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Gentrification : an intra-urban predictive model Tourigny, Mark Claude 1988

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GENTRIFICATION:  AN INTRA-URBAN PREDICTIVE MODEL  by MARK CLAUDE TOURIGNY •A.  (English Literature),  The U n i v e r s i t y  Columbia,  A THESIS SUBMITTED IN  of  British  198 6  PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE (BUSINESS  ADMINISTRATION)  in THE FACULTY OF GRADUATE STUDIES Commerce and B u s i n e s s  We a c c e p t t h i s to  the  thesis  required  THE UNIVERSITY  as  conforming  standard  OF BRITISH COLUMBIA  JUNE ©  Administration  1988  Mark C l a u d e T o u r i g n y ,  1988  In presenting  this thesis in partial fulfilment  of the  requirements for an advanced  degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department  or  by  his  or  her  representatives.  It  is  understood  that  copying or  publication of this thesis for financial gain shall not be allowed without my written permission.  Department of  (Xrlpg^  /-o ^  d  The University of British Columbia 1956 Main Mall Vancouver, Canada V6T 1Y3 Date  DF.fin/ft-n  fcip  siv^x't^  ^  fw^li^  0  f  &u<>> A<hb  ABSTRACT  S i n c e 1970, the  domain o f  dilapidated groups. the  many i n n e r - c i t y  low-income  As a consequence, c a p i t a l  phenomenon i s  and p r i c e  analyzes  of  reviews  gentrification  the  the  a l a g between t h e  start  of  increased  housing.  This  "gentrification." gentrification  t e s t the first  literature,  r e a l housing p r i c e s .  prices  can, therefore,  following  stetge  demographic t r a n s i t i o n ,  rising  central  has  w i t h i n an e c o n o m i c f r a m e w o r k ,  uses r e g r e s s i o n a n a l y s i s to is  socio-economic  invested  inner-city  commonly c a l l e d  This thesis  were  groups occupying cheap,  h o u s i n g have a t t r a c t e d h i g h e r  condition  There  neighbourhoods t h a t  of  be p r e d i c t e d  hypothesis:  gentrif ication,  and t h e  An i n c r e a s e  in  second real  undergo  stage,  housing  by o b s e r v i n g  neighbourhoods are beginning t o  and  which demographic  change. The i n t r a - u r b a n thesis the  regresses the  1970s a g a i n s t  1960s.  gentrification  the  The s a m p l e  Vancouver,  change i n  is  Ottawa-Hull,  housing prices  i n d e e d be p r e d i c t e d neighbourhoods are  for  r e a l housing p r i c e s  95  inner-city and  census t r a c t s  the  from  Toronto.  in gentrifying  analysis  to  is  that  neighbourhoods  by o b s e r v i n g w h i c h starting  this  during  change i n demographics d u r i n g  The c o n c l u s i o n from s t a t i s t i c a l rising  model d e s i g n e d  can  inner-city  undergo demographic  change.  ii  TABLE OP CONTENTS  ABSTRACT  i  L I S T OF T A B L E S  v i  L I S T OF F I G U R E S 1.  v i i i  INTRODUCTION  2. L I T E R A T U R E  i  1  REVIEW  4  " R I N G E D " S T R U C T U R E THEORY  4  G E N T R I F I C A T I O N THEORY  6  Demographic  7  Economic  8  Urban Amenities  10  Housing Market  10  Government P o l i c y  13  Gentrification  13  Stages  Future G e n t r i f i c a t i o n ESTIMATION  MODELS  14 15  Inter-urban Gentrification  15  Intra-urban Gentrification  18  C H A P T E R SUMMARY 3. G E N T R I F I C A T I O N  I N A N ECONOMIC FRAMEWORK  H O U S I N G MARKET BACKGROUND Demand Supply  22 25 25 25  .  Capital  Stock  27 29  FILTRATION  29  GENTRIFICATION  31  i i i  CHAPTER 4.  A  SUMMARY  CANADIAN  33  INTRA-URBAN  G E N T R I F I C A T I O N MODEL  35  MODEL  37  Premise  37  Sample  37  Dependent  Variables  Explanatory Data  Variables  42  Limitations  EXTENSIONS CHAPTER  47  TO T H E MODEL  48  SUMMARY  Regression 5.  41  50  Equations  51  DATA A N A L Y S I S  53  CORRELATION  ANALYSIS  53  Variables  53  Cities  57  Lag  60  REGRESSION  ANALYSIS  61  Explanatory  V a r i a b l e s from  Explanatory  V a r i a b l e s , Both  Comparison CHAPTER  Between  One P e r i o d  Models  SUMMARY  6. S U M M A R Y , C A V E A T S ,  Periods  Pooled  62 ...  69 71 74  AND CONCLUSION  76  SUMMARY  76  CAVEATS  79  CONCLUSION  80  REFERENCES  82  APPENDIX  84  A  iv  APPENDIX B  92  APPENDIX C  100  APPENDIX D  108  APPENDIX E  109  v  L I S T OF  TABLES  1  Summary o f  2  % Change i n H o u s i n g P r i c e s p e r Room Relative  to  Correlation Analysis  the  54  CMA  56  3  Summary o f M u l t i p l e  4 5  Comparison o f "Best Model" A d j u s t e d R s Summary: Multiple Regression of Period 2 G e n t r i f i c a t i o n against Pooled Period 1 and 2 D e m o g r a p h i c E x p l a n a t o r y V a r i a b l e s  6  F - S t a t Comparison of Value2 Complete v s Reduced Models Correlation Matrix,  8  Correlation Value,  10  63 66  2  7  9  Regression Analysis  3 Cities  Value,  73 Combined Rent  84  and 85  Vancouver  Coefficients  86  f o r Rent  and  Vancouver  11  Correlation Matrix,  12  Correlation Value,  for  2  Combined  Correlation Matrix, Correlation  Regression R s :  3 Cities  Coefficients  70  87 Ottawa-Hull  Coefficients  for  Rent  88 and  Ottawa-Hull  13  Correlation  14  C o r r e l a t i o n C o e f f i c i e n t s f o r Rent and Value, Toronto M u l t i p l e Regression of Rent, 3 C i t i e s Combined M u l t i p l e Regression of Value, 3 C i t i e s Combined  93  17  Multiple  Regression of Rent,  94  18  Multiple  Regression of Value,  19  Multiple  Regression of Rent,  20  Multiple  Regression of Value,  21  Multiple  Regression of Rent,  15 16  Matrix,  89 Toronto  90  91 92  Vancouver Vancouver Ottawa-Hull Ottawa-Hull Toronto  95 ....  96  ...  97 98  vi  22  Multiple  23  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2 , a g a i n s t P e r i o d 1 and P e r i o d 2 Explanatory Variables Pooled, 3 C i t i e s Combined  100  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2, a g a i n s t S e l e c t e d P e r i o d 1 a n d Period 2 Explanatory Variables Pooled, 3 C i t i e s Combined  101  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2 , a g a i n s t P e r i o d 1 and P e r i o d 2 Explanatory V a r i a b l e s Pooled, Vancouver  102  M u l t i p l e R e g r e s s i o n o f Rent and V a l u e , P e r i o d 2, a g a i n s t S e l e c t e d P e r i o d 1 and Period 2 Explanatory Variables Pooled, Vancouver  103  24  25  26  27  28  29  30  31  Regression of Value,  Toronto  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2, a g a i n s t P e r i o d 1 a n d P e r i o d 2 Explanatory Variables Pooled, Ottawa-Hull  99  ...  104  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2, a g a i n s t S e l e c t e d P e r i o d 1 and Period 2 Explanatory Variables Pooled, Ottawa-Hull  105  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2 , a g a i n s t P e r i o d 1 and P e r i o d 2 Explanatory Variables Pooled, Toronto  106  M u l t i p l e R e g r e s s i o n o f R e n t and V a l u e , P e r i o d 2, a g a i n s t S e l e c t e d P e r i o d 1 a n d Period 2 Explanatory Variables Pooled, Toronto  107  C a l c u l a t i o n of F - s t a t i s t i c f o r Comparison Between Reduced and C o m p l e t e M o d e l Value R s  108  2  vii  L I S T OF FIGURES  1  Neighbourhood  2  Optimal Maintenance  3  Vancouver Inner-City Housing P r i c e I n c r e a s e s R e l a t i v e t o CMA, 1 9 7 1 - 1 9 8 1  38  Ottawa-Hull Inner-City Housing P r i c e I n c r e a s e s R e l a t i v e t o CMA, 1 9 7 1 - 1 9 8 1  39  Toronto Inner-City Increases Relative  40  4 5  Housing Market Strategy  Housing t o CMA,  Price 1971-1981  26 26  v i i i  CHAPTER 1  INTRODUCTION  "Gentrification" post-1970  i s one o f many l a b e l s g i v e n t o  phenomenon o f  rejuvenation. "inner-city  revitalization,"  "urban r e - i n v a s i o n "  the  same phenomenon: domain o f  dilapidated,  neighbourhood  O t h e r names i n c l u d e " r e v e r s e  and  were t h e  inner-city  "inner-city  (Hamnett,  the  rehabilitation,"  1984).  many c e n t r a l - c i t y  filtration,"  They a l l  refer  to  neighbourhoods that  low-income groups o c c u p y i n g cheap,  "filtered"  socio-economic groups.  h o u s i n g have a t t r a c t e d As a consequence,  higher  capital  i m p r o v e m e n t s made by t h e h i g h e r - i n c o m e g r o u p s h a v e increased the  c o n d i t i o n and p r i c e o f  (Berry,  Ley,  1985;  The  1985;  Hamnett,  literature posits that  gentrification,  attracted  CBD  (Central  and  by i t s  effect  i n the  Business D i s t r i c t )  is  high;  income i s s t i l l  limited.  Once t h e r e  of  low-paid  proximity  There i s  This f i r s t  low s o c a p i t a l  no  immediate  group  of  remain  investment  h a s b e e n some m o d e r a t e r e n o v a t i o n first  s p e c u l a t o r s and h i g h e r  group o f  to  amenities  s m a l l so neighbourhood v a c a n c i e s  t h e h o u s i n g s t o c k by t h i s however,  relatively  employment a n d  cheap h o u s i n g .  gentrifiers  stage  an i n n e r - c i t y n e i g h b o u r h o o d .  on h o u s i n g p r i c e s , t h o u g h .  their  earliest  t o the neighbourhood by i t s  relatively  housing  1984).  a few w e l l - e d u c a t e d b u t  y o u n g p r o f e s s i o n a l s move i n t o They a r e  inner-city  is to  gentrifiers,  income g r o u p s a r e  attracted  1  to  the  1985;  n e i g h b o u r h o o d and b i d up p r i c e s Melchert  In  other  and N a r o f f , words,  (Berry,  Ley,  1987).  housing p r i c e s  in a  neighbourhood f o l l o w  a l o g i s t i c S-curve  Melchert  and N a r o f f ,  1987).  initial  change i n t h e  neighbourhood t h a t  1985;  There  is  gentrifying (Ley,  a l a g between  demographic m i l i e u  is gentrifying  1985;  of  and t h e  an  the  inner-city  rise  in  neighbourhood housing p r i c e s . The p u r p o s e o f model d e s i g n e d t o there  is  consequent r i s e inner-city  thesis  is  t e s t what t h e  a l a g between  in a gentrifying  price  this  the  inner-city  to  present  literature  start  of  neighbourhoods w i l l  demographic  educated,  s i n g l e s and c h i l d l e s s c o u p l e s b e g i n t o move Gentrification  the  and have  i n c r e a s e s by o b s e r v i n g which ones a r e  Since  transition  one c a n p r e d i c t  gentrify  demographic change as y o u n g , w e l l  regression  implies:  n e i g h b o u r h o o d and  in housing p r i c e s ,  a  which  future  undergoing CBD e m p l o y e d in.  c a n be m e a s u r e d two w a y s :  socio-  economic change i n a n e i g h b o u r h o o d o r h o u s i n g market (Ley  1985).  