 : 54 LABEL= VACRTLAG > 472 TRANS V72 = 0 . 20 STRATA = V44 : 55 LABEL= VACRTLAG > 473 TRANS V72 =0. 35 STRATA = V44 : 56 LABEL= VACRTLAG > 474 TRANS V72 =0. 50 STRATA = V44 : 57 LABEL= VACRTLAG > 475 TRANS V72 =0. 80 STRATA = V44 : 58 LABEL= VACRTLAG > 476 TRANS V72 = 1 . 10 STRATA = V44 : 59 LABEL= VACRTLAG > 477 TRANS V72 = 1 . 05 STRATA = V44 : 60 LABEL= VACRTLAG > 478 TRANS V72 = 1 . 00 STRATA = V44 : 6 1 LABEL= VACRTLAG > 479 TRANS V72 = 1 . 10 STRATA = V44 : 62 LABEL= VACRTLAG > 480 TRANS V72 = 1 . 20 STRATA = V44 : 63 LABEL= VACRTLAG > 48 1 TRANS V73 = 5 . 22 STRATA = V44 : 36 LABEL= RLINTLAG > 482 TRANS V73 = 6 . 1 1 STRATA = V44 : 37 LABEL= RLINTLAG > 483 TRANS V73 = 3 . 47 STRATA = V44 : 38 LABEL= RLINTLAG > 484 TRANS V73 = 4 . 94 STRATA = V44 : 39 LABEL= RLINTLAG > 485 TRANS V73 = 6 . 38 STRATA = V44 : 40 LABEL= RLINTLAG > 486 TRANS V73 = 1 . 20 STRATA = V44 : 42 LABEL= RLINTLAG > 487 TRANS V73 = 1 . 60 STRATA = V44 : 45 LABEL= RLINTLAG > 488 TRANS V73 =-5.89 STRATA=V44:47 ' LABEL =RLINTLAG > 489 TRANS V73 = 3 . 18 STRATA = V44 : 50 LABEL= RLINTLAG > 490 TRANS V73 = 3 . 93 STRATA = V44 : 53 LABEL= RLINTLAG > 49 1 TRANS V73 = 4 . 80 STRATA = V44 : 54 LABEL= RLINTLAG > 492 TRANS V73 =-4.02 STRATA=V44:55 LABEL =RLINTLAG > 493 TRANS V73 = 5 . 99 STRATA = V44 : 56 LABEL= RLINTLAG > 494 TRANS V73 = 5 . 44 STRATA = V44 : 57 LABEL= RLINTLAG > 495 TRANS V73 = 5 . 48 STRATA = V44 : 58 LABEL= RLINTLAG > 496 TRANS V73 = 2 . 49 STRATA = V44 : 59 LABEL= RLINTLAG > 497 TRANS V73 = 3 . 6 1 STRATA = V44 : 60 LABEL= RLINTLAG > 498 TRANS V73 = 2 . 77 STRATA = V44 : 6 1 LABEL= RLINTLAG > 499 TRANS V73 = 3 . 18 STRATA = V44 : 62 LABEL= RLINTLAG > 500 TRANS V73 = 0 . 82 STRATA = V44 : 63 LABEL= RLINTLAG > 501 TRANS V74 = 4 . 62 STRATA = V44 : 36 LABEL= APRTNLAG > 502 TRANS V74 = 4 . 30 STRATA = V44 : 37 LABEL= APRTNLAG > 503 TRANS V74 = 4 . 25 STRATA = V44 : 38 LABEL= APRTNLAG > 504 TRANS V74 = 4 . 89 STRATA = V44 : 39 LABEL= APRTNLAG > 505 TRANS V74 = 3 . 82 STRATA = V44 : 40 LABEL= APRTNLAG > 506 TRANS V74 = 5 . 14 STRATA = V44 : 42 LABEL= APRTNLAG > 507 TRANS V74 = 2 . 83 STRATA = V44 : 45 LABEL= APRTNLAG > 508 TRANS V74 = 0 . 79 STRATA = V44 : 47 LABEL= APRTNLAG > 509 TRANS V74 = 2 . 06 STRATA = V44 : 50 LABEL= APRTNLAG > 5 10 TRANS V74 = 1 . 99 STRATA = V44 : 53 LABEL= APRTNLAG > 51 1 TRANS V74 = 0 . 01 STRATA = V44 : 54 LABEL= APRTNLAG > 512 TRANS V74 =-0.88 STRATA=V44:55 LABEL =APRTNLAG > 513 TRANS V74 =0. 49 STRATA = V44 : 56 LABEL= APRTNLAG > 514 TRANS V74 = 1 . 19 STRATA = V44 : 57 LABEL= APRTNLAG > 515 TRANS V74 = 0. 72 STRATA = V44 : 58 LABEL= APRTNLAG > 516 TRANS V74 = 2 . 85 STRATA = V44 : 59 LABEL= APRTNLAG > 517 TRANS V74 = 1 . 45 STRATA = V44 : 60 LABEL= APRTNLAG > 518 TRANS V74 = 2 . 67 STRATA = V44 : 6 1 LABEL= APRTNLAG > 519 TRANS V74 = 3 . 43 STRATA = V44 : 62 LABEL= APRTNLAG > 5 20 TRANS V74 = 1 . 91 STRATA = V44 : 63 LABEL= APRTNLAG > 521 TRANS V75 = 4 . 08 STRATA = V44 ': 36 LABEL= INFLALAG > 522 TRANS V75 = 3 . 22 STRATA = V44 : 37 LABEL= INFLALAG > 523 TRANS V75 = 5 . 52 STRATA = V44 : 38 LABEL= INFLALAG > 524 TRANS V75 = 3 . 95 STRATA = V44 : 39 LABEL= INFLALAG > 525 TRANS V75 = 2 . 73 STRATA = V44 : 40 LABEL= INFLALAG > 527 TRANS V75 = 7 . 82 STRATA = V44 : 42 LABEL= INFLALAG > 528 TRANS V75 = 7 . 