"Forestry, Faculty of"@en . "DSpace"@en . "UBCV"@en . "Ottens, Johannes"@en . "2010-01-22T04:04:31Z"@en . "1973"@en . "Master of Forestry - MF"@en . "University of British Columbia"@en . "A technique for estimating the impact of a change in forest policy upon the future level of employment within a region is developed and assessed. The theory, methodology, and relative merits of economic base studies, input-output analysis and simulation modelling are discussed as suitable alternative techniques for impact analysis. The economic base study used in conjunction with location quotients is used in this investigation owing to time and data restrictions. The benchmark, economy is British Columbia. The study region, which is located within the Kamloops Forest District, has been defined in terms of data collection units, trade and functions, and timber flows. The calculated value of the employment multiplier is 3.05. This overstates the true value of the regional multiplier due to the product mix problem, incomplete external trade data for both the benchmark economy and the study region, and failure to account for indirect exports of the benchmark economy. The policy studied is the close utilization policy which was officially implemented on January 1, 1966. The definition, method of implementation and purpose of this policy are discussed. The impact of the close utilization policy on the structure and employment of the regions forest industry in 1971 and in 1980 are estimated. Using the calculated employment multiplier, the total impact of the policy is estimated. In 1971, there were fewer jobs in the study region than there might have been if the close utilization policy had not been implemented. It is predicted that, by about 1980, without the close utilization policy, changes in forest industry structure and market demands which would have resulted from economic forces alone would have led to the same levels of annual harvests, tree sizes harvested, average productivity and average sawmill capacity as had been achieved earlier by implementing the policy. Suggestions are given for improving the accuracy and precision of estimates of future timber harvests, and productivity in logging and sawmilling. Public agencies should include estimates of the impact on employment of their proposed policies and investments in their benefit-cost analyses."@en . "https://circle.library.ubc.ca/rest/handle/2429/18929?expand=metadata"@en . "THE USE OF REGIONAL ECONOMIC TECHNIQUES TO ANALYZE FOREST POLICY IMPACTS: THE CASE OF THE IMPACT OF CLOSE UTILIZATION POLICY ON THE LEVEL OF EMPLOYMENT WITHIN THE KAMLOOPS REGION by JOHANNES OTTENS B.S.F. , University of Br i t ish Columbia, 1968 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF FORESTRY in the Department of Forestry We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA June, 1973 In presenting 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 of the requirements f o r an advanced degree at the U n i v e r s i t y of B r i t i s h Columbia, I agree that the 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 reference and study. I f u r t h e r agree that permission f o r extensive copying of t h i s t h e s i s f o r s c h o l a r l y purposes may be granted by the Head of my Department or by h i s r e p r e s e n t a t i v e s . I t i s understood that copying or p u b l i c a t i o n of t h i s t h e s i s f o r f i n a n c i a l gain s h a l l not be allowed without my w r i t t e n permission. Department of The U n i v e r s i t y of B r i t i s h Columbia Vancouver 8 , Canada Date i i ABSTRACT A technique for estimating the impact of a change in forest policy upon the future level of employment within a region is developed and assessed. The theory, methodology, and relative merits of economic base studies, input-output analysis and simulation modelling are discussed as suitable alternative techniques for impact analysis. The economic base study used in conjunction with location quotients is used in this investigation owing to time and data restr ict ions. The benchmark, economy is Brit ish Columbia. The study region, which is located within the Kami oops Forest D is t r i c t , has been defined in terms of data collection units, trade and functions, and timber flows. The calculated value of the employment multipl ier is 3 .05 . This overstates the true value of the regional mult ipl ier due to the product mix problem, incomplete external trade data for both the benchmark economy and the study region, and fai lure to account for indirect exports of the bench-mark economy. The policy studied is the close ut i l i zat ion policy which was o f f i c i a l l y implemented on January 1, 1966. The def in i t ion, method of implementation and purpose of this policy are discussed. The impa.ct of the close ut i l i zat ion policy on the structure and employment of the regions forest industry in 1971 and in 1980 are i i i estimated. Using the calculated employment mult ip l ier , the total impact of the policy is estimated. In 1971, there were fewer jobs in the study region than there might have been i f the close ut i l i zat ion policy had not been implemented. It is predicted that, by about 1980, without the close ut i l i zat ion policy, changes in forest industry structure and market demands which would have resulted from economic forces alone would have led to the same levels of annual harvests, tree sizes harvested, average productivity and average sawmill capacity as had been achieved earl ier by implementing the policy. Suggestions are given for improving the accuracy and precision of estimates of future timber harvests, and productivity in logging and sawmilling. Public agencies should include estimates of the impact on employment of their proposed policies and investments in their benefit-cost analyses. iv TABLE OF CONTENTS Page Chapter I Introduction 1 Chapter II Possible Approaches to Analysing Forest Policies for Planning Purposes 6 Economic Efficiency Implications of Forest Policies 7 Economic Impact of Forest Policies 10 Economic Impact 10 Economic Planning Models 11 1. Economic Base Studies 12 a. Economic Base Theory 12 b. Assumptions of the Regional Economic Base Model 15 c. Units of Measurement 17 d. Measuring Sectors 19 i . Surveys 20 i i . Assumptions 20 i i i . Location Quotients 20 i v . Minimum Requirements Technique 27 e. Criticisms of Economic Base Studies 28 2. Input-Output Model 32 3. Other Economic Planning Models 36 Approach Used 37 Chapter III The Study Region and i ts Economy 40 Definition of the Study Region 40 The Nature of Economic Regions 40 The Purpose of the Study Region 42 Definition of the Study Region 44 The Study Region as a Data Collection Unit 44 The Study Region as a Functional Unit 46 The Study Region Timbershed 53 1. Delineating the Timbershed 57 a. The 1965 Timbershed 66 b. The 1971 Timbershed 71 The Economy of the Study Region 76 The Study Region 79. The Benchmark Economy 84 Value of the 1961 Regional Employment Mult ipl ier 86 Evaluation of the 1961 Mult ipl ier 89 Value of the 1966 Regional Employment Mult ipl ier 9.5 V Chapter IV The Effect of the Close Ut i l i zat ion Policy on the Employment Level in the Study Region 100 The Close Ut i l i zat ion Policy 100 Definition and Implementation of the Close Ut i l i zat ion Policy 100 Calculation of the Allowable Annual Cut 101 Allocation of the Allowable Annual Cut 104 Stumpage Appraisals 106 Depletion Records 107 Modified Methods of Implementing the Close Ut i l i zat ion Policy 109 Purpose of the Close Ut i l i zat ion Policy 110 Effect of the Close Ut i l i zat ion Policy 115 Approach and Assumptions 115 The Effect of the Close Ut i l i zat ion Policy on the Level of Employment in 1971 117 Timber Supply 117 Logging and Sawmilling 129 1. Logging 130 a. Logging Costs and Productivity 130 b. Logging Productivity and Employment in 1971 136 2. Sawmilling 142 a\u00C2\u00BB> Economies of Scale in Sawmilling 142 b. Effects of the Close Ut i l i zat ion Policy on Sawmilling Productivity 155 i . Lumber Production . 1 6 0 i i . Average Revenue from Mil l ing Smallwood 161 i i i . Additional Costs of Processing Smallwood 163 i v . Sawmill Industry Structure in 1971. 164 v. Sawmilling Employment in 1971 167 Regional Employment in 1971 172 Effect of the Close Ut i l i zat ion Policy on the Level of Employment in 1980 173 Timber Supply 173 Logging 175 Sawmilling 176 Pulp Mi l l 179 Regional Employment in 1980 180 Chapter V Conclusions 183 Mult ipl ier Analysis 183 vi Impact of the Close Ut i l i zat ion Policy ]j*3 Short-Term Impact ^ Long-Term Impact J\u00C2\u00B0\u00C2\u00B0 Suggested Improvements in Estimation Methods I B D Footnotes -|9 2 Bibliography 201 Appendices v i i LIST OF TABLES Tables Page 1 Distribution of annual harvests in the Kami oops Forest Dist r ic t among types of land status -1961 to 1971. 54 2 Estimated distribution of Br i t ish Columbia's timber harvest, 1965 to 1971. 59 3 Timbersheds of sawmilling centres, December, 1965.. 60 4 Summary of the distribution of timber supplies of timbershed PSYU's, .December, 1965.. 62 5 Sawmill capacity by sawmilling centres, December, 1965. 68 6 Timbersheds of sawmilling centres, December, 1971. 72 7 Summary of the distribution of timber supplies of timbershed PSYU's, December, 1971. .74 8 Sawmill capacity by sawmilling centres, December, 1971. 77 9 Employment by industry in the study region, 1961. 80 10 Calculation of employment mult ip l ier , 1961. 87 11 Distribution of sales of resource industries of Br i t ish Columbia, 1955. 93 12 Employment in resource.industries in Br i t ish Columbia indirectly linked to exports, 1961. 94 13 Employment mult ipl ier part ia l ly adjusted for indirect exports of Br i t ish Columbia, 1961. 96 14 Allowable annual cut increases of PSYU's in the study region.- 119 15 Allowable annual cut increases of Tree Farm Licences in the study region. 121 v i i i Volumes available for quota increases in PSYU Proportion of smallwood volume by PSYU. Loqging productivity in the Kami oops Forest Dist r ic t and in Brit ish Columbia, 1962-1971. Comparison of log scales. Sawmilling productivity in the Interior of Br i t ish Columbia, 1960-1970. Study sawmills used by Dobie (1971). Manufacturing costs per M fbm of lumber for circular saw sawmills. Manufacturing costs per M fbm of lumber for small log sawmills. Number of employees per establishment in sawmills and planing mil ls in Br i t ish Columbia, 1967 and 1968. Operating sawmill and lumber production in Brit ish Columbia, 1955-1971. Distribution of sawmills in the study region of firms with quotas and Tree Farm Licences. Employment by sawmill s i ze . Employment in sawmilling in 1971. ix LIST OF ILLUSTRATIONS Income and commodity flows in a regional economy. The study region, Br i t ish Columbia, 1961 Census Divisions and Region Six . Br i t ish Columbia, major highways and study region. Br i t ish Columbia, main railways and study region. Br i t ish Columbia, Region Six and Forest D is t r i c t s . Timber flows in the study region - 1965. Timber flows in the study region - 1971. Annual Harvests from Timber Sales and TFL's in the Kamloops Forest D is t r i c t , 1955-1965. Sawmilling productivity in the Interior of Br i t ish Columbia, 1960-1965. Traditional Long-run average cost curve. \"L\"-shaped Long-run average cost curve. Short-run average cost curves for different scales of plant and long-run average cost curve. Production cost related to sawmill capacity for three small log sawmills. Labour requirements by sawmill scale. X APPENDICES Appendices Page I Table 1 Ranger d i s t r i c t timbersheds, 1965. 201 Table 2 Ranger d i s t r i c t timbersheds, 1971. 207 II Employment by industry required for self -suff ic iency in Brit ish Columbia in 1961. 211 III Allowable annual cut increases of individual firms. 214 xi ACKNOWLEDGEMENT I wish to thank the following persons for their assistance by providing information for this thesis: Mr. D. Cartwright, formerly of the Department of Industrial Development, Trade, and Commerce, V ictor ia , Br i t ish Columbia, Mr. T. Laanemae, Stat ist ics Canada, Vancouver, Brit ish Columbia, Mr. J.A. Mcintosh, Western Forest Products Laboratory, Vancouver, Brit ish Columbia, Mr. D.W. Munro, Weyerhaeuser Canada Limited, Kamloops, Brit ish Columbia, Mr. B.E. Neighbour, B.C. Forest Service, Kamloops, Br i t ish Columbia, Mr. D.M. Roussel, Canada Manpower Centre, Kamloops, Br i t ish Columbia. I also wish to thank Dr. D. Haley, my Graduate Program Committee Chairman; Dr. H.C. Davis, School of Community and Regional Planning; Dr. J . Dobie, Western Forest Products Laboratory; and Dr. J.H.G. Smith, Faculty of Forestry for their encouragement and guidance. Special thanks are also due to my wife, Diane, for her patience and help. Johannes Ottens, June 20, 1973 1 CHAPTER I INTRODUCTION The role which public forest policy has in regional industrial and economic development is probably nowhere as evident as in Br i t ish Columbia. The very fact that almost 95% of the province's approximately 138 mil l ion acres of forest land is provincially owned and administered by the B.C. Forest Service in the public interest ensures that forest policies can influence the structure and performance of the forest industry. It is generally recognized that public forest policies in Br i t ish Columbia do, in fact , influence a l l aspects of the forest industry (Haley, 1971; Nagle, 1970). Changes in the forest industry of the province, however, are not confined to that industry, but s p i l l over into the rest of the economy as wel l . The extent to which the rest of the economy is affected by changes in the forest industry dictate that forest policy formulation and implementation in Br i t ish Columbia deserve more careful planning than has been done in the past. The forest industry is an engine of growth in Brit ish Columbia (Denike and Leigh, 1972). The forest industry, in 1971, directly employed 83,200 persons or 10% of the total provincial labour force and generated about $2,183 mil l ion sel l ing value of factory shipments in manufacturing or 47% of the provincial total (Dept. of Industrial Development, Trade, and Commerce, 1972d). Moreover, the forest industry and i ts employees support sizeable service, construction. 2 and pay taxes. These are among the indirect impacts which the forest industry has on the rest of the province. It is estimated on the basis of a study of the total impact of the forest industry on the economy of Ontario (Hedlin, Menzies and Associates, 1969) that each new job in the forest industry generates almost two other jobs in other industries (Reed, 1972). Even from this brief account i t should be apparent that forest policy changes could conceivable result in signif icant impacts in a large portion of the province's economy. Br i t ish Columbia forest policy characterist ical ly has been developed in a pragmatic fashion on a basically technical forest management framework. Policy implementation has been f lex ib le , with changes made readily as new circumstances arose. Many policies have been based on intuit ion and implemented on a t r i a l and error basis with seemingly l i t t l e formal planning (Haley, 1971; Nagle, 1970; Pearse, 1970; Carney, 1967). The degree of planning involved in developing the close ut i l i zat ion p o l i c y j for example, is reflected by several comments made by the former Minister of Lands, Forests and Water Resources: Although some operators already have been working to close ut i l i zat ion standards and the principles have been applied to a degree in recent decisions regarding establishment of new and expanded pulp and mil l capacities, the impact of this new programme is almost incalculable. Consider alone the fact that the actual range of increase in volume throughout the province is from 15% to 1700%, depending on the timber stand. Then add the unknown factor of degree of application of the policy by industry . . . and I think you' l l agree a crystal ball might be more useful than a computer. 3 In the meantime, i f more policies and programmes are needed, I can promise you we w i l l provide them. The demand for wood products w i l l match the exploding population and we don't intend to be le f t behind. (Wil l iston, 1966a, p. 34) Later, in Apri l 1966, he admitted that the B.C. Forest Service had not foreseen the d i f f i cu l t ies which were being experienced by sawmill operators with respect to technology and equipment, financing and number of sawmills per area (especially in the Cariboo area). The former minister's answer to this turn of events was, \" . . . I have found there is only one way to find out the answers and that is to start and then see what happens.\" (Wil l iston, 1966c, p. 32). He then suggested a few changes, such as promoting more integrated m i l l s , fewer mil ls and mil l l icencing, which might be required to set the industry onto the path toward complete forest u t i l i za t ion . The i n i t i a l results of the close ut i l i zat ion policy in A p r i l , 1966 indicate that a more formal approach to forest resource planning is jus t i f i ed . Nagle (1970) suggested that more effective forest resource planning can be accomplished by assuming a more formal approach to the following: 1. the estimation of future developments as a basis for policy decisions, with relatively less reliance on past developments at decision-time, 2. expl ic i t formulation of the aims of policy, and rather less incidental action, 3. co-ordinated action by individual ministries and firms, not random action. (Nagle, 1970, p. 23) 4 Planning in this sense requires a mathematical formulation of a sector or regional economy. This model is used to forecast developments in the sector or economy which w i l l take place assuming no action on the part of the board of planners. The result of this forecast is compared with the stated aims of the economy. The board can then set up a plan or a careful statement of changes which are necessary to meet the stated aims of the economy. Much of Br i t ish Columbia forest policy was intended to have regional economic effects. The core of this forest policy is the sustained y ield forest management policy. Sustained y ie ld forest management was defined by Sloan (1957) as \" . . . a perpetual y ie ld of wood of commercially usable quality from regional areas in yearly or periodic quantities of equal or increasing volume.\" Although other benefits of maintaining continuous forest cover such as protection of watershed, s o i l , recreation and wi ld l i fe values were alleged, the objectives which were stressed are economic. A sustained-yield policy has, as one objective, the maintenance of forest cover and growth, thus ensuring a perpetual supply of raw material for the forest industries, with consequent s tab i l i t y of industrial communities and assurance of permanent pay-rol ls . (Sloan, 1957, p. 40) The developments in forest tenures which followed the implementation of sustained y ield policy were disigned not to merely obtain revenues from Crown forests, but to provide growing and stable employment (Sloan, 1957). Therefore, i t would be appropriate that forest policy makers should use regional economic and forestry modelling tools to aid them in rational administration of the Crown forests in the best 5 interest of the public. In Chapter I I , two possible approaches to analysing forest policies - economic eff iciency, or maximizing net revenue from the forest resources and the incidence of the effects of such policies w i l l be br ief ly discussed. The approach used in this study, as well as other possible regional economic approaches, w i l l be outlined. In Chapter II I , the study region and i ts economy w i l l be described. Also, in this chapter, the value of a s ta t i c , regional, employment multipl ier w i l l be estimated using the location quotient technique. In Chapter IV, the B.C. Forest Service's close ut i l i zat ion policy w i l l be described and i ts effects on the structure and employment on the Kamloops region's forest industry in 1971 and 1980 w i l l be estimated. Using the estimated value of the employment mult ip l ier , the total impact of the close ut i l i zat ion policy on employment in the study region wi l l be estimated. In the f inal chapter, the technique used in this study w i l l be evaluated as a planning tool for forest policy makers. 6 CHAPTER II POSSIBLE APPROACHES TO ANALYSING FOREST POLICIES FOR PLANNING PURPOSES The analytical approach which a forest resource planning board chooses to use should be appropriate to the goals of the economy which the board serves. The more important goals of the Brit ish Columbia forest administration have been to encourage growing and stable employment in forest industries which w i l l foster stable communities, fu l le r ut i l i zat ion of the forest resource in mil ls and in logging, as well as to raise public revenue from provincial forest resources (Haley, 1971; Nagle, 1970). Policies to achieve these major goals are (1) to manage Crown forests on a sustained y ield basis, (2) to offer long-term and non-competitive tenure arrangements to encourage investments in mil ls and forest management by private companies (3) to encourage the adoption of closer ut i l i zat ion standards, and more recently, (4) to induce the forest industry tc expand more quickly to the physical l imits of the forest resource. These policies have been a major influence in shaping the structure, investment and product-mix of the forest industry; and in affecting the course of regional develop-ment in Br i t ish Columbia (Haley, 1971; Nagle, 1970). Subsequent policy formulation and implementation should take into consideration the implications of these changes on the economic efficiency of allocations of resources among forest industry sectors and other forest uses, as 7 well as on the incidence of these changes on various groups and the environment. The board should not consider economic efficiency to the exclusion of incidence of effects of various forest pol ic ies . Although this thesis is concerned with developing and using tools to analyse the incidence of forest policy effects, the question of economic efficiency implications of forest policies deserves some discussion in order to indicate the direction in which such analysis could take. ECONOMIC EFFICIENCY IMPLICATIONS OF FOREST POLICIES Sustained y ield forest management and related policies in Brit ish Columbia have been c r i t i c a l l y examined (Pearse, 1970; Smith and Haley, 1970; Haley, 1977; Pearse, 1965). More recently, the B.C. Forest Service has been insist ing that the industry adopt close ut i l i zat ion standards in order to reduce wood waste. Although, exceptions are made for s i l v icu l tura l and some economic reasons, uniform sets of rules apply for a l l stand types, regardless of their location. The implications of this policy as far as economic efficiency is concerned have not been studied in deta i l . In may be f ru i t fu l for both the B.C. Forest Service and industry to determine how much economic waste is being introduced into the forest industry by reducing physical waste. It is unlikely that this policy can be just i f ied on economic grounds. 