increase total the  T h i s t h e s i s measures g e n t r i f i c a t i o n  in central-city  housing p r i c e s r e l a t i v e  CMA ( C e n s u s M e t r o p o l i t a n  change i n r e n t s  and d w e l l i n g  neighbourhoods r e l a t i v e to to  1981  to  1971.  against  the  values  The m o d e l in  CMA d u r i n g t h e  from t h e  Ottawa-Hull,  and  inner-city  by  the  to  the  regresses  city-centre  demographic changes d u r i n g the  The s a m p l e i s  of Vancouver,  Area).  change  period period  census  1971 1961  tracts  Toronto.  2  The model assumes t h a t c e n t r a l r i s i n g rents  and v a l u e s r e l a t i v e t o  gentrifying,  i.e.,  c o n d i t i o n are reasonable wrong,  however,  In  most c a s e s ,  One example  rise  is  if  an i n n e r - c i t y  r i s e because of  assumption  a  is  residential  commercial.  improved but  rezoning.  assumption i s  Rents  increased dwelling  Rising values  will  and  values  in this  case  will is  gentrification. There are  introductory literature Chapter  five  one.  for  chapters Chapter  theories  following  2 reviews  explaining  Canadian i n t r a - u r b a n this  thesis.  Chapter  6 summarizes the  and c o n c l u s i o n s o f  the  thesis  anticipate  rejuvenation. an  inner-city  4 describes  r e g r e s s i o n model  the  results  and d i s c u s s e s  of  the  the  the in model.  caveats  analysis.  The c o n c l u s i o n s from t h i s s o c i a l planners  gentrification  affects  Chapter  5 presents  first  inner-city  gentrification  Chapter  this  the  3 e x a m i n e s how g e n t r i f i c a t i o n  neighbourhood's housing market.  to  the  b e c a u s e h o u s i n g demand h a s n o t  h o u s i n g c o n d i t i o n has not  not  CMA a r e  o f when t h e  neighbourhood has been rezoned t o not  the  with  n e i g h b o u r h o o d h o u s i n g demand a n d  rising.  one.  neighbourhoods  thesis will  and d e v e l o p e r s ,  be o f  interest  b o t h o f whom e n d e a v o r  to  h o u s i n g demand and p r i c e s .  3  CHAPTER 2 LITERATURE REVIEW  T h i s c h a p t e r b e g i n s by summarizing  theories  f o r the  " r i n g e d " s t r u c t u r e t h a t c h a r a c t e r i z e d pre-1970 urban (the  poor  the c i t y  living  periphery).  gentrification city  at the city  c e n t r e and t h e r i c h  design  living at  The c h a p t e r t h e n r e v i e w s t h e  literature  f o rtheories explaining  inner-  r e j u v e n a t i o n and f o r e s t i m a t i o n models d e s i g n e d t o  predict i t .  "RINGED" STRUCTURE THEORY The urban  "ringed" structure that characterized  d e s i g n was t h e r e s u l t  stock.  of " f i l t r a t i o n "  and s t y l e o b s o l e s c e n c e o f a g i n g  h o u s i n g p r o m p t e d h i g h e r income g r o u p s  all  o f the housing  Lowry n o t e s t h a t b o t h p h y s i c a l d e t e r i o r a t i o n a n d  technological  (Lowry,  pre-1970  1960).  households  Muth s u g g e s t s t h a t  central-city  t o seek  new  as t h e r e a l  i n c r e a s e d over time,  housing  incomes o f  a l l income  groups  increased the q u a n t i t y of t h e i r housing over time 1969). advanced city  S i n c e t h e newest, l a r g e s t ,  a n d most  technologically  h o u s i n g was c o n s t r u c t e d i n s u c c e s s i v e r i n g s  p e r i p h e r y where v a c a n t  l a n d was a v a i l a b l e ,  k e p t m o v i n g f u r t h e r away f r o m t h e c i t y wealthy  (Muth,  core.  income g r o u p next group,  whose v a c a t e d h o u s i n g , and so on.  As a r e s u l t ,  i n turn,  t h e wealthy  Each  moved, t h e i r v a c a t e d h o u s i n g a t t r a c t e d  a t the  time the  the next  attracted the  the housing  stock  4  "filtered"  down t h e  income h i e r a r c h y .  the d i s c a r d e d housing at h o u s i n g was l e a s t Filtration  the  (Berry,  city  inherited  c o r e where demand  of the housing stock i s a r e s u l t  older central-city  r e c e i v e d by t h e  revenues,  of  supply  Lowry e x p l a i n s t h a t  housing decreased, the  l a n d l o r d s decreased as w e l l .  reduction in their  for  1985).  d e c i s i o n s a s w e l l a s demand o n e s . demand f o r  The p o o r  as  rent  To o f f s e t  landlords reduced or  the  stopped  m a i n t e n a n c e and t h u s h a s t e n e d t h e p h y s i c a l d e t e r i o r a t i o n central-city e v e n more  housing stock.  (Lowry,  As a r e s u l t ,  Warner's the  half  centre t r i e d  ringed urban  theory.  of t h i s  century,  effecting outward  a succession of  (Short,  1984).  this  and  the  during  city  invading  r i n g o f h o u s i n g whose  invaded the next  ring,  and s o o n ,  income g r o u p s b e i n g " p u s h e d "  Warner t e l l s  innovations s t a r t i n g with the of  residents of  t o d i s t a n c e themselves from  in turn,  theory  Burgess e x p l a i n s t h a t  i m m i g r a n t s by i n v a d i n g t h e n e x t residents,  structure  " i n v a s i o n and s u c c e s s i o n "  "streetcar"  first  demand d e c r e a s e d  1960).  Other explanations of the include Burgess's  o f how  streetcar  century allowed the wealthy  i n the flee  "rural  grime  The p o o r were p r o h i b i t e d b y commuting  (Warner,  the  from t h e  part  of  costs  core to  early  industrial  suburbs.  city  to  transportation  and n o i s e o f t h e the  of  ideal"  1962).  5  GENTRIFICATION THEORY B e f o r e b e g i n n i n g t h e d i s c u s s i o n on resurgence,  one must f i r s t  note t h a t not a l l  neighbourhoods d e t e r i o r a t e d Hamnett  reports that there  neighbourhoods i n the U . S . centres  (Hamnett,  central-city inner-city  as f i l t r a t i o n t h e o r y h a v e b e e n many  predicts.  elite  t h a t have p e r s i s t e d i n  city  1984).  Ley notes t h a t Canadian c i t y  c e n t r e s have  not  degenerated to the  degree t h a t American ones have because  of three  the  and i t s  reasons: negative  relative  externalities,  absence o f heavy the  c o n t i n u i n g presence of  t h e m i d d l e - c l a s s , and o n g o i n g p r i v a t e (Ley,  1986).  system the  Two o t h e r  induced f l i g h t  Canadian welfare  institutionalized from c i t y  ( G o l d b e r g and M e r c e r ,  With the  trend  investment  (Canadian poor are not as poor as American poor)  racially  review  sector  reasons are the  a b s e n c e i n Canada o f  class)  industry  c e n t r e s by t h e  (no middle-  1979).  a b o v e s t i p u l a t i o n made, we c a n now move t o  of g e n t r i f i c a t i o n of  racism  and  inner-city  theories  resurgence.  e x p l a i n i n g the I  will  rely  a  post-1970  primarily  on  two p a p e r s t h a t h a v e s u m m a r i z e d t h e v o l u m i n o u s gentrification  literature:  Hamnett's  "Gentrification  and  R e s i d e n t i a l Location Theory:  A Review and A s s e s s m e n t "  (1984)  Explanations for  and L e y ' s  Gentrification:  "Alternative  A Canadian Assessment" (1986).  G e n t r i f i c a t i o n e x p l a n a t i o n s c a n be s o r t e d , done,  into  Inner-City  four mutually  as Ley has  non-exclusive categories:  6  demographic, A fifth  economic,  explanation  Demographic:  urban a m e n i t i e s ,  i s government The p o s t w a r  s u r g e i n h o u s i n g demand a s i t the  1970s.  policy.  b a b y boom c o h o r t entered  As household f o r m a t i o n  central-city  a reduction  decrease rate,  the  increase  increase  of  families  (two  contributed  rates,  of  single-parent,  to  accommodated t h i s Contributing  i n the  Smith notes portion  of  1960s a n d t h e  i n the  childless,  1987).  relatively  the  divorce and  individuals)  all the  i n household s i z e  i n the  professional,  work f o r c e , breaking  the  down o f  f e m a l e work high-income  for  improved,  opportunity  CBD j o b s .  been a  large  feminist  movement  "sexual  apartheid"  Berry,  as  closed to  of  the  made many women  in  them  economic  women grew a n d b i r t h - c o n t r o l cost of  during  force,  occupations accessible to  According to  1970s.  neighbourhoods  to  decrease  the  non-nuclear  households.  the  buyers  The  growth i n s m a l l  opportunities the  of  and  1970s t h a t h a d b e e n t r a d i t i o n a l l y  (Smith,  1970s.  tripling  central-city  high-paying professional the  the  in  pressure  f i r s t - t i m e home  t h a t w h i l e women h a v e a l w a y s the  to  the  b u r g e o n i n g h o u s i n g demand o f  1970s was an i n c r e a s e  especially  the  o r more u n r e l a t e d the  h o u s i n g market  single-person households,  Medium and h i g h - d e n s i t y  the  growth i n  i n household s i z e  i n marriage  cohort  caused a  neighbourhoods.  Associated with t h i s is  the  increased,  on s u b u r b a n h o u s e p r i c e s d r o v e t h e inexpensive  and h o u s i n g m a r k e t .  child-rearing  techniques rose  7  (Hamnett,  1984).  A third  demographic e x p l a n a t i o n  urban sprawl.  As  commuting t i m e t o CBD  especially  since the  escalated,  the  to  became a t t r a c t i v e .  the  point  CBD out,  for gentrification  1973  o i l embargo, commuting  accessibility  however, t h e  of c e n t r a l - c i t y As  commuting  Ley  minority are  inner-city gentrifiers  are  t y p i c a l l y y o u n g u r b a n i t e s who  The  gentrification  show t h a t o n l y Instead,  second g e n e r a l  w h i t e - c o l l a r employment. growth i n the Canada was  a  gentrifiers  explanation  has  increased,  so h a s  As  is  growth i n s e r v i c e  reports that the  industries.  the  for  and  the  1981  in resource  downtown work  the d e s i r a b i l i t y  of  and  percentage  f o u r times g r e a t e r than job growth i n  manufacturing  in  speculated.  s e r v i c e s e c t o r b e t w e e n 1971  and  true.  small  Gentrification  industrial Ley  both  choose t o remain  form households.  i s the post  neighbourhoods  Hamnett  a b a c k - t o - t h e - c i t y movement a s w i d e l y Economic:  costs  empirically hold  returning suburbanites.  i n n e r - c i t y when t h e y not  and  and,  cost/accessibility  argument f o r g e n t r i f i c a t i o n does n o t Surveys of  employment  is  force  proximate  neighbourhoods. W h i l e CBD  w h i t e - c o l l a r employment h a s  m a n u f a c t u r i n g employment has t h a t m a n u f a c t u r i n g has the to  s u b u r b s f o r two relatively  manufacturing  suburbanized.  