91 STRATA = V44 : 45 LABEL= INFLALAG • A I > 529 TRANS V75 = 15.68 STRATA=V44:47 LABEL=INFLALAG > 530 TRANS V75 = 7 .70 STRATA=V44:50 LABEL=INFLALAG > 531 TRANS V75 = 7.81 STRATA=V44:53 LABEL=INFLALAG > 532 TRANS V75 = 7.01 STRATA = V44 : 54 LABEL = INFLALAG > 533 TRANS V75 = 15.90 STRATA=V44:55 LABEL=INFLALAG > 534 TRANS V75 = 5 .80 STRATA=V44:56 LABEL=INFLALAG > 535 TRANS V75 = 6.32 STRATA = V44 : 57 LABEL=INFLALAG > 536 TRANS V75 = 5.63 STRATA=V44:58 LABEL=INFLALAG > 537 TRANS V75 = 8.01 STRATA=V44:59 LABEL=INFLALAG > 538 TRANS V75 = 6 . 9 0 STRATA=V44:60 LABEL=INFLALAG > 539 TRANS V75 = 7.74 STRATA = V44 :61 LABEL = INFLALAG > 540 TRANS V75 = 7.16 STRATA=V44:62 LABEL=INFLALAG > 54 1 TRANS V75 = 9 .63 STRATA=V44:63 LABEL=INFLALAG > 542 TRANS V76 = .03 STRATA = V44 : 36 LABEL = INTCHGE > 543 TRANS V76 = - .34 STRATA=V44:37 LABEL=INTCHGE > 544 TRANS V76 = - . 1 0 STRATA=V44:38 LABEL=INTCHGE > 545 TRANS V76 = .22 STRATA=V44:39 LABEL=INTCHGE > 546 TRANS V76 = .03 STRATA=V44:40 LABEL=INTCHGE > 547 TRANS V76 = - .05 STRATA=V44:42 LABEL=INTCHGE > 548 TRANS V76 = .16 STRATA=V44:45 LABEL=INTCHGE > 549 TRANS V76 = .83 STRATA = V44 :47 LABEL = INTCHGE > 550 TRANS V76 = - . 58 STRATA=V44:50 LABEL=INTCHGE > 55 1 TRANS V76 = .07 STRATA = V44 :53 LABEL = INTCHGE > 552 TRANS V76 = .07 STRATA=V44:54 LABEL=INTCHGE > 553 TRANS V76 = - . 0 9 STRATA=V44:55 LABEL=INTCHGE > 554 TRANS V76 = - .03 STRATA=V44:56 LABEL=INTCHGE > 555 TRANS V76 = - .65 STRATA = V44 : 57 LABEL=INTCHGE > 556 TRANS V76 = -.61 STRATA=V44:58 LABEL=INTCHGE > 557 TRANS V76 = .01 STRATA = V44 : 59 LABEL=INTCHGE > 558 TRANS V76 = .00 STRATA=V44:60 LABEL=INTCHGE > 559 TRANS V76 = - . 1 7 STRATA = V44:6 1 LABEL=INTCHGE > 560 TRANS V76 = .11 STRATA=V44:62 LABEL=INTCHGE > 561 TRANS V76 = .03 STRATA = V44 :63 LABEL = INTCHGE > 562 TRANS V77 = -69 STRATA=V44:36 LABEL=APTC0MCH > 563 TRANS V77 = -209 STRATA=V44:37 LABEL=APTCOMCH > 564 TRANS V77 = 174 STRATA=V44:38 LABEL=APTCOMCH > 565 TRANS V77 = 126 STRATA=V44:39 LABEL=APTCOMCH > 566 TRANS V77 = -123 STRATA=V44:40 LABEL=APTCOMCH > 567 TRANS V77 = 283 STRATA=V44:42 LABEL=APTCOMCH > 568 TRANS V77 = 156 STRATA=V44:45 LABEL=APTCOMCH > 569 TRANS V77 = 313 STRATA=V44:47 LABEL=APTCOMCH > 570 TRANS V77 = 245 STRATA=V44:50 LABEL=APTCOMCH > 571 TRANS V77 = -908 STRATA=V44:53 LABEL=APTCOMCH > 572 TRANS V77 = 497 STRATA=V44:54 LABEL=APTCOMCH > 573 TRANS V77 = -57 STRATA=V44:55 LABEL=APTCOMCH > 574 TRANS V77 = 64 STRATA=V44:56 LABEL=APTCOMCH > 575 TRANS V77 = 208 STRATA=V44:57 LABEL=APTCOMCH > 576 TRANS V77 = -163 STRATA=V44:58 LABEL=APTCOMCH > 577 TRANS V77 = -140 S1RATA=V44:59 LABEL=APTCOMCH > 578 TRANS V77 = 54 STRATA=V44:60 LABEL=APTCOMCH > 579 TRANS V77 = 613 STRATA=V44:6 1 LABEL = APTCOMCH > 580 TRANS V77 = -331 STRATA=V44:62 LABEL=APTCOMCH > 58 1 TRANS V77 = 13 STRATA=V44:63 LABEL=APTCOMCH > 582 TRANS V78 = 341 STRATA=V44:36-54 LABEL=HHCHANGE > 583 TRANS V78 = 663 STRATA = V44 :55-63 LABEL = HHCHANGE > 584 TRANS V79 = .89 STRATA=V44:36 LABEL=RLINTCHG > 585 TRANS V79 = -2.64 STRATA = V44 :37 LABEL = RLINTCHG > 586 TRANS V79 = 1.47 STRATA=V44:38 LABEL=RLINTCHG > 587 TRANS V79 = 1.44 STRATA=V44:39 LABEL=RLINTCHG > 588 TRANS V79 = - .46 STRATA=V44:40 LABEL=RLINTCHG 0 0 I > 589 TRANS V79 = -2 .29 