8 ' Policies have recently been introduced to encourage the intensif ication of forest management, i . e . increased investments in forest management at the intensive margin (B.C. Forest Service Forest Productivity Committee, 1972). The basic premise for more intensive management is that future gains in volume increment w i l l allow an increased allowable annual cut now. The phenomenon, called the \"allowable annual cut effect ,\" should be scrutinized before any such investments are undertaken (Schweitzer et al_., 1972; Haley, 1972). Forest policy can affect the structure of the forest industry. The trend in Br i t ish Columbia forest industry toward fewer and larger integrated firms has been partly the result of forest pol ic ies . Some of the implications of increasing economic concentration in forest products manufacturing and in forest land control in Br i t ish Columbia have been studied (McLeod, 1971; Ottens, 1971; Tobin, 1970). Forest policy has accelerated the disappearance of smaller and older mi l l s . It is not always economically eff ic ient to phase out old sawmills in order to improve productivity in the industry (Foster, 1972). A similar confusion of technical with economic efficiency was displayed by the Fisheries Service of Canada with their vessel licencing scheme (Pearse, 1972). The salmon f leet may be much more eff ic ient than i t was, but i ts unit cost per ton of catch has probably increased. Analysis in this vein should be conducted for the forest industry to prevent hasty and possible ineff ic ient phasing out of older sawmills. 9 The forest product mix can be and, in fact , has been influenced by forest pol ic ies . During the 1960's the government was encouraging the establishment of new, and the expansion of exist ing, pulp mil ls in Br i t ish Columbia. Currently, the B.C. Forest Service is encouraging the expansion of the lumber industry by their \"third band\" policy which makes increased timber volumes available to sawmill firms who are operating in Public Sustained Yield Units and possess adequate plants to u t i l i ze increased timber volumes (Dingwall, 1969). Matching the manufacturing f a c i l i t i e s with the wood resources without regard for market trends and regional comparative advantage for various forest products can be avoided by adopting appropriate planning techniques (Nagle, 1970). F inal ly , the spatial distribution of establishments relative to their wood supply and markets ought to be examined. Spatial relat ion-ships of the forest industry in Bri t ish Columbia, using the techniques of economic geography, have been conducted for the coast by Hardwick (1963) and for the north central interior by Mullins (1967). While these two studies forecast future trends in location and structure of the forest industry, they were not expressly concerned with spatial economic eff iciency. Spatial efficiency studies carried out for the forest industry have used spatial equilibrium transportation models^ (Holley, 1968; Callahan, 1962) or cost comparisons based on hypothetical mil ls (Haviland, et. al_., 1968), or shift-share analysis (Ashby, 1962). These studies were conducted for a l l , or almost a l l , of North America, but could be adapted for inter-regional analysis in one province. 10 Economic Impact of Forest Policies Before examining models which may be used to measure the effects on regional economies, the concept of economic impact w i l l be explained. Economic Impact Economic impact has been defined by Waggener (1972) as follows: Generally, i t is the sum affects of pressures, adjust-ments, and other types of response expressed in the context of economic act iv i ty . Other types of impacts which are currently receiving increasingly more attention are environmental and soc ia l , as well as impacts of forestry policy on non-timber forest uses. These various types of impacts do not occur independently of one another. For instance, a change in total employment in a community may be the result of a forest policy designed to affect the forest's productivity, the water quality of local r ivers , or the setting aside of forest land for parks. The reason for such regional employment effects resulting from forest management policies is that regions consist of a number of interacting social and natural systems, such as the economy, population and forest. These systems, in turn, are composed of smaller interacting systems, or subsystems. The mechanisms by which subsystems in a region interact with one another are called \"linkages.\" Some of these \"linkages\" w i l l be developed further in another section of this chapter. 11 Planning models which provide an estimate of the order of magnitude and direction of the consequences of forest policies and which take into account these linkages can be extremely complex. However, the planning which is actually used wi l l be governed by the purposes and resources of the planners. A simple, straight l ine , projection of regional economic trends may y ield just as accurate and more plausible results than a complex and sophisticated model. Of course, such a simple model w i l l not l ike ly reveal much knowledge about the interactions among the various systems of which the region is comprised. Other important considerations which enter into the choice of models are the necessity for completeness in the fore-cast, and the data, budget and personnel available (Hamilton, et a l . , 1969). Economic Planning Models Economic planning models consist of a synthesis of two types of models, one describing the interrelationships among sectors in the region or the structure of the regional economy, and the other estimat-ing the changes within sectors of the regional economy. These models range in complexity from economic base studies and input-output analyses accompanied by economic trend forecasts to dynamic regional growth simulation models. A brief survey of the application of regional economic models to the investigation of forest impact problems indicates that economic base and input-output techniques have been used most frequently. For reasons which wi l l become evident from the following review, the economic base technique wi l l be used in this study. Therefore, that technique w i l l be examined in some 12 detail while the other methods wi l l be given only a short review. 1. Economic Base Studies (a) Economic Base Theory Economic base theory is an application of Keynesian multipl ier theory to a regional economy. The Keynesian aggregate demand function may be expressed as y = c + i + g + e (1) where y is the total regional income derived from the expenditures on consumption c , investment i , government g and exports e . If consumption varies l inearly with income, then any autonomous change in any element of the aggregate demand wi l l result in a more than proportionate change, via the mult ip l ier , in the level of regional income such that y = TTF Ce + i + g + e) (2) where b is the marginal propensity to consume and the multipl ier is \u00E2\u0080\u0094\u00E2\u0080\u0094 . Economic base theorists stress the importance of the export element in aggregate demand of a region. Base theory divides a regional economy into two sectors, basic and service. The basic sector or economic base of a region consists of economic act iv i ty in industries which produce goods and services for markets outside the 13 region. The service or non-basic sector consists of economic act iv i ty in industries which produce goods and services for local consumption. The regional economic base supports the region's consumption of local ly produced goods and services as well as i ts imports. The economic base multipl ier concept can be expressed by Y = ( ^ ) e (3) where services are a constant k proportion of the total economic act iv i ty in the region y , the multipl ier is ( ) and e is basic sector act iv i ty . Since y = s + e , where s is economic act iv i ty in the service sector, equation (3) can be rewritten as y = (1 + 1 ) e (4) e The service to basic ratio or i . indicates that each unit of basic e activ ity accounts for s units of service act iv i ty . The multipl ier is then (l + I) or \u00C2\u00A3 . e e In the broadest sense, the economic base includes a l l regional economic act iv i ty the level of which depends on economic forces which are exogenous to the region, such as export demand and interest rates. - In general practise, only exports are measured as the region's economic base. The local or service sectors include local consumption, residential construction, business investment and expenditures, and government investment and expenditures i f purchasing decisions for 14 these depend solely on local factors, i . e . factors which are endogenous to the region. Intermediate inputs are indirectly linked to either the export or service sector (Tiebout, 1962). For example, a region's sawmill industry may export lumber. If the local logging industry sel ls i ts logs to the local sawmills, then logging would be linked to exports and logs c lassi f ied as indirect exports. The relationships between the basic and service sectors can be demonstrated by a flow diagram (Figure 1). Imports of Final and Inter- Imports of Intermediate mediate Goods and Services Goods and Services FIGURE 1. Income and commodity flows in a regional economy (After Davis and Hainsworth, 1970). 15 i Flow set (1) represents the exported goods and services, which have been produced in the basic sector, leaving the region and in return for which money payments enter the regional economy. Total income of the region is increased i n i t i a l l y from the sale of these exports. Flow set (2) indicates the backward linkages from the f inal export producing industries to the intermediate goods and services producers. This flow further increases the regional income. Flow set (3) represents a Keynesian or income multipl ier process through expenditure by the recipients of income from the basic sector and through sub-sequent rounds of respending by the recipients of incomes from the i n i t i a l rounds of the income multipl ier process. Flow sets (4) and (5) represent leakages from the economy in the form of imports of f inal and intermediate goods and services. Imports of intermediate goods and services by the basic sector reduces the income resulting from the backward linkages from the f inal export producers. Similar ly , the imports of intermediate goods and services by the service sector reduces income which could be earned i f these were produced loca l ly . Furthermore, i f local residents spend their incomes on imported f inal goods arid services, the income multipl ier effect w i l l be diminished. (b) Assumptions of the Regional Economic Base Model The base model which has just been described is a simple, stat ic and short-run concept. The assumptions of this model are as follows: 1. Exports give the primary, i f not the sole, support to regional 16 economic growth. The level of income created in the export and local investment sectors depends on forces other than the level of local income (Tiebout, 1962). Changes in the level of act iv i ty in any of the subsectors of the economic base have the same effect cn the regional economy. For example, a given increase in lumber exports have the same effect on the income flow in the economy as an equivalent increase in copper ore exports (Davis and Hainsworth, 1970). The proportion of service sector act iv i ty relative to the total economic act iv i ty within the region is invariable over time and in response to the levels of exports. This implies that the average and marginal propensities to consume local ly are equal (Davis and Hainsworth, 1970). The actual propensity to consume local ly is more properly expressed as the product of the propensity to consume local ly and the income created per dollar of local consumption sales in order to account for the import content of service sector sales. (Tiebout, 1962). The income form of the base multipl ier is then where x is total regional income, e is exports, i is local investment, c^ is the propensity to consume loca l ly , and c 2 is the income created per dollar of local consump-tion sales. 17 4. Interregional feedback from increases in exports is considered negligible (Davis and Hainsworth, 1970). 5. A pool of unemployed resources, labour and capital ex ist , either inside or outside the region, which the regional economy can draw on. Otherwise increased export demands would only result in increased prices (Davis and Hainsworth, 1970). The short-run basic mult ipl ier model is generally considered valid for forecasts of up to two years (Tiebout, 1962). Forecasts of export levels and local investment are made for the coming time period and the impact on the total regional economy are estimated by means of the mult ipl ier . (c) Units of Measurement Which unit to use to measure basic and service economic act iv i ty in the model depends on the model's purpose as well as avai lab i l i ty of data. Base theory seeks to l ink the output in basic industries in a region to the total regional output as has already been demonstrated (Figure 1). The obvious units of measurement to use include physical output, sales, value-added, and income and expenditures accounts (Tiebout, 1962; Andrews, 1954). Physical output can be dismissed as a measurement unit because physical units cannot be added across industries or even within indus-t r ies . Therefore, physical output must be reduced to a common denominator, usually in money terms. 18 Sales, the value of total transactions, is not a suitable unit of measurement either. Sales double count actual economic act iv i ty because intermediate goods and services are included in the sales value of each f irm. Value-added, the sales of each firm less cost of intermediate goods and services, avoids the double counting problem of sales. How-ever, besides the d i f f i cu l t ies in securing the necessary data, establish-ing what proportion of the value-added accrues as income to local residents is even more d i f f i c u l t . Income and expenditure accounts would allow the investigator to derive the size of a l l the flows of income shown in Figure 1 and therefrom the relevant propensities and the division between basic and service production in the region. However, not only would the data required be expensive to col lect , the local residents and businessmen would have to be very co-operative. In view of the d i f f i cu l t ies encountered in attempting to use these units, payroll and, more often, employment have been commonly used in economic base studies as proxies for dollar value of output and income. Employment, cr the number of jobs, is the most commonly used unit of measurement for economic base studies for several reasons. The concept of the job is easily understood by non-economists, is often a central government policy consideration and is often the most accessible form of data available. In using employment as a proxy for income or output, i t i s impl ic i t ly assumed that changes in employment w i l l parallel changes in output. This assumption wi l l lead to both 19 short-run and long-run errors (Siege!, 1966). In the short-run, this assumption implies that the regional production function is l inear and homogeneous. However, i t is more l ike ly that regional firms w i l l experience diminishing returns as output increases in the short-run. For instance, at times of f u l l employment an increase in a region's exports may only result in an increase in per capita income (Lane, 1966). In the long-run, this assumption denies that productivity w i l l improve over time. For both these reasons i t is better, i f possible, to measure the changes in economic act iv i ty in terms of output and then to convert output to employment. Another remedy may be to use payrolls as a proxy for income. Payrolls are positively associated with labour productivity. However, the drawback is that payroll data impl ic i t ly give more weight to a high-income job than a low-income job. Such a valuation of jobs may not be appropriate for public policy. A common misconception in using employment as a proxy for income is the implication that the income multipl ier is equivalent to the employemnt multipl ier (Lane, 1966). It must be kept in mind that the income multipl ier is a function of the propensity to consume and to import, in i ts simplest form. On the other hand, the employment mult ipl ier is a function of the e last ic i t ies of the aggregate supply curves for labour faced by the investment goods industries and the consumer goods industries. (d) Measuring Sectors One of the main problems in conducting economic base studies 20 is the separation of the basic sector from the service sector. The four methods used to derive the service-to-basic ratio are (1) surveys, (2) assumptions, (3) location quotients and (4) minimum requirements techniques. (i) Surveys It is generally agreed that the survey method of collecting data and dividing the total income of the community into basic, service and intermediate sectors which was described by Tiebout (1962) is the best. The intermediate goods and services producing industries are \"traced out\" into either the basic or service sector. Unfortunately, this method is very time-consuming and expensive. An economic base study with the purpose of providing a better understanding of the Ontario forest industry sector, and i ts direct and indirect impacts on the provincial economy, used surveys (Hedlin, Menzies and Associates, 1969). ( i i ) Assumptions The assumption method, by which industries are segregated into sectors according to the investigator's judgement, can be dismissed, except in the simplest regional economies, as being unacceptable (Tiebout, 1962). ( i i i ) Location Quotients Location quotients, sometimes called concentration rat ios, 21 coefficients of local izat ion, or coefficients of special ization, are measures of self -suff ic iency of an economic area. The use of location quotients results in a method which compares the relative concentration of employment, industry by industry, in the study region to another, larger region which is referred to as the benchmark economy. In the f o i l owing: R./x LQj = J L _ ( 6 ) . N./X LCh is the location quotient for industry i , R... is the employment in industry i . within the study region, x is the total regional employment, N. is the employment in industry i within the bench-mark economy, and X is the total employment in the benchmark economy. If LQ_. is equal to unity, then the study region is regarded as being se l f - suf f ic ient in production from industry i , neither exporting nor importing i ts products. If LQ_ is greater than unity the study region is regarded as being specialized in production from industry i and to export excess output. The opposite implies that the study region is an importer of products from industry i . The ratio of the sum of the basic employment to the sum of the service employment is used to determine the regional employment mult ipl ier . An example w i l l serve to i l lust rate the method of using location quotients. In equation (6), let x be 20,000, N. be 80,000 and X be 800,000 employees. If LQi is equal to unity, a l l of R. would be employed to produce for local consumption, then 22 xN R i = 1 _ 20,000(80,000) 800,000 2,000 Therefore, employment in industry i must be 2,000 in order for the region to be se l f -suf f ic ient in production from industry i . If R. were actually 3,000 employees, then 2,000 would be employed in production for local markets, which leaves 1,000 employees to produce for the export market. If R.. was actually 1,000, then a l l of the 1 ,000 v/orkers would be engaged in the service sector and the region would be regarded as being an importer of products from industry i . If . R. was actually 2,000, then a l l 2,000 workers would be in the service sector and the region would be in the service sector and the region would be se l f - suf f ic ient in industry i production. The location quotient method makes several assumptions which necessitate making adjustments to the results arrived at by using equation (6). F i r s t l y , the location quotient technique assumes that the consumption patterns of the study region and the benchmark economy are the same for both f inal consumption and intermediate goods and services. Appropriate adjustments could be made for interregional differences in tastes, demand patterns, standards of l i v i n g , income distribution and prices which could be revealed through geographical budget studies (Davis and Hainsworth, 1970; Tiebout, 1962). 23 Secondly, i t is assumed that there is no difference in labour productivity between the study region and the benchmark economy. These assumptions ignore differences in the economies, locational deter-minants of industries, differences in f inal and intermediate products, specialized goods and product di f ferent iat ion, and net exports of the benchmark economy (Davis and Hainsworth, 1970; Tiebout, 1962). Thirdly, an adjustment can be made i f the benchmark economy is a significant net importer or exporter of certain goods and services (Davis and Hainsworth, 1970). The benchmark economy is assumed to be se l f - suf f ic ient and to have zero net imports or exports. Therefore, i f the benchmark economy imports a quantity of products of industry i which requires m units of labour, then the location quotient for industry i in the study region is calculated as follows: R i / X , % L q i \" (N, I m j )/X ( 7 ) where X becomes (N. + m.) instead of N- . i 1 1 i What is considered to be the main flaw in the location quotient technique is that the level of exports of the study region is sensitive to the level of aggregation of industry c lassi f icat ion used. This flaw has been labelled the \"problem of product mix\" and is the result of the form in which data by industry are available. Stat ist ics Canada (1970) defines an industry as . . . a group of operating units e.g. companies or establishments, 24 engaged in the same or a similar kind of economic act i v i t y , e.g. logging camps, coal mines, clothing factories, department stores, laundaries. (Statist ics Canada, 1970, p. 7) Industries are c lassi f ied by various Standard Industrial Classif ication (S.I.C.) levels by means of a numerical coding system in which the level of aggregation of industries is indicated by the number of digits in each industry code number. Industries which include a narrow range of act iv i t ies or products are c lass i f ied by three- and four-dig i t S.I .C. groups. These three- and four -digit S. I .C. industries are combined into Major Groups and. these in turn into Divisions. The exports of one industry may be s ta t i s t i ca l l y absorbed by the imports of another i f both industries are grouped together into a lower S.I .C. d ig i t level industry. For example, suppose that the Major Group 8- Wood Products Industry in the study region consists of Sawmills, Planing Mil ls and Shingle M i l l s , S.I .C. 251, and Veneer and Plywood M i l l s , S. I .C. 252, each employing 300 persons. Let total employment in the region and in the benchmark economy be 10,000 and 100,000 persons respectively. Let employment in the benchmark economy in S.I .C. 251 and S.I .C. 252 be 2,000 and 4,000 persons respectively. Then, by equation (6), the level of basic employment can be determined as follows: S. I .C. 251 basic employment = 300 - (10 000 \u00E2\u0080\u00A2 \u00C2\u00A3*PPP.) = 100 v lu\u00C2\u00BBuuuioo,ooo ; S.I .C. 252 basic employment = 300 - (10 ,000^000) = _ 1 Q 0 25 Therefore, the study region must import the production of 100 workers in S.I .C. 252. If the two industries are grouped into Major Group 8 - Wood Products Industry, basic employment becomes 6 0 0 - (10,000^\u00C2\u00B0\u00C2\u00B0\u00C2\u00B0) - 0 . It is possible that the level of aggregation of S.I .C. 251 may tend to reduce the estimated basic employment, since there are different species and types of sawmill products cut. No method of correcting this error is known. Therefore, in every instance, the basic employment derived from location quotients w i l l be understated (Tiebout, 1962). It can be concluded that the location quotients technique w i l l always result in an understatement of the size of the basic sector. What the technique measures is only part of the regional economic base, so that the employment mult ipl ier i t established wi l l not be correct. The significance of this discrepancy between the 'true' mult ipl ier and the one actually derived