moved t o t h e  reasons:  inexpensive  First,  risen, Mills  less expensive the  rail  land  change from  t r u c k t r a n s p o r t a t i o n has  f r o m l o c a t i n g n e a r CBD  explains  yards.  of  rail  freed Second,  8  the  change i n p r o c e s s i n g t e c h n o l o g y has  m a n u f a c t u r i n g from a l a n d i n t e n s i v e , to  a land extensive,  collar city  horizontal  one  transformed  vertical (Mills,  changing economic base o f into  a global perspective,  how a new i n t e r n a t i o n a l  d i v i s i o n of  Bluethe  administrative  s t a p l e s from d e v e l o p i n g n a t i o n s The a d v e n t  the w o r l d ' s a d m i n i s t r a t i v e  conducted p r i m a r i l y  of  new d i v i s i o n o f  trade  activities  are  i n t h e West w h i l e m a n u f a c t u r i n g o n e s  done i n t h e d e v e l o p i n g n a t i o n s . l a b o u r are as  The r e a s o n s f o r  this  follow:  Cheap o c e a n i c t r a n s p o r t a t i o n c o r p o r a t i o n s to manufacture  allows i n the  d e v e l o p i n g n a t i o n s and e x p o r t the  No  c o r p o r a t i o n s has changed i n t e r n a t i o n a l  Now,  the  service/  and t h e n s h i p b a c k m a n u f a c t u r e d g o o d s .  patterns.  Cohen e x p l a i n s  s e c t o r i n western developed n a t i o n s .  l o n g e r d o e s t h e West i m p o r t  multinational  postindustrial  l a b o u r has reduced  m a n u f a c t u r i n g s e c t o r and i n c r e a s e d t h e  2)  1972) .  centre to the suburbs.  western c i t i e s  1)  activity  h o u s e h o l d s have f o l l o w e d m a n u f a c t u r i n g o u t o f  To p u t t h e  are  flow  multinational cheap-labour  f i n i s h e d goods back  to  West.  Today's technology allows  instantaneous communication  between t h e w e s t e r n head o f f i c e s and t h e d e v e l o p i n g nation branch p l a n t s . 3)  Developing nations boost t h e i r exporting  manufacturing  s e c t o r s by e n c o u r a g i n g  subsidiaries to  locate  and  multinational  there.  9  As a consequence o f t h i s labour, while  new i n t e r n a t i o n a l  d i v i s i o n of  the manufacturing s e c t o r has d e c r e a s e d i n the  CBD w h i t e - c o l l a r  employment h a s grown  G e n t r i f i c a t i o n was f a c i l i t a t e d  by e d u c a t e d ,  (Cohen,  West  1981).  administrative  and p r o f e s s i o n a l CBD e m p l o y e e s l o c a t i n g c l o s e t o  their  jobs. Urban A m e n i t i e s : "gentry" couples  are t y p i c a l l y (Berry,  non-nuclear the  C o n v e n t i o n a l wisdom i s t h a t  amenities  amenities  the upwardly m o b i l e young c h i l d l e s s  1985).  families  With the  i n the  of the c i t y  of the  entertainment,  the  1970s,  centre  suburbs.  i n c r e a s e i n c h i l d l e s s and gentry  over the  Proximity to  restaurants,  households chose child  city  related  culture,  and employment became  favoured  o v e r s c h o o l s and p l a y g r o u n d s . The V i c t o r i a n a r c h i t e c t u r e became p o p u l a r .  of  central-city  I n n e r - c i t y neighbourhoods t h a t  housing were  c o n s i d e r e d h i s t o r i c a l p r e s e r v a t i o n a r e a s w e r e d e s i r e d by the  gentrifiers.  gentrifiers  were a t t r a c t e d  in dilapidated The l e s s " s w e a t the b e t t e r  Melchert  equity"  (Melchert  gentrification  Much o f t h e increase  to  found  that  older housing that,  c o n d i t i o n , was o f g o o d s t r u c t u r a l  Housing Market: effect  and N a r o f f  required to  and N a r o f f ,  restore  quality.  the housing,  1987).  Housing market  factors that  a r e b o t h demand and s u p p l y  gentrification  although  helped related.  literature posits that  the  i n demand f o r h o u s i n g i n c o n j u n c t i o n w i t h  i n c r e a s i n g mortgage r a t e s  i n the  1970s c a u s e d a n  10  affordability  c r i s i s for  first-time  home b u y e r s .  T h e baby  boom home b u y e r s were c o n s e q u e n t l y f o r c e d t o  the  cheap h o u s i n g o f the c i t y  not c h o i c e .  As Ley p o i n t s o u t , two-fold: the  First,  inner-city  however,  the  over the  and f a m i l i e s ,  Second,  choice of  some h i g h e r  prefer  status  typically  not  crisis.  arguments  f o r the  resurgence of  n e i g h b o u r h o o d s c a n be made f r o m a s u p p l y  perspective:  reverse f i l t r a t i o n ,  the  inverse  relationship  between new h o u s i n g c o n s t r u c t i o n a n d r e h a b i l i t a t i o n , the  rent  is  inner-city  households that are  Three h o u s i n g market centre  argument  suburbs.  a f f e c t e d b y an a f f o r d a b i l i t y  city  flaw i n t h i s  s u r v e y s show t h a t most g e n t r i f i e r s  n e i g h b o u r h o o d s were t h e renters  c e n t r e by d e f a u l t ,  relatively  and  gap.  Filtration inner-city  d e s c r i b e s how d e c r e a s i n g demand  housing p r i o r to  1970  led to  r e d u c e d maintenance by l a n d l o r d s .  housing " f i l t e r e d " Conversely,  down t h e  By t h i s  of the process,  central-city  central-city  t o d e m o g r a p h i c and employment c h a n g e s i n t h e encouraged l a n d l o r d s t o more r e n t .  renovate  Reverse f i l t r a t i o n ,  rehabilitation  of the  inner-city  so t h a t they therefore,  (Lowry,  1960).  h o u s i n g due 1970s could collect  led to  the  housing stock.  Berry argues t h a t r e h a b i l i t a t i o n inversely related  and  h o u s i n g and t h u s  income h i e r a r c h y  i n c r e a s e d demand f o r  rents  Reduced maintenance  hastened the p h y s i c a l d e t e r i o r a t i o n d e c r e a s e d demand f u r t h e r .  lower  for  of  to the b u i l d i n g c y c l e .  older housing i s When t h e  supply  11  of  new h o u s i n g d e c l i n e s b e c a u s e o f  high interest  rates,  renovating  existing  formations  i n the  economic r e a s o n s ,  h o u s i n g demand i s supply.  The s u r g e o f h o u s e h o l d  Consequently, the  f o r h o u s i n g was accommodated by t h e housing (Berry,  Smith,  large  approach to g e n t r i f i c a t i o n .  financial  institutions  The most e f f i c i e n t  h o u s i n g market  i s to  because of  vacant  land,  are  finance  their  large  requirement  typically  compete f o r  funds; therefore,  housing w i l l  and t h e  large  rent  housing i f  the  received for  its  As s t a t e d explanations,  it  is  the  large  (Smith, earlier  funds i n  of  cannot central-city  until  difference  Inner-  there  between  and t h e  According to  invest  of  city  homeowner  1970s f o r  the  developments  tracts  the  rehabilitated  enough i n t h e to  S m i t h who  housing d e t e r i o r a t e s .  "rent gap",  institutions  redevelopment  for  maintenance  existing use.  r e n t g a p was l a r g e financial  their  continue to deteriorate  sufficiently for  central-  capital  residential  i n suburbs at  The s i n g l e c e n t r a l - c i t y  housing i s c u r t a i l e d  of  According to  maximize  use of  periphery.  city  renovation  i s championed by N e i l  accumulation.  that,  b a b y boom demand  1980).  The " r e n t gap" t h e o r y a Marxist  of  and r e c e s s i o n i n w h i c h new h o u s i n g  construction lagged.  takes  by  1970s was c o n c u r r e n t w i t h a p e r i o d  combined i n f l a t i o n  city  satisfied  e.g.,  Smith,  a  the  rent the  developers  in central-city  is  and  housing  1982). i n the  gentrification  d i s c u s s i o n on d e m o g r a p h i c was f o u n d n o t  to  be a  12  b a c k - t o - t h e - c i t y movement a s w i d e l y b e l i e v e d . literature  The  s u g g e s t s , however, t h a t g e n t r i f i c a t i o n may i n  f a c t be a b a c k t o - t h e - c i t y movement o f c a p i t a l  rather  than  people. Government P o l i c y : gentification that public  The f i f t h  explanations  s e c t o r redevelopment  redevelopment  o f an  i n Vancouver  Ley notes  inner-city  the catalyst  f o r private  of the surrounding area.  s p e c t a c u l a r example i s t h e m u n i c i p a l Creek  category of  i s government p o l i c y .  n e i g h b o u r h o o d has o f t e n been market  and f i n a l  T h e most  redevelopment  that precipitated private  of False  redevelopment  of neighbouring Fairview Slopes. Government i n v o l v e m e n t i n i n n e r - c i t y c a n , however, h a v e a d e s t a b i l i z i n g  effect.  Mercer argue t h a t t h e r e l a t i v e v i t a l i t y c e n t r e s compared t o A m e r i c a n l e s s government i n t e r v e n t i o n . programs  i n t h e U.S. d i s t o r t  where t h e p r o g r a m s  ones  contrast,  Canadian  neighbourhood  t r u e market  demands  renewal markets  creates  investment.  redevelopment  (Goldberg and Mercer,  that during the e a r l i e s t  i n part to  housing  Investment has been  G e n t r i f i c a t i o n Stages:  no e f f e c t  This  city  As a  continues to deteriorate.  inner-city  predominantly p r i v a t e .  o f Canadian  Large-scale urban  a r e implemented.  t h e neighbourhood  G o l d b e r g and  i s attributed  u n c e r t a i n t y which d i s c o u r a g e s p r i v a t e result,  rehabilitaion  In  has been i n response t o  1979) .  Most o f t h e l i t e r a t u r e  reports  stage o f g e n t r i f i c a t i o n there i s  on n e i g h b o u r h o o d h o u s i n g p r i c e s .  Well-educated  13  but  still  and  c o u p l e s , as w e l l as s t u d e n t s and a r t i s t s ,  to the  relatively  inner-city  amenities,  l o w - p a i d young p r o f e s s i o n a l s i n g l e s  by i t s  proximity  and cheap h o u s i n g .  of housing r e h a b i l i t a t i o n ,  i.e.,  d e v e l o p e r s and h i g h e r  neighbourhood.  moderate first  attracted  CBD e m p l o y m e n t ,  Only a f t e r  t h e h o u s i n g s t o c k made b y t h i s do  to  are  there  is  evidence  renovations  wave o f  income g r o u p s i n v e s t  Ley,  in  T h i s s e c o n d wave o f g e n t r i f i e r s  1983;  Melchert  and N a r o f f ,  Future G e n t r i f i c a t i o n : hand,  the  the f o r c e up  1980s:  Hamnett muses t h a t ,  First,  the b i r t h r a t e has d i m i n i s h e d the cohort.  