STRATA=V44:42 LABEL=RLINTCHG > 590 TRANS V79 = -2 .59 STRATA=V44:45 LABEL=RLINTCHG > 591 TRANS V79 = 1.64 STRATA=V44:47 LABEL=RLINTCHG > 592 TRANS V79 = -2 .39 STRATA=V44:50 LABEL=RLINTCHG > 593 TRANS V79 = .87 STRATA=V44:53 LABEL=RLINTCHG > 594 TRANS V79 = -8 .82 STRATA=V44:54 LABEL=RLINTCHG > 595 TRANS V79 = 10.01 STRATA=V44:55 LABEL=RLINTCHG > 596 TRANS V79 = - .55 STRATA=V44:56 LABEL=RLINTCHG > 597 TRANS V79 = .04 STRATA=V44:57 LABEL=RLINTCHG > 598 TRANS V79 = -2 .99 STRATA = V44 : 58 LABEL = RLINTCHG > 599 . TRANS V79 = 1.12 STRATA=V44:59 LABEL=RLINTCHG > 600 TRANS V79 = - .84 STRATA=V44:60 LABEL=RLINTCHG > 601 TRANS V79 = .41 STRATA=V44:61 LABEL=RLINTCHG > 602 TRANS V79 = -2 .36 STRATA=V44:62 LABEL=RLINTCHG > 603 TRANS V79 = 1.96 STRATA=V44:63 LABEL=RLINTCHG > 604 TRANS V80= - .32 STRATA=V44:36 LABEL=ERCHANGE > 605 TRANS V80 = - .05 STRATA=V44:37 LABEL=ERCHANGE > 606 TRANS V80= .64 STRATA=V44:38 LABEL=ERCHANGE > 607 TRANS V80= -1 .07 STRATA=V44:39 LABEL=ERCHANGE > 608 TRANS V80 = .78 STRATA=V44:40 LABEL=ERCHANGE > 609 TRANS V80 = -2.31 STRATA=V44:42 LABEL=ERCHANGE > 610 TRANS V80 = - .64 STRATA=V44:45 LABEL=ERCHANGE > 61 1 TRANS V80= .70 STRATA=V44:47 LABEL=ERCHANGE > 612 TRANS V80 = .79 STRATA=V44:50 LABEL=ERCHANGE > 613 TRANS V80= -1 .98 STRATA=V44:53 LABEL=ERCHANGE > 614 TRANS V80= - . 8 9 STRATA=V44:54 LABEL=ERCHANGE > 615 TRANS V80= 1.37 STRATA=V44:55 LABEL=ERCHANGE > 6 16 TRANS V80 = .70 STRATA=V44:56 LABEL=ERCHANGE > 617 TRANS V80 = - .47 STRATA=V44:57 LABEL=ERCHANGE > 6 18 TRANS V80= 2.13 STRATA=V44:58 LABEL=ERCHANGE > 6 19 TRANS V80= - 1 . 4 0 STRATA=V44:59 LABEL=ERCHANGE > 620 TRANS V80 = 1.22 STRATA=V44:60 LABEL=ERCHANGE > 621 TRANS V80 = .76 STRATA=V44:61 LABEL=ERCHANGE > 622 TRANS V80 = -1 .52 STRATA=V44:62 LABEL=ERCHANGE > 623 TRANS V80 = 1.04 STRATA=V44:63 LABEL 3ERCHANGE > 624 TRANS V8 1 = -87 STRATA=V44:36 LABEL=APTSTSCH > 625 TRANS V8 1 = -329 STRATA=V44:37 LABEL=APTSTSCH > 626 TRANS V8 1 = -303 STRATA=V44:38 LABEL=APTSTSCH > 627 TRANS V8 1 = 131 STRATA=V44:39 LABEL 3 APTSTSCH > 628 TRANS V8 1 = 173 STRATA=V44:40 LABEL=APTSTSCH > 629 TRANS V8 1 = 659 STRATA=V44:42 LABEL=APTSTSCH > 630 TRANS V8 1 = -61 STRATA=V44:45 LABEL 3 APTSTSCH > 631 TRANS V8 1 = -689 STRATA=V44:47 LABEL 3 APTSTSCH > 632 TRANS V8 1 = 342 STRATA=V44:50 LABEL=APTSTSCH > 633 TRANS V8 1 = -444 STRATA=V44:53 LABEL 3 APTSTSCH > 634 TRANS V8 1 = 130 STRATA=V44:54 LABEL=APTSTSCH > 635 TRANS V8 1 = 575 STRATA=V44:55 LABEL=APTSTSCH > 636 TRANS V8 1 = 419 STRATA=V44:56 LABEL=APTSTSCH > 637 TRANS V81 = -456 STRATA=V44:57 LABEL=APTSTSCH > 638 TRANS V8 1 = 30 STRATA=V44:58 LABEL=APTSTSCH > 639 TRANS V8 1 = -11 STRATA=V44:59 LABEL=APTSTSCH > 640 TRANS V81 = 698 STRATA=V44:60 LABEL=APTSTSCH > 64 1 TRANS V8 1 = -737 STRATA=V44:61 LABEL=APTSTSCH > 642 TRANS V81 = -616 STRATA=V44:62 LABEL=APTSTSCH > 643 TRANS V8 1 = 167 STRATA=V44:63 LABEL=APTSTSCH > 644 CODE V82 = V7 LABE L = NEWWE CASES = ALL STRATA=NONE > 645 CODE V83=V8 LABEL=NEWKITS CASES=ALL STRATA=NONE > 646 CODE V84 = V9 LABEL = NEWEV CASES = ALL STRATA =NONE > 647 CODE V85=V10 LABEL=NEWMAR CASES=ALL STRATA=NONE > 648 CODE V86 = V11 LABE L = NEWKERR STRATA =NONE I ON > 649 TRANS V87=-.3 STRATA 3 V44:36*V82:1 LABEL=SUBVACRT > 651 TRANS V 8 7 - - . 