depends upon the size of the regional economy and how stable the basic ratio (e/x) is over time (Siege!, 1966). In i ts favour, location quotients have signif icant advantages over the survey method in that they are less time consuming and less costly. Also location quotients automatically account for indirect basic act iv i ty which must be \"traced out\" when the survey method is used. In a previous example, i t was shown how a region's logging 26 industry may be indirectly linked to the basic sector through i t s sales of logs to the local sawmilling industry which exports lumber. A region with a larger proportion of employment in sawmilling than the benchmark (which is se l f - suf f ic ient in the production of a l l goods and services) is also l ike ly to have a larger proportion of i t s employ-ment in logging. Even though the logs are sold or transferred to local sawmills, they are indirectly tied to lumber exports. Location quotients w i l l show logs as exports of the region and, thus, measure indirect exports. When the survey method is used, information about the destination of sales from local industries are required to \"trace out\" indirect exports (Tiebout, 1962). For purposes of projection, either the survey or location quotient technique wi l l y ie ld accurate results, given that certain restr ict ive conditions, which w i l l be discussed later , are sat is f ied , and provided that the mult ipl ier is used correctly (Siege!, 1966). For example, let the location quotient for the forest industry in a region by 1/10 and the employment mult ipl ier by 10. If one-third of the region's forest industry employment is basic, and the forest products industry expands by 300 workers, the correct impact on the regional economy would = (1/3)(300)(10) = 1,000 jobs, provided that the service-to-basic ratio remains constant over time. Several regional forest economic studies have used the location quotient technique. Maki et aj_. (1968) developed timber dependency indicators for f i fteen economic areas within the Douglar-fir region of the United States. Their timber dependency indicator was the 27 percentage of the area's total excess employment which was accounted for by the forest products industry. Their results formed the basis for a series of timber supply studies in the Douglas-fir region which were carried out by the U.S. Forest Service. Austin (1969) used the values of the timber dependency indicators to i l lust rate the importance of the timber flows within the Douglas-fir region and the possible regional economic impacts of alternative timber land management pol ic ies , A more analytical use of the indicators was made by Schallau et al_. (1969) in their study of the effect of sustained yei ld forest management upon employment, population and economic s tab i l i t y of timber-dependent areas of the Douglas-fir region. In this study, the employment and population projections were based on production forecasts. (iv) Minimum Requirements Technique A th i rd , but l i t t l e used, indirect method of measuring the regional economic base is the minimum requirements technique. This method is a refinement of the location quotient technique in that i t recognizes that the base ratio decreases in value as the size of the regional economy increases (Ullman and Dacey, 1960). This technique estimates the minimum percentage of a regional labour force which is required in various industries of i ts economy in order to satisfy i ts own needs. Any proportion of the labour force in excess of this minimum requirement is regarded to be export employment. For each sector, the percentage of the total regional labour force employed in that sector in each region is calculated for several regions a l l of which have about the same size of population. The minimum percentage 28 calculated for that particular sector is used to estimate export employment in the study region. This procedure is repeated for the other sectors. The minima are summed to produce the total service employment percentage. Then the service-basic ratio may be calculated for the study region. In order to avoid using the minima derived from the inclusion of some atypical regions, some workers have used not the th lowest but the n lowest percentages. However, this practise could be unreliable unless good judgement is excercised (Tiebout, 1962). (e) Criticisms of Economic Base Studies Besides the criticisms of the units of measurement and the methods of measurement of regional economic base which are used, much cr i t ic ism has been leveled at using economic base studies for regional planning at a l l . These criticisms are concerned with three main weak-nesses of traditional economic base studies: 1. Exports are the only source of autonomous spending in the region, 2. The base ratio is assumed to stay constant over time, such that long-run response and adjustments in the region are ignored, and 3. Base studies show the results or expected results of economic growth processes, but do not describe these processes. 29 Exports are not the only source of autonomous spending, although in many regions exports may be the most s ignif icant . Other sources of autonomous spending include local investment, government . operations and transfer payments. In the long-run, however, factors other than autonomous spending probably play a larger role in in i t ia t ing regional growth (Lane, 1966; Tiebout, 1962). Tiebout (1962) has suggested a formulation of a income multipl ier which assumes that a l l of the local sectors generate income in the long-run. However, his multipl ier does not take into account possible changes in propensities to consume and to invest. Besides, the data requirements would lead most investigators to use the base ratio formulation as in equations (3) and (4), or some other method instead. Even though there is empirical evidence to show that the base ratio decreases as the size and degree of isolation of the regional economy increases, i t is assumed in most base studies that the base ratio w i l l remain constant to the end of the forecasting period (Barkley and A l l i son , 1968; Siege!, 1966; Tiebout, 1962; Ullman and Dacey, 1960). The value of the base ratio has been hypothesized to decrease rapidly as the size of the economy increases upto a threshold size where the rate of decline in the base ratio decreases (Siege!, 1966). The threshold size of the community depends, among other things, on the scale economies present in various types of service industries. The actual change in the base ratio depends on changes in population, total community income and per capita income (Tiebout, 1962). Further instabi l i ty in the value of the base ratio results from either transitory effects or a lag in response in the service sector to adjust to changes in the basic sector. These effects may be on-going 30 before, during and after the measurement of the base. Therefore, the measured base ratio may not be in equilibrium as assumed because the effects of a number of changes in the base in a number of previous time periods are s t i l l working themselves out (Siege!, 1966). Finding the true size of the mult ipl ier may be thwarted by changing influences of region s ize , i f not by the resulting project size. It is possible to take some precautions, however. F i rs t , avoid using very small regions as planning units. Secondly, i f i t is possible, use secondary information to temper the analysis results. In rapidly growing regions, such errors may not have severe consequences since over-estimates of economic act iv i ty may be corrected by rapid population growth (Siegel, 1966). This leads to a third precaution. It may be advisable to estimate a range of forecasted economic act iv i ty rather than a single value. These precautions can be taken to minimize forecasting errors which are caused by long-run adjustments within the region. However, the traditional economic base model does not take these long-run adjustments into account in a direct manner. Factors such as response lags, influences of total income and income per capita changes, region size changes and scale economies on the interrelationships between sectors have been mentioned already. Economic base studies impl ic i t ly take into account import substitution by means of the multipl ier (Tiebout, 1962). However, base studies do not account for long-run changes in technology, productivity or transportation costs in the service sector. Not many economic models can. These changes have to be introduced separately to modify forecasts made by 31 the base study (Tiebout, 1962). These considerations lead to another major class of crit icisms of the use of base studies. Many base studies are purported to predict regional economic growth. To do this is to ignore the distinction between short-run and long-run considerations (Lane, 1966). Economic multipl ier theory explains economic expansion of output, income and employment in response to increases in aggregate demand, i f unemployment exists i n i t i a l l y ; i . e . base theory explains the results of the growth process by assuming away the problems of the growth process i t s e l f (Barkley and A l l i son , 1968; Lane, 1966; Siegel, 1966). Economic growth requires more than an increase in the stock of resources. In most base studies the supply of natural and human resources, and captial are assumed to be unlimited. The assumption of unlimited supplies has been shown to be dangerous even in the short-run in a small region (Lane, 1966). An expansion of the basic sector in a small isolated region would, in the short-run, result in increased employment and wages in the basic sector, and a decline of employment in the service sector. The fact that base theory deals only with demand-sided problems l imits i ts use in solving problems of under-developed regions with \"sticky\" emmigration. These supply-sided problems require solutions of how to increase regional output and per capita income (Siegel, 1966). Improvements which have been suggested to make base theory more useful in this direction include a more dynamic treatment of economic structural changes in response to autonomous spending and to local income and population levels , inclusion of micro-economic 32 relationships at the firm level and information on resource ava i lab i l i t y (Barkley and A l l i son , 1968). 2. Input-Output Model Substantial improvements over the economic base model have been made by the input-output model. The input-output model abandons the base-service dichotomy by disaggregating the economy into several interrelated sectors. In this way one of the most important and weakest assumptions of the economic base study, that the service income depends on and remains a constant proportion of basic income, is overcome. In addition, the input-output model deals with investment, government and consumption expenditures, as well as exports, as sources of in i t ia t ing economic growth (Davis, 1970; I sard, 1960). Regional input-output analysis demonstrates the flow of money into a regional economy's sectors, i ts circulation among the region's sectors and i ts leakage from the regional economy. The analysis uses three matrices: a transaction matrix, a technical coefficient matrix and a.direct -plus- indirect coefficient matrix. The second and third matrices are derived from the f i r s t . The transaction matrix consists of accounting balance equations such that purchases by sectors are l is ted in columns under each sector and sales are l is ted in rows across from each sector. The models are generally closed, i . e . they treat households as an endogenous sector rather than part of the exogenous f inal demand. The transactions matrix may be expressed as a set of the following n accounting equations showing total sales of any sector i i 33 n 1 x + y. = x ( i , j = 1, 2, . . . n) (8) j=1 1 J 1 1 where x^- is the value of the output of sector i purchased by sector j , y.j is the f inal demand for the output of sector i , and X| is the value of the total output of sector i . The sales of each sector must equal i ts purchases. Therefore, we can write: n I x . . + y. = x, ( i , j = 1, 2, . . . n) (9) i=1 'J J J where y . is the f inal payments made by sector j and x. = x- for a l l i = j . The technical coefficient matrix shows the distribution of purchases or expenditures by each sector among the other sectors and the outside world. The second matrix is written as the matrix (a^j) where a. . = x^./Xj . This matrix shows the f i r s t round of responding of receipts by each sector or what is often referred to as the technical multipl ier effect. The direct -plus- indirect coefficients matrix shows the completed process of responding of increased sales incomes by local sectors. It is derived by substituting the matrix (a. .) into equation (9) to y ie ld n x. = 2 a , , x, + y_. (10) 34 This equation may be reduced and solved for total output as a function of f inal demand to y ield X = ( I - A ) - 1 Y (11) where X = (xn-) , i = 1, 2, . . . n ; Y = (y..) , i = 1, 2, . . . n ; A = (an-j) ; I = identity matrix; and (I-A)\"\"' is the matrix of direct -plus- indirect coefficients which is usually written in i t s transposed form for convenience of reading tabular information. The matrix column totals are sectoral income mult ipl iers. To obtain the change in local income resulting from an increase in f inal demand for sector i , multiply the column total of sector i by the change in i ts sales. To obtain the change in income in any other sector, say, households from an increase in sales to sector i , multiply the direct -plus- indirect coefficient under sector i and across from households by the increase in sales. Several studies have demonstrated how the regional input-output model can be used to estimate regional economic impacts of changes in forest-related policies and industries. One study used a transaction matrix based on published data to aid in explaining the direct and indirect impacts which the resource sectors had upon the s tab i l i t y of the rest of the Brit ish Columbia economy (Deutch, et a l . , 1959). The study concluded that the three resource sectors, forestry, f isher ies, and mining, were not interdependent. Also, the fu l l force of the economic fluctuations in the resource industries was not 35 transmitted entirely to other parts of the economy because most of the direct resource income was spent outside of Brit ish Columbia. Fluctuations were found to be less violent in the rest of the economy than they were in the resource industries and tended to lag behind those of the resources industries by (about a year or even longer. The changes in forest policies and industrial structure which were studied in the remaining studies f a l l into seven categories: (1) changes in the composition of industry groups (Hughes, 1970), (2) addition of a new type of business to the region (Main, 1971; Hughes, 1970; Gamble, 1968), (3) automation in the forest industry (Main, 1971; Gamble, 1968), (4) the closing down of a sector (Main, 1971; Gamble, 1968), (5) an expansion of timber harvesting within the region (Main, 1971; Hughes, 1970; Gamble, 1968), (6) reduction in timber harvesting in a trade-off between the forest industry and outdoor recreation (Waggener, 1972), and (7) the consequences of alternative types of forest land ownership (Hughes, 1970; Muench, 1966). Besides estimating \u00E2\u0080\u00A2impacts' by multiplying changes in f inal demand by direct -plus- indirect coeff icients, impacts can also be estimated as changes in values of multipliers caused by adding or deleting a l l of parts of sectors, or by otherwise altering matrix coeff icients. An improvement on the regional input-output model is the interregional model which shows the transactions not only among sectors, but among regions as well (Kaiser, 1972). Despite the improvements of the regional input-output model over the economic base model, the input-output model assumption 36 that technical coefficients are stable through time makes results valid only in the short-run. Therefore, forecasts require a knowledge of what the technical coefficients w i l l be at the end of the prediction period. An additional d i f f i cu l ty is that the input-output model requires considerably more data. An attempt to incorporate the theoretical improvements of the input-output model into the economic base model and yet save data gathering and model building expenses is described by Tiebout (1962). This approach, or intersectoral flow model, uses employment created by sales dollars and results in the construction of only the row of the input-output matrices. 3. Other Economic Planning Models Even with the improvements which have been made to the standard economic base model, multipl ier analysis s t i l l lacks predictabil i ty in the long-run. Forecasts based on mult ipl ier analysis either assume away or ignore dynamic growth processes or supply-sided factors (Barkley and A l l i son , 1968). Several attempts have been made to produce dynamic simulation models which take into account that a regional economy may not be a simple, l inear system but actually a considerably more complex non-linear system (Forrester, 1969). A small-area economic base study was conducted by Swanson and Waldmann (1970) through simulation techniques. Their model exp l ic i t l y incorporated feedback between population (labour supply) and employment (potential .jobs) sectors to determine population, migration, job changes, labour force, participation rate changes, and industrial 37 location and growth. There was no provision made for technological change. A simulation model has also been used to increase the capability of an input-output model to assess the impact on the economy of the Greater Vancouver Regional Distr ict of local and national policies and to provide insights into the regional growth process (Davis and Goldberg, 1972). Technological change and effects of automation can be accounted for in the model by changing the technical coefficients in the matrix. The simulation portion of this model forecasts f inal demands, and links the forecasting model to the employment (input-output model) sector through equations describing changes in regional population. Improvements of these dynamic models over solely demand or supply oriented models have been gained at increases in costs of data collection and model construction. Such models would be appropriate for a multi-agency planning board which requires a comprehensive rather than a partial analysis. APPROACH USED The approach used in this study i s , by necessity, a compromise in which the purpose of the study, the weaknesses of regional economic models, and the data and time restrictions are major considerations. The purpose of the study is not to demonstrate the details of the structure of a regional economy, but to estimate the changes in regional employment from a change in forest policy. Regional accounts data are meager compared to data which are available for the province. Accounts data for the province, in turn, are scarcer than those for 38 the nation. Time and resource did not permit carrying out a survey to obtain data required to construct a more detailed regional economic model. For these reasons, the demand side of the planning model which was used in the study is an economic base study. The basic sectors w i l l be segregated from the service sector by means of location quotients using published data and Brit ish Columbia as the benchmark economy. Some of the weaknesses of the location quotients and economic base study techniques w i l l be compensated for to the extent which limited data, resources, and time wi l l allow. The other portion of the planning model provides the fore-cast of change in basic employment. The labour supply is assumed to be unlimited, but the questions of forest resource ava i lab i l i t y , technological and productivity changes, and the changes in capital are accounted for . The forest policy which w i l l be examined is the B.C. Forest Service close ut i l i zat ion policy of 1966. The details of the policy w i l l be given in Chapter IV. It is suff icient for the present to recognize that the close ut i l i zat ion policy caused a change in both volume and log size of the timber supply in the region, as well as technological and productivity changes which are embodied in newly required capital equipment. This portion of the planning model is an attempt to trace through the change timber supply and forest industry to forecast changes in forest industry employment in the region. F i r s t l y , the change in the level of forest industry employment from 1965 to 1971 with and without the new policy w i l l be estimated. The difference between the two estimates represents the 39 direct impact of the policy on forest industry employment in 1971. The total impact of the policy on regional employment w i l l be estimated by means of the employment mult ipl ier . The results of these projections wi l l be compared with actual 1971 employment data in order that the projection model may be recalibrated. With the recalibrated model, the impact of the policy in 1980 w i l l be forecast. 40 CHAPTER III THE STUDY REGION AND ITS ECONOMY In this chapter, the study region wi l l be defined and the value of i ts regional employment multipl ier w i l l be determined. DEFINITION OF THE STUDY REGION The Nature of Economic Regions Economic base studies and forecasting models describe and predict economic act iv i ty within economic regions. The properties of economic space and some types of regions which are used have been examined by several regional scientists (Fox and Kumor, 1965; Losch, 1963; Wrobel, 1962; Isard, 1956; Fisher, 1955; Perroux, 1950). Economic regions have several general characteristics in common. F i r s t l y , each region is defined to serve a particular purpose. The structures and boundaries of study regions wi l l vary according to needs of analysts and planners. These may range from studies of impacts of certain events on regional employment to studies of general regional social welfare. Secondly, regions must be delineated to fac i l i ta te data col lect ion. The location of data collection units, such as census enumeration areas, often dictate the f inal definit ion of the . study region, since many studies depend on published data. 41 Thirdly, almost a l l regions have a hierarchical structure of nodes, or centres around which functions are polarized. These may be centres of government, administration, production, consumption, employment or trade. The various functions which are carried out at centres can be ranked according to the area of hinterland which is required to support each function. Those requiring the largest extent of hinterland would be performed in the \"regional capital c i t y . \" Those requiring a smaller radial extent of hinterland to support them may be conducted in smaller centres. The radial extent required by the \"regional capital city\" functions forms the theoretical regional boundary. The f i e ld of influence of each node can also be thought of as a \"density f i e l d , \" the density of which declines with distance from the node in response to the cost of overcoming distance. These \"density f ie lds\" are also bounded by inst i tut ional and topographical barriers. Fourthly, each region contains a number of homogeneous attributes. These may be types of geographic features or resource endowments, types of economic act iv i ty , cost and price structures, some policy or program, a social or cultural characterist ic, the jur isdict ion of an agency, to name a few. Lastly, regions vary over time. The distribution and levels of activ ity at nodes wi l l change in the long-run in response to internal and external s t imul i , thus altering the configuration of the region. The study region was defined considering the above regional characteristics. 