Second,  the mid-1960s  s i z e of the  current gentrifiers  white-collar On t h e much c a p i t a l  of  office  e m p l o y e e s away f r o m t h e o t h e r h a n d , Hamnett  inner-city  As w e l l ,  gentry  inner-city  rear  their  not in age  the there  t h a t might  is  draw  inner-city. is  too  neighbourhoods to be  Ley p o i n t s out t h a t g e n t r i f i e r s  to  one  decline  Third,  neighbourhoods w i l l  Canada i n c l u d e o l d e r e m p t y - n e s t e r s . leave the  will  reasons that there  invested in gentrified  expect that these abandoned.  decentralization  on t h e  20-30 y e a r  may move t o  s u b u r b s o n c e t h e y b e g i n t o have c h i l d r e n . now a t r e n d  (Berry,  1987).  demographic reasons f o r g e n t r i f i c a t i o n  c o n t i n u e beyond t h e  to  gentrifiers,  t h e demand a n d , c o n s e q u e n t l y , t h e p r i c e o f h o u s i n g 1985;  urban  Even i f families,  in  young c o u p l e s the  older  should remain.  14  ESTIMATION MODELS While  the gentrification  literature  abounds w i t h  d e s c r i p t i v e a n a l y s e s , t h e r e a r e few p r e d i c t i v e reported.  T h i s s e c t i o n o f t h e c h a p t e r r e v i e w s two  i n t e r - u r b a n g e n t r i f i c a t i o n models: model and t h e L o n d o n / L e e / L i p t o n urban  gentrification,  discussed.  David Ley's  U.S. m o d e l .  Ley's Canadian  Canadian  For intra-  m u l t i - c i t y model i s  No m u l t i - c i t y model f o r U.S. i n t r a - u r b a n  g e n t r i f i c a t i o n was f o u n d city  models  i n the literature  analyses are presented:  s o two s i n g l e -  the Melchert/Naroff  Boston  model a n d t h e Laska/Seaman/McSeveney New O r l e a n s o n e . Inter-urban G e n t r i f i c a t i o n : the p r e d i c t i v e a b i l i t i e s housing,  amenity,  Ley's  of thirty-five  1985 s t u d y  demographic,  and economic i n d e p e n d e n t  variables  a g a i n s t a r e v i t a l i z a t i o n dependent v a r i a b l e Canadian  CMAs.  proportional  change i n a CMA's i n n e r - c i t y  administrative  university  The  education.  sector  technical,  with a  dependent  as f o l l o w s : - 1971 % O u a r t e r n + % U n i v r 2  v a r i a b l e s were m e a s u r e d a t v a r i o u s t i m e s  during the t e n year period. primarily  managerial,  The r e v i t a l i z a t i o n  %Quarternary + %University 2  independent  quaternary  occupations) and persons  v a r i a b l e was c a l c u l a t e d 1981  f o r twenty-two  R e v i t a l i z a t i o n was m e a s u r e d a s t h e  b e t w e e n 1971 a n d 1981 ( p r o f e s s i o n a l , and  tested  from census  The d a t a was o b t a i n e d  a n d CMHC p u b l i c a t i o n s .  15  Ley found t h a t the revitalization The h i g h e s t capita only  at  were t h e  strongest simple c o r r e l a t i o n s e c o n o m i c and a m e n i t y  space per  D e m o g r a p h i c and h o u s i n g v a r i a b l e s  fared  modestly. Next,  multiple  after  finding excessive m u l t i c o l l i n e a r i t y  r e g r e s s i o n , Ley c o n d u c t e d a p r i n c i p l e  regression. method was  The h i g h e s t a d j u s t e d R .61.  p r e d i c t o r s of  2  inner-city  Ley summarizes h i s  his analysis,  f a c t o r s were t h e  inter-urban  best  towards  private  and/or not  public  complete—  Canadian i n n e r - c i t y  revitalization  during  A secondary c o n d i t i o n f o r  revitalization  was  inner-city  conducive to  offer  p h y s i c a l and c u l t u r a l  a high quality  of  life.  Contrary  literature,  f o r housing i n the  1970s d i d n o t h a v e more o f  Canadian i n n e r - c i t y  the  that  amenities  s p e c u l a t i o n i n the  (Ley,  Ley  a n a l y s i s by c o n c l u d i n g  s e r v i c e employment was a f u n d a m e n t a l — b u t  1970s.  this  revitalization.  t h a t economic o r i e n t a t i o n  condition for  during  components  achieved using  Consistent throughout  f o u n d t h a t e c o n o m i c and a m e n i t y  the  variables.  s i n g l e c o r r e l a t i o n was w i t h o f f i c e  .65.  with  to  t h e b a b y boom demand s u r g e an e f f e c t  n e i g h b o u r h o o d s t h a n on t h e  on  suburbs  1985). London e t  analysis  of  al.  c o n d u c t e d an i n t e r - u r b a n  forty-eight  v a r i a b l e s were t h e  U.S.  cities.  p r e s e n c e and t h e  The degree  gentrification  dependent of  gentrification  t h a t t h e s e c i t i e s had e x p e r i e n c e d by  1983.  Values  d e p e n d e n t v a r i a b l e s were o b t a i n e d b y  mailing  for  the  16  questionnaires to  sociology,  s t u d i e s departments cities. the  The q u e s t i o n n a i r e  T h e r e were e i g h t 1970  children,  capita  test  the  the  the  cultural  s i z e of  to  labour  estimate  the  was  force that  hypothesis that the the  cooperate  greater  the  from  b a b y boom  was the  number o f  per  historic  corporate headquarters,  The r e a l t o r  the  derived  population that  amenities,  presence of  realtors.  per c a p i t a ,  in  t h e p r o p o r t i o n t h a t was w h i t e - c o l l a r ,  number o f  number o f  of the  urban  cities.  independent v a r i a b l e s  the percentage  districts,  and  recipients  in their  the proportion of the  blue-collar,  to  asked the  census t h a t measured t h e  population,  science,  i n c o l l e g e s and u n i v e r s i t i e s  extent of g e n t r i f i c a t i o n  the  political  and  the  m e a s u r e was i n c l u d e d  fewer  the  the p o t e n t i a l  number o f ability  i n promoting g e n t r i f i c a t i o n  by  to  realtors  of  realtors  manipulating  market. London e t  analysis, signs.  all  al. the  found t h a t  in a simple  independent v a r i a b l e s  had t h e  anticipated  The s t r o n g e s t c o r r e l a t i o n w i t h g e n t r i f i c a t i o n  manufacturing multiple  employment a t - - . 4 1 .  The c o n c l u s i o n  r e g r e s s i o n was t h a t g e n t r i f i c a t i o n  t o h a v e o c c u r r e d i n c i t i e s w i t h low employment, presence, power  correlation  (although  adjusted R t-statistic  2  was  interestingly,  strong  b e t a was o n l y - . 0 8 ) .  .43;  only three than  2  was most  likely  corporate  high concentration  it's  greater  from  manufacturing  many h i s t o r i c d i s t r i c t s ,  and,  was  The  of  realtor  best  independent v a r i a b l e s  (London e t  al.,  had a  1986).  17  Comparing the gentrification literature,  Ley s t u d y o f  and t h e  Canadian  London e t  one must f i r s t  al.  inter-urban  American study to  question the  subjective  questionnaire  t h a t London u s e d t o m e a s u r e  Nevertheless,  both studies concur with the  the  importance  inner-city  of  in cities  s t u d i e s a l s o show t h a t , demographic v a r i a b l e s gentrification. market for  i n the  contrary  to  the  1970s b u t  data,  two d e p e n d e n t v a r i a b l e s  non-gentrified  ones)  and t h i r t y - f o u r  however,  individual  to  model b l o c k s and  independent  variables.  from t h e  197 0  U.S.  amenity,  s e l e c t the best p r e d i c t o r s  independent v a r i a b l e s  blocks into  Melchert  and  their  from  Naroff  f o u r c a t e g o r i e s by t h e m s e l v e s  in a logistic regression.  the  Naroff  (gentrified  independent v a r i a b l e s ,  f o u n d t h a t none o f t h e significant  and  Using  or economic.  using t-tests  thirty-four  model  blocks.  Their  C e n s u s a n d were c a t e g o r i z e d a s b e i n g e i t h e r  After  importance  Melchert  The i n d e p e n d e n t v a r i a b l e s were d e r i v e d  social,  housing  The M e l c h e r t / N a r o f f  which b l o c k s had g e n t r i f i e d .  consisted of  the  slight.  randomly s e l e c t e d Boston i n n e r - c i t y  identified  Both  in  L e y ' s study found i t s  was  and  literature,  p l a y e d a modest r o l e  Boston Redevelopment A u t h o r i t y  the  sector  about  t h a t have g e n t r i f i e d .  Intra-urban G e n t r i f i c a t i o n :  housing,  literature  The London s t u d y d i d n o t t e s t  gentrification  u s e d 437  gentrification.  a s t r o n g CBD w h i t e - c o l l a r  amenities  the  were  Collectively,  did accurately  respective gentrified  classify and  18  non-gentrified for  groups.  goodness o f  fit,  (eight degrees of Melchert gentry not  Using the  freedom)  and a p - v a l u e  and N a r o f f ' s  housing too o l d t h a t  preferred  Gentry  Boston Model  it  Neighbourhoods o f f e r i n g  indicated  used i n the  .05. that  (1900-1920)  would r e q u i r e  substantial  buffer  these  CBD employment  between  households  (Melchert  activity  in  highly  & Naroff,  gentrification  68 c e n s u s  existence,  extent,  and p e a k y e a r  Renovation  l e v e l s were m e a s u r e d b y t h e  sales  i n a census t r a c t .  level  of  Laska et  ownership t r a n s f e r s  of housing r e h a b i l i t a t i o n . measuring the  characteristics  of  the  r e g r e s s i o n produced the renovation,  .64;  renovation,  .54.  1987).  variables  activity.  number o f  house  assumed t h a t  i n a neighbourhood i s  locational, tracts.  R s: 2  renovation,  indicated  attractive,  high  evidence  and h o u s i n g  multiple  existence  of  .44;  of  that  a  independent  social,  Stepwise  following  T h e New O r l e a n s model  f a v o u r e d by r e n o v a t o r s .  renovation  al.  all  tracts:  T h e r e were 22  extent of  with architecturally  of  but  and  L a s k a / S e a m a n / M c S e v e n e y New O r l e a n s m o d e l ,  b a s e d on r e n o v a t i o n  but  home a n d w o r k .  two c h a r a c t e r i s t i c s  T h e r e were t h r e e d e p e n d e n t  variables  l e s s than  d e p r e s s e d h o u s i n g v a l u e s as w e l l were  a t t r a c t i v e to gentry  5.63  older housing  located near t h e i r  t o have a s l i g h t  exhibiting  statistic  t h e model h a d a c h i - s q u a r e o f  households p r e f e r r e d  renovation.  Hosmer-Lemeshow  year  peak  neighbourhoods  p r e - 1 9 3 9 h o u s i n g were  Proximity  t o p u b l i c h o u s i n g was a  19  strong deterrent gentrification proximity  to  to  literature,  industry  renovators while deterrent  renovation.  