7 STRATA = V44 :38*V82 : 1 LABEL-SUBVACRT > 656 TRANS V87=.00 STRATA=V44:47*V82:1 LABEL=SUBVACRT > 663 TRANS V87=.55 STRATA=V44:58*V82:1 LABEL=SUBVACRT > 665 TRANS V87=-.1 STRATA=V44:60*V82:1 LABEL=SUBVACRT > 668 TRANS V87=-.15 STRATA=V44:63*V82:1 LABEL=SUBVACRT > 669 TRANS V87=-1.5 STRATA=V44:36*V83:1 LABEL=SUBVACRT > . 6 7 0 TRANS V87=.25 STRATA=V44:37*V83:1 LABEL=SUBVACRT > 671 TRANS V87=.25 STRATA=V44:38*V83:1 LABEL=SUBVACRT > 672 TRANS V87=-.5 STRATA=V44:39*V83:1 LABEL=SUBVACRT > 673 TRANS V87=-.5 STRATA=V44:40*V83:1 LABEL=SUBVACRT > 674 TRANS V87=.05 STRATA = V44 :42*V83 : 1 LABEL=SUBVACRT > 675 TRANS V87=.05 STRATA=V44:45*V83:1 LABEL=SUBVACRT > 677 TRANS V87=.00 STRATA=V44:50*V83:1 LABEL=SUBVACRT > 679 TRANS V87=-.05 STRATA=V44:54*V83:1 LABEL=SUBVACRT > 680 TRANS V87=.05 STRATA=V44:55*V83:1 LABEL=SUBVACRT > 682 TRANS V87=.1 STRATA=V44:57*V83:1 LABEL=SUBVACRT > 684 TRANS V87=-.1 STRATA=V44:59*V83:1 LABEL=SUBVACRT > 685 TRANS V87=-.1 STRATA=V44:60*V83:1 LABEL=SUBVACRT > 687 TRANS V87=.00 STRATA = V44 :62*V83 : 1 LABEL = SUBVACRT > 692 TRANS V87=-.7 STRATA=V44:39*V84:1 LABEL=SUBVACRT > 694 TRANS V87=.35 STRATA = V44:42 *V84: 1 LABEL = SUBVACRT > 697 TRANS V87=.00 STRATA=V44:50*V84:1 LABEL=SUBVACRT • > 698 TRANS V87=.15 STRATA = V44:53 *V84: 1 LABEL = SUBVACRT > 699 TRANS V87=.15 STRATA=V44:54*V84:1 LABEL=SUBVACRT > 700 TRANS V87=.3 STRATA=V44:55*V84:1 LABEL=SUBVACRT > 701 TRANS V87=.3 STRATA=V44:56*V84:1 LABEL=SUBVACRT > 702 TRANS V87=.25 STRATA = V44 :57*V84 : 1 LABEL = SUBVACRT > 703 TRANS V87=.25 STRATA = V44 :58*V84 : 1 LABEL = SUBVACRT > 704 TRANS V87=.3 STRATA=V44:59*V84:1 LABEL=SUBVACRT > 705 TRANS V87=.3 STRATA=V44:60*V84:1 LABEL=SUBVACRT > 706 TRANS V87=-.05 STRATA=V44:61*V84:1 LABEL=SUBVACRT > 717 TRANS V87=.00 STRATA=V44:50*V85:1 LABEL=SUBVACRT > 724 TRANS V87=-.15 STRATA=V44:59*V85:1 LABEL=SUBVACRT > 729 TRANS V88=-161 STRATA=V44:36 LABEL=NEWVACCH > 730 TRANS V88=-78 STRATA=V44:37 LABEL=NEWVACCH > 731 TRANS V88=76 STRATA=V44:38 LABEL=NEWVACCH > 732 TRANS V88=-38 STRATA=V44:39 LABEL=NEWVACCH > 733 TRANS V88=-17 STRATA=V44:40 LABEL=NEWVACCH > 734 TRANS V88=33 STRATA=V44:42 LABEL=NEWVACCH > 735 TRANS V88=-14 STRATA=V44:45 LABEL=NEWVACCH > 736 TRANS V88=97 STRATA=V44:47 LABEL=NEWVACCH > 737 TRANS V88=25 STRATA=V44:50 LABEL=NEWVACCH > 738 TRANS V88=-172 STRATA=V44:53 LABEL=NEWVACCH > 739 TRANS V88=119 STRATA=V44:54 LABEL=NEWVACCH > 740 TRANS V88=131 STRATA=V44:55 LABEL=NEWVACCH > 741 TRANS V88=56 STRATA=V44:56 LABEL=NEWVACCH > 742 TRANS V88=-57 STRATA=V44:57 LABEL=NEWVACCH > 743 TRANS V88=-1 STRATA=V44:58 LABEL=NEWVACCH > 744 TRANS V88=4 STRATA=V44:59 LABEL=NEWVACCH > 745 TRANS V88 = -76 STRATA = V44 :60 LABEL =NEWVACCH > 746 TRANS V88=156 STRATA=V44:61 LABEL=NEWVACCH > 747 TRANS V88=27 STRATA=V44:62 LABEL=NEWVACCH > 748 TRANS V88=-221 STRATA=V44:63 LABEL=NEWVACCH > 749 TRANS V89=1.0 STRATA=V44:53-63 LABEL=REZONING > 750 TRANS V89=0.0 STRATA=V44:36-51 LABEL=REZONING > 752 TRANS V90=- .80 STRATA=V44:36 LABEL=VACRTCHG > 753 TRANS V90=- .10 STRATA=V44:37 LABEL 3VACRTCHG > 754 TRANS V90=-. 