42 The Purpose of the Study Region The study region was defined in such a way that almost a l l of the employment effects which are caused by forest policy changes can be accounted for. For this purpose, the region had to be small enough to allow for analysis at a local leve l , but large enough to internalize the most signif icant effects of implementing a forest policy change. For example, suppose that a change in forest policy was to increase the allowable annual cut on a l l forest land and that this led to an increase in timber supply of a community sawmill. The increased timber supply would l ike ly result in the employment of additional loggers and mil l workers who would immigrate into the community. If the study region does not include a l l of the forest land within economic hauling distance from the community, the model can not predict the increase in employment which would result from the policy to increase timber supplies. The study region must also be large enough to prevent large fluctuations in the base ratio in the long-run. Unfortunately, i t is not certain what threshold size a region must be to obtain a base ratio which w i l l not change drastical ly as the region grows (Siegel, 1966). It is more d i f f i c u l t to define a small region which w i l l fac i l i ta te the accounting of almost a l l of the employment effect of a change in timber supply on the coast than in the Interior of Brit ish Columbia. In the Interior, logs must be transported to mil ls mainly 43 over land routes which generally follow major valleys. Given these restricted transportation routes and freight economies, the l imits of an interior community timbershed can be delineated with some degree of confidence. On the coast, logs may be trucked directly to m i l l s , or f i r s t l y to tide water and then towed to m i l l s . Log towing costs are much lower than trucking costs, and towing routes are not as restricted as land routes. Therefore, on the coast, logs may be drawn from relatively larger distances and more sources than in the inter ior . Consequently, coastal sawmill communities may have a less definite timbershed than their interior counterparts. A loss of timber supplies in one area on the coast, due to, for example, forest land withdrawl for park land, may be replaced by another source elsewhere along tide water, provided that an alternative supply exists. For these reasons, a coastal economic region must include almost the entire coast l ine , making i t v i r tual ly impossible to analyse the effects of changing timber supply on small coastal regions. The Brit ish Columbia coastal forest industry and i ts timbershed has been described in more detail by Hardwick (1963). The minimum, size of inter ior timbershed regions can be expected to increase as the value of forest products increases and as advances in transportation technology and routes occur. Changes in the spatial structure of the forest industry in the north central portion of Br i t ish Columbia from 1909 to 1966 were analysed by Mullins (1967). 44 Definition of the Study Region To meet the purpose outlined previously, the study region has been defined as a data collection unit , a functional unit and a timbershed. The Study Region as a Data Collection Unit The study region is the unit for which employment by industry data are currently available. Unfortunately, the results of the 1971 Canadian Census were not available in time for this study. Therefore, 1961 Census data are the most current which are available for both the province and the study region. Estimates of 1971 employment by industry have been made for the Kami oops Manpower Centre for their area. Corresponding data for the province are not readily available. The study region corresponds to Region Six or the Shuswap-Chilcotin Region in the interior of Brit ish Columbia, as described in the Regional Index of Br i t ish Columbia-!966 (Dept. of Industrial Development, Trade, and Commerce, 1966) (hereafter referred to as the Index), less the Williams Lake-Chilcotin Area (Figure 2). Region Six is divided into areas which consist of one dr more School D is t r ic ts . The six areas are as follows: 1. Ashcroft - Clinton Area 2. Kami oops Area 3. Li l looet Area 4. Merritt Area 46 5. Shuswap Lake - Salmon Arm Area 6. Williams Lake - Chi lect in Area Economic data for Region Six have been derived from 1961 Census Division Six data. The two units d i f fer s l ight ly in several respects (Figure 3). Census Division Six consists of Electoral Areas whereas Region Six consists of School D is t r ic ts . Also Region Six (45,215 square miles) is larger than Census Division Six (31,420 square miles). Region Six includes portions of Tweedsmuir Park and the Quesnel Lake D is t r i c t , which are part of Census Division Eight. The two areas are sparsely populated so that including them in Region Six while using only Census Division Six data w i l l not introduce serious errors. In 1961, the population in Region Six was 68,485 persons compared to 66,290 persons in Census Division Six, which is a difference of 1,185 persons over 13,765 square miles. The study region is also equivalent to the Kami oops Manpower Centre Area plus the Shuswap Lake-Salmon Arm Area. The Study Region as a Functional Unit The study region, besides being a data collection unit , approximates a fa i r l y completely functional region with Kami oops as i ts primary centre of employment, trade and administration. Kami oops accounts for a major portion of both the study ' region's population and labour force. In 1961, the population of Kamloops (including the Town of North Kamloops which is now a part 4 7 FIGURE 3. British Columbia, 1961 Census Divisions and Region Six. Scale approx 120 miles per inch A. Region Six \u00C2\u00A33 1961 Census Divisions _ _ 48 of Kamloops) was 16,290 persons or 30% of the population of the study region (55,427 persons). In 1966, the population of Kamloops was approximately 22,078 persons or 31% of the population of the study region. In 1971, the population of Kamloops was 25,599 persons (Dept. of Industrial Development, Trade, and Commerce, 1972a). Of the total employment in the study region in 1961, which amounted to 17,770 persons, industries in Kamloops accounted for 6,012 persons or 34%. In the same year, Kamloops accounted for 64% of employment in the service industries^ and 55% of employment in trade in the study region. Kamloops' share of the regional labour force as well as i ts location at the junction of the main transportation systems (Figures 4 and 5) suggests i ts importance as a trade centre for the region. The boundary of the study region delineates the l imits of the area which is l ike ly to be served by the commercial establishments located in Kamloops. In some instances, however, i t is not clear whether persons l iv ing at the fringes of the region depend on Kamloops or another node as their trade centre. For instance, i t is not clear what proportion of the population l i v ing in the Shuswap Lake-Salmon Arm Area depend on Vernon and KeTowna to supply their needs rather than Kamloops. A Kamloops Manpower Centre economist believes that one new shopping centre development in Vernon could be suff ic ient to attract almost a l l the population of the Shuswap Lake-Salmon Arm Area away from Kamloops (Roussel, interview, 1973)\". Any difference between the study region and the actual trading area is probably not Highways , Study Region 50 FIGURE 5. Bntish Columbia, main railways and study region. CNR, Canadian National Railways C.PR. Canadian Pacific Railway Study Region l.'.'/A B C R British Columbia Railway Railways , , , W P &Y. White Pass and Yukon Route Under Construction \u00E2\u0080\u00A2 + + NAR. Northern Alberta Railway Under Survey 51 very signif icant since the population in the outlying area is quite sparse. Furthermore, data avai labi l i ty precludes defining the study region on this basis more precisely. Kamloops is also the headquarters of the B.C. Forest Service for the administration of the Kamloops Forest D is t r ic t . The forest policy which this study wi l l examine is administered by the B.C. Forest 2 Service from this headquarters over a l l of the study region (Figure 6). The region's largest forest products company, Weyerhaeuser Canada L td . , has major offices and a 1,250-tons per day capacity Kraft pulp mil l located at Kamloops. Weyerhaeuser also has sawmills at Kamloops, Vavenby, Merritt and Lumby. Weyerhaeuser controls a major portion of the study region's timber resources, holding-one small Tree Farm Licence3 (No. 35), Pulp Harvesting Area^ No. 2, and 5 cutting rights in several Public Sustained Yield Units (PSYU). The pulp mil l purchases a l l chips which have been manufactured from wood harvested in PHA No. 2. Other centres in the study region serve the lower order requirements of the population in their surrounding areas, but are mainly dependent upon primary resource industries such as logging, sawmilling, mining and ranching. B.C. Forest Service Ranger Stations,are based in some of these secondary nodes. From these Stations, Forest Ranger staff implement forest policy at a local level under the direction of headquarters staff in Kamloops. 52 FIGURE 6. British Columbia, Region Six and Forest Districts. LEGEND Scale approx 1 2 0 miles per inch Region Six E_ES___ Forest District Boundaries 53 The Study Region Timbershed The study region so far has been defined in terms of data collection and functions. The purpose of this study also requires that the region be defined in terms of a timbershed. The timbershed for the entire study region is the sum of a l l forest product manu-facturing centres, in terms of volume of annual wood supply, which are included within the study region. The region's timber supply originates from forest lands which are under three broad categories of ownership. These are Crown lands which are owned by the Province, Federal lands which include Indian Reserves, and Crown Grants, which are privately held (Table 1). From 1961 to 1971 Crown lands accounted for 82% of the annual harvest in the Kamloops Forest Distr ict compared to 2% from Federal lands and 15% from Crown Grants. Of the Crown lands, during the same period, PSYU's and TFL's accounted for 72% and 5% of the annual harvest in the Kamloops Forest D is t r i c t , respectively, while Timber Licences, Timber Berths and Farm Wocdlots accounted for only 0.5%, 3% and less than 0.1% respectively. The proportions of the annual harvest which come from these various forest lands vary according to prevailing market conditions. During periods of high stumpage rates, proportionately more timber w i l l usually be cut from forest lands other than Farm Woodlots, Timber Sales and TFL's. The reason is that only statutory royalty rates, or, in some cases no royalty, is paid for timber harvested from Timber Licences, Timber Berths and Crown Grants (Sloan, 1957). 54 TABLE 1. Distribution of annual harvests in the Kamioops-jForest Distr ict among types of land status - 1961 to 1971 . Years Land Status Timber Timber Farm Timber : Tree Farm Mi seel lan- ^rowr)^ Federal Crown Total Licences Berths Wood-Lots Sales ' Licences ; eous \u00E2\u0080\u00A2 . Lands Grants M cf (percent) ' i 1961 944 (0.5) 4,286 (2.1) 15 157,143 (76.8) 9,152 (4.5) 1,585 i (0.8) i 173*125 (84.7) 4,452 (2.2) 26,818 (13.1) 204,395 (100.0) 1962 744 (0.3) 3,556 (1.6) 22 170,431 (77.2) \u00E2\u0080\u00A2. .11,075 \u00E2\u0080\u00A2\"\u00E2\u0080\u00A2 \u00E2\u0080\u00A2' (5.0) j 1,732 !i (0.8) 187,560 (84.9) 5,957 (2.7) 27,377 (12.4) 220,891 (100.0) 1963 1,514 (0.6) 3,390 (1.3) 58 191,837 (75.2) 11,503 (4.5). \ '3,808 , (1.5) . 212,111 (83.2) 8,100 (3.2) 34,838 (13.7) 255,050 (100.0) 1964 2,738 (1.1) 6,867 (2.7) 32 177,585 (70.5) ' 12,510 (5,0) 3,320 ] (1.3) \u00E2\u0080\u00A2 . 203,051 (80.6) 9,351-(3.7) 39,605 (15.7) 252,008 (100.0) 1965 3,100 (1.3) 9,898 (4.2) 22 164,071 (69.6) 11,892 ' (5.0) i 6,239 1 (2.6) 195,222 (82.7) 6,453 (2.7) 34,514 (14.6) 236,189 (100.0) 1961 - 1965 1,808 (0.8) 5,599 (2.4) 30 172,213 (73.7) . 11,226 (4.8) : 3,337 \u00E2\u0080\u00A2 7. \u00E2\u0080\u00A2 R.D.8. M cf per year {% of AAC of PSYU or TFL) 13, Shuswap 1,091 (15.09) 3,841 (51.32). 6,419 (.89.04) 5,172 (86.27) 2,128 (65.64) 32 (0.96) \u00E2\u0080\u00A2 108 (1.44) - 6 (0,08) 483 (8.06) 9,471 (97.57) 593 Cl 8.291 2,154. (64.76) 2,484 (33,19) 5,876 (81.29) 515 08.931 625 392 (18.79) (11,79) . . 2 2,184 (0,0.6) (66,61). 71 7,279 (0.81) (82,72) . 67 (.2.46) Clinton Ashcroft Merritt Blue River R.D.12. R.D.16. R.D.17, R.D.18. 100 Mile House R.D.24 (Part) 3,183 (37.23) 44 (0.64) 3,744 (43.79) 5,212 (75.61) 1,361 (19.74) 117 0 .21) 9,632 (.94,81) (0,41) 1,207 04.12) 22 (0.32) 73 14. Yalakom Subtotals 1 1 , 3 5 1 7 , 4 4 6 1 5 , 1 8 5 6 , 5 7 4 1 0 , 3 7 0 67 ( 1 2 . 7 7 ) ( 8 . 3 8 ) ( 1 7 . 0 8 ) ( 7 . 4 0 ) ( 1 1 . 6 7 ) ( 0 . 0 8 ) TFL 16 2 , 3 0 0 TFL 18 5 , 8 0 0 TFL 33 788 TFL 35 3 , 5 0 0 Subtotals 1 7 , 1 5 1 7 , 4 4 6 5 , 8 0 0 6 , 5 7 4 1 0 , 3 7 0 855 Imports Lac La Hache Similkameen Total Supply 1 7 , 1 5 1 7 , 4 4 6 ' 2 0 , 9 8 6 6 , 5 7 4 1 0 . 3 7 0 855 1 . Source; Appendix I, Table 2 . 3 , 9 9 6 ( 9 2 . 8 7 ) 3 , 9 9 6 3 , 2 2 7 8 , 9 5 6 11,no 3 1 1 o ? q ( 4 . 5 0 ) ( 3 . 6 3 ) ( 1 0 . 0 7 ) ( 1 2 . 5 0 ) ( 0 . 0 3 ) ( 1 . 3 8 ) 3 , 9 9 6 3 , 2 2 7 8 , 9 5 6 1 1 , 1 1 0 31 1 , 2 2 9 1 , 4 3 5 2 , 6 8 0 3 , 9 9 6 3 , 2 2 7 8 , 9 5 6 1 3 , 7 9 0 31 2 , 6 6 4 TABLE 7. Summary of the distribution of timber supplies of timbershed PSYU's, December, 1971 . Quota Quota Quota Forest Total Distributed Exported Unassigned Service Reserve AAC M cf per year (% of AAC of PSYU) 1. Adams 6,967 (96.39) 261 (3.61) 7,228 (100.00) 2. Barriere 5,655 (94.33) 100 (1.67) 21 (0.35) 219 (3.65) 5,995 (100.00) 3. Big Bar 8,134 (95.13) 64 (0.75) 352 (4.12) 8,550 (100.00) 4. Botanie 6,639 (96.32) 4 (0.05) 250 (3.63) 6,893 (100.00) 5. Eagle 582 (21.39) 1,886 (69.31) 149 (5.48) 104 (3.82) 2,721 (100.00) 6. Kamloops 9,588 (98.77) 119 (1.23) 9,707 (100.00) 7. Nehalliston 2,721 (83.93) 400 (12.34) 4 (0.12) 117 (3.61) 3,242 (100.00) 8. Nicola 9,632 (94.81) 160 (1.58) 367 (3.61) 10,159 (100.00) 9. Niskonlith 3,203 (96.30) 3 (0.09) 120 (3.61) 3,326 (100.00) 10. North Thompson 6,464 (86.37) 707 (9.46) 32 (0.43) 280 (3.74) 7,484 (100.00) n . Raft 6,452 (89.12) 505 (7.01) 18 (0.25) 261 (3.62) 7,209 (100.00) 12. Salmon Arm 2,186 (66.67) 596 (18.17) 376 (11.47) 121 (3.69) 3,279 (100.00) 13. Shuswap 7,350 (83.52) 515 (5.86) 611 (6.94) 324 (3.68) 8,800 (100.00) 14. Yalakom 3,996 (92.87) 150 (3.48) 157 (3.65) 4,303 (100.00) Totals 79,542 4,873 1,428 3,052 88,895 (89.48) (5.48) (1.61) (3.43) (100.00) 1. Sources: Appendix I, Table 2 and Kamloops Forest D is t r ic t , \"List of Established Licencees as of January 1st, 1972;\" and \"Sawmills and Planer Mi l ls by Ranger D is t r ic ts , \" March 1st, 1972. 76 timber supply from TFL's increased by the f u l l amount allowed by the revised annual allowable cut calculated to the close ut i l i zat ion standard. The timber supply which was imported from the Lac La Hache and Similkameen PSYU's also increased. The total annual timber supply which was assigned to sawmills in the study region in 1971 was 96,046 M c f , an increase of 28,683 M cf or 43% over 1965. While the timber supply increased by 1971, the number of active sawmills declined by 25% below the 1965 leve l , and their total capacity increased by almost 19% (Table 8). In 1971, there were 90 active sawmills with a combined capacity of 2,773 M fbm per 8-hour sh i f t . Of these, 44 sawmills with a capacity of 2,439 M fbm per 8-hour sh i f t , or 50% of the active sawmills with 88% of the capacity, were assigned annual cutting rights within the timbershed. The number of small mil ls without quotas declined by almost 50% below the 1965 level . These data indicate that the number of sawmills was declining while their average size was increasing. THE ECONOMY OF THE STUDY REGION The value of the employment multipl ier for the study region was determined using the location quotient technique with employment as the unit of measurement of regional economic act iv i ty and Brit ish Columbia as the benchmark economy. The location quotient using employment as the unit of measurement was used for reasons of data l imitations. Br i t ish Columbia was chosen to be the benchmark economy TABLE 8. Sawmill capacity by sawmilling centres, December, 1971 \u00C2\u00BB Active Sawmills With Quotas Without Quotas Totals Sawmilling Centres 1 : \" \u00E2\u0080\u00A2 M fbm per 8-hour sh i f t (number of sawmills) R.D.2. Birch Island 430 30 460 (3) (2) (5) R.D.3. Barriere 200 27 227 (2) (7) (9) R.D.4. Kamloops 389 96 485 (5) (13) (18) R.D.5. Chase 203 23 226 (8) (5) (13) R.D.6. Salmon Arm 331 51 382 15) (9) (14) R.D.7. Sicamous 65 9 74 (2) (3) (5) R.D.8. L i l looet 110 13 123 (1) (3) \u00E2\u0080\u00A2 (4) R.D.12. Clinton 91 15 106 (6) (2) (8) R.D.16. Ashcroft 100 (1) 60 (2) 160 (3) R.D.17. Merritt 375 (14) 10 (1) 385 (5) R.D.18. Blue River 80 (4) -80 (4) R.D.24. 100-Mile House (Part) 65 (2) -65 (2) Totals 2,439 (43) 334 (47) 2,773 (90) 1. Sources: Appendix I, Table 2 and Kamloops Forest D is t r ic t , \"List of established Licensees as of January 1st, 1972;\" and \"Sawmills and Planer Mi l ls by Ranger D is t r ic ts\" , March 1, 1972. 79 in order to satisfy the assumptions of the location quotient technique that the benchmark and study region have similar consumption patterns and production functions for both intermediate and f inal products. It was assumed that Bri t ish Columbia was a more appropriate benchmark than Canada or a group of provinces. The steps followed in determining the regional employment multipl ier are as follows: 1. Compilation of employment by industry for the study region; 2. Compilation of employment by industry for the benchmark, and adjustment of these data to satisfy the benchmark self -suff ic iency assumption; 3. Computation of the 1961 regional employment mult ip l ier ; 4. Evaluation of the resulting 1961 regional employment mult ip l ier ; and 5. Estimation of the value of the regional employment mult ipl ier in 1966. The Study Region Compilation of employment by industry for the study region (Table 9) involved two steps. F i r s t l y , the employment by industry data for 1961 were extracted from the Index and other sources for Region Six. Secondly, the corresponding data for the Williams Lake-Chilcotin Area were subtracted from that of Region Six to arrive at data for the study region. The data which were used to estimate employment by industry for Region Six were actually labour force by industry for 1961 Census Division Six. 80 TABLE 9. Employment by industry in the study region,.1961. 1960 Industrial Divisions S. I .C. Major Groups* Codes Three Digit Industries 002-021 031, 039 041-047 , 051-099 101-109 286-289 151-249 271-274 251 254 251,254 Agriculture Forestry Fishing and Trapping Mines (including Mi l l i ng ) , Quaries, and Oil Wells Manufacturing Industries (Non-Durable Goods Manufacturing Industries excluding Paper and A l l ied Industries) Food and Beverage Industries Pr int ing, Publishing and A l l ied Industries Other Non-Durable Goods Manufacturing Industries (Durable Goods Manufacturing Industries) (Forest Products Industries) Paper and A l l ied Industries Wood Industries Sawmills (excluding. Shingle Mi l ls ) Sash, Door and Planing Mi l ls (Sawmilling) 1961 Census Division 6 No. of Persons (1) Percent of Total 2,340^ 1,540Z 17 698 10.55 6.95 0.08 3.15 4,199 18.95 374 71 1.69 0.32 103 200 0.46 0.91 3,825 3,789 17.26 17.10 4 3,430 3204 3,789 Cariboo Dist Regional r i c t Quesnel Area of Region 8 Williams Lake -ChiIcotin Area of Region 6 Study Region No. of Persons (2) Percent of total No. of Persons No. of Persons No. of Persons Percent of Total 865 : 9.71 404 461 1,879 10.57 689 7.74 408 281 1,259 17 7.07 0.01 175 1.97 155 20 678 3.81 2,812 31.57 1,477 1,335 2,864 333 j . 3.73 157 176 198 1.11 2,479 27.84 1,320 1,159 2,666 2,641 14.89 81 252 251, 256-259 Veneer and Plywood Mi l ls Other Wood Industries 4 39 0.18 '.< 261-268, 291-399 (Non-Forest Products Industries) , 36 0.16 i 1 25 0.14 404-421 Construction Industries 1,302 5.87 419 .j 4.71 197 111 1,080 6.08 501-579 Transportation, Communications, and other U t i l i t i e s 3,069 13.84 833 ;l . 9.36 394 439 2,630 14.82 602-631 642-699 Trade Whole Trade Retail Trade 2,657 526 2,131 11.98 2.37 9.61 1,023 ;! 11.49 483 540 . 2,117 419 1,698 11.92 2.36 9.56 701-737 Finance, Insurance and Real Estate 408 1.84 126 | 1.42 59 67 341 1.92 801-864 Community, Business and Personal Service Industries 4,091 18.45 . 1,449 16.27 684 765 3,326 18.78 902-991 Public Administration and Defence 1,084 4.89 5 1 3 ; 5.76 y ranger staff for their own Ranger Distr icts and compiled in the Forest Distr ict Annual Reports. Stat ist ics Canada gathers employment data by means of annual questionnaires to a sample of logging firms. Since small firms either do not report or are not sampled, i t is l ike ly that Forest Distr ict Annual Reports data are used by Stat ist ics Canada to supplement their employment estimates. If the B.C. Forest Service is inconsistent in reporting their employment data, Stat ist ics Canada estimates wi l l be signif icantly affected since the majority of logging firms are quite small in the inter ior . Lacking better data, logging productivity for~the study region was assumed to be 55.65 M cf per man-year in 1965.