however,  Laska et  the al.  al.,  t o p a r k s and u n i v e r s i t i e s  and t h e  s h o u l d be s c r u t i n i z e d . not of  gentrification.  Both models i g n o r e  (the  i g n o r e s e d u c a t i o n and income l e v e l s literature  considers these  the  sales activity  is  A better one.  Ley's  inference  neighbourhood t r a i t s  multi-city  of  renovation  model i s  t h a t the  included a l l  literature  gentrification.  a n a l y s i s of  subjective  As w e l l ,  intra-urban  than the Melchert  L e y ' s methodology f o r t h a t used i n h i s  predictive  though  In  activity  David L e y ' s  the  New  from  abilities  one.  of twenty-six  the  speculates to  of  be  Ley conducted a rather  than  gentrification  was  and L a s k a m o d e l s .  intra-urban  inter-urban  Canadian  rejuvenation  a s i n g l e - c i t y one and h i s measurement less  even  model  questionable.  intra-urban  of  neighbourhood  determinants.  independent v a r i a b l e s  determinants  model  the  Melchert/Naroff  as w e l l )  do  neighbourhood  c h a r a c t e r i s t i c s as g e n t r i f i c a t i o n Orleans model,  the  Both models a r e p a r o c h i a l ; t h e y  a s b e i n g an i n d e p e n d e n t v a r i a b l e  to  i n both  Laska/Seaman/McSeveney models  occupational c h a r a c t e r i s t i c s of a g e n t r i f i e d  the  for  was a  c l a i m t o b e — n o r s h o u l d be r e g a r d e d a s — a g e n e r a l intra-city  that  1982).  The c o n c l u s i o n s r e g a r d i n g g e n t r i f i c a t i o n Melchert/Naroff  found  and w a r e h o u s i n g was a n a t t r a c t i o n  proximity  (Laska e t  Contrary to  a n a l y s i s was Ley t e s t e d  independent  similar  the  variables  20  against a revitalization inner-city  Canadian census t r a c t s .  comprised the Montreal,  dependent v a r i a b l e  inner-city  Ottawa,  Revitalization  e d u c a t i o n between  When m u l t i p l e  neighbourhoods of  Halifax,  T o r o n t o , E d m o n t o n , and V a n c o u v e r .  change i n a t r a c t ' s  Ley f i r s t  quaternary  1971  proportional  s e c t o r and  and 1981.  university  The i n d e p e n d e n t  conducted a simple c o r r e l a t i o n a n a l y s i s . regression yielded high m u l t i c o l l i n e a r i t y ,  t h a t h e o b t a i n e d was  strongest determinant  gentrification  elite  n e i g h b o u r h o o d s n e a r CBD and e n v i r o n m e n t a l The t h i r d  gentrification  was t h e a b s e n c e o f  incomes,  1971  to  1981  beginning of the  during the rents  in  religious affiliation  and  gentrified  p e r i o d would a l s o have had a high proportion at  average  of the  period. literature,  Ley found t h a t t h e r e  Canadian neighbourhoods t h a t  1971 t o  1971  were  of neighbourhood  and few b l u e c o l l a r w o r k e r s  Contrary to the no r e n t g a p .  Next,  amenities  A neighbourhood that  varied housing types,  unmarried people,  2  of  area.  strongest determinant  non-english speakers. d u r i n g the  R  i s a neighbourhood's proximity  an a l r e a d y e s t a b l i s h e d i n n e r - c i t y  favoured.  The b e s t  he  .36.  Ley found t h a t the  to  variables  1971.  c o n d u c t e d a p r i n c i p l e components r e g r e s s i o n .  intra-urban  462  The c e n s u s t r a c t s  was a g a i n m e a s u r e d a s t h e  were m e a s u r e d a t  for  was  gentrified  1981 p e r i o d h a d a v e r a g e h o u s e v a l u e s  greater  than the  city  average  (Ley,  and  1985).  21  CHAPTER SUMMARY T h i s c h a p t e r began by r e v i e w i n g t h e o r i e s 1970  "ringed" spatial  Filtration,  segregation of  the  pre-  income g r o u p s .  i n v a s i o n and s u c c e s s i o n ,  and  transportation  i n n o v a t i o n s e x p l a i n why t h e w e a l t h y t y p i c a l l y periphery of the c i t y  for  and t h e p o o r l i v e d a t  l i v e d at  the  the  city  centre. Gentrification theories e x p l a i n the post-1970 are  cited  i n the  phenomenon o f  literature  inner-city  to  resurgence  c a t e g o r i z e d as b e i n g d e m o g r a p h i c , e c o n o m i c , u r b a n  amenities,  housing market,  and g o v e r n m e n t p o l i c y .  D e m o g r a p h i c r e a s o n s t h a t s t i m u l a t e d demand f o r  inner-city  neighbourhoods i n the  1970s i n c l u d e t h e m a t u r a t i o n  of  b a b y boom c o h o r t ,  reduction of household s i z e ,  and  urban sprawl. of  the  Growth i n CBD employment made t h e  inner-city  neighbourhoods d e s i r a b l e  for  the  proximity  white-collar  w o r k e r s ; m a n u f a c t u r i n g employment d e c r e a s e d a n d suburbanized. increase  Changing l i f e - s t y l e s ,  especially  i n c h i l d l e s s two-income f a m i l i e s ,  neighbourhoods c l o s e to urban a m e n i t i e s .  favoured T h e 1970s h o u s i n g  m a r k e t and a w i d e n i n g r e n t gap made i n n e r - c i t y profitable.  Government p o l i c y e n c o u r a g e d  rehabilitation  stage of  gentrification  into  neighbourhood but are  the  reinvestment  inner-city  i n some c a s e s and d i s c o u r a g e d i t  Housing p r i c e s are not a f f e c t e d  the  during the  in  others.  initial  when l o w - i n c o m e CBD e m p l o y e e s move affected  income g r o u p s and d e v e l o p e r s move  later  once h i g h e r  in.  22  The l i t e r a t u r e p r e d i c t s t h a t w h i l e reasons f o r g e n t r i f i c a t i o n t o o much c a p i t a l  to  e x p e c t them t o be abandoned s o o n .  invested in gentrified  T h i s chapter then presented f i v e  inter-urban  models c o r r o b o r a t e  amenities  s t u d i e s do n o t surge f o r i n the of  1980s,  there  neighbourhoods  predictive  models  for  L e y ' s C a n a d i a n and L o n d o n ' s A m e r i c a n the  t h a t a s t r o n g CBD w h i t e - c o l l a r inner-city  demographic  may d i m i n i s h i n t h e  is  gentrification.  the  s e c t o r and t h e  precipitate  support the  housing i n the  h o u s i n g market  literature's  presence  gentrification.  theses that the  1970s and t h e  i n the  assertion  The  of two  b a b y boom demand  affordability  1970s were s t r o n g  crisis  determinants  gentrification. Two U . S .  intra-urban  Melchert/Naroff  m o d e l s were r e v i e w e d :  B o s t o n model and t h e L a s k a / S e a m a n / M c S e v e n e y  New O r l e a n s o n e .  Melchert  n e i g h b o u r h o o d s most l i k e l y  and N a r o f f  not d i l a p i d a t e d  house v a l u e s .  Laska et  gentrification  literature,  preferred  proximity  to  al.  found  that  t o have g e n t r i f i e d  would have been near but not a d j a c e n t had o l d e r but  the  to  in  Boston  CBD e m p l o y m e n t ,  h o u s i n g , and h a d d e p r e s s e d  found t h a t c o n t r a r y gentrifiers  industry  to  i n New O r l e a n s  and w a r e h o u s i n g r a t h e r  p a r k s and u n i v e r s i t i e s .  The m e t h o d o l o g i e s u s e d i n  two m o d e l s , h o w e v e r ,  questionable.  Ley's  intra-urban  Canadian aggregated better  are  the  gentrification  inner-cities  designed than the Melchert  model f o r  than  these  eight  was more c o m p r e h e n s i v e and and L a s k a m o d e l s .  Ley  23  found t h a t p r o x i m i t y elite  a r e a was t h e  to  an a l r e a d y  strongest  established  determinant  of  inner-city  gentrification.  N e i g h b o u r h o o d s n e a r CBD and e n v i r o n m e n t a l  amenities  also  neighbourhoods  likely  to  have g e n t r i f i e d  w i t h few r e l i g i o u s The m a j o r  h o u s e h o l d s a n d few n o n e n g l i s h  contradiction  l i t e r a t u r e was t h e gentrification.  between  absence o f  In  Canada d u r i n g t h e  as w e l l as  fact,  period  Ley's  a r e n t gap i n  in  and  speakers. the  Canadian  Ley found t h a t g e n t r i f i c a t i o n f r o m 1971  w i t h neighbourhoods t h a t had h i g h e r house v a l u e s  results  were  to  1981  than  was  in  associated  average  rents  and  1971.  24  CHAPTER 3 GENTRIFICATION  Chapter  2 reviewed  explanations  IN AN ECONOMIC FRAMEWORK  the  o f why demand f o r  has i n c r e a s e d s i n c e the  early  how a c h a n g e i n demand f o r affects  gentrification inner-city 1970s.  This chapter  and c a p i t a l  stock.  The f o l l o w i n g Economic Theory "Filtering  The  chapter  of housing market  Filtration  then viewed w i t h i n t h i s  examines  housing  that neighbourhood's housing market.  supply,  economic  and  demand,  gentrification  framework.  d i s c u s s i o n i s b a s e d on H e n d e r s o n ' s  and t h e  Cities  (1977)  and H o u s i n g S t a n d a r d s :  for  neighbourhoods  a neighbourhood's  begins w i t h a background a n a l y s i s  are  literature  and L o w r y ' s  book  article  A Conceptual A n a l y s i s "  (1960).  HOUSING MARKET BACKGROUND Demand:  Figure  1 illustrates  neighbourhood housing market. measures the landlords  amount  i n the  measures the services  is  per u n i t of  the  a homogeneous d i v i s i b l e  a function  neighbourhood  g o o d s , and t h e  price  axis,  H  of  good s o l d a t  neighbourhood.  income,  P , Housing  q u a n t i t y and q u a l i t y  per u n i t w i t h i n the  public  vertical  location,  H,  by  of housing s e r v i c e s .  uniform p r i c e of  axis,  of housing s e r v i c e s supplied  a combination  h o u s i n g and i s  competitive  The h o r i z o n t a l  neighbourhood;  price  a  a  Demand  is  amenities,  of housing r e l a t i v e  to  other  25  Figure 1  Neighbourhood Housing Market \ 4 \.  \  \  \\  \  \ \  i_  Q-po  © o 1.  0-  , ..  \  \ \  \ v  \  \  \  \  \y  /  /  /  N  \  \.  X X  V  ^  \ \  p i  \  \  \s  s  1  H°  H  2  D°  D  H  D  1  H 2  Housing S e r v i c e s  Figure 2  Optimal Maintenance Strategy  k(t)«  k(o°  k(t) kO)=  Maintenance Capital 26  neighbourhoods.  T h e demand c u r v e s l o p e s down b e c a u s e o f  the d i m i n i s h i n g marginal u t i l i t y determined  by i n v e s t m e n t  of housing.  d e c i s i o n s made b y l a n d l o r d s .  s u p p l y c u r v e s l o p e s up b e c a u s e o f t h e f i x e d available  f o r housing  Supply i s The  amount o f l a n d  and because o f d i m i n i s h i n g m a r g i n a l  r e t u r n s t o c a p i t a l when a p p l i e d t o l a n d f o r p r o d u c i n g housing  services.  