10 STRATA = V44:38 LABEL = VACRTCHG > 755 TRANS V90=-.75 STRATA=V44:39 LABEL=VACRTCHG O > 756 TRANS V90 = - .75 STRATA=V44: 40 LABEL=VACRTCHG > 757 TRANS V90 = .10 STRATA=V44:42 LABEL=VACRTCHG > 758 TRANS V90 = .00 STRATA=V44:45 LABEL=VACRTCHG > 759 TRANS V90= - .05 STRATA=V44: 47 LABEL=VACRTCHG > 760 TRANS V90= .00 STRATA=V44:50 LABEL=VACRTCHG > 76 1 TRANS V90 = .05 STRATA=V44:53 LABEL=VACRTCHG > 762 TRANS V90 = .05 STRATA=V44:54 LABEL=VACRTCHG > 763 TRANS V90= .15 STRATA=V44:55 LABEL=VACRTCHG > 764 TRANS V90 = .15 STRATA=V44:56 LABEL=VACRTCHG > 765 TRANS V90 = .30 STRATA=V44:57 LABEL=VACRTCHG > 766 TRANS V90 = .30 STRATA=V44:58 LABEL=VACRTCHG > 767 TRANS V90= - .05 STRATA=V44: 59 LABE L =VACRTCHG > 768 TRANS V90= - .05 STRATA=V44: 60 LABEL=VACRTCHG > 769 TRANS V90= .10 STRATA=V44:61 LABEL=VACRTCHG > 770 TRANS V90= .10 STRATA=V44:62 LABEL=VACRTCHG > 77 1 TRANS V90= - .05 STRATA=V44: 63 LABEL=VACRTCHG > 772 TRANS V9 1 = 1277 STRATA=V44: 37 LABEL=NEWHH > 773 TRANS V9 1 = 1277 STRATA=V44: 38- 40 LABEL = NEWHH > 774 TRANS V9 1 = 1184 STRATA=V44: 42 LABEL=NEWHH > 775 TRANS V91 = 1426 STRATA=V44: 45- 47 LABEL=NEWHH > 776 TRANS V91 = 1381 STRATA=V44: 50 LABEL=NEWHH > 777 TRANS V91 = 424 STRATA=V44:53-56 LABEL=NEWHH > 778 TRANS V91 = -418 STRATA=V44: 57- 60 LABEL=NEWHH > 779 TRANS V91 = 2133 STRATA=V44: 61- 63 LABEL=NEWHH > 780 TRANS V92 = 1.12 STRATA=V44: 37 LABEL=NEWVRATE > 78 1 TRANS V92 = 5.4 1 STRATA=V44: 38 LABEL=NEWVRATE > 782 TRANS V92 = 5.42 STRATA=V44: 39 LABEL=NEWVRATE > 783 TRANS V92 = 4 .02 STRATA=V44: 40 LABEL=NEWVRATE > 784 TRANS V92 = 5.53 STRATA=V44: 42 LABE L = NEWVRATE > 785 TRANS V92 = 2.71 STRATA=V44: 45 LABEL=NEWVRATE > 786 TRANS V92 = 9 .47 STRATA=V44: 47 LABEL=NEWVRATE > 787 TRANS V92 = 25.61 STRATA=V44 :50 LABE L = NEWVRATE > 788 TRANS V92 = 6 .78 STRATA=V44: 53 LABEL=NEWVRATE > 789 TRANS V92 = 13.13 STRATA=V44 :54 LABEL=NEWVRATE > 790 TRANS V92 = 20 .58 STRATA=V44 :55 LABEL=NEWVRATE > 79 1 TRANS V92 = 26 .03 STRATA=V44 :56 LABEL=NEWVRATE > 792 TRANS V92 = 2 9 . 2 0 STRATA=V44 :57 LABEL=NEWVRATE > 793 TRANS V92 = 19.83 STRATA=V44 : 58 LABEL=NEWVRATE > 794 TRANS V92 = 19.55 STRATA=V44 : 59 LABEL=NEWVRATE > 795 TRANS V92 = 16._44 STRATA = V44 :60 LABEL=NEWVRATE > 796 TRANS V92 = 23.81 STRATA=V44 :61 LABEL=NEWVRATE > 797 TRANS V92 = 2 1 . 49 STRATA = V44 :62 LABEL=NEWVRATE > 798 TRANS V92 = 11.99 STRATA=V44 :63 LABEL=NEWVRATE > 799 TRANS V93 = 91 .02 STRATA=V44 : 37 LABEL=RLRENT2 > 800 TRANS V93 = 8 8 . 8 9 STRATA=V44 :38 LABEL=RLRENT2 > 801 TRANS V93 = 88 .22 STRATA=V44 : 39 LABEL=RLRENT2 > 802 TRANS V93 = 87 .12 STRATA=V44 :40 LABE L = RLRENT2 > 803 TRANS V93 = 76 .66 STRATA=V44 :42 LABEL=RLRENT2 > 804 TRANS V93 = 65.71 STRATA=V44 :45 LABEL=RLRENT2 > 805 TRANS V93 = 54 .58 STRATA=V44 :47 LABEL=RLRENT2 > 806 TRANS V93 = 49 .04 STRATA=V44 :50 LABEL=RLRENT2 > 807 TRANS V93 = 46 .36 STRATA=V44 :53 LABEL=RLRENT2 > 808 TRANS V93 = 4 1 . 76 STRATA = V44 :54 LABEL=RLRENT2 > 809 TRANS V93 = 4 2 . 5 0 STRATA=V44 :55 LABE L = RLRENT2 > 8 10 TRANS V93 = 42 .97 STRATA=V44 : 56 LABEL=RLRENT2 > 81 1 TRANS V93 = 43 .54 STRATA=V44 :57 LABEL=RLRENT2 > 812 TRANS V93 = 42 .34 STRATA=V44 :58 LABEL=RLRENT2 > 813 TRANS V93 = 4 1 . 4 9 STRATA=V44 :59 LABEL=RLRENT2 > 8 14 TRANS V93 = 3 8 . 