\u00E2\u0080\u0094 The. optimum number and sizes of machines which should be used to achieve least unit costs depend on the nature of the timber, terrain and numerous other factors. It is generally believed that there are constant returns to scale in logging. Constant returns to scale occur-when, in the long-run, doubling output requires 136 doubling every input, given the state of technology and production process. In the long-run, a l l factors of production, including capital equipment, land and management, are variable. Therefore, for a given set of logging conditions, average logging costs w i l l be constant regardless of the size of output and provided that the production unit is operating at capacity. In 1965, the cost of logs, which were harvested in accessible, good quality sawlog stands in the southern interior and hauled 20 miles to the sawmill, was at least $16 per C cf for most operators (Smith, 1968). In order to account for areas in the study region where logging costs are generally higher because of rougher terrain, poorer timber quality and long hauling distances, i t was assumed that the average logging cost in the study region in 1965 was $20 per C cf . (b) Logging Productivity and Employment in 1971 To determine the effects of the close ut i l i zat ion policy on logging costs and employment, i t was only possible to speculate on some of the short-run effects for any given forest area, regardless of the size of the operation and s k i l l of loggers. In the long-run, operators could be expected to make some adjustments to their logging methods to keep costs at least somewhere near their former levels. Increases in fe l l ing costs could be expected to be negligible as a result of logging to a one-foot stump and a six^inch diameter top CMcIntosh, 1968). However, fe l l i ng costs per C cf increases with 137 decreasing stem dbh. The fe l l ing time per C cf for 8-inch dbh trees is twice that for 11-inch dbh trees (Mcintosh and Csizmazia, 1965). Small trees are also generally branchier than large trees and take more time to limb. Fell ing time would be further increased by the need to take more care to prevent breakage of small trees and longer top logs (Mcintosh, 1968). Since fe l l ing accounts for a major proportion of the logging costs, employment per C cf could be expected to increase as a result of logging to close tu i l i zat ion standards in the short-run and where fe l l i ng cannot be mechanized. Skidding costs could be expected to increase primarily as a result of avoiding breakage of small trees and tops (Mcintosh, 1968). Skid t ra i l s must be straight and spaced such that trees can be fel led parallel to skid t ra i l s and then skidded with a minimum of deflection. Increases in costs of skid t r a i l construction may be compensated by an increase in volume recovered per acre logged. As there would be more stems in a given turn volume, more chokers must be set per turn, and additional loggers may be required to hook-up turns. Care to prevent breakage would also have to be exercised in loading and unloading logs onto and off trucks (Mcintosh, 1968). Loading costs may be increased as a result of having to handle smaller pieces. Landing construction costs may be increased because larger landings would be required to accommodate a greater number 0 f pieces per unit volume and more debris. Scaling costs would also be expected to be higher due to the large number of pieces handled per unit volume. However, 138 weight scaling, being introduced into - the inter ior at that time, was expected to help to reduce scaling costs (Smith, 1968). Trucking costs would be expected to increase as a result of the d i f f i cu l t y of building loads from smaller pieces. If loading time per load increased, the volume which could be hauled by each truck per day would be decreased. This could be compensated for by building improved logging roads, the cost of which may be just i f ied by faster hauling and by the larger volume per acre harvested. If better grades of roads are not b u i l t , the increased t ra f f i c per acre logged would result in higher maintenance costs. From this brief examination, i t can be concluded that, in the short-run, logging costs and labour requirements per C cf would increase. Smith (1968) estimated that logging costs in smallwood stands are about 30% higher than in good quality saw-log stands. , In order to reduce costs in the long-run, work habits of existing logging crews and equipment would have to be modified (Mcintosh, 1968). Equipment used to harvest Douglas-fir sawlog stands is not suitable for lodgepole stands which generally consist of much smaller stems. The ab i l i t y of any logging firm to adjust, fu l l y to logging smaller trees depends'on the size of i t s operation and diversity of timber types and terrain i t is working i n . Several types of information are required to make a reasonable estimate of the impact of close ut i l i zat ion on logging employment in the long-run. F i r s t l y , a survey of timber types and logging conditions, similar to the land c lassi f icat ion scheme which was developed for the University of B.C. Research Forest at Haney, Br i t ish Columbia by Lacate (1968), should be conducted for the region. 139 Secondly, a study of the su i tab i l i t y of various types of production unit and techniques in different categories of logging conditions should be determined as suggested by Mcintosh and Csizmazia (1965). Thirdly, the structure and behavior of the logging industry should be studied. These three types of information would enable forest policy makers to forecast the logging industry's response to changing timber supplies better than extrapolation of apparent average produc-t i v i t y trends based on aggregate employment and production s ta t i s t i cs . Some information sources which are already available to the B.C. Forest Service included TFL and PSYU working plans, and stumpage appraisals. Lacking this information for use in this study, i t was only possible to estimate the rate of increase in logging productivity from trends and surmise which technological changes would be adopted by 1971. It was reasonable to expect that the trend in productivity from 1962 to 1965 would be reversed between 1966 and 1971. Crawler tractors could be expected to be replaced by wheeled skidders in almost a l l logging firms after 1965. If wheeled skidders were used to skid '80% of the timber harvested in 1971 and i f the results of the study by Mcintosh and Csizmazia (1965) were valid for other timber types and terrain, then skidding productivity would increase by about 80% x 45% or 36%. Since skidding accounts for about 60% of man-hours paid in conventional logging, adoption of wheeled skidders would increase productivity by about 22%. Felling productivity could be expected to decline in stands where hydraulic shears and pulpwood harvesting equipment could not be used. Additional productivity 140 improvements in fe l l ing w i l l probably not be achieved for quite some time in the region. Most of the terrain is too rugged for the eff ic ient use of tree shears and processors. Presently, tree shears have been used to a small degree in the Kamloops Forest Distr ict in some Douglar-f i r and lodgepole pine stands in PSYU's with even terrain such as the Nehalliston (Neighbour, interview, 1973). Productivity in f e l l i n g , limbing and topping in the smallwood portions, which average 39% by volume, would decrease by about one-half and in the entire stand by 39% x 50% or 20%. Since fe l l ing accounts for about 40% of the man-hours paid in conventional legging, the decline in logging productivity could amount to about 40% x 20% or 8%. Therefore, by 1971 total logging productivity could increase by 22% - 8% or 14% i f only wheeled skidders are adopted. Further increases in productivity required to compensate for extra care to prevent breakage during skidding and loading could be achieved by training machine operators to adapt to new conditions. Changing from the B.C. Cubic to the B.C. Firmwood Scale would increase the numerical value of average productivity. The effect of changing over to the Firmwood Scale has been studied for four inter ior species (Table 19). However, these data are not suff ic ient to determine the effect of changing scaling rules on apparent logging productivity in the region. If the volume of the annual harvest increased by 25% by changing to the Firmwood Scale, the estimated average productivity would be 79.13 M cf per man-year in 1971. The actual productivity in the Kamloops Forest Distr ict was apparently 82.88 M cf per man-year in 1971 (Table 18). 141 TABLE 19. Comparison of log scales. Fi rmwood cubic seale Species No. of Logs scaled Lumber cubic scale (%) Douglas-fir 1 2,010 108 Spruce* 780 104 3 Hemlock 417 159 Cedar3 262 152 1. Source: Gunn, e_t al_. (1966). 2. Source: Mcintosh (1968). 3. Source: Dobie, et al_. (1970). 142 In the absence of the close u t i l i z a t i o n , only very small volumes of smallwood would be logged. Fel l ing productivity would not decline and i t is possible that about 80% of the skidding would be conducted with wheeled skidders. Under these assumptions, logging productivity in the study region would be 67.79 M cf per man-year in 1971. I f , as was estimated, average productivity in 1971 was 68 M cf per man-year without the close ut i l i zat ion pol icy, then logging employment would be 1,203 and 1,362 persons, respectively. Since, the reported average productivity in 1965 was 55.65 M cf per man-year, there were 1,281 persons employed in harvesting timber from Timber Sales and TFL's that year. Reported logging employment within the study region on a l l forms of forest tenure declined from 1,958 persons in 1965 to 1,825 persons in 1971. 2. Sawmilling (a) Economies of Scale in Sawmilling During 1960 to 1965, productivity in sawmills in the inter ior of Br i t ish Columbia increased at a compound rate of 1.9% per year (Figure 10). Productivity increased from 0.212 to 0.255 MM fbm per man-year during 1960 to 1965 and from 0.269 to 0.293 MM fbm per man-year during 1966 to 1970 (Table 20). Productivity was improved by substituting capital for some labour. As a result , the proportion of fixed costs increased to the extent that by 1968, given the prevailing product prices and factor costs, sawmills with capacities less than 40 M fbm per 8-hour shi f t became uneconomical to operate (Dobie, 1971). TABLE 20. Sawmilling productivity in the Interior of Brit ish Columbia, 1960-1970 . Total Employees Lumber Production Productivity Year (No. of persons) (MM fbm) MM fbm/man-yr Man-yrs/MM fbm 1960 11,559 2,455 0.212 4,708 1961 11,399 2,664 0.234 4,279 1962 12,032 2,984 0.248 4,032 1963 13,167 3,338 0.254 3,945 1964 14,793 3,603 0.244 4,106 1965 14,918 3,800 0.255 3,926 1966 13,535 3,639 0.269 3,719 1967 11,549 3,196 0.277 3,614 1968 11,736 3,667 0.312 3,200 1969 13,253 3,785 0.286 3,501 1970 13,545 3,973 0.293 3,409 1. Source: Stat is t ics Canada, Sawmills and Planing M i l l s , Cat. No. 35-204, 1960-1970. FIGURE 10. Sawmilling productivity in the Interior of Brit ish Columbia, 1960-1965 (Source: Table 20). 145 Using the survivor technique, Dobie (1971) found that, from 1955 to 1968, there was an increase in the number of sawmills with a capacity greater than 40 M fbm per 8-hour sh i f t in the interior of Br i t ish Columbia. The survivor technique is a method of determining whether there are economies of scale in industries by testing whether there is a s ta t i s t i ca l l y signif icant difference between the distribution of plant sizes at two points in time. These results were verif ied by constructing cost curves using the results of sawmill productivity research and published cost information. Increasing returns to scale, or economies of scale, occur when, in the long-run, doubling output does not require doubling every input, given the state of technology and a certain production process. The generally accepted shape of the long-run average cost (LRAC) curve is convex to the scale axis of \"U\"-shaped (Figure 11). The causes for the increasing returns or negatively sloping portion of the LRAC curve are as follows (Dobie, 1971; St ig ler , 1966): 1. division and specialization of labour and equipment as plant size increases, 2. improved harmonization of specialized equipment as plant size increases, 3. cost of purchase and instal lat ion of machinery increases less in proportion to the increase in machine capacity, 4. economies associated with large-scale purchases of inputs, . __\u00E2\u0080\u0094 _ _ _ _ _ _ \u00E2\u0080\u0094 , f Output FIGURE 1 1 . Traditional Long-run average cost curve. 147 5. qualitative as well as quantitative improvement in out-put as plant size increases, and 6. lower administrative costs per unit of output as scale increases. The most frequently given explanation for the increasing portion of the LRAC curve is that after a certain s ize , the plant or firm becomes unwieldly to manage (St igler , 1966). However, there is evidence that the size of plant for which decreasing returns occur have not been achieved yet in sawmilling in Br i t ish Columbia (Dobie, 1971; 1973). Therefore, the LRAC curve for sawmilling appears to be L-shaped (Figure 12). The LRAC curve is an envelope of short-run average cost (SRAC) curves for a given type of sawmill of different capacities (Figure 13). Capacity may be defined in a physical sense as \" . . . the maximum attainable output per period of time given the log input, the technical process, and the product.\" (Dobie, 1971, p. 82). Stigler (1966, p. 157) defined capacity as \" . . . the out-put at which short-run and long-run marginal costs are equal,\" which corresponds to the scale at which the SRAC curve is tangent to the LRAC, However, the economic capacity definition is more d i f f i c u l t to apply empirically than physical capacity. The shapes of the constructed SRAC curves indicate that the two definitions of capacity probably coincide in larger sawmills. These cost curves were also used to make sawmill employment projections for the study region. Output FIGURE 12. \"L\"-shaped Long-run average cost curve. Output FIGURE 13. Short-run average cost curves for different scales of plant and long-run average cost curve. 150 In order to ensure that valid cost comparisons would be made between different sizes of sawmills, Dobie (1971) divided his study sawmills into three groups on the basis of log input (Table 21). TABLE 21. Study sawmills used by Dobie (1971). Sawmill Sawmill Type Log Diameter Limits Log Length Limits Group (inches) (feet) I coastal sawmills 10-24 10-24 II inter ior sawmills 6-23 12-20 III small log sawmills 4-12 12-20 The coastal group included c i rcular , band and log gang sawmills which processed hemlock. The inter ior group included only circular saw-mil ls which processed Douglas-fir. The small log group included scrag and chipper headrig sawmills which processed a mixture of white spruce (Picea glauca (Moench) Voxx.), lodgepole pine (Pinus contorta Dougl. var. l a t i f o l i a Engelm. and alpine f i r (Abies lasiocarpa (Hook.) Nutt.) . Most of the sawmills were completely se l f -contained, produced chips and rough, green lumber and were independently operated (Dobie, 1973, interview). A l l of the inter ior and small log sawmills, except for two, were located in the southern inter ior of Br i t ish Columbia. For each of the study sawmills, Dobie (1971) calculated lumber productivity, in M fbm per hour, using regression equations 151 of sawmill productivity on log size and the size distribution of specific log inputs. The log inputs of each sawmill group con-sisted of the total logs processed in the sawmills during the research into the effect of log size on sawmill productivity. Then, using published costs of productive factors, the average costs of operating each sawmill for one, two and three shifts for 240 days per year were determined. F inal ly , the average costs of each sawmill were plotted over yearly production and retabulated by 5 MM fbm per year production classes (Tables 22 and 23). Data for coastal sawmills were not reproduced because the present study deals with an interior region. Cost curves for study sawmills 18, 19 and 20 i l lus t rate that SRAC of each sawmill declines rapidly as yearly production increases up to a certain point (Figure 14). After this scale of output, i t is probable that no further production can be coaxed from the sawmill without incurring extremely high unit costs. Therefore, according to the physical def in i t ion, capacity of the sawmill is the output at which SRAC is minimum. I t . i s d i f f i c u l t to determine the exact tangency points between the SRAC curves and the LRAC curve. Since the LRAC for sawmills appears to be L-shaped, economic capacity w i l l approach physical capacity at LRAC becomes constant. The declining positions of the SRAC curves tend to support the results of the survivor analysis that there are increasing returns to scale in sawmilling. There is also some evidence that there are separate economies of scale in labour, power, management and plant (Dobie, 1971). As capacity increases, the number of TABLE 22. Manufacturing costs per M fbm of lumber for circular saw sawmills . Annual Study Mi l l Number' Production \u00E2\u0080\u00A2 ($ M/fbm) MM fbm 1 22 30 31 32 10 43 39 39 40 39 15 34 30 31 30 30 20 28 26 27 26 27 25 25 24 25 24 24 30 23 22 35 21 40 20 45 19 1. Source: Dobie (1971) pp. 77-102. 2. Study mil l numbers refer to sawmills studies by Dobie, op. c i t . . TABLE 23. Manufacturing costs per M fbm of lumber for small log sawmills . Annual Production Study Sawmill Number ($ per M fbm) 2 MM fbm 16 18 19 21 23 24 17 20 25 10 36 36 61 37 38 66 40 40 37 20 25 25 34 28 27 39 27 28 27 30 20 25 22 21 27 22 21 21 40 21 18 17 22 18 18 50 18 16 19 16 16 60 15 17 14 70 13 15 80 12 14 90 11 13 100 12 1. Source: Dobie, 0p_. C i t . , P. 107. 2. Mil ls no. 17, 20, and 25 are scrag mi l l s , the rest are chipper headrig sawmills. 154 6 Q R 10 h O I i I i I i 0 20 40 60 80 too Prodwcvtioin. per Year (MM fbm) FIGURE 14. Production cost related to sawmill capacity for three small log sawmills (After Dobie, op_. c i t . ) . 155 man-hours per unit of output decreases (Table 24). Average cost w i l l decrease as the size of plant increases only i f the mi l l is operated at capacity. For example, the average cost of operating study mil l number 18 at capacity is less than producing the same level of output in mil l number 19 which has a larger capacity (Figure 14). A rational sawmill investment decision maker must take into account the costs of processing the volume and size distribution of his timber supply in various available sizes and types of sawmills. Many small sawmill firms were forced to exit from the industry primarily because they had insuff icient timber supplies to just i fy expansions to achieve economies of scale which were required to remain competitive. The number of sawmills in Brit ish Columbia during 1955 to 1965 decreased from 2,489 to 1,191. During the same period, total capacity in Brit ish Columbia decreased from 28,016 to 26.729 M fbm per 8-hour sh i f t . Concurrently, lumber production continued to increase (Table 25). These trends indicate that capacity was being concentrated into fewer mil ls and more fu l l y u t i l i zed . Many larger firms acquired smaller firms while other firms merged to increase their timber supplies to just i fy sawmill expansions (Wood, 1970). (b) Effects of the Close Ut i l izat ion Policy on Sawmilling Productivity The close ut i l i zat ion policy was expected to accelerate the trend toward fewer and larger sawmills operating near capacity. TABLE 24. Number of employees per establishment in sawmills-,and planing mills in British Columbia, 1967 and 1968 . Shipments per Establishment Production and Related Workers Administrati on Office and Sales Workers per MM fbm Value of Shipments ($) MM fbm 1967 1968 1967 1968 100,000- 199,999 1.25- 2.50 7.36-3.68 7.40-3.70 1.06-0.53 1.15-0.58 200,000- 499,999 2.50- 6.25 6.78-2.71 7.10-2.84 0.86-0.34 0.98-0.39 500,000- 999,999 6.25-12.50 4.80-2.40 4.46-2.23 0.57-0.28 0.54-0.27 1,000,000-4,999,999 12.50-62.50 6.36-1.27 5.55-1.11 0.77-0.15 0.65-0.13 5,000,000- 62.50- 5.96- 4.86- 0.61- 0.52-1. Source: Statistics Canada, Unpublished Data, Forestry Statistics Section, Ottawa, Ontario. TABLE 25. Operating sawmill and lumber production in Brit ish Columbia, 1955-1971 . Estimated 8-Hour Lumber Daily Capacity Production Year Number : (M fbm) (MM fbm) 1955 2,489 28,016 4,914 1956 2,435 29,080 4,735 1957 2,255 26,752 4,412 1958 2,010 27,694 4,850 1959 2,005 28,280 4,949 1960 1,938 29,432 5,305 1961 1,778 29,025 5,620 1962 1,627 28,234 6,004 1963 1,541 29,339 6,734 1964 1,417 28,865 7,095 1965 1,191 27,641 7,449 1966 1,116 26,729 7,319 1967 931 22,757 7,110 1968 902 22,822 7,811 1969 974 23,432 7,696 1970 881 23,670 7,764 1971 627 24,315 8,970 1. Source: Stat ist ics Canada, Sawmills and Planing M i l l s , Cat. No, 35-204, 1955-1971. CO 159 Since the feed rate in conventional sawmills for small logs is much ; slower than for larger logs (Dobie, 1971, 1968, 1967; Dobie et a l . , 1967), i t was expected that many firms would insta l l small log sawmills to process the increased volume of smallwood economically. Only firms which had adequate smallwood supplies to just i fy investing in a small log sawmill of economical size were expected to remain in the industry (Wil l iston, 1966c). Without the close ut i l i zat ion policy, i t is conceivable that only a few firms which held quotas in PSYU's containing a large proportion of lodgepole pine, such as the Nehalliston, would insta l l small log sawmills. In 1965, B.C. Interior Sawmill Ltd. had a Chip'n Saw headrig sawmill with a daily capacity of 40 M fbm.. It could be expected that i f the price of chips was adequate, firms located within PHA No. 2 which have suff icient sawmill capacity would insta l l barkers and chippers to supply the existing pulpmill with an adequate chip supply. It has been found that sawmills must have a daily capacity of over 30 M fbm to just i fy the instal lat ion of barking and chipping equipment (Smith, 1968). Assuming a lumber recovery factor of 7.5 board feet per cubic foot of log input, lumber production in.1971 would be 653.789 MM fbm or 148.575 MM fbm, more than in 1965. It was assumed that a l l the timber 4n the present analysis consist of sawlogs. Therefore, a larger lumber recovery factor is used in this analysis than in Chapter III . If productivity of labour in sawmilling continued to increase at 1.9% per year, (Figure 10), productivity in 1971 would be 0.285 MM fbm per man-year. As a result , sawmilling employment in 1971 would be 2,295 persons, 160 or 314 persons more than in 1965. The change in employment from 1965 to 1971 under the close, ut i l i zat ion policy was estimated empirically as well as by extrapolating productivity trends, because i t was expected that the policy would cause the trend toward larger capacity and small log sawmills to accelerate. The change in employment was determined empirically by 1. predicting the structure of the industry in 1971, 2. estimating the productivity of the restructured industry, and 3. determining the change in employment caused by the change in productivity. The change in industry structure was estimated on the basis of investment decisions facing the original firms of 1965. It was assumed that firms wi l l insta l l small log sawmills with barking and chipping equipment i f the increase in revenue was greater than their increased sawmilling costs. Al l firms which could not afford to insta l l a small log sawmill would either (1) saw their additional smallwood portions in conventional sawmills and insta l l barking and chipping equipment, or (2) exit from the industry i f they could not afford to insta l l barking and chipping equipment. (i) Lumber Production The potential change in annual lumber production was determined by using average lumber recovery factors for sawlogs and 161 smallwood. The lumber recovery factor in circular sawmills increases as log diameter increases, while i t is almost constant for a l l diameters in scrag and chipper-headrig sawmills (Dobie, 1971). Lumber recovery also varies among sawmills and with log quality. Since the Firmwood Cubic Scale does not allow deductions for lumber defects, the lumber recovery in 1971 for a given log input and sawmill was less in 1971 than in 1965. Lumber recovery factors were assumed to be 5.5 and 7.0 board feet per cubic foot of log input for smallwood and sawlog volumes respectively (Dobie, interview, 1972). Lumber recovery was reduced more for smallwood than for sawlogs because the smallwood volume, as i t was defined in this study, includes a larger proportion of wood which is unsuitable for sawing into lumber than the sawlog volume. Lumber production decreased by 91.8 MM fbm from sawlogs and increased by 201.1 MM fbm from smallwood (Appendix II I) . ( i i ) Average Revenue from Mil l ing Smallwood The price of the numerous species, grades and sizes of lumber varies widely. Rather than calculate an average lumber price from price l i s t s , or use the average price of an \"indicator\" lumber species, such as spruce in the inter ior , an average lumber value for 1965 was determined by dividing the value of Br i t ish Columbia lumber exports by the quantity exported (Dept. of Industrial Development, Trade, and Commerce, 1972c). This average value, $72 per M fbm, excludes insurance and freight charges. 