Supply: landlords  Equilibrium  i s a t H ° and Pjr 0  The amount o f h o u s i n g  i s a positive  s e r v i c e s produced  by  f u n c t i o n o f t h e amount o f c a p i t a l  i n v e s t e d by them,  dh(t)/dK(t)  where h ( t ) i s h o u s i n g is  the t o t a l  capital  > 0  s e r v i c e s produced stock of housing  however, d i m i n i s h i n g m a r g i n a l applied to a fixed  (1)  i n time  services.  t and K ( t ) There are,  r e t u r n s when c a p i t a l i s  amount o f l a n d when p r o d u c i n g  housing  services:  d h(t)/dK(t) 2  For the p r o f i t optimal any  2  < 0  maximizing  landlord,  amount o f m a i n t e n a n c e t o i n v e s t  (2)  t h e r e i s an i n h i s housing at  time  t:  the landlord  benefit,  MB,  o f maintenance equals t h e t o t a l  o p p o r t u n i t y c o s t , MC,  should invest u n t i l  the marginal marginal  where  27  MB  and,  = VMP  with  =  K  P  * MP  H  =  K  (3)  P (dh(t)/dK(t)) H  i n t e r e s t rate r, the  p r i c e of  capital  immediate d e p r e c i a t i o n of maintenance c a p i t a l time t  Equating  (3)  to  f o r the  =  (4)  (r +  landlord.  The  any  time period  Figure  2  = MC,  maintenance strategy  m a i n t e n a n c e and horizontal invested  marginal  the  the  The  invest  in  =  (r +  a(t))P  (5)  K  landlord's time period of  optimal t.  capital  The  vertical  invested  benefit derived;  in  the  amount o f m a i n t e n a n c e  capital  marginal  cost  of maintenance  opportunity  cost  of  price of  i n t e r e s t and  marginal  maintenance  i.e.,  cost  marginal  marginal  maintenance c a p i t a l  housing  f o r any  at time t .  total  foregone  the  a x i s measures the  maintenance:  The  in  t.  illustrates  a x i s measures the  optimal  landlord should  H  the  the  (4)  establishes the  P (dh(t)/dK(t))  is  and  invested  a(t))P  m a i n t e n a n c e s u c h t h a t MB  for  K  as a ( t ) ,  MC  path  P ,  capital  instantaneous  invested  benefit curve  services times the  i s the  investing in  times the  sum  depreciation  i n time t  of that  i s subjected  p r i c e of  curve  one  change i n h o u s i n g  unit  to  (4).  of  services  28  produced  ( 3 ) ;i tslopes  marginal  returns to capital  maintenance and  MC°  Stock:  The t o t a l  (initial  time  I f a(t)  t fora l l capital  capital  capital  stock  (maintenance) existing  capital  0  housing capital yearly  i s the rate of depreciation  stock,  then  i s gross  t h e change  housing i n the  investment the depreciated  stock,  = k(t)  (6)  - a(t)K(t)  n e i g h b o u r h o o d w o u l d h a v e no c h a n g e i n t h e  stock  o f housing  level  o f demand w o u l d be c o n s t a n t  s e r v i c e s from one p e r i o d t o t h e n e x t .  The f l o w o f annual  capital,  previous  i n that period, k ( t ) , less  dK(t)/d(t)  perfectly  of  invested i n neighbourhood  i n any p e r i o d  capital  A static  stock  l a n d and c o n s t r u c t i o n c o s t s p l u s  K(t) i s the total  vary.  t° i s k(t)°, w h e r e MB  i s t h e sum o f a l l d e p r e c i a t e d  maintenance expenses).  and  of  intersect.  services  in  ( 2 ) . The e q u i l i b r i u m l e v e l  f o r the l a n d l o r d i n time  Capital  inputs  down b e c a u s e o f d i m i n i s h i n g  offset  and r e a l  maintenance,  t h e annual  The  p r i c e s would not  k ( t ) , would  depreciation of the existing  a(t)K(t).  FILTRATION Filtration  c a n be i l l u s t r a t e d  equations  and F i g u r e s  filtering  occurs  1 a n d 2.  using  Henderson's  On t h e d e m a n d  side,  i n a n e i g h b o u r h o o d when demand  f o ri t s  29  housing from  p r e f e r e n c e f o r new  c i t y core.  adds t o t h e s t o c k o f used  neighbourhood. used  housing  housing  housing  vacated  i n the  m a r k e t i s c o n s t a n t , t h e demand  relative  t o t h e supply decreases  t h e demand c u r v e  shifts  they  ofthe  Because t h e number o f h o u s e h o l d s  F i g u r e 1,  falls  When t h e y m o v e , t h e i r  away  housing  land i n t h e suburbs;  " p u s h e d " away b y t h e n e g a t i v e e x t e r n a l i t i e s  housing  i n the  f o r used  and p r i c e s  fall.  D° t o D  and P °  from  1  H  t o PJJ . 1  On t h e s u p p l y s i d e , housing the  income groups a r e " p u l l e d "  i s c o n s t r u c t e d on vacant  industrial  In  Higher  t h e c i t y centre by t h e i r  which are  decreases.  with a f a l l  i n t h e neighbourhood  left  side  and thus  i ntheprice of a decrease  decreases.  to  I f r and a ( t ) remain  1  i n F i g u r e 2.  marginal benefit  The MB  0  curve  shifts  back  constant, the  c o s t o f m a i n t e n a n c e now e x c e e d s t h e m a r g i n a l by t h e v e r t i c a l d i s t a n c e ab.  T o k e e p MC e q u a l t o  MB, t h e l a n d l o r d  must reduce  in  I n F i g u r e 2, k ( t ) ° s h i f t s  maintenance.  Reducing  K  of (5),i . e . , the marginal benefit o f  maintenance c a p i t a l , MB  i n VMP ,  maintenance,  the p r o f i t maximizing  t h e amount o f c a p i t a l  back t o k ( t ) . 1  therefore, i sa rational landlord  when h o u s i n g  invested  decision f o r  prices are  falling. The  capital  stock i n t h e neighbourhood  Because l a n d l o r d s w i l l capital,  reduce  decline.  t h e flow o f maintenance  t h e change i n t h e s t o c k o f h o u s i n g  negative because t h e r i g h t  will  side  capital  will  be  o f (6) i s n e g a t i v e , i . e . ,  30  k(t)  i s l e s s than a ( t ) K ( t ) . Reduced maintenance h a s t e n s p h y s i c a l  w h i c h d e p r e s s e s demand and p r i c e s more. fall  back again, maintenance w i l l  and t h e c a p i t a l  stock w i l l  demand a n d p r i c e  even t h e l a n d l o r d ' s point,  fixed  the landlord w i l l  Filtration traditional filtered  T h e MB  be c u r t a i l e d  diminish  f o r h o u s i n g may  depreciation  further.  fall  At  to the  Central-city  down t h e income s t r a t a b e c a u s e o f t h e  maintenance.  By 1970,  demand, p r i c e s ,  central  this  the housing.  i n n e r - c i t y neighbourhood.  falling  e v e n more,  t o a l e v e l where n o t  d e s c r i b e s what h a s h a p p e n e d  r e l a t i o n s h i p between  will  Eventually,  costs are covered. abandon  curve  city  housing  reinforcing  and  n e i g h b o u r h o o d s became  home f o r low income g r o u p s o r , a s i n some U.S.  extremes,  abandoned w a s t e l a n d s .  GENTRIFICATION S i n c e 1970,  demand f o r i n n e r - c i t y h o u s i n g b y  income g r o u p s h a s r e t u r n e d . t h i s h a s happened.  First, Growth  The l i t e r a t u r e  higher  explains  t h e economic base o f t h e i n service oriented,  why city  may  have changed.  CBD  employment and t h e s u b u r b a n i z a t i o n — o r d e c l i n e — o f  c o l l a r m a n u f a c t u r i n g employment may city's  p r o x i m i t y t o t h e CBD  white-collar  h a v e made t h e  blue  inner-  a t t r a c t i v e t o t h e downtown  w o r k e r b u t no l o n g e r s o f o r t h e b l u e - c o l l a r one. life-styles  have changed.  The p o s t p o n e m e n t  r e a r i n g may  h a v e made y o u n g a d u l t s  of  Second,  child-  f a v o u r t h e downtown  social  amenities that  family  oriented  city  ones o f f e r e d  disparity  filtered  Victorian favoured  i nprice  inner-city  "good buy".  offers  i n t h e suburbs.  b e t w e e n new s u b u r b a n  over t h e contemporary  services  has r i s e n ,  K  H  to the  H  rises  (the l e f t  One  to P  of gentrification  P , of a unit  i n F i g u r e 2.  2  now e x c e e d  be.  investment  VMP  become  shift the  by a l a n d l o r d  i s t h e converse  a  The  P ° rises  2  invested  Because t h e p r i c e ,  distance  D° t o D .  the effect  effect.  o u t t o MB  The  design o f t h e suburbs.  i n F i g u r e 1 from  neighbourhood  inner-  h o u s i n g and  may h a v e  o f t h e above reasons w i l l  amount o f c a p i t a l  maintenance  inexpensive.  of the inner-city  On t h e s u p p l y s i d e ,  shifts  Third,  h o u s i n g may h a v e m a d e t h e i n n e r - c i t y  architecture  demand c u r v e  city  over the  F o u r t h , t a s t e s may h a v e c h a n g e d .  any combination  the  living  h o u s i n g may h a v e b e c o m e r e l a t i v e l y  growing  or  inner-city  i n a  2 H  .  on  central-  filtration of housing  side  of (5)). MB  Marginal benefits of  marginal costs by t h e v e r t i c a l  The l a n d l o r d  i n maintenance  responds capital.  by increasing h i s k(t)° s h i f t s  out t o  k(t) . 2  The  capital  gentrifying  stock o f housing w i l l  neighbourhood  than depreciation, In  gentrifying  maximizing  i finvestment,  a(t)K(t),  i n equation  neighbourhoods,  landlord w i l l  capital,  i . e . , he w i l l  services  produced.  rise  k ( t ) , i sgreater 6.  therefore,  increase the level  increase the level  At first,  i n a  of  a  profit  maintenance  of housing  increased housing  services  32  0  will  entail  rehabilitation  of  the  original  housing.•  demand c o n t i n u e s t o  r i s e and t h e MB c u r v e c o n t i n u e s  shift  the  out,  however,  demolish the time t o  redevelop i s  n  >  v  o  +  D  o +  B  V  d e m o l i t i o n c o s t , and B  0  i s the  n  cost of  a gentrifying  flows  from a  and q u a n t i t y  D  of  is  Q  the  the  c o n s t r u c t i n g a new  construction period  neighbourhood,  i n c r e a s e d demand and p r i c e s e f f e c t quality  optimal  i s the present value  s t r u c t u r e plus l o s t rent during the In  The  n  flows of the e x i s t i n g s t r u c t u r e ,  1977).  to  when  new h o u s i n g s t r u c t u r e ,  (Clapp,  to  profitable  i s the present value of the b e n e f i t  n  benefit  it  o r i g i n a l h o u s i n g and r e d e v e l o p .  v  where V  l a n d l o r d may f i n d  If  therefore,  an i n c r e a s e i n  the  of housing s u p p l i e d .  CHAPTER SUMMARY G e n t r i f i c a t i o n and i t s examined w i t h i n t h e i n a net  change t o  housing s e r v i c e s . i n the  capital  increase. referred  filtration,  same e c o n o m i c f r a m e w o r k .  Both  a neighbourhood's c a p i t a l  stock  While  stock,  For t h i s  antithesis,  filtration  gentrification  effects effects  reason, g e n t r i f i c a t i o n  t o as "up" o r  "reverse"  On t h e demand s i d e , t h e c i t y h o u s i n g by h i g h e r  a net  is  a  c a n be result of  decrease  net often  filtration.  