9 0 STRATA=V44 :60 LABEL=RLRENT2 > 815 TRANS V93 = 37 .98 STRATA=V44 :61 LABEL=RLRENT2 VD I > 816 TRANS V93 > 8 17 TRANS V93 > 8 18 TRANS V94 > 819 TRANS V94 > 820 TRANS V94 > 82 1 TRANS V94 > 822 TRANS V94 > 823 TRANS V94 > 824 TRANS V94 > 825 TRANS V94 > 826 TRANS V94 > 827 TRANS V94 > 828 TRANS V94 > 829 TRANS V94 > 830 TRANS V94 > 83 1 TRANS V94 > 832 TRANS V94 > 833 TRANS V94 > 834 TRANS V94 > 835 TRANS V94 > 836 TRANS V94 > 837 TRANS V95 > 838 TRANS V95 > 839 TRANS V95 > 840 TRANS V95 > 84 1 TRANS V95 > 842 TRANS V95 > 843 TRANS V95 > 844 TRANS V95 > 845 TRANS V95 > 846 TRANS V95 > 847 TRANS V95 > 848 TRANS V95 > 849 TRANS V95 > 850 TRANS V95 > 851 TRANS V95 > 852 TRANS V95 > 853 TRANS V95 > 854 TRANS V95 > 855 TRANS V95 > 856 TRANS V96 > 857 TRANS V96 > 858 TRANS V96 > 859 TRANS V96 > 860 TRANS V96 > 86 1 TRANS V96 > 862 TRANS V96 > 863 TRANS V96 > 864 TRANS V96 > 865 TRANS V96 > 866 TRANS V96 > 867 TRANS V96 > 868 TRANS V96 > 869 TRANS V96 > 870 TRANS V96 > 87 1 TRANS V96 > 872 TRANS V96 > 873 TRANS V96 > 874 TRANS V96 > 875 TRANS V97 35 .45 STRATA=V44:62 LABEL=RLRENT2 34 .07 STRATA=V44:63 LABEL-RLRENT2 473 STRATA-V44:37 LABEL=STARTS 170 STRATA-V44:38 LABEL-STARTS 301 STRATA=V44:39 LABEL-STARTS 474 STRATA=V44:40 LABEL=STARTS 807 STRATA-V44:42 LABEL-STARTS 222 STRATA-V44:45 LABEL-STARTS 193 STRATA-V44:47 LABE L-STARTS 508 STRATA-V44:50 LABEL-STARTS 160 STRATA=V44:53 LABEL=STARTS 290 STRATA=V44:54 LABEL=STARTS 705 STRATA-V44:55 LABEL-STARTS 1124 STRATA-V44:56 LABEL-STARTS 668 STRATA-V44:57 LABEL-STARTS 698 STRATA = V44:58 LABEL = STARTS 687 STRATA=V44:59 LABEL-STARTS 1385 STRATA=V44:60 LABEL=STARTS 648 STRATA=V44:61 LABE L-STARTS 32 STRATA-V44:62 LABEL -STARTS 199 STRATA-V44:63 LABEL=STARTS 1 12 24 STRATA = V44 37 LABEL -REALCOST 1 18 40 STRATA -V44 38 LABEL =REALCOST 127 45 STRATA -V44 39 LABEL -REALCOST 144 01 STRATA -V44 40 LABEL =REALCOST 153 67 STRATA = V44 42 LABEL =REALCOST 147 60 STRATA -V44 45 LABEL =REALCOST 135 76 STRATA = V44 47 LABEL -REALCOST 1 15 28 STRATA -V44 50 LABEL -REALCOST 122 14 STRATA -V44 53 LABEL -REALCOST 1 12 51 STRATA = V44 54 LABEL -REALCOST 1 18 10 STRATA = V44 55 LABEL -REALCOST 1 24 25 STRATA = V44 56 LABEL -REALCOST 129 60 STRATA = V44 57 LABEL -REALCOST 1 36 29 STRATA -V44 58 LABEL -REALCOST 145 58 STRATA = V44 59 LABEL -REALCOST 139 06 STRATA -V44 60 LABEL -REALCOST 144 18 STRATA -V44 61 LABEL -REALCOST 149 08 STRATA = V44 62 LABEL -REALCOST 150 60 STRATA -V44 63 LABEL -REALCOST 3.51 STRATA-V44:37 LABEL-NEWVRLAG 1.12 STRATA-V44:38 LABEL-NEWVRLAG 5.41 STRATA-V44:39 LABEL-NEWVRLAG 5.42 STRATA-V44:40 LABEL-NEWVRLAG 3.25 STRATA-V44:42 LABEL-NEWVRLAG 4 .18 STRATA-V44:45 LABEL-NEWVRLAG 2 .20 STRATA-V44:47 LABEL-NEWVRLAG 22 .19 STRATA-V44:50 LABEL-NEWVRLAG 13.68 STRATA-V44:53 LABEL-NEWVRLAG 6 .78 STRATA-V44:54 LABEL-NEWVRLAG 13.13 STRATA-V44:55 LABEL-NEWVRLAG 20 .58 STRATA-V44:56 LABEL-NEWVRLAG 26 .03 STRATA-V44:57 LABEL-NEWVRLAG 2 9 . 2 0 STRATA-V44:58 LABEL-NEWVRLAG 19.83 STRATA-V44:59 LABEL-NEWVRLAG 19.55 STRATA-V44:60 LABEL-NEWVRLAG 16.44 STRATA-V44:6 1 LApEL-NEWVRLAG 23.81 STRATA-V44:62 LABEL-NEWVRLAG 21 .49 STRATA-V44:63 LABEL-NEWVRLAG 9 5 . 1 6 STRATA-V44:37 LABEL-RLRNTLAG CN VO I > 875 TRANS V97 = 91 . 02 STRATA=V44: 38 LABEL=RLRNTLAG > 877 TRANS V97 = 88 . 89 STRATA=V44: 39 LABEL=RLRNTLAG > 878 TRANS V97 = 88 . 22 STRATA=V44: 40 LABEL=RLRNTLAG > 879 TRANS V97 = 82 . 01 STRATA=V44: 42 LABEL=RLRNTLAG > 880 TRANS V97 = 70 . 54 STRATA=V44: 45 LABEL=RLRNTLAG > 88 1 TRANS V97 = 59 . 