162 Although this value is not comparable to the sel l ing price, i t probably approximates the average revenue realized by sawmilling f i rms. The price for chips received by sawmill operators in the Kamloops region in 1966 varied from $9.50 to $10.00 per oven dry unit, including freight charges (Christ ie, 1967). An interior oven dry unit is equal to the quantity of chips which weighs 2,400 pounds when a l l the moisture has been removed. Smith (1968) reported that a cost and profit study, conducted by Price Waterhouse and Co, for the Northern Interior Lumberman's Association (NILA), revealed that, in 1966, net chip revenue of 13 NILA mil ls from 165,000 oven dry units of chips was $8,70 per unit. . It was assumed that $8.70 per unit was also realized by sawmill operators in the Kamloops region. The average recoveries of chips per M fbm of lumber output in scrag and chipper headrig sawmills are 0.52 and 0.66 cubic feet sol id wood equivalent respectively (Dobie and Wright, 1972). In the inter ior , the average sol id wood equivalent of one oven dry unit of chips is about 100 cubic feet for a l l species (Dobie, et al_., 1970). Average revenue of chips per M fbm of lumber from scrag and chipper headrig sawmills was $4.52 and $5.74 respectively. Total average revenue of lumber and chips per M fbm for scrag and chipper headrig sawmills was $76.52 and $77.74 respectively. Assuming that logging costs are $20 per C cf , the average wood cost was $42.96 per M fbm which leaves an average revenue from processing smallwood of about $34 per M fbm. 163 ( i i i ) Additional Costs of Processing Smallwood Cost increases of firms which instal led small log sawmills possibly included, besides instal l ing and operating the new m i l l , additional management personnel, log yard space, planer and dry k i ln f a c i l i t i e s and the loss of lumber production from sawlog volumes. The loss of production of sawlog volumes may make expansion of the other cost items unnecessary. Lacking more complete cost data, only the added cost of the small log sawmill was estimated using the cost curves constructed by Dobie (1971). Potential lumber production from smallwood for individual firms ranged from 0.01 to 16.1 M fbm. Study mil l number 18, which has a daily capacity of 35 M fbm, provided the lowest average cost throughout this range of annual output. The annual output required to break even with this sawmill is about 10 MM fbm. Additional costs of firms which could not afford to insta l l a small log sawmill resulted mainly from processing small logs in their conventional sawmills. Although their increased cost could be estimated by using the results of productivity research, this was not done for this study. Instead i t was assumed that firms with sawmills having a daily capacity of over 30 M fbm and which could not afford to ins ta l l a small log sawmill could afford to process smallwood in their conventional sawmills and insta l l barking and chipping equipment. 164 (iv) Sawmill Industry Structure in 1971 The daily capacities of sawmills of firms which could insta l l small log sawmills were increased by 35 M fbm. The daily capacities of those firms which could only afford barking and chipping equipment were le f t unchanged from their levels in 1965. Firms which could not afford either of these investment alternatives were deleted from the industry. As a result , the number of sawmills in the region declined from 49 in 1965 to 23 in 1971, primarily because a l l firms with sawmill capacities less than 21 M fbm exited from the industry (Table 26). Concurrently, average daily capacity increased from 43 to 88 M fbm. Such a drastic change would be moderated i f the smaller firms which could not afford to operate to close ut i l i zat ion standard had been able to find alternative timber supplies. In 1971, there were actually 20 sawmills in the study region with daily capacities over 21 M fbm and 21 sawmills with daily capacities less than 21 M fbm (Table 26). Average daily capacity was 55 M fbm. A majority of the small sawmill firms held very small quotas in 1971, such that they either operated intermittently or had other sources of timber. Therefore, i f average capacity in 1971 had been weighted by annual lumber production instead of number of sawmills, i ts value would probably be closer to 88 rather than 55 M fbm per 8-hour sh i f t . TABLE 26. Distribution of sawmills in the study region of firms with quotas and Tree Farm Licences. 1965' 19712 1971 Estimated Sawmill No. of Cum. No. of Cum, No. of Cum. 8-hour Mi l ls d i s t r ib . Mil ls d is t r ib . Mil ls d is t r ib . Capaci ty (M fbm) 5 - 10 6 0.123 10 0.245 0 0.000 11 - 20 15 0.430 11 0.514 0 0*000 21 - 30 5 0.532 0 0.514 1 0.043 31 - 40 4 0.614 1 0.538 4 0.218 41 - 50 4 0.696 3 0.611 3 0.348 51 - 60 3 0.757 1 0.635 1 0.391 61 - . 70 3 0.818 4 0.733 3 0.521 71 - 80 3 0.879 1 0.757 2 . 0.608 81 - 90 ^ 1 0.899 0 0.757 0 0.608 91 - 100 0 0.899 1 0.781 2 0.695 101 no 0 0.899 1 0.805 0 0.695 m - 120 121 - 130 131 - 140 141 - 150 151 + 1 2 1 0 1 0.919 0.960 0.980 0.980 1.000 0 0 1 2 5 0.805 0.805 0.829 0.878 1.000 2 1 0 0 4 0.782 0.825 0.825 0.825 1.000 Totals 49 41 23 1. Source: Table 5 2. Source: Table 8 167 (v) Sawmilling Employment in 1971 The number of persons employed per establishment by sawmill size was determined using production and employment data for the circular sawmills and mil l number 18 studied by Dobie (1971) and five other sawmills obtained from an unpublished Stat ist ics Canada (1968) study (Table 27). Employment data for Dobie's study sawmills only included mil l f loor workers. Therefore, the number of planer m i l l , dry k i l n , log yard, lumber yard and administrative employees remained to be estimated. In 1965, 1,237 of 5,093 persons, or 24%, employed in sawmills and planing mills in the Kamloops Forest Dist r ic t were employed in planing mil ls (Kamloops Forest Distr ict Annual Report, 1965). The proportion of production workers, other than those on the mil l f loor , is probably closer to 30%. Eleven percent of the total employees in the five sawmills included the Stat ist ics Canada study were in administrative, office and sales positions. It was assumed that these proportions'were similar in a l l sawmills with dai ly : capacities of over 21 M fbm. The number of man-years employed per MM fbm of annual lumber production was plotted over sawmill scale in MM fbm so that the employment could be determined for any sawmill size (Figure 15). Ideally, regional sawmilling employment would be calculated by summing employment in each of the sawmills which were expected to be active in 1971. However, the range of the available data was too small to extrapolate to other sawmill sizes. Furthermore, there was no way to predict mergers and acquisitions which would occur during 1966 to 1971. Therefore, an aggregate TABLE 27, Employment by sawmill s ize . Study Daily Yearly M i l l Floor Other Administrative Total Man-Years Sawmill Capacity Production Employees Production Employees Employees per No. (M fbm) (MM fbm) Employees MM fbm 22 1 37.6. 27 42 18 7 67 2.48 30 1 39.2 28 45 19 8 72 2.57 32 1 41.6 29 45 19 8 72 2.48 31 1 48.0 34 45 19 8 72 2.12 1 1 65.6 47 54 23 8 85 1.81 i t . Can. 55 39.5 9 90 2.28 18 1 35.2 25 36 15 6 57 1.58 Source: Dobie, op_. c i t . , Page 88. -2. Source: Stat ist ics Canada, Unpublished data, Forestry Statist ics Section, Ottawa, 1968. for f ive Br i t ish Columbia interior conventional sawmills. 169 3.00 r 2.501 2.00L 150 -1-00 -50 -O J 1 1 1 1 L_ SO 30 40 50 60 Yearly Lumber Production C MM ?bm) FIGURE 15. Labour requirements by sawmill scale (Source: Table 170 approach had to be followed. It was estimated that, in 1971, of 201.1 MM fbm of lumber sawn from smallwood volumes, 55.6 MM fbm would be produced by conventional sawmills, 103.1 MM fbm would be produced in small log sawmills and 42.4 MM fbm would be produced in sawmills owned by firms which acquired the quotas of firms which were predicted to exit from the industry. It was assumed that the firms with small log sawmills would acquire the quotas of firms which had le f t the industry. The average daily capacity of conventional sawmills which processed smallwood was 53 M fbm and required 2.15 man-years to produce one MM fbm of lumber. A l l small log sawmills were assumed to have an average daily capacity of 35 M fbm which required 1.58 man-years per MM fbm of lumber produced. The average daily capacity of sawmills processing sawlog volumes was 76 M fbm which required 1.76 man-years per MM fbm of lumber produced. Using these employment per MM.fbm rat ios , i t was estimated that, under the close ut i l i zat ion policy, sawmilling employment in 1971 amounted to 1,038 persons (Table 28). This was 943 persons less than in 1965 and 1,257 less than in 1971 without the policy. If productivity of labour in sawmilling increased annually at a compound rate of 1.9% (Figure 10), productivity in 1971 would be 0.285 MM fbm per man-year. As a result , sawmilling employment in 1971 under the close ut i l i zat ion policy would be 2,038 persons. This was 57 persons more than in 1965 and 257 persons less than estimated in 1971 without the policy. Actual sawmill employment in the study region, reported in TABLE 28. Employment in sawmilling in 1971. Sawmill Type Conventional Sawmi11 Small Log Sawmill Sawlogs Lumber Production (MM fbm) z Average Sawmill Daily Capacity (M fbm per 8-hours) 3 Man-Years Per MM fbm Employment (No. of Persons) 379.8 76 1.76 688 Log Input 1 Smallwood Smallwood 55.6 53 2.15 120 145.5 35 1.58 230 Totals 580.9 88 1.79 1,038 1. Firms l is ted in Appendix III with less than 10 MM fbm lumber production from smallwood are assumed to saw smallwood in conventional sawmills. 2. L.R.F. for sawlogs is 7.0; for smallwood, 5.5. 3. Source: Table 27 and Figure 15. 172 the Kamloops Forest Dist r ic t Management Annual Reports of 1965 and 1971, increased from 2,356 persons in 1965 to 2,603 persons in 1971, or by 10%. The estimated and actual changes in employment are not s t r i c t l y comparable because the actual data include employment in sawmills which was accounted for by timber inputs logged on tenures besides TFL's and (quota) Timber Sales. Regional Employment in 1971 Under the close ut i l i zat ion policy, i t was estimated, using 1965 data, that there were 154 more logging jobs and 257 to 1,257 less sawmilling jobs in 1971 in the study region than there might have been without the policy. The proportion of jobs in logging and sawmilling which was basic was 49% and 88% respectively such that the net decrease in basic employment was 182 to 1,182 jobs. The value of the employment mult ipl ier (3.05) was judged to be an over estimate for the study region in 1966. It is l ike ly that the value of the multipl ier would s t i l l be less than three in 1971. Therefore, i t is only possible to state that, using the empirical estimate, under the close ut i l i zat ion policy, there were between 1,182 and 3,546 fewer jobs in the study region in 1971 than there might have been i f the policy had not been implemented. Using the extrapolated sawmill employment estimate, under the close ut i l i zat ion policy, there were between 182 and 546 fewer jobs in the study region in 1971 than there might have been i f the policy had not been implemented. In 1971, there were an estimated 29,274 persons employed 173 within the Kamloops Manpower Centre Area (Roussel, interview, 1973). This area is equivalent to the study region without the Shuswap Lake-Salmon Arm Area of Region Six. Therefore, without the close ut i l i zat ion policy there might have been approximately between 4% and 12% more persons employed in the study region in 1971, using the empirical sawmill analysis, and between 0.6% and 1.8% more persons using the extrapolated sawmill analysis Effect of the Close Ut i l i zat ion Policy on the Level of Employment in 1980 Timber Supply In the absence of the close ut i l i zat ion policy, annual harvests from Timber Sales and TFL's were assumed to continue to increase at a compount rate of 4.4% during 1965 to 1980 such that the 1980 timber supplies would be 128,436 M cf for sawmilling and 136,024 M cf for logging. These volumes are both less than the allowable annual cuts, calculated to close tu i l i zat ion standards, of PSYU's and TFL's in the study region, but indicate that more smallwood must be logged in the future than in 1971. If i t is assumed that smallwood w i l l be sawn in small log sawmills and sawlogs in conventional sawmills which have average lumber recovery factors of 6.6 and 7.5 board feet per cubic foot of log input respectively, and that 25% of the annual harvest would be smallwood, then, regional lumber production in 1980 would be 800.2 MM fbm. The close ut i l i zat ion policy requires- that, after 1971, a l l trees must be logged to a 4-inch diameter top and a l l logging waste 174 w i l l be charged against allowable annual cuts. Further increases in annual harvests w i l l depend upon when trees less than 7-inches dbh can be logged economically. In the study region, where fu l l mechanization of logging is unlikely to take place by 1980, logging costs for these smaller trees can be expected to be mich higher than for trees 7.1 inches dbh and over. Therefore, unless lumber prices increase suff ic ient ly to just i fy logging these smaller trees, the volume of trees under 7.1-inches dbh which are harvested w i l l depend on the wood requirements of the Kamloops pulp m i l l . The allowable annual cut of PHA No. 2, calculated to close ut i l i zat ion standards with a 6-inch diameter top, is 150,585 M cf per year. If 39% of the allowable annual cut were processed in small-log sawmills with an average chip y ie ld of 35%, and i f 61% of the allowable annual cut were processed in conventional sawmills with an average chip y ie ld of 30%, the maximum annual y ie ld of chips from PHA No. 2 would be 48,311 M cf. Assuming that 190 cubic feet of green wood are required to produce one short ton of air -dry screened and bleached kraft pulp (Dobie and Wright, 1972), the potential y ie ld of chips from sawmills operating to close ut i l i zat ion stands in PHA No, 2 is suff ic ient to produce 300,907 short tons of a i r -dry , screened and bleached kraft pulp per year. Additional chips could be purchased from sawmill firms which process timber from neighbouring PSYU's and TFL's or chips could be produced from pulpwood. It can be concluded that, although i t w i l l be unnecessary to log less than 7.1-inch dbh trees, a l l operators within PHA No. 2 and others within chip hauling distance of the pulp mil l must operate 175 to close ut i l i zat ion standards in order to keep the Kamloops pulp mil l operating at fu l l capacity. Therefore, i t was assumed that, in 1980, the entire allowable annual cut of the study region w i l l be logged to close u t i l i za t ion . The same conclusion was reached by the B.C. Forest Service. In 1971, i t became mandatory for a l l firms in PHA No. 2 to operate to close ut i l i zat ion standards in order to assure that the Kamloops pulp mil l would have a suff ic ient chip supply. The awarding of TSHL's and third-band wood were also measures toward this end. The volume of timber supplies in the region in 1980 for logging w i l l be 180,034 M cf , after deducting the Forest Service Reserve. If 90% of the allowable annual cut of PSYU's in the region w i l l be processed in sawmills located in the study region, the volume of timber available, in 1980, for sawmilling w i l l be 166,018 M cf . If a l l of the smallwood volume is processed in small log sawmills and a l l of the sawlog volume, in conventional sawmills, and i f small log and conventional sawmills have lumber recovery factors of 5.5 and 7.0 board feet pet cubic foot of log input, lumber production from timber harvested from regional PSYU's and TFL's w i l l be 899.0 MM fbm. Logging Productivity in logging is not l ike ly to increase s i g n i f i -cantly beyond the levels which were estimated for 1971 because mechanization beyond the use of wheeled skidders does not appear 176 feasible in the region and timber quality w i l l continue to decline. Therefore, i t was assumed that improvements in logging technology which are suitable for adoption in the region wi l l be suff ic ient to maintain productivity at 80 and 68 M cf per man-year with and without the close ut i l i zat ion policy respectively, until 1980. Under these assumptions, logging employment in 1980 wi l l be 2,250 and 2,000 persons with and without the close ut i l i zat ion policy respectively. Actual employment and log production data indicate that, in 1971, average productivity in logging in the Kamloops Forest Distr ict was 82.88 M cf per man-year. If the volume of the annual harvest increased by 25% by changing to the Firmwood Cubic Scale, average productivity without the close ut i l i zat ion policy would be 62 M cf per man-year in 1971. If i t is also assumed that productivity wi l l remain relatively constant unti l 1980, logging employment wi l l be 2,172 and 2,194 persons with and without the close ut i l i zat ion policy. Therefore, according to actual 1971 employment and log production data, implementing the close ut i l i zat ion policy in 1966 may have l i t t l e impact on logging employment by 1980. According to 1965 information, there w i l l be 250 more logging jobs in 1980 than there would be i f the policy had not been implemented. Sawmilling Productivity can be expected to increase as older sawmills are replaced by larger, automated sawmills with faster feed-rates. Most of the new sawmills in the interior are expected to have capacities 177 of between 100 and 200 M fbm per 8-hour sh i f t (Dobie, 1973). If , in the absence of the close ut i l i zat ion policy, productivity continued to increase from i ts 1965 level of 0.225 MM fbm per men-year at 1.9% per year, average productivity would be 0.338 MM fbm per man-year and there would be 2,367 persons employed in sawmilling in the region in 1980. Under the close ut i l i zat ion policy, average productivity in sawmilling in 1971 was estimated empirically to be 0.560 MM fbm per man-year. If productivity increases from its estimated 1971 level at 1.9% per year, average productivity would be 0.663 MM fbm per man-year and there would be 1,356 persons employed in sawmilling in the region in 1980. Based on the empirical estimate, there w i l l be 1,011 fewer sawmilling jobs in the study region in 1980 as a result of implementing the close ut i l i zat ion policy in 1966. If , under the close ut i l i zat ion policy productivity is extrapolated from its 1965 level to 1980 of 1.9% per year, productivity would be 0.338 MM fbm per man-year and there would be 2,660 persons employed in sawmilling in the region in 1980. This estimate suggests that there w i l l be 293 mere sawmilling jobs in the study region in 1980 as a result of implementing the close ut i l i zat ion policy. Actual sawmilling production and employment data for the interior of Br i t ish Columbia indicate that'productivity increased from 0.255 to only 0.293 MM fbm per man-year during 1965 to 1970 (Statist ics Canada, Cat. No. 35-204). This trend implies that more small sawmills remained in the industry than was estimated. There are several reasons for th is . F i r s t l y , up to 1971, the close ut i l i zat ion 178 policy was implemented on a voluntary basis. Therefore, many smaller sawmilling firms continued to operate to intermediate ut i l i zat ion standards. Secondly, several new sawmills which would replace smaller plants were s t i l l under construction or in the planning stage. For example, construction of Weyerhaeuser Canada Ltd. 's new 200 M fbm per 8-hours capacity sawmill at Vavenby had just begun in 1970. This mil l replaced the company's two older 65 M fbm per 8-hour capacity sawmills at Blue River and Avola. Thirdly, the price of lumber increased to an unprecedented high level in 1969 and induced many marginal sawmills to re-enter the market. Unless current lumber prices are high enough to allow small sawmill firms to insta l l chippers and barkers, these firms w i l l probably be prevented by economies of scale barriers from entering the market again. After 1965, the number of sawmills in Br i t ish Columbia declined steadily from 1,116 to 902 in 1968 (Table 25). In 1969, the number of sawmills increased to 974, after which i t declined steadily again. These short-run fluctuations make i t impossible to establish a rel iable average productivity trend. However, i t is unlikely that small sawmills w i l l s ignif icantly influence average productivity of the industry in the region in the future. Mandatory adoption of the Firmwood Cubic Scale and close ut i l i zat ion standards w i l l deprive most smaller firms of their timber supplies. Therefore, employment in 1980 may be near the empirically estimated level . However, i t can only be concluded that the close ut i l i zat ion policy w i l l result in there being between 293 more and 1,011 fewer saw-mil l ing jobs in 1980 than there might have been without the policy. 179 Pulp Mil l The close ut i l i zat ion policy made i t possible for Weyerhaeuser Canada Ltd. to just i fy the expansion of i ts pulp mil l from 250 to 1,250 tons of bleached kraft pulp per day by assuring the company of an adequate chip supply. It was in the company's long-term interest to expand i ts pulp mil l because one of the sections in the PHA No. 2 agreement entit led the Minister to grant another applicant which was interested in establishing a second mil l in the area the option to purchase pulpwood in PHA No. 2 which was not being ut i l i zed (Fowler, 1966). Costs estimated by R.A. Daley and Co. (1969) indicate that there are economies of scale in pulp manufacturing. This study stated that to achieve an average manufacturing cost of $106 per ton in 1965 required a mil l capacity of 100,000 tons per year operating at 90% of capacity. To maintain a unit cost of $106 per ton in 1968 required a mil l capacity of 250,000 tons per year operating at 90% of capacity. Therefore, i t seems l ike ly that Weyerhaeuser's mi l l may have become marginal i f i t had not been expanded to more than double i ts i n i t i a l capacity. The market expectations for the pulp industry for the 1970's is not optimistic (G. Tower Fergusson L td . , 1972). As a result of high demands for pulp in the early 1960's, world pulp mil l capacity increased rapidly. After 1966, world demand for pulp declined with the result that average operating rates have declined. Since 1967, average operating rates have fluctuated between 80% to 90% of annual pulp mil l capacity. During 1970 to 1972, low returns on investment, 180 low demand for pulp and new government anti -pol lution regulations resulted in postponement of several previously scheduled expansions. With such low expectations, i t seems l ike ly that without an assured adequate chip supply, the capacity of the Kamloops pulpmill would not have been expanded to 1,250 tons per day unti l market expectations improved or until an adequate chip supply could be developed. Therefore, without the close ut i l i zat ion policy, pulp mil l employment in 1980 would have remained at 235 persons. With the close u t i l i z -ation policy, employment in 1980 wi l l be 400 persons. The same conclusion could have been arrived at with information known in 1965. Regional Employment in 1980 On the basis of 1965 information, i t was estimated using the empirical sawmill employment analysis that, in 1980, there w i l l be 250 more legging jobs, 1,011 less sawmill jobs, and 165 more pulpmill jobs as a result of the close ut i l i zat ion policy. Using the extrapolated sawmill employment analysis, there w i l l be 293 more sawmilling jobs. Recent data indicated that there w i l l be 22 more legging jobs in 1980 as a result of the policy. It was assumed that the base ratios of individual industrial groups w i l l not change appreciably during 1961 to 1980. According to 1965 information and using the empirical sawmill employment estimate, there wi l l be 622 less basic jobs in 1980 as a result of the close ut i l i zat ion policy, compared to 526 more basic jobs as estimated by using the extra? polated sawmill employment. According to more recent information and using the empirical sawmill estimate, there wi l l be 756 less basic 181 jobs in 1980 as a result of the policy compared to 392 more jobs estimated using the extrapolated sawmill employment. The value of the regional employment mult ipl ier is unlikely to exceed three by 1980, although i t may be larger than i t was in 1966 or 1971. Therefore i t is possible to state that the impact of the close ut i l i zat ion policy on regional employment in 1980 wi l l be between 622 and 1,866 less jobs using 1965 data and the empirical sawmill employment estimate, between 526 and 1,578 more jobs using 1965 data and the extrapolated sawmill employment estimate, between 756 and 2,268 less jobs using recent data and the empirical sawmill employment estimate, and between 392 and 1,176 more jobs using recent data and the extrapolated sawmill estimate. The labour force in the Kamloops Manpower Centre Area is expected to increase at a compount rate of 8.4% during 1971 to 1977 (Roussel, interview, 1973). If the labour force continues to increase at this rate, the labour force wi l l consist of 65,089 persons in 1980. Assuming that 6% of the labour force w i l l be unemployed, there w i l l be 61,183 persons employed in the area in 1980. Therefore, as a result of the close ut i l i zat ion policy, i t was estimated, using the empirical sawmill employment analysis and both 1965 and recent data, that there w i l l be between 1% and 3% fewer persons employed in the study region in 1980. Using the same data, but using extrapolated sawmill employment analysis instead, i t is estimated that there wi l l be between approximately less than 1% and 2% more persons employed in the study region in 1980 as a result of the close ut i l i zat ion policy. 