recent d e s i r a b i l i t y  income g r o u p s b i d s up t h e  of  inner-  price  of  33  housing i n central neighbourhoods. p r o f i t maximizing landlords  On the supply side,  i n these g e n t r i f y i n g  neighbourhoods respond to the price-induced  increase  i n the  marginal benefits of maintenance by increasing the flow of maintenance c a p i t a l .  As a r e s u l t , g e n t r i f y i n g  neighbourhoods receive a net increase to t h e i r t o t a l stock of housing services.  34  CHAPTER 4  A CANADIAN INTRA-URBAN GENTRIFICATION MODEL  Chapter explanations rebounded point  1970.  Chapter  o f v i e w , how t h e r i s e  these The  literature f o r  o f why demand f o r c e n t r a l - c i t y  after  higher prices in  2 reviewed t h eg e n t r i f i c a t i o n  3 examined,  neighbourhoods from  i n h o u s i n g demand  and an increased  an  effected  supply o f housing  services  neighbourhoods. literature  gentrification,  posits  are attracted  that  i nt h ee a r l i e s t  well-educated butrelatively  p r o f e s s i o n a l s move i n t o  an i n n e r - c i t y  t o t h eneighbourhood  stage o f  l o w - p a i d young  neighbourhood.  by i t s proximity  employment a n d a m e n i t i e s and b y i t s r e l a t i v e l y housing. there  economic  Because  their  i sno immediate  incomes  effect  ares t i l l  They t o CBD  cheap  l o w , however,  on housing p r i c e s .  Not u n t i l  t h e r e h a s been moderate r e n o v a t i o n t o t h eh o u s i n g s t o c k by this  first  wave o f g e n t r i f i e r s  income groups up  (Berry,  attracted  neighbourhood  initial  t o t h eneighbourhood  and higher  and prices b i d  1985; Ley, 1985; M e l c h e r t and N a r o f f ,  I n o t h e r words,  Melchert  arespeculators  follow  and Naroff,  housing prices a logistic 1987).  S-curve  There  change i n t h edemographic  neighbourhood  that  neighbourhood  housing prices.  once housing p r i c e s  i na  i sgentrifying  1987).  gentrifing (Ley,  1985;  i sa l a g between t h e milieu  o f an inner-city  and t h er i s e i n  As discussed  do b e g i n t o r i s e ,  i n C h a p t e r 3,  t h em a r g i n a l  benefit  35  o f maintenance landlords further marginal the  investment  increase maintenance.  and r a p i d  rise  benefits  Improved  even more,  and s o o n .  n e i g h b o u r h o o d becomes g e n t r i f i e d .  that  ignited  the  present  this  implies:  undergoing the  By t h i s  chapter—and  this  Changes i n t h e  the  in a gentrifying  consequent r i s e  as y o u n g , w e l l - e d u c a t e d  socio-economic p r o f i l e  m e a s u r e d by t h e (Ley,  1985).  on e a c h o t h e r .  improvement  gentrification  as an i n c r e a s e  in this  i n an  Change i n p r i c e w i l l  t h e m o d e l and w i l l demographic  be t h e  are  viz.,  CBD e m p l o y e d in. of  a  central-  Gentrification  a  c a n be  other,  or  both  thesis  defines  inner-city  neighbourhood's housing p r i c e s r e l a t i v e whole.  will  h o u s i n g market have  i n one o r t h e  The model p r e s e n t e d  start  in housing p r i c e s ,  neighbourhoods  its  to  inner-city  gentrification,  n e i g h b o u r h o o d and c h a n g e s i n effect  spark  thesis—is  S i n c e t h e r e i s a l a g between  phase of  of  process.  s i n g l e s and c h i l d l e s s c o u p l e s b e g i n t o move  reinforcing  wave  i n c r e a s e s by o b s e r v i n g w h i c h o n e s  demographic change,  city  process,  n e i g h b o u r h o o d was t h e  which i n n e r - c i t y  first  a  raises  the  n e i g h b o u r h o o d and t h e  future price  which  t e s t what  demographic t r a n s i t i o n  one c a n p r e d i c t  housing effects  The i n i t i a l  a r e g r e s s i o n model d e s i g n e d t o  literature  have  the  gentrification  The p u r p o s e o f  maximizing  i n demand and p r i c e s ,  " Y u p p i e s " t h a t moved i n t o  of  r i s e s so p r o f i t  to  the  dependent  be r e g r e s s e d a g a i n s t  CMA a s a variable  in  neighbourhood  change.  36  This chapter w i l l sectional, this  first  d e s c r i b e the Canadian  i n t r a - u r b a n g e n t r i f i c a t i o n model p r e s e n t e d i n  thesis.  E x t e n s i o n s t o t h e model d e s i g n e d t o e v a l u a t e  the model's p r e d i c t i v e a b i l i t y results  cross-  from  will  t h e n be  regression analysis w i l l  described.  follow  The  i n Chapter  5.  MODEL  Premise:  Since g e n t r i f i c a t i o n  phenomenon t h a t been i n i t i a l  started  h o u s i n g p r i c e s d u r i n g t h e 1970s. r e g r e s s e s changes i n i n n e r - c i t y 2,  changes d u r i n g p e r i o d 1961,  Sample: tracts  and  The  Vancouver,  20  three c i t i e s w e s t mix  model,  neighbourhood  t o 1981,  1,  1961  t o 1971.  and  1981  Canada  distribution  housing  A l l data  from O t t a w a - H u l l ,  and  were s e l e c t e d b e c a u s e  F i g u r e s 3,  cities  and  CMAs t h a t 4,  and  of  tracts 55  200  census  Vancouver,  census  tracts form  i s 20  that  the from  from T o r o n t o .  t h e y r e p r e s e n t an  because  The east-  t h e y a r e among  the  r e p o r t s t o have  gentrified  5 show t h e i n n e r - c i t y  boundaries  t h e sample f o r each c i t y .  Ley  i s derived  census.  I n n e r - c i t y census  of census  in  a g a i n s t demographic  the i n n e r - c i t i e s  Ottawa-Hull.  o f Canadian  1960s i n  therefore,  s a m p l e i s 95 o f a p p r o x i m a t e l y  major Canadian  (1985). of  1971  The  e v e n i d e n t i t y numbers i n t h e 1961  sample.  six  The  t h a t comprise  Toronto, had  1971,  during the  t h a t e x p e r i e n c e d an e s c a l a t i o n  prices during period  a  i n t h e 1970s, t h e r e s h o u l d h a v e  demographic t r a n s i t i o n s  those neighbourhoods  from t h e  i s r e p o r t e d t o be  The  boundaries  are  those  37  LEGEND: -  Rent  -  Value increased at  -  R e n t and V a l u e b o t h i n c r e a s e d 10% more t h a n CMA  -  R e n t and V a l u e b o t h i n c r e a s e d l e s s t h a n CMA  -  Not i n c l u d e d i n t h e  F i g u r e 3:  increased at  least least  10% more t h a n CMA i n c r e a s e 10% more t h a n  CMA i n c r e a s e  sample  Vancouver i n n e r - c i t y housing p r i c e r e l a t i v e t o CMA, 1 9 7 1 - 1 9 8 1 .  increases  38  LEGEND:  |  -  Rent  -  Value increased at  -  R e n t and V a l u e b o t h i n c r e a s e d 10% more t h a n CMA  -  R e n t and V a l u e b o t h i n c r e a s e d l e s s t h a n CMA  1 -  increased at  least  Not i n c l u d e d i n t h e  F i g u r e 4:  least  10% more t h a n CMA i n c r e a s e 10% more t h a n CMA i n c r e a s e  sample  Ottawa i n n e r - c i t y h o u s i n g ; p r i c e r e l a t i v e t o CMA, 1 9 7 1 - 1 9 8 1 .  increases  39  LEGEND:  |  |  -  Rent  -  Value increased at  -  R e n t and V a l u e b o t h i n c r e a s e d 10% more t h a n CMA  -  R e n t and V a l u e b o t h i n c r e a s e d l e s s t h a n CMA  -  Not  F i g u r e 5:  increased at  least  included i n the  least  10% more t h a n CMA i n c r e a s e 10% more t h a n CMA i n c r e a s e  sample  Toronto i n n e r - c i t y housing p r i c e r e l a t i v e t o CMA. 1 9 7 1 - 1 9 8 1 .  increases  40  defined  by L e y  (1985) b a s e d on t h e CMHC document  Canadian Inner C i t y (Brown and B u r k e ,  1971  t o 1976:  Handbook  1979).  Dependent V a r i a b l e s : dependent  A Statistical  The  A l l the v a r i a b l e s  i n the  model,  and e x p l a n a t o r y , a r e d e s i g n e d t o m e a s u r e t h e  performance  o f an i n n e r - c i t y c e n s u s t r a c t r e l a t i v e t o t h e  performance  o f t h e CMA  T h e r e a r e two  as a  whole.  dependent  variables.  changing housing p r i c e s during period first  dependent  2,  1971  t o 1981.  The  v a r i a b l e measures t h e p e r c e n t change i n a  census t r a c t ' s average rent p e r c e n t change,  Both measure  1971  to  p e r room r e l a t i v e t o t h e  CMA  1981:  RENT2 = 1981  CT mean/room - 1971 1971 CT mean/room  m/r  - 1981  x  The  second dependent  CMA 1971  m/r CMA  - 1971 CMA mean/room  m/r  100  v a r i a b l e measures t h e p e r c e n t  c h a n g e i n a c e n s u s t r a c t ' s m e d i a n v a l u e p e r room r e l a t i v e t o t h e CMA  change,  1971  to  1981: VALUE2 =  1981  CT m e d i a n / r - 1971 m/r 1971 CT median/room  - 1981 CMA m/r - 1971 CMA 1971 CMA m e d i a n / r o o m x  100  R e n t s and v a l u e s a r e c a l c u l a t e d one  m/r  i s t o compare t h e p r i c e o r r e n t  " p e r room" b e c a u s e , i f o f an  inner-city  41  dwelling larger  to  a suburban d w e l l i n g ,  dwellings  i n the  one must c o m p e n s a t e  suburbs than  i n the  city  b e t t e r m e a s u r e o f p r i c e o r r e n t when c o m p a r i n g sized housing i s size  of  "per square foot"  census t r a c t dwellings  A potential it  i s not  data  rather  of h i s dwelling.  The c e n s u s d a t a ,  corroborated with actual  for  example,  recorded that dwelling Estate  $171,726.  for June,  sold for  the  Figures  the  3 to  housing p r i c e  variables.  census data  value  been 1981 The  1981  median  census  increases greater  Surrey,  a p p e a r s t o be i n the  than the  There are  group of  of  relatively  to  1971,  accurate. s a m p l e had  CMA i n p e r i o d  14  explanatory  as young, w e l l - e d u c a t e d ,  2.  explanatory variables  is 1,  c h i l d l e s s couples  a n d s i n g l e CBD p r o f e s s i o n a l s b e g i n t o move i n t o city  less  Langley,  d e s i g n e d t o measure d e m o g r a p h i c c h a n g e s d u r i n g p e r i o d 1961  Board  single-family  include the  5 show w h i c h t r a c t s  The f i r s t  market  Since the Vancouver Real  does not  Explanatory V a r i a b l e s :  The  The  i n the  average  e x p e n s i v e V a n c o u v e r CMA m u n i c i p a l i t i e s and W h i t e - R o c k ,  data.  has  1981.  that  The V a n c o u v e r R e a l E s t a t e  1981,  $179,730.  Board s t a t i s t i c  the  however,  reported  average  VALUE2 i s  estimate  c e n s u s was m a i l e d t o h o u s e h o l d s i n J u n e ,  is,  on t h e  market s a l e s d a t a .  V a n c o u v e r CMA d w e l l i n g v a l u e  A  different  than o b j e c t i v e  owner-occupier to  core.  available.  