14 STRATA=V44: 47 LABEL=RLRNTLAG > 882 TRANS V97 = 49 . 81 STRATA=V44: 50 LABEL=RLRNTLAG > 883 TRANS V97 = 46 . 31 STRATA=V44: 53 LABEL=RLRNTLAG > 884 TRANS V97 = 46 . 36 STRATA=V44: 54 LABEL=RLRNTLAG > 885 TRANS V97 = 4 1 . 76 STRATA=V44: 55 LABEL=RLRNTLAG > 886 TRANS V97 = 42 . 50 STRATA=V44: 56 LABEL=RLRNTLAG > 887 TRANS V97 = 42 . 97 STRATA=V44: 57 LABEL=RLRNTLAG > 888 TRANS V97 = 43 . 54 STRATA=V44: 58 LABEL=RLRNTLAG > 889 TRANS V97 = 42 . 34 STRATA=V44: 59 LABEL=RLRNTLAG > 890 TRANS V97 = 4 1 . 49 STRATA=V44: 60 LABEL=RLRNTLAG > 891 TRANS V97 = 38 . 90 STRATA=V44: 61 LABEL=RLRNTLAG > 892 TRANS V97 = 37 . 98 STRATA=V44: 62 LABEL=RLRNTLAG > 893 TRANS V97 = 35 . 45 STRATA=V44: 63 LABEL=RLRNTLAG > 894 TRANS V98 = 1 1 1 .64 STRATA=V44 :37 LABEL=RLCSTLAG > 895 TRANS V98 = 1 12 . 24 STRATA=V44 : 38 LABEL=RLCSTLAG > 896 TRANS V98 = 1 18 . 40 STRATA=V44 :39 LABEL=RLCSTLAG > 897 TRANS V98 = 127 . 45 STRATA=V44 : 40 LABEL=RLCSTLAG > 898 TRANS V98 = 15 1 . 46 STRATA=V44 : 42 LABEL=RLCSTLAG > 899 TRANS V98 = 142 . 94 STRATA=V44 : 45 LABEL=RLCSTLAG > 900 TRANS V98 = 140 .00 STRATA=V44 :47 LABEL=RLCSTLAG > 901 TRANS V98 = 103 . 1 1 STRATA=V44 : SO LABEL=RLCSTLAG > . 902 TRANS V98 = 1 16 . 80 STRATA=V44 : 53 LABEL=RLCSTLAG > 903 TRANS V98 = 122 . 14 STRATA=V44 :54 LABEL=RLCSTLAG > 904 TRANS V98 = 1 12 .51 STRATA=V44 :55 LABEL=RLCSTLAG > 905 TRANS V98 = 1 18 . 10 STRATA=V44 : 56 LABEL=RLCSTLAG > 906 TRANS V98 = 124 . 25 STRATA=V44 : 57 LABEL=RLCSTLAG > 907 TRANS V98 = 129 .60 STRATA=V44 : 58 LABEL=RLCSTLAG > 908 TRANS V98 = 136 . 29 STRATA=V44 : 59 LABEL=RLCSTLAG > 909 TRANS V98 = 145 . 58 STRATA=V44 :60 LABEL=RLCSTLAG > 910 TRANS V98 = 139 .06 STRATA=V44 :61 LABEL=RLCSTLAG > 91 1 TRANS V98 = 144 . 18 STRATA=V44 :62 LABEL=RLCSTLAG > 912 TRANS V98 = 149 .08 STRATA=V44 :63 LABEL=RLCSTLAG > 913 TRANS V99 = 31 STRATA=V44:37 LABEL=NEWVACMF > 914 TRANS V99 = 107 STRATA=V44:38 LABEL=NEWVACMF > 9 15 TRANS V99 = 69 STRATA=V44:39 LABEL=NEWVACMF > 916 TRANS V99 = 52 STRATA=V44:40 LABEL=NEWVACMF > 917 TRANS V99 = 74 STRATA=V44:42 LAB EL = NEWVACMF > 918 TRANS V99 = 39 STRATA=V44:45 LABEL=NEWVACMF > 919 TRANS V99 = 138 STRATA=V44:47 LABEL=NEWVACMF > 920 TRANS V99 = 449 STRATA=V44:50 LABEL=NEWVACMF > 92 1 TRANS V99 = 194 STRATA=V44:53 LABE L = NEWVACMF > 922 TRANS V99 = 313 STRATA=V44:54 LABEL=NEWVACMF > 923 TRANS V99 = 444 STRATA=V44:55 LABEL=NEWVACMF > 924 TRANS V99 = 500 STRATA=V44:56 LABEL=NEWVACMF > 925 TRANS V99 = 443 STRATA=V44:57 LABEL=NEWVACMF > 926 TRANS V99 = 442 STRATA=V44:58 LABEL=NEWVACMF > 927 TRANS V99 = 446 STRATA=V44:59 LABEL=NEWVACMF > 928 TRANS V99 = 370 STRATA=V44:60 LABE L = NEWVACMF > 929 TRANS V99 = 526 STRATA=V44:61 LABEL=NEWVACMF > 930 TRANS V99 = 553 STRATA=V44:62 LABEL=NEWVACMF > 931 TRANS V99 = 332 STRATA=V44:63 LABEL=NEWVACMF > 932 TRANS V100 = 7 . 222 STRATA=V44 : 37 LABEL=AVGPPSF > 933 TRANS V100 = 7 . 429 STRATA=V44 :38 LABEL=AVGPPSF > 934 TRANS V100 = 5 . 902 STRATA=V44 :39 LABE L = AVGPPSF > 935 TRANS V100 = 6 . 250 STRATA=V44 :40 LABEL=AVGPPSF vo i > 936 TRANS V100 = 8 . 201 STRATA = V44 : 42 LABEL=AVGPPSF > 937 TRANS V100= 25 .000 STRATA=V44 :45 LABEL=AVGPPSF > 938 TRANS V100= 13 .518 STRATA=V44 : 47 LABEL=AVGPPSF > 939 TRANS V100 = 13 . 254 STRATA=V44 :50 LABEL=AVGPPSF > 940 TRANS V100= 13 .887 STRATA=V44 : 51 LABEL=AVGPPSF > 94 1 TRANS V100= 15 . 