182 It appears that by 1980 both the absolute and relative impacts of the close ut i l i zat ion 'pol icy wi l l have diminished. One reason for this result is the pulp mil l expansion. By about 1980, without the close ut i l i zat ion pol icy, changes in forest industry structure and market demands which would have resulted from economic forces alone would have led to the same levels of annual harvests, tree sizes harvested, average productivity, and average sawmill capacity as had been achieved ear l ier by implementing the policy. 183 CHAPTER V CONCLUSIONS Mult ipl ier Analysis Although the economic base study used in conjunction with location quotients provide the most inexpensive and least time consuming method of modelling a regional economy, the regional employ-ment multipl ier obtained by this method w i l l always overstate the true value of the mult ipl ier . Three sources of error which were encountered include (1) the product mix problem, (2) incomplete external trade data for both the benchmark economy and the study region, and (3) fai lure to adjust employment by industry data of the bench-, mark economy in order to account for indirect exports. The product mix problem can not be completely remedied. Unless the last two sources of error are resolved, the value of the mult ipl ier obtained by the location quotients w i l l be unreliable for use in impact analysis, except to set an extreme upper l imit for the mult ipl ier . It may be possible to develop more complete external trade information for both regions and the province. Indirect exports may be accounted for i f an input-output matrix were developed for Br i t ish Columbia. Impact of the Close Ut i l izat ion Policy Owing to a lack of suff icient data and time, the impact of 184 the close ut i l i zat ion policy could not be determined precisely. Given the assumptions of this study, i t was possible to estimate a range of magnitude and the direction of the regional employment impact of the forest policy change. Of the variables used in the analysis, only the values of the lumber recovery factor, which were used to estimate levels of lumber production, were not based directly upon published information. Instead, lumber recovery factor values were developed in consultation with a sawmill expert of the Western Forest Products Laboratory. Therefore, the values which were used in this study should be fa i r l y reasonable. However, a small change in any one of the assumed values of the lumber recovery factors may signif icantly change the estimated employment impact of adopting the close ut i l i zat ion policy. For example, i f the lumber recovery factor which was assumed to prevail in the absence of the close ut i l i zat ion policy was decreased by 10% from 7.50 to 6.75 board feet per cubic foot, the corresponding number of sawmill jobs would decline from 2,295 to 2,066 in 1971 and from 2,395 to 2,130 in 1980. This 10% change would decrease the impact of the close ut i l i zat ion policy on basic employment, in 1971, by 31% using the empirical sawmill employment estimate, and by 127% using the extrapolated estimate. In 1980, the impact of the policy would be decreased by 29% and 32% using the empirical sawmill employment estimate with 1965 and recent data respectively, and by 40% and 59% using the extrapolated sawmill employment estimate with recent and 1965 data respectively. 185 Short-Term Impact 1. The sawlog timber portion of quotas was decreased, while the small-wood portion was increased. 2. Average productivity in logging was decreased in the region because the rugged terrain does not permit a signif icant degree of mechanization in logging beyond the adoption of wheeled skidders. As a result of extending the intensive margin of logging, employment increased. Further increases in logging employment resulted from the extension of the timber supply at the extensive margin. 3. More sawmills with capacities of less than 30 M fbm per 8-hour sh i f t remained in the industry than was indicated by the empirical sawmill employment analysis. However, the increase in timber supplies accelerated the trend toward larger and high-speed sawmills. Average productivity increased as average daily capacity increased. Sawmilling employment declined because the effect of increased productivity on employment surposed the normal effect of increased lumber production. 4. In 1971, i t was estimated, using the empirical sawmill employment analysis, that there were between 4% and 12% less jobs in the region than there might have been i f the close ut i l i zat ion policy had not been implemented. Using the extra-polated sawmill employment analysis, i t was estimated that there were between 0.6% and 1.8% less jobs, in 1971, due to the policy. 186 Long-Term Impact By about 1980, without the close ut i l i zat ion policy, changes in forest industry structure and market demands, which would have resulted from economic forces alone, would have led to the same levels of annual harvests, tree sizes harvested, average productivity and, average sawmill capacity as had been achieved ear l ier by implementing the policy. Suggested Improvements in Estimation Methods It has been demonstrated that the economic base mult ipl ier derived by the location quotient technique should be used with caution by regional economic planners. Future work in regional economic planning in forestry should be directed toward improving current knowledge of the production functions of the forest industry within regions. Further insight into the nature of these processes w i l l enable planners to estimate impacts of forest policy changes more accurately than is currently possible. Timber harvest projections can be determined more precisely than by extrapolation by f i r s t forecasting market demands for forest products and relating these to economically available timber supplies. Reliable predictions of logging productivity can not be achieved by extrapolating past trends, because of changing scaling rules and probable yearly inconsistencies in reported employment. Instead, logging productivity forecasts should be based upon 187 productivity research, regional logging conditions and industry studies. From the results of these studies, i t would be possible to determine how soon logging innovations which are feasible in the region w i l l be adopted. The B.C. Forest Service may have much of the required information already in their stumpage appraisal f i l e s and working plans. Rather than extrapolating average productivity trends, oroductivity in sawmilling could be predicted more precisely i f \" industry structure changes could be forecasted and i f employment data by sawmill capacity were available. The survival technique, which is used to determine the existence of economies of scale, could be modified to estimate future industry structure. A similar technique, referred to as the cohort-survival technique, has been used for a long time by demographers to forecast future population levels by age and sex groups. This technique might be applicable to studies in changes in sawmill industry structure. Although the precision of forecasts may be improved by using more sophisticated techniques, accuracy can only be improved by using accurate information. The results of this investigation provide information about the impact of a policy on regional employment. Although employment is a primary concern to governments, other costs and benefits which result from alternative policies must be considered as wel l . Conversely, many public forest policies and forestry investments are just i f ied by public agencies on the basis of the allowable annual cut effect. Since these agencies are charged with managing forest 188 resources in the public's interest, the impact of proposed policies and investments on employment should be an integral part of their analyses of benefits and costs. 189 FOOTNOTES CHAPTER I 'Essential ly, close ut i l i zat ion policy involves the option of an operator of Togging to close ut i l i zat ion standards in return for which the operator is allowed to increase his annual allowable cut up to one-third of i t s former level . Close ut i l i za t ion standards in the Interior constitute logging a l l wood between a 12-inch stump and a 4-inch top diameter of a l l trees of 7.1-inches diameter at breast height and larger; on the Coast, a 12-inch stump and a 6-inch top diameter of a l l trees 9.1-inches diameter at breast height and larger. Allowance is made for decay but not for waste and breakage. Applicants for close ut i l i zat ion sales and cutting permits must have a one year contract for chips, which usually requires that operator have a sawmill with barking and chipping equipment. Stumpage for smallwood is charged at a f la t rate of 55 cents per cunit (100 cubic feet) unti l 1978. The close ut i l i zat ion policy w i l l be discussed in more detail further in this thesis. CHAPTER II 'Spatial equilibrium transportation models are used to deter-mine the spatial distribution of industries which w i l l result in a shipment pattern which wi l l minimize transportation costs between producing and consuming regions. o Shift-share analysis gauges the economic growth performance of a regional economy compared to a reference economy, such as a nation, with-respect to changes in employment due to regional efficiency and to regional industrial composition. 190 CHAPTER III The service industries include the Transportation, communi-cations and other u t i l i t i e s industries; Finance, insurance and real estate industries; Community, business and personal service industries; and Public administration and defence as described in Stat ist ics Canada, Standard Industrial Classif ication Manual, Information Canada, 1970, pp. 23-43. 'In 1972, about 70% of the area of the Big Bar Public Sustained Yield Unit was included in the newly formed Cariboo Forest D is t r i c t . 3A tree Farm Licence (TFL) is an agreement between a forest products company and the B.C. Forest Service whereby the company has exclusive cutting rights on a parcel of Crown and private forest land. The TFL is renegiotable every 21 years. In return, the company must manage the TFL on a sustained yield basis according to an approved management plan. Sustained y ield forest management consists of manag-ing a parcel of forest land to y ie ld equal or increasing harvests of timber annually or periodically in perpetuity. A^ Pulp Harvesting Area is an area of forest land which is subject to an agreement between a pulp company and the B.C. Forest Service which gives the company the right of f i r s t refusal to purchase wood chips which are manufactured from timber harvested from the area for a renewable term of 21 years. Each PHA consists of several Public Sustained Yield Units (see footnote 5). See Ralph A. Fowler, \"The Pulpwood Potential in Pulpwood Harvesting Area No. 2.(Kamloops),\" B.S.F. thesis , Fac. For., U .B .C , 45 pp. for a detailed description of PHA No. 2. Weyerhaeuser has recently surrendered their exclusive right to log pulpwood in PHA'No. 2 (see Dept. of Industrial Development, trade, and Commerce, \"The Li l looet-Nicola Region,\" V ictor ia , 1972b, p. 60). bA Public Sustained Yield Unit (PSYU) is a parcel of forest land which is managed on a sustained y ie ld basis by the B.C. Forest Service. Timber within PSYU's is disposed of by temporary tenures called Timber Sales. Forest Service Reserve is a portion of the allowable annual cut of a PSYU which is held by the B.C. Forest Service in case of timber losses resulting from catastrophes such as forest f i r e s , disease epidemics, insect infestations and storms. 191 CHAPTER IV 'Since the time of writing this thesis, the B. C. Forest Service has announced that, the stumpage appraisal system for the interior of Br i t ish Columbia wi l l be signif icantly revised, effective September 1, 1973 (B.C. Forest;Service, 1973). The major changes include the discontinuance of the 55 cents per cunit for close ut i l i zat ion timber. Close ut i l i zat ion timber w i l l be appraised in the 's'Sfne manner as other timber. 192 BIBLIOGRAPHY Andrews, R.B. 1954. Mechanics of the urban economic base: the problem of base measurement. Land Economics (February, 1954): 52-60 in Pfouts, R.W. ed. 1960. The techniques of urban analysis. Chandler-Davis Publishing Co., N.J. Ashby, Lowell D. 1962. Studies in interregional competition and the purposes they serve. Society of American Foresters Annual Meeting Proceedings, Atlanta, Georgia, 1962: 84-89. Austin, John W. 1969. Timber flows and ut i l i zat ion patterns in the Douglas-fir Region, 1966. Pacif ic Northwest Forest and Ranger Exp. S ta . , U.S.D.A. Forest Serv. Res. Pap. P..N.W. 89, 88 pp. Barkley, P.W. and T.H. A l l i son , Jr . 1968. Economic base studies in resource administration. Land Economics (44): 470-79. Bowland, J .F . 1971. Economic indicators in forestry and forest-based industries in Canada: 1961/69. Canadian Forestry Service, Forest Economics Research Institute, Ottawa, 90 pp. B.C. Forest Service 1965. Circular letter to operators, October 1, 1965, Victoria summarized in Brit ish Columbia Lumberman 49(11): 48, 50. B.C. Forest Service, Forest Production Committee, 1972. The functions and programme of the Forest Productivity Committee. B.C. Forest Service, V ictor ia , 9 pp. (mimeo.). B.C. Forest Service 1973. An outline of the revision of the interior appraisal system. Information sheet distributed at a meeting of the B.C. Forest.Service and representatives of the forest industry, June 14, 1973, V ictor ia , Br i t ish Columbia, 5 pp. (mimeo.). Callahan, John C. 1962. The competitive situation of selected regional forest product industries. Society of American Foresters Annual Meeting Proceedings, Atlanta, Georgia, 1962: 103-108. Carney, Pat. 1967. Let the chips f l y : Technology vs. economics. B.C. Lumberman, (May 1967): 46-47, 92. Chr ist ie , R.G. 1967. An analysis of chip handling in the B.C. inter ior . B.S.F. thesis, Faculty of Forestry, Univ. B.C., Vancouver, B.C., 49 pp. + Appendices. Clutterham, Donald B. 1970. An investigation of factors affecting the productivity of rubber-tired skidders in the Prince George Area. B.S.F. thesis, Fac. For. , Univ. B.C., 44 pp. + Appendices. 193 Daley. R.A. and Co. Ltd. 1969. The Canadian forest products industry. Toronto, 81 pp. Davis, H.C. and M.A. Goldberg, 1972. An economic model of the Vancouver region. Univ. of B.C. 12 pp. (mimeo). Davis, H.C. and G. Hainsworth, 1970. The cariboo Regional D is t r i c t . Canadian Environmental Sciences. Economic Development Report, 46 pp. Denike, K.G. and Roger Leigh, 1972. Economic geography 1960-70 in Robinson, J . Lewis ed. 1972. Brit ish Columbia. Studies in Canadian Geography, 22 nd. International Geographical Congress, Montreal 1972, University of Toronto Press, pp. 67-86. Dept. of Industrial Development, Trade, and Commerce 1972a. Br i t ish Columbia facts and s ta t i s t i cs . Vol. 24, Victor ia . Dept. of Industrial Development, Trade, and Commerce 1972b. The Li 1looet-Nicola Region. V ictor ia , 163 pp. Dept. of Industrial Development, Trade and Commerce 1972c. The sawmill industry of Br i t ish Columbia. V ictor ia , 76 pp. Dept. of Industrial Development, Trade, and Commerce 1972d. Summary of economic activ ity in Br i t ish Columbia, 1972. V ictor ia , 61 pp. and supplement. Dept. of Industrial Development, Trade, and Commerce 1971. Br i t ish Columbia manual of resources and development. V ictor ia , 54 pp. Dept. of Industrial Development, Trade, and Commerce 1970. The Brit ish Columbia pulp and paper industry. V ictor ia , 81 pp. Dept. of Industrial Development, Trade, and Commerce 1966. Regional index of Br i t ish Columbia - 1966. B ictor ia , 551 pp. Deutsch, J . J . , S.M. Jamieson, T.I . Mattuzzewski, A.D. Scott and R.M. W i l l . 1959. Economics of primary production in Br i t ish Columbia, vol 1 and 5 (6 vo ls . ) , University of Brit ish Columbia, Vancouver, Br i t ish Columbia. Dingwall, Donald C. 1969. Here's what B.C.'s \"third band\" timber is and who may log i t . Canadian Forest Industries 89(3): 96-102. Dobie, J . 1973. Economies of scale and trends in sawmill capacity in Br i t ish Columbia. For. Chron. 49(2): 79-82. Dobie, J . 1972. Canadian Forestry Service, Western Forest Products Laboratory, Vancouver, B.C., Interview, 29 November 1972. 194 Dobie, J . 1972. Firmwood cubic scaling and conversion factors in Brit ish Columbia. Canadian Forestry Service, Western Forest Products Laboratory, Vancouver, Information Report VP-X-95, 14 pp. Dobie, J . 1971. Economies of scale in sawmilling in Br i t ish Columbia. Ph.D. Thesis, School of Forestry, Oregon State Univ., 124 pp. Dobie, J . 1968. A comparison of productivity with small logs in various types of sawmills. Proceedings of the High-Speed Headrig Conference, Syracuse, N.Y., November 12-15, 1968, pp. 47-65, reprint. Dobie, J . 1967. How chipper headrigs reduce small-log processing costs. Canadian Forest Industries, 87(8): 60-65. Dobie, J . , C F . McBride and J.A. Mcintosh 1970. Conversion returns for decadent cedar-hemlock type in the Brit ish Columbia inter ior . Canadian Forestry Service, Western Forest Products Laboratory, Information Report VP-X-65, 20 pp. Dobie, J . , W.J. Sturgeon and D.M. Wright 1967. An analysis of the production characteristics of chipper headrigs, scrag mil ls and log-gang m i l l s . Canadian Forestry Service, Western Forest Products Laboratory, Vancouver, B.C., Information Report VP-X-21, 20 pp. Dobie, J . and D.M. Wright 1972. Conversion factors for the forest-products industry in western Canada. Canadian Forestry Service, Western Forest Products Laboratory, Vancouver, B.C., Information Report VP-X-97, 60 pp. Fairhurst, K.B. 1968. The close ut i l i zat ion policy of the Br i t ish Columbia Forest Service. B.S.F. thesis, Fac. For. , Univ. B.C., 72 pp. Fisher, Joseph L. 1955. Concepts in regional economic development. Papers and Proceedings of the Regional Science Association, vol . 1: W2-W20. Flora, D.F. 1965. Economic evaluation of potential European pine shoot moth damage in Ponderosa Pine Region. U.S. Forest Service, Pacif ic Northwest Forest and Range Experiment Station, Res. Paper PNW 22. Forrester, Jay W. 1969. Urban dynamics. M.I.T. Press, Cambridge, Mass., 285 pp. Foster, B.B. 1972. Marginal logs and prof i tab i l i t y of low investment sawmills. Jour. For. 70(T):26-27. 195 Fowler, R.A. 1966. The pulpwood potential in Pulp Harvesting Area No. 2 (Kamloops). B.S.F. thesis, Faculty of Forestry, Univ. B.C., 45 pp. Fox, K.A. and T.K. Kumar 1965. The functional economic area: delineation and implications for economic analysis and policy. Papers and Proceedings of the Regional Science Association, vol . 15: 57-85. Gamble, Hayes B. 1968. The regional economic role of forest products industries. Jour. For. vol 66(6): 462-466. Gunn, D.C., G.R. Bailey and J.A. Mcintosh 1966. B.C. Lumberman, (April 1966): 4 pp. (Reprint). Gunn, D.C. and F.W. Guernsey 1958. Skidding time studies in the B.C. southern inter ior . B.C. Lumberman (February 1958): 24-25, 28, 30. Haley, David 1972. The economic analysis of act iv i t ies designed to accelerate stand growth in the context of the managed forest. Paper prepared for the Stand Management Committee, 63rd Western Forestry and Conservation Association, Seattle, Wash., December 6, 1972, 10 pp. (mimeo). Haley, David 1971, Influence of public policies on the development of the forestry sector in Br i t ish Columbia. Paper presented at Annual Meeting of the American Agricultural Economics Association, Carbondale, I l l i n o i s , 10 pp., mimeo. Haley, David 1966. An economic appraisal of sustained y ie ld forest management. Ph.D. thesis. Faculty of Forestry, Univ. B.C., Vancouver, 313 pp. Hardwick, W.G. 1963. Geography of the forest industry of coastal Br i t ish Columbia. Canadian Association of Geographers, B.C. Div. , Dept. of Geography, Univ. B.C., Vancouver, Occasional Papers in Geography No, 5, 91 pp. Hamilton, H.R., S.E. Goldstone, J.W. Milliman, A.L. Pugh II I , E.B. Roberts and A. Zellner 1969. Systems simulation for regional analysis: An application to river-basin planning. The M.I.T. Press, Cambridge, Mass., 407 pp. Hansen, W.L., R.T. Robson and CM. Tiebout 1961. Markets for California products. California Economic Development Agency, Sacramento, Cal i fornia. Haviland, W.E., N.S. Takacsy, E.M. Cape 1968. Trade l iberal izat ion and the Canadian pulp and paper industry. Canada in the Atlantic Economy - 5 , Private Planning Association of Canada, University of Toronto Press, 107 pp. 196 Hedlin, Menzies and Associates Ltd. 1969. The Ontario forest industry: Its direct and indirect contribution to the economy. Ontario Dept. of Lands and Forests, 74 pp. Holley, D.L. 1970. Location of the softwood plywood and lumber industries: A regional programming analysis. Land Economics, 46(2):127-137. Hughes, Jay M. 1970. Forestry in Itasca County's Economy: an input-output analysis. Agricultural Experiment Station, University of Minnesota, Forestry Series 4, Miscellaneous Report 95, 98 pp. Husch, B. 1963. Forest mensuration and s t a t i s t i c s . The Ronald Press Co., New York, 474 pp. Isard, Walter 1960. Methods of regional analysis: an introduction to regional science. The M.I.T. Press, Massachusetts, 784 pp. Isard, Walter 1956. Regional science, the concept of region, and regional structure. Papers and Proceedings of the Regional Science Association, Vol. 2: 13-26. Kaiser, H.F., J r . 1972. Multi-regional input-output model for forest resource analysis. Forest Science, 18(1): 46-53, Reprint. Lacate, D.S. 1965. Forest land c lassi f icat ion for the University of Br i t ish Columbia Research Forest. Canadian Forestry Service, Ottawa, Pub. No. 1107, 23 pp. Lane, Theodore 1966, The urban base mult ip l ier : an evaluation of the state of the art . Land Economics, (42): 339-47. Losch, August 1963. The nature of economic regions. Southern Economic Journal, vo l . 29 (August 1963) in Friedmann, John and William Alonso, eds., 1965. Regional Development and Planning, M.I.T. Press, pp. 107-115. Mahood, Ian 1966. Participation on a panel discussion on the close ut i l i zat ion policy at the Cariboo Lumber Manufacturers Association's Annual Meeting, March, 1966, Williams Lake, B.C. reported in the Truck Logger 22(5):56-58. Main, A.C. 1971. The impact of forestry and forest-related industries on a local economy, Baldwin County, Alabama. Ph.D. thesis, Auburn Univ. Auburn, Alabama, 279 pp. Maki, Wilbur R., Con H. Schallau, and John H. Beuter 1968. Importance of timber-based employment to the economic base of the Douglas-f i r region of Oregon, Washington and northern Cal i fornia. PNW For. and Range Exp. Stat . , U.S.D.A. For. Ser. Research Note PNW-76, 6 pp. 197 McGraw, W.E. 1962. Variable factors affecting skidding production in logging. Canadian Forestry Service, Ottawa, Tech. Note No. 28, 15 pp. Mcintosh, J.A. 1973. Canadian Forestry Service, Western Forest Products Laboratory, Vancouver, B.C., Interview, 10 May 1973. Mcintosh, J.A. 1968. An example of how close-U harvesting could affect wood volumes and logging practices. Canadian Forest Industries, 88(7): 44-51 (reprint). Mcintosh., J ,A. and J . Csizmazia 1965. Harvesting lodgepole pine in the B.C. Interior. Canadian Forest Industries, (June 1965) reprint. 5 pp. McLeod, M.R. 1971. The degree of economic concentration in the Brit ish Columbia forest industry. B.S.F. thesis, Faculty of Forestry, Univ. B.C., Vancouver, 174 pp. Muench, John Jr . 1966. Impact of public vs. private ownership of timber land on a rural economy. Jour. For. 64(11): 721 -^727. Mull ins, D.K. 1967, Changes in location and structure in the forest industry of North Central Br i t ish Columbia: 1909-1966. M.A. thesis, Dept. of Geography, Univ. B.C., 131 pp. Munro, D.W. 1973. Weyerhaeuser Canada L td . 0 Kamloops, B.C., Interview, 9 January 1973. Nagle, George S. 1970. Economics and public policy in the Forestry sector of Br i t ish Columbia. Ph.D. thesis, Yale University, 198 pp. + bibliography. Neighbour, B.E. 1973. B.C. Forest Service, Kamloops, B.C., Interview, 10 January 1973. Nixon, G.R.W. and D.C. Gunn 1957. Fell ing and bucking time studies. B.C. Lumberman 41(3): 14, 16, 18. Ottens, J . 1971. Foreign investment, in the Br i t ish Columbia forest industry. Forestry 519 Report, Faculty of Forestry, Univ. B.C., 69 pp. Pearse, P.H. 1971. Rationalization of Canada's west coast salmon fishery: an economic evaluation. Paper prepared for the O.E.C.D. Symposium on Fisheries, November, 1971, 29 pp., mimeo. Pearse. P.H. 1970. Conflicting objectives in forest policy: the case of Br i t ish Columbia, For. Chron. 46(6):281-287, 198 Pearse, P.H. 1965. Distortions in the market for forest land. For. Chron. 41(4):406-418. Perroux, Francios 1950. Economic space:, theory and applications. Quarterly Journal of Economics, vol . 64 (February 1950) in Friedmann, John and William Alonso, eds., 1965. RegionaT\" Development and Planning, M.I.T. Press, pp. 21-26. Peters, J .E . 1969. Commodity trade flows of Br i t ish Columbia. 1961-1964. M.A. thesis, Dept. of Economics, Univ. B.C., 226 pp. Province of Br i t ish Columbia 1968. Forest Act. Queen's Printer* V ictor ia , B.C. Reed, F.L.C. 1972. The impact of the forest industry in Bri t ish Columbia. Paper prepared for presentation at the Truck Loggers Convention, Vancouver, B.C. (mimeo) 13 pp. Roussel, D.M. 1973. Canada Manpower Centre, Kamloops, B.C., Interview, 9 January 1973. Schallau, Con, Wilbur Maki and John Beuter 1969. Economic impact projections for alternative levels of timber production in the Douglas-fir region. The annals of Regional Science, Vol. I l l , No. 1, pp. 96-106 (Reprint). Schwietzer, D.L,, Sassaman, R.S. and C H . Schallau 1971. Allowable cut effect - Some physical and economic implications. Jour. For. 70(7):415-418, Siegel , R.A. 1966. The economic base and mult ipl ier analysis. Urban Affairs Quarterly 2(2):24-38. Sloan, Gorden McG. 1957. Report of the commission relating to the forest resources of Br i t ish Columbia, 1956. Queen's Printer, V ictor ia , 888 pp. (2 vols,).. Smith, J.H.G. 1968. Competitive position of pulpwood in B.C. in Streyffert , Thorsten 1968. World pulpwood. Almquist and Wiksel l , Stockholm, pp. 142-158. Smith, J.H.G. and David Haley 1970. Canadian forest managers must learn how to expand and modulate yields in a Higher quality environment, in Canadian Council of Resource Ministers 1970. Forestry reader. Montreal, Paper No. 21, 12 pp. Smith, J.H.G. and A. Kozak 1970. Analysis of trends and variations ir^ annual harvest of timber in Brit ish Columbia as a guide to expansion and modulation of y i e l d . Faculty of Forestry, Univ. B.C., 10 pp., mimeo. 199 St ig ler , G.J. 1966. The theory of price. 3rd Ed. The Macmillan Co., New York, 355 pp. Stat ist ics Canada 1970. Standard industrial c lassi f icat ion manual. Cat. No. 12-501 occasional, Ottawa. Stat ist ics Canada 1969. Input-output structure of the Canadian Economy, 1961. Vol. 1, 2. Cat. No. 15-501 Occasional, Ottawa. Stokes, J .S . 1965. Log salvage and pulp harvesting. The Truck Logger 21(3):38-39. Swanson, Carl V. and Raymond J . Weldmann 1970. A simulation model of economic growth dynamics. American Institute of Planners Journal 36(5):314-322. Tiebout, Charles M. 1962. The community economic base study. Committee for Economic Development. Supplementary Paper No. 16, 86 pp. Tobin, L.R. 1970. Influences of the Br i t ish Columbia Forest Service close ut i l i zat ion policy on the forest products industry in interior Br i t ish Columbia. Ph.D. comprehensive exam., Univ. Wash., mimeo., 24 pp. Tower, G., Ferguson Ltd. 1972. The Canadian forest products industry. Toronto, 115 pp. The Truck Logger 1966. Summaries of briefs submitted to the Legis-lative Select Standinq Committee on Forestry, March, 1966, V ictor ia , B.C. (Apr i l , 1966): 16-19. Ullman, E.L. and M.F. Dacey 1960. The minimum requirements approach to the urban economic base. Papers and Proceedings of the Regional Science Association, vol . 6: 174-194. Waggener, Thomas R. 1972. Estimating the economic impact of changes in the supply of timber. College of Forest Resources, Univ. Wash., 12 pp., mimeo. Wi l l i s ton, R.G. 1969. Calculating allowable cut. Industrial Progress of the North, 2(2):5,32. Wi l l i s ton , R.G. 1966a. Address presented at the 56th Western Forestry and Conservation Conference, December 8-10, 1965, Vancouver, B.C. in the Truck Logger 22(l) :30-32, 34. Wi l l i s ton, R.G. 1966b. Brief submitted to the Legislative Select Standing Committee on Forestry, March, 1966, V ictor ia . Summarized in the Truck Logger (April 1966):16-17. 200 Wil l i s ton , R.G. 1966c. Address presented at the Interior Lumber Manu-facturers Association annual meeting, April 29, 1966, Penticton, B.C. in the Truck Logger, 22(7):32-34. Wi11iston s R.G. 1966d. Address to operators in the Kamloops Region, November, 1966, Kamloops, B.C., reported in the Truck Logqer 22(12):15. Wi l l i s ton , R.G. 1965. Address presented at the Truck Loggers Association Convention, January. 1965, Vancouver, B.C. in The Truck Logger 21(2):14-17. Wi l l i s ton, R.G. 1961. Address to the Northern Interior Lumberman's Association, May 24, 1961, Prince George, B.C. Wood, A.R. 1970. The growth and financing of integrated forest product companies in Brit ish Columbia. B. Com. thesis, Faculty of Commerce and Business Administration, Univ. B.C., Vancouver, B.C. Wrobel, Adnrzej 1962. Regional analysis and the geographic concept of region. Papers and Proceedings of the Regional Science Association, vol , 8: 37-41. Young, E.L. 1969. Calculation of annual allowable cuts. Address presented to the Northern Interior Lumberman's Association, January 15, 1969, Prince George, B.C. 39 pp. mimeo. 1 APPENDIX I - TABLE 1. Ranger d is t r i c t timbersheds, 1965 . Sawmi11 Number Wood Supply Sawmills (excluding separate planer mil ls) 2 3 Type Capacity PSYU Volume TFL (M cf per year) 1. 2. BIRCH ISLAND RANGER DISTRICT (No. 2.) Clearwater Timber Prod. Ltd. Birch Island Lbr. Co. Ltd. S 200 Raft TFL 18, S 65 Adams Raft 59 2,500 2,559 668 2,407 3,075 r o o 3. BARRIERE RANGER DISTRICT (No. 3.) Fadear Creek Lumber Co. Ltd. X-S 125 Barriere. Nehalliston Niskonlith North Thompson 3,693 1,418 116 81 5,318 KAMLOOPS RANGER DISTRICT (No. 4.) 4. Kuchak, John P 5 Kamloops 52 5 . Lingren, W.F. P .6 Kamloops 8 6 . Long & Son Lbr. Ltd, S 15 Kamloops 226 7. Pondosa Pine Co. Ltd. X-S . . 70 Kamloops Shuswap TFL 16. 1 ,152 136 1,500 2 , 7 8 8 8 , Balco Forest Prods. Ltd. X-S 50 Kamloops Niskonlith North Thompson 135 670 1 , 8 4 4 2 ,649 9 . B.C. Interior Sawmills Ltd. XCBS-S 140 Barriere Kamloops Nehalliston TFL 3 5 . 337 543 445 1 ,800 3,125 10. Buff Lumber Ltd. X-S 50 Kamloops 524 n . Frolich Sawmills Ltd. X, P P P 15 10 20 Kamloops Nehalliston Niskonlith 4 , 9 0 3 46 45 4 , 9 9 4 12, H.K. Lumber Ltd. X-S 60 Niskonlith Shuswap 519 460 979 13. Kamloops Lumber Co. Ltd. X-S 90 14. 15. 16. 17. 18. 19. 20. CHASE RANGER DISTRICT (No. 5.) Blanc, C P . Holding Lbr. Co. Ltd. Cave, Phi l ip & Green, R.J. Federated Co-op Ltd. S X-S P . X-S 5 130 5 60 MacKay, A.B. Raboch Sawmills Ltd. Thielman, J .E . G.W. P P P 12 17 7 Botanie Kamloops Niskonlith Raft Shuswap Shuswap Adams Niskonlith Salmon Arm Niskonlith Salmon Arm Shuswap Eagle Salmon Arm Salmon Arm Salmon Arm 2L SICAMOUS RANGER DISTRICT (No, 7.) Maclean Sawmills Ltd. P 17 Eagle 973 1,082 423 931 338 3,747 16 4,082 467 4,549 12 110 1,464 3,546 30 5,150 17 4 9 ro o co 1,288 22. Shuswap Timber Ltd. X-S 35 Eagle 353 LILLOOET RANGER DISTRICT (No. 8,) 23. Setor Lake Lumber Co. Ltd. X-S 40 Yalakom 50 24. Commercial Lumber Co. Ltd. X-S 65 Yalakom 1,752 P 25 25. Beaton Bros. Lumber Co. Ltd. P 25 Yalakom 22 CLINTON RANGER DISTRICT (No. 12.) 26. Cattermole - Thretheway P 15 Big Bar 1,293 Contractors Ltd. P 12 Botanie 44 o 27. Clinton Sawmill L td . P 30 Big Bar 1,890 P 20 P 20 P 20 ASHCR0FT RANGER DISTRICT (No. 16.) 28. Gateway Lbr. Co. Ltd. X-P 20 Big Bar 107 Botanie 2,444 2,551 29. Savona Timber Holdings Ltd. X-S 60 Big Bar 2,701 Botanie 1,465 Kamloops 177 4,343 MERRITT RANGER DISTRICT (No. 17.) 30. Aspen P.V. Lumber Ltd. X-S 50 Nicola Kamloops Similkameen 634 88 9 731 31. Coldwater Lbr. Co. Ltd. X-P 15 Nicola Similkameen 260 151 411 32. Drew Sawmills Ltd. X-S 40 Kami oops 97 33. Kamloops Pulp & Paper Co. Ltd. X-S 80 Botanie Kamloops Nicola 48 154 143 345 34. Nicklin Logging Co. Ltd. X-P 25 Nicola 374 35. Nicola Valley Sawmills Ltd. X-S 115 Nicola 2,396 36. Roth, Balser Sawmill X-P 30 Nicola 63 . BLUE RIVER RANGER DISTRICT (No. 18.) 37. Blue River Sawmills Ltd. X-S 75 North Thompson 1,251 38. Janes, Art Hurricane Steel Industries S 20 North Thompson 22 39. Yellowhead Sawmills Ltd. S 50 North Thompson 674 40. Kamloops Pulp & Paper Co. Ltd. X-S 75 North Thompson 1,528 885 1,413 100 MILE HOUSE (South) RANGER DISTRICT (No. 24.) (Portion with study region) 41, Greenlake Forest Prod. Ltd. X-S 20 Big Bar Lac La Hache 316 298 614 42. Komori Equipment Ltd. X-S 40 Big Bar Botanie 335 22 357 1. Source: Kamloops Forest D is t r ic t Annual Management Report, 1965, 2. Type - P - Portable; S - Stationary; X - planer, in conjunction with sawmill; C - Chipper; B - Barker; S - Smallwood side. 3. Capacity - M fbm per 8-hour sh i f t . 207 APPENDIX I - TABLE 2. Ranger d i s t r i c t timbersheds, 1971 . Sawmill ? 3 number Sawmills Type' Capacity (excluding separate planer mil ls) BIRCH ISLAND RANGER DISTRICT (No. 2.) 1. Clearwater Timber Prod. Ltd. (Vavenby Division) XCB-S 65 2. Clearwater Timber Prod. L td . XCBS-S 165 3. Weyerhaeuser Canada Ltd. (Vavenby Branch) XCBS-S 200 BARRIERE RANGER DISTRICT (No. 3.) 4. Fadear Creek Lumber Co. Ltd. XCBS-S 180 5. Gilbert Smith Forest Products Ltd. XCB-S 20 KAMLOOPS RANGER DISTRICT No. 4. 6. Balco Forest Products Ltd. VXCB-S 135 Wood Supply PSYU TFL I.U. C U . Total Volume (M cf per year) Adams 668 223 891 Raft. 2,985 995 3,980 TFL 18 2,500 3,300 5,800 6,153 4,518 10,671 Adams 150 50 200 North Thompson 2,881 960 3,841 Raft 1,829 610 2,439 4,860 1,620 6,480 Barriere 3,773 1,258 5,031 Nehalliston 1,534 511 2,045 North Thompson 81 27 108 5,388 1,796 7,184 Barriere 141 0 141 Nehalliston 62 21 83 Niskonlith 24 8 32 Raft 6 0 6 233 29 262 Kamloops 3,621 1,207 4,828 Niskonlith 848 283 1,131 North Thompson 1,863 621 2,484 -. 6,332 2,111 8,443 208 7. H. Buff Lumber Co.. Ltd. XCB-S 35 8. Crown Zellerbach Canada XCB-S 59 9. Long & Son Lumber Ltd. X-S 19 10. Weyerhaeuser Canada Ltd. (B.C. Interior Sawmills Ltd.) XCBS-S 150 CHASE RANGER DISTRICT (No. 5.) 11. ' Bischoff, Arthur P 3 12. Blanc, Chas. P. S 5 13. Holding Lumber Co. Ltd. XCBS-S 160 P 2G 14. Lewis, George (G & M Cedar Ltd.) P 5 15. Bridge, G.D. P 3 16. L i t t l e River Shake & Shingles Co. S 2 SALMON ARM RANGER DISTRICT (No. 6.) 17. Bell Pole Co. Ltd. P 6 18. Federated Co-Operatives Ltd. VWXCBS-S 252 19. . Tappen Valley Timber Ltd. CBS-S 65 20. Thielman, J . E . , & G.W. P 5 21. Whitehead, Howard P 3 Kamloops 1,544 515 TFL 16 1,500 800 3,044 1,315 Kamloops 229 76 TFL 35 1,800 1,700 Barriere 362 121 Kamloops 1,710 570 Nehalliston 445 148 Niskonlith 767 256 5,084 2,795 Shuswap 17 0 Shuswap 16 0 Salmon Arm _2_ \u00C2\u00A3 18 0 Adams 4,407 1,469 Niskonlith 469 ' 156 47876\" T^bTb Shuswap 10 0 Shuswap 19 0 Shuswap 9 0 Shuswap 264 0 Salmon Arm 47 0_ 311 0 TFL 33 385 403 Niskonlith 294 98 Salmon Arm 1,543 514 Shuswap 5,261 1,754 Eagle 386 129 7,869 27898\" Salmon Arm 48 16 Salmon Arm 10 0 Salmon Arm 6 0 2,059 2,300 4,359 305 3,500 483 2,280 593 1,023 \u00C2\u00BB 77879* 17 16 2 T8 5,876 625 6,501 1\u00C2\u00B0 19 9 264 47 311 788 392 2,057 7,015 515 10,767 64 10 6 209 SICAMOUS RANGER DISTRICT (No. 7.) Drew Sawmill Ltd. XCB-S 45 Rogers Pass Forest Prodts Ltd. X-S 20 LILL00ET RANGER DISTRICT (No. 8.) Commercial Lumber Co. Ltd. XCBS-S 110 CLINTON RANGER DISTRICT (No. 12.) B.C. Forest Products Ltd. P 16 Clinton Sawmills Ltd. P 15 (Part of) 100 MILE HOUSE (south) RANGER DISTRICT (No. 24.) Greenlake Forest Products Ltd. X-S 20 Komori Equipment Ltd. XCBS-S 45 ASHCROFT RANGER DISTRICT (No. 16.) Savona Timber Co, Ltd. VWXCBS-S 100 MERRITT RANGER DISTRICT (No. 17.) Aspen Planers Ltd. XCB-S 70 K.P. Wood Products Co. Ltd. XCB-S (central Division) (Weyco) Eagle 41 '41 55 Eagle 9 3 12 Yfflakom 2,997 999 3,996 Big Bar 1,293 0 1,293 Botanie 44 0, 44 T 7 3 3 T 0 \u00E2\u0080\u00A2 \"T733T Big Bar 1,890 0 1,890 Big Bar 316 0 316 Lac La Hache 29j3 0 298 614 0 614 Big Bar 668 223 891 Botanie 22 0 22 Lac La Hache \u00E2\u0080\u00A2 853 284 1,137 1,543 507 2,050 Big Bar 2,808 936 3,744 Botanie 3,909 1,303 5,212 6,717 27219\" 87956' Kamloops 88 29 117 i i c o l a 1,425 475 1,900 175T3 50? 273T7 Botanie 1,021 340 1,361 l i c o l a 3,143 1,048 4,191 7J7T6T 1,388 \"5~55Y 210 32. Nicola Valley Sawmills Ltd, 33. O'Neil & Devine Ltd. XCBS-S P XCBS-S 150 15 65 Nicola Similkameen Similkameen 2,656 1,952 4,608 58 885 651 1,536 19 3,541 2,603 67T4T 77 34. 35. 36. Anderson, Otto BLUE RIVER RANGER DISTRICT (No. 18.) P 5 Fedoruk, Gordon (Cedar Creek Products) Mazur Timber Co. Ltd. SP SP 5 10 North Thompson North Thompson North Thompson 4 22 0 0 4 22 1. Sources: Kamloops Forest D is t r i c t , \"List of Established Licencees as of January 1st, 1972-\" \"Sawmills and Planer Mi l ls by Ranger Distr icts\" March 1st, 1972; and \"TFL 's - Kamloops Forest D is t r i c t , 1970.\" 2. Type: P - Portable; S - Stationary; SP - Semi-Portable; X - Planer, in conjunction with sawmill; C - Chipper; B - Barker; S - Smallwood Side; V - Veneer; and W - Plywood Plant. 3. Capacity - M fbm per 8-hour s h i f t . 211 APPENDIX II - Employment by industry required for self -suff iciency in Br i t ish Columbia in 1961. Industrial Divisions Major Groups Three-Pi g i t Industries Sell ing Value of Factory Shipments ($000) Exports ($000) Imports ($000) Consumption ($000) Employment (number of persons) Workers per $000 Production Sel f -suf f ic ient Employment (number of persons) Agriculture 100,090a 24,200b 14,178b 94,068 2 a , 8 2 5 b \u00C2\u00BB c , d 0.2380 22,388 Forestry 291,775 f !U400 b b 230,375 20,900e 0.0717 20,103 Fishing and Trapping 38,77# b b 38,778 16,805 s 0.4334 16,805 Mines (including mi l l ing) , Quaries and Oil Wells 188,542h 64,715b b 123,827 7,887C 0.0418 5,176 Manufacturing Industries 1,967,091 920,845 1,051,783 2,098,020 97,518 0.0489 125,033 (Non-durable Goods Manufacturings Industries excluding Paper and Al l ied Industries) \u00C2\u00BB. 479,781 38,239 242,504 684,046 22,709 0.0473 s 41,719 Food and Beverage Industries 399,7771 38,000b : 63,527 425,304 15.4441 0.0386 16,417. Tobacco Products Industries' Rubber and Plastics Products Leather1 Industries Textile Industries ' \u00E2\u0080\u00A2 , Knitting Mi l ls Clothing Industries i 690] 2,135] 8,646 . N/A . 12.7131 b \" . b 112 b N/A \" 239\u00C2\u00B0 23,700b N/A b 22,344? 30,548 N/A b 102,385 23,700 690 24,479 39,194 N/A 114,859 238! 7301 N/A . 1.5001 0.0386 0.0942 0.1115 0.0844 N/A 0.1180 915: 65 2,729 \u00E2\u0080\u00A2 3,308 N/A : \u00E2\u0080\u00A2-: 13,553-(Non-durable Goods Manufacturing Industries excluding Paper and A l l i e d ; Food and Beverage; and Print ing, Publishing and'Allied Industries) 24,184 239 178,977 202,922 2,533 0.1047 20,570 Print ing, Publishing and A l l ied Industries \u00E2\u0080\u00A2 . 55,820 i \u00E2\u0080\u0094 \u00E2\u0080\u0094 55,820 4J7321 0.0848 4,73.2 (Durable Goods Manufacturing Industries) 1,487.310 882,615 .809,279 1,413,974 73,548 0.0495 69,992 \', (Forest Products Industries) 879,246 694,216 \u00E2\u0080\u0094 \"185,030 46,930 0.0534 9,715 Paper and A l l ied Industries 323,1431' 250,455b b 72,688 l l , 1 2 2 t 0.0344 2,500 212 Wood Industries Sawmills (excluding shingle mil ls) Sash, Door and Planing Mi l l s (excluding hardwood flooring) (Sawmilling) Veneer and' Plywood Mi l l s Shingle Mi l ls Wood Box;factories Coffin and Casket Industry Miscellaneous Wood Industries (Other Wood Industries) (Non-Forest Products^ Industries) Furniture and/Fixture Industries Primary Metal Industries Metal Fabricating Industries (except machinery and transport tation equipment industries) Machinery Industries (except electr ical equipment) Transportation Equipment Industries Electr ical Products Industries Non-Metallic Mineral Products Industries Petroleum and Coal Products Industries Chemical and Chemical Products Industries Miscellaneous Manufacturing Industries Confidential.. Construction Industries Transportation, Communication and Other U t i l i t i e s 556,1031 443,761 - \u00E2\u0080\u0094 368,7841 349,300b \u00E2\u0080\u0094 66.6191' 435,403 349,300 \u00E2\u0080\u0094 91.4141 71 ,347 b b 16,183] 812! 799] 11,492'' 29,286 15,997b 7,117b 23,114 b ; HI b 608,061 188,399 809,279 22.2601 b 19,732b 177,7261 T46,385b 237,300b 158,231 8,614 ' 300,539 83.8351 8,614 225,100b 20.9271 b b 53.4691 b 59,500 b 17.4191 b 15,939 32,224n \u00E2\u0080\u0094 \u00E2\u0080\u0094 ' 110,0511 \u00E2\u0080\u00A2 71,8611 33,400b .46,300 b 12.8391 ' ' \u00E2\u0080\u0094 205,408b 5.4531 \u00E2\u0080\u0094 N/A N/A N/A N/A N/A N/A 112,342 19,484 66,619 86,103 20,067 186 812 799 4,375 6,172 1,228,941 41,992 268,640 434,217 300,321 20,927 112,969 33,358 32,224 110,051 84,761 218,247 5,453 N/A 35,80s 1 24,215 1 3 .321 1 27,536 6,146 1,373J 93] 76. 584 1 2,126 26,618 1,926 6,641 11,011 4,959 i 1.619 1 4 , 4 3 s 1 1,02s 1 1.8321 1,2941 2.517 1 1.261 1 369 1 27,507\u00C2\u00B0 0.0644 0.0632 0.0672 0.0848 0.1145 0.0951 0.0508 0.0726 0.0438 0.0865 0.0374 0.0696 0.0590 0.0569 0.0118 0.0359 0.0982 0.0677 7,215 5,461 .1,348 15 93 \u00E2\u0080\u00A276' 222 406 73,599 3,469 10,047 30,221 1,968 1,832 1,294 2,967 21,432 369 27,507 N/A 59,330 l 59,330' 213 Trade Wholesale Trade Retail Trade Finance, Insurance and Real Estate Community, Business and Personal Service\u00E2\u0080\u00A2Industries Public Administration and Defence Industry Unspecified or Undefined N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 92,411 C\u00C2\u00BB J 28,747*; \u00E2\u0080\u00A2 6 3 , 6 4 7 C s J 20,510 c 103,983' 46,001C 15,997C 92,411 28,764 63,647 20,510 103,983 46,001 15,997 Totals 532,674 555,244 Sources: a) Stat ist ics Canada, 1966 Census of Canada - Agriculture, Br i t ish Columbia, 96-611, Vol. 5(5-4), Table 1. b) Peters (1969). c) Stat ist ics Canada, 1961 Census of Canada, \"Labour Force: Earnings, Hours and Wages by Industries and Provinces\", 94-542, Vol. Table 28. d) Stat ist ics Canada, 1961 Census of Canada. Agriculture, Br i t ish Columbia 96-540. e) Davis and Hainsworth (1970), Table 1. f) Stat is t ics Canada, Logging, 25-201, 1961. g) Stat ist ics Canada, Fisheries S ta t i s t i cs : Br i t i sh Columbia, 24-208, 1961. h) Stat is t ics Canada, Preliminary Estimate of Canada's Mineral Production 26-202, 1962. i ) Stat is t ics Canada, Manufacturing Industries of Canada. Section F. Br i t ish Columbia, Yukon arid Northwest Tern tor i es, 31-208, 1961, Table 6. j ) Stat ist ics Canada, 1961 Census of Canada, Wholesale and Retail Trade, 97-502, Table 4. 214 APPENDIX III - Allowable annual cut increases of individual f i rms 1 . Volume 1965 Volume - 1971 Volume Increase Sawmills Total Sawlog Portion Smallwood Portion Total Clearwater Timber Prod. Ltd. Birch Island Lumber Co. Ltd. Fadear Creek Lumber Co. Ltd. BIRCH ISLAND RANGER DISTRICT (R.D.2.) 2,559 3,075 5,878 4,100 BARRIERE RANGER DISTRICT (R.D.3.) 5,308 7,078 KAMLOOPS RANGER DISTRICT (R.D.4.) Kuchak, John 52 Lingren, W.F. 8 Long and Son Lbr. , Ltd. 226 Pondosa Pine Co. Ltd. 2,788 Balco Forest Prod. Ltd. 2,649 B.C. Interior Sawmills Ltd. 3,125 Buff Lumber Ltd. 524 Frolick Sawmills Ltd. (including Halston Lbr. L t d . , Terrace Forest Prod. L td . , Joseph Fro l i ck ) . 4,994 H.K. Lumber Ltd. 979 Kamloops Lumber Co. Ltd. 3,747 52 8 226 3,554 3,487 5,085 524 5,024 1,305 4,635 3,879 2,797 4,369 28 5 122 1,995 2,268 2,400 283 2,715 817 2,792 M cf per year 1,999 1,303 2,709 24 3 104 1,559 1,219 2,645 241 2,309 488 1,843 3,319 1,025 1,770 0 0 0 766 838 1,960 0 30 326 888 Sawlog Portion Smallwood Portion 1,320 \u00E2\u0080\u00A2 278 - 939 \u00E2\u0080\u00A2 24 3 \u00E2\u0080\u00A2 104 \u00E2\u0080\u00A2 793 \u00E2\u0080\u00A2 381 - 685 \u00E2\u0080\u00A2 241 -2,279 \u00E2\u0080\u00A2 162 \u00E2\u0080\u00A2 955 1,999 1,303 2,709 24 3 104 1,559 1,219 2,645 241 2,309 488 1,843 CHASE RANGER DISTRICT (R.D.5.) Blanc, C P . 16 21 13 Holding Lumber Co. Ltd. 4,549 6,066 3,937 SALMON ARM RANGER DISTRICT (R.D.6.) Cave, Phi l ip & Green, R.J. 12 16 10 Federated Co-operatives Ltd. 5,535 7,655 4,730 MacKay, A.R. 17 23 14 Raboch Sawmills Ltd. 4 5 3 Thielman, J .E . & G.W. 9 12 A'* 8 SICAMOUS RANGER DISTRICT (R.D.7.) MacLean Sawmills Ltd. 1,288 1,717 1,099 Shuswap Timber Ltd. 353 471 301 LILL00ET RANGER DISTRICT (R.D.8.) Seton Lake Lumber Co. Ltd. 50 67 40 Commercial Lumber Co. Ltd. 1,752 2,336 958 Beaton Bros. Lumber Co. Ltd. 22 29 17 CLINTON RANGER DISTRICT [R,D.12.) Cattermole - Thretheway 1,337 1,783 948 Contractors Ltd. Clinton Sawmills Ltd. 1,890 2,520 1,336 ASHCROFT RANGER DISTRICT (R.D.16.) Gateway Lumber Co. Ltd. 2,551 3,402 1,966 Savona Timber Holding Ltd, 4,343 5,731 3,138 8 2,129 5 1,517 3 612 2,129 6 2,925 9 2 4 4 2,120 6 1 2 805 3 1 1 6 2,925 9 2 4 618 170 429 118 189 52 618 170 27 958 12 17 584 7 10 374 5 27 958 12 835 1,184 446 630 - 389 - 554 835 1,184 1,436 2,593 851 1,388 - 585 -1,205 1,436 2,593 216 MERRITT RANGER DISTRICT (R.D.17.) Aspen P.V. Lumber Ltd. 731 945 537 Coldwater Lumber Co. Ltd. 411 548 323 Drew Sawmills Ltd. 97 97 52 Kamloops Pulp & Paper Co. Ltd. 3,345 4,409 2,509 Nick!en Logging Co. Ltd . 374 497 283 Nicola Valley Sawmills Ltd. 2,396 3,195 1,821 Roth, Balser Sawmill 63 84 48 BLUE RIVER RANGER DISTRICT (R.D.I8.) Blue River Sawmills Ltd. 1,251 1,668 1,101 Janes, Art 22 29 19 Yellowhead Sawmills Ltd. 674 899 593 Kamloops Pulp & Paper Co. Ltd. 2,413 3,217 2,123 100 MILE HOUSE (south1 RANGER DISTRICT (R.D.24.) Greenlake Forest Prod. Ltd. 614 818 461 Komori Equipment Ltd. 1,210 1,613 936 Totals 67,363 90,829 5.4,254 1, Source: Appendix I, Table 1 and Table .15, \ 408 225 45 1,900 214 1,374 36 214 137 0 1,064 123 799 21 567 10 306 1,094 417 7 225 804 194 88 45 836 91 575 15 408 225 45 1,900 214 1,374 36 150 3 81 290 567 10 . 306 1,094 357 677 204 403 - 153 - 274 357 677 36,575 23,466 -13,109 36,575 "@en . "Thesis/Dissertation"@en . "10.14288/1.0075364"@en . "eng"@en . "Forestry"@en . "Vancouver : University of British Columbia Library"@en . "University of British Columbia"@en . "For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use."@en . "Graduate"@en . "The use of regional economic techniques to analyze forest policy impacts : the case of the impact of close utilization policy on the level of employment within the Kamloops region"@en . "Text"@en . "http://hdl.handle.net/2429/18929"@en .