377 STRATA=V44 :53 LABEL=AVGPPSF > 942 TRANS V100 = 16 .688 STRATA=V44 : 54 LABEL=AVGPPSF > 943 TRANS V100 = 15 .627 STRATA=V44 : 55 LABEL=AVGPPSF > 944 TRANS V100 = 16 .029 STRATA=V44 : 56 LABEL=AVGPPSF > 945 TRANS v i o o = 26 . 175 STRATA=V44 : 57 LABEL=AVGPPSF > 946 TRANS V100 = 20 . 522 STRATA=V44 : 58 LABEL=AVGPPSF > 947 TRANS V100= 18 .314 STRATA=V44 : 59 LABEL=AVGPPSF > 948 TRANS V100= 17 . 867 STRATA=V44 :60 LABEL=AVGPPSF > 949 TRANS V100= 18 .071 STRATA=V44 :61 LABEL=AVGPPSF > 950 TRANS V100= 28 . 333 STRATA=V44 : 62 LABEL=AVGPPSF > 95 1 TRANS V100 = 23 . 855 STRATA=V44 : 63 LABEL=AVGPPSF > 952 TRANS V101 = V100/V38 STRATA = N0NE LABEL=RLAVGSP > 953 TRANS V102 = 0 . ' 00 STRATA=V44:37 LABEL=LOCINDEX > 954 TRANS V102 = 0 . ' 00 STRATA=V44:38 LABEL=LOCINDEX > 955 TRANS V102 = -2 .00 STRATA = V44 : 39 LABEL=LOCINDEX > 956 TRANS V102 = O . i 00 STRATA=V44:40 LABEL=LOCINDEX > 957 TRANS V102 = - 1 . 50 STRATA = V44 : 42 LABEL=LOCINDEX > 958 TRANS V 102 = O . i 00 STRATA=V44:45 LABEL=LOCINDEX > 959 TRANS V102 = 3 . i 00 STRATA=V44:47 LABEL=LOCINDEX > 960 TRANS V102 = -2 .00 STRATA = V44 : 50 LABEL=LOCINDEX > 961 TRANS V102 = - 1 .00 STRATA=V44 : 51 LABEL=LOCINDEX > 962 TRANS V102 = -3 .00 STRATA=V44: 53 LABEL=LOCINDEX > 963 TRANS V102 = -2 . 57 STRATA = V44 : 54 LABEL=LOCINDEX > 964 TRANS V102 = -2 .63 STRATA=V44: 55 LABEL = LOC INDEX > 965 TRANS V102 = -3 .00 STRATA=V44: 56 LABEL=LOCINDEX > 966 TRANS V102 = - 1 .50 STRATA=V44: 57 LABEL=LOCINDEX > 967 TRANS V102 = -0 . 27 STRATA=V44: 58 LABEL=LOCINDEX > 968 TRANS V102 = - 1 .67 STRATA=V44: 59 LABEL=LOCINDEX > 969 TRANS V102 = - 1 .80 STRATA = V44 : 60 LABEL=LOCINDEX > 970 TRANS V102 = -3 .00 STRATA = V44 : 6 1 LABEL=LOCINDEX > 97 1 TRANS V102 = 0 . 0 0 STRATA=V44:62 LABEL=LOCINDEX > 972 TRANS V102 = 3 .00 STRATA=V44:63 LABEL=LOCINDEX > 973 TRANS V103 = -2 . 454 STRATA=V44 : 37 LABEL=NEWRMLAG > 974 TRANS V103 = -3 .609 STRATA=V44 : 38 LABEL=NEWRMLAG > 975 TRANS V103 = -3 .463 STRATA=V44 : 39 LABEL=NEWRMLAG > 976 TRANS V103 = -3 .090 STRATA=V44 :40 LABEL=NEWRMLAG > 977 TRANS V103 = -3 . 703 STRATA=V44 : 42 LABEL=NEWRMLAG > 978 TRANS V103 = -5 . 528 STRATA=V44 : 45 LABEL=NEWRMLAG > 979 TRANS V103 = -7 . 988 STRATA=V44 : 47 LABEL=NEWRMLAG > 980 TRANS V103 = -8 . 430 STRATA=V44 : 50 LABEL=NEWRMLAG > 98 1 TRANS V103 = -7 . 166 STRATA=V44 : 51 LABEL=NEWRMLAG > 982 TRANS V 103 = -4 .051 STRATA=V44 : 53 LABEL=NEWRMLAG > 983 TRANS V103 = -2 . 389 STRATA=V44 : 54 LABE L = NEWRMLAG > 984 TRANS V103 = -4 .319 STRATA=V44 : 55 LABEL=NEWRMLAG > 985 TRANS V103 = -3 . 343 STRATA=V44 : 56 LABEL=NEWRMLAG > 986 TRANS V103 = - 1 . 599 STRATA=V44 : 57 LABEL=NEWRMLAG > 987 ' TRANS V103 = - 1 . 324 STRATA=V44 : 58 LABEL=NEWRMLAG > 988 TRANS V103 = -2 . 109 STRATA=V44 : 59 LABEL=NEWRMLAG > 989 TRANS V103 = -0 .099 STRATA=V44 :60 LABEL=NEWRMLAG > 990 TRANS V103 = - 1 . 562 STRATA=V44 :61 LABEL=NEWRMLAG > 991 TRANS V103 = -3 .062 STRATA=V44 : 62 LABEL=NEWRMLAG > 992 TRANS V103 = -5 .090 STRATA=V44 : 63 LABEL=NEWRMLAG > 993 TRANS V92=17.87 STRATA=V44:51 LABEL=NEWVRATE > 994 TRANS V64 = -2.84 STRATA=V44:51 LABEL=CAPRATE 995 TRANS V66= 12. 12 STRATA=V44:51 LABEL=NOMCAPRT -3-

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