problem w i t h the v a r i a b l e  i s b a s e d on s u b j e c t i v e  census asks the  but  for  a  central-  neighbourhood.  42  GROUP 1: 1)  P e r c e n t c h a n g e i n 20 t o t h e CMA c h a n g e ,  34 y e a r o l d s  1961 t o  relative  1971:  AGE1 = 1971 CT% 20-34 v r s - 1961% 1961 CT% 20-34 y e a r s o l d  1971 CMA% 2 0 - 3 4 v r s - 1961% 1961 CMA% 2 0 - 3 0 y e a r s o l d  x 100  2)  P e r c e n t change i n u n i v e r s i t y the  CMA c h a n g e ,  1961 t o  educated r e l a t i v e  to  1971:  UNVRS1 = 1971 CT% u n i v e r . e d . - 1961% 1961 CT% u n i v e r . e d u c a t i o n  1971 CMA% u n i v e r . e d . - 1961% 1961 CMA% u n i v e r . e d u c a t i o n  x 100  3)  P e r c e n t change i n p r o f e s s i o n a l , a d m i n i s t r a t i v e , managerial 1961 t o  and  o c c u p a t i o n s r e l a t i v e t o t h e CMA c h a n g e ,  1971:  PRFOC1 = 1971 CT% p r o f / a d m i n - 1961% 19 61 CT% p r o f / a d m i n / t e c h  1971 CMA% p r o f / a d m i n - 1961% 1961 CMA% p r o f / a d m i n / t e c h  x 100  4)  P e r c e n t change i n female the  CMA c h a n g e ,  1961 t o  labour  force relative  to  1971:  FMLBR1 = 1971 CT% fern, w r k r s - 1961% - 1971 CMA% fern, w r k r s - 1961% 1961 CT% f e m a l e w o r k e r s 1961 CMA% f e m a l e w o r k e r s x 100 43  5) P e r c e n t change i n f e m a l e and  administrative  professional,  technical,  o c c u p a t i o n s r e l a t i v e t o t h e CMA  c h a n g e , 1961 t o 1971: FMPR0C1 = 1971 CT% fm.prf/adm - 1961% - 1971 CMA% 1961 CT% f e r n . p r o f / a d m n / t e c h 1961 CMA%  f m . p r f / a d m - 1961% fern.prof/admn/tech  x 100  6) P e r c e n t change i n n o n - f a m i l y h o u s e h o l d s  relative to  t h e CMA change, 1961 t o 1971: NFMHS1 = 1971 CT% n o n - f a m i l v - 1961% - 1971 CMA% 1961 CT% n o n - f a m i l y h s h l d s 1961 CMA%  non-familv non-family  - 1961% hshlds  x 100  7) Change i n a v e r a g e  number o f c h i l d r e n p e r f a m i l y  r e l a t i v e t o t h e CMA c h a n g e , 1961 t o 1971: CHLD1 = (1971 CT mean c h i l d r e n p e r f a m i l y - 1961 mean) (1971 CMA mean c h i l d r e n p e r f a m i l y - 1961 mean)  8) P e r c e n t change i n no r e l i g i o u s a f f i l i a t i o n  relative  t o t h e CMA change, 1961 t o 1971: N0RLG1 = 1971 CT% no r e l i g i o n -1961% - 1971 CMA% no r e l i g i o n -1961% 1961 CT% no r e l i g i o n 1961 CMA% no r e l i g i o n  x 100 44  Explanatory variables consensus t h a t the  L e y 1986,  result  of  especially  variable gentry 1985,  Variables  theories  typically  f e m a l e work  6 reflects  the  7 measures the  force,  L e y 1985,  conclusions  Hamnett  from L e y ' s  pioneering gentry  eight  families  adults  (Smith  8 is  1985  included to  while  children  1987,  in  Berry  test  t e n d t o be n o n - c o n f o r m i s t s . "no r e l i g i o u s  non-conformity  (Ley,  Ley used  affiliation"  the  as a  variables—except correlation with  the  variables.  demographic v a r i a b l e s  f o r p e r i o d 2,  the  1985).  p e r i o d 1 demographic  dependent housing p r i c e  one o f  research that a neighbourhood's  CHLD1—are e x p e c t e d t o have a p o s i t i v e  The e i g h t  that  1984) .  Canadian census category for  consensus  d e c r e a s i n g number o f  Explanatory variable  1971  to  are  1981,  similarly  t o be u s e d i n  e x t e n s i o n s t o t h e model t h a t a r e d i s c u s s e d a t this  largely  f o r h o u s e h o l d s composed o f  couples, s i n g l e s , or unrelated  calculated  is  Smith  form n o n - p a t r i a r c h h o u s e h o l d s .  6 is a catchall  surrogate  Berry  4 and 5 t e s t  that gentrification  an i n c r e a s e i n t h e  households that are  All  (Hamnett 1984,  well-  i n t h e p r o f e s s i o n a l h i g h - i n c o m e CBD j o b s .  gentrifiers  childless  young  CBD e m p l o y e e s  Explanatory variable  Variable  are predominantly  Smith 1987).  and B e r r y ' s s i m i l a r the  the  "gentry"  educated w h i t e - c o l l a r 1985,  1 through 5 r e f l e c t  the  end  the of  chapter.  45  GROUP 2: The s e c o n d g r o u p o f v a r i a b l e s to  a n a l y z e t h e h o u s i n g market 9)  1961  to  included i n the  prior to period  P e r c e n t change i n r e n t change,  is  relative  to  model  2.  the  CMA p e r c e n t  1971:  RENT1 = 1971  CT mean/room - 1961 m / r 1961 CT mean/room  -  x  10)  1971  CMA m / r - 1961 CMA m / r 1961 CMA m e a n / r o o m  100  P e r c e n t change i n v a l u e r e l a t i v e p e r c e n t c h a n g e , 1961  to  to  t h e CMA  1971:  VALUE1 = 1971  CT m e d i a n / r - 1961 m / r 1961 CT m e d i a n / r o o m  x  11)  Potential difference  for  1971 CMA m / r - 1961 CMA m / r 1961 CMA m e d i a n / r o o m 100  an i n c r e a s e i n r e n t ,  measured as  the  (in  standard deviations)  between  a  census t r a c t ' s  a v e r a g e r e n t and t h e  average  rent  of the  inner-city,  1971:  RSTZDV = 1971  CT mean r e n t / r o o m - 1971 i n n e r - c i t y mean 1971 i n n e r - c i t y s t a n d a r d d e v i a t i o n  rent/room  46  12)  Potential  for  an i n c r e a s e i n v a l u e ,  measured as  the d i f f e r e n c e  (in  census t r a c t ' s  m e d i a n v a l u e and t h e m e d i a n  of the  standard deviations)  inner-city,  between  a  value  1971:  VSTZDV = 1971  CT m e d i a n r e n t / r o o m - 1971 i n n e r - c i t y m e d i a n 1971 i n n e r - c i t y s t a n d a r d d e v i a t i o n  13)  VANDUM = Dummy v a r i a b l e  f o r Vancouver  14)  OTTDUM = Dummy v a r i a b l e  for  Ottawa-Hull  E x p l a n a t o r y v a r i a b l e s 9 and 10 t e s t the  "best  favour the  correlation 2.  z-scores that  (1987)  in  test  that  neighbourhoods t h a t  offer  buy".  i s that  it  Although there the  and N a r o f f  inner-city  Data Limitations: data  11 and 12 a r e  conclusion of Melchert  gentrifiers the  for  c h a n g e i n h o u s i n g p r i c e s between p e r i o d s 1 a n d Explanatory variables  the  rent/room  The paramount l i m i t a t i o n  is available  i s a mini census every  demographic i n f o r m a t i o n  information  in ten-year  i s excluded.  and a l l  of  periods  five  the  only.  years,  much o f  of the housing p r i c e  One w o u l d e x p e c t t h a t  if  there  is  a l a g between t h e b e g i n n i n g s o f d e m o g r a p h i c  transformation  i n an i n n e r - c i t y  in housing  prices, will  the  n e i g h b o u r h o o d and t h e  rise  l a g w o u l d be l e s s t h a n t e n y e a r s .  n o t p i c k up t h e  lag i f  both events occur  The model i n the  same  47  ten-year  period.  Another l i m i t a t i o n p r i c e s p e r room r a t h e r  of  the  data  than per  i s the  square  use of  foot  as  housing  discussed  above. The t h i r d  handicap i n the  were i n s t i t u t e d ended i n of  the  1984;  i n Canada i n  data  1975.  stock,  have been under r e n t c o n t r o l  attenuate the  1971  in period  1,  to  1981,  1961  to  first 1981  is  80-85%  estimated  years  (CMHC,  change i n average  i n response to  controls  have them.  example,  i n the in  controls  Vancouver r e n t  for  w h i l e 50-60% were u n d e r c o n t r o l  p e r i o d 2,  that rent  Ottawa and T o r o n t o s t i l l  Vancouver r e n t a l  controls w i l l  is  of  controls  1988). rents  demographic  to  Rent  in changes  1971.  EXTENSIONS TO THE MODEL The f i r s t of  the  extension to  three c i t i e s  t h e model w i l l  separately  to  test  be t o  for  run  each  inter-city  variation. The s e c o n d , are  included to  designed to to  1981,  1971.  third,  and f o u r t h  address the  predict  following  housing p r i c e  But even i f  correlation  relationship  prices  there  between  the  two  is  the  model  The m o d e l  changes i n p e r i o d 1,  found between  changes, a  1961  2,  is 1971  to  the  causal  i s not proven.  is a reinforcing  to  issue:  w i t h demographic changes i n p e r i o d  d e m o g r a p h i c c h a n g e s and p r i c e  stated,  extensions  relationship  As  already  between  and n e i g h b o u r h o o d s o c i o - e c o n o m i c s t a t u s .  housing  Period  1  48  demographic changes might be t h e consequence o f , r a t h e r than t h e determinant o f , p r i c e i n c r e a s e s t h a t s t a r t e d i n p e r i o d 1 and continued The explanatory resolve the issue.  i n t o p e r i o d 2.  v a r i a b l e s RENT1 and VALUE1 w i l l  help  I f p e r i o d 2 housing p r i c e i n c r e a s e s a r e  s t r o n g l y c o r r e l a t e d t o p e r i o d 1 i n c r e a s e s , then any c o r r e l a t i o n between demographic changes i n p e r i o d 1 and p r i c e changes i n p e r i o d 2 cannot be c o n s i d e r e d  causal.  In a d d i t i o n t o t h e RENT1 and VALUE1 t e s t , t h e r e a r e t h r e e extensions  t o t h e model t h a t e v a l u a t e t h e  r e l a t i o n s h i p i n t h e model between p e r i o d 1 demographic and p e r i o d 2 p r i c e changes.  The f i r s t e x t e n s i o n  regresses  RENT1 and VALUE1 a g a i n s t t h e p e r i o d 1 demographic explanatory  variables.  I f t h e p e r i o d 1 demographic  v a r i a b l e s p r e d i c t contemporaneous  period 1 p r i c e increases  i n t h e e x t e n s i o n b e t t e r than they p r e d i c t p e r i o d 2 p r i c e i n c r e a s e s i n t h e model, then t h e r e s u l t s o f t h e model must be  questioned. The second e x t e n s i o n  r e g r e s s e s RENT2 and VALUE2  a g a i n s t t h e p e r i o d 2 demographic e x p l a n a t o r y  variables.  I f p e r i o d 2 p r i c e i n c r e a s e s a r e p r e d i c t e d by contemporaneous extension  p e r i o d 2 demographic v a r i a b l e s i n t h e  b e t t e r than they a r e p r e d i c t e d by p e r i o d 1  demographic v a r i a b l e s i n t h e model, then t h e r e s u l t s o f t h e model must be  questioned.  The t h i r d e x t e n s i o n  r e g r e s s e s RENT2 and VALUE2 a g a i n s t  pooled p e r i o d 1 and p e r i o d 2 demographic v a r i a b l e s .  The  49  utility period those  of  this  extension  is appealing.  The e f f e c t  2 p r i c e s by d e m o g r a p h i c v a r i a b l e s  in period  i n p e r i o d 2 c a n be compared d i r e c t l y .  nature  of  the  transition  l a g between  neighbourhood  and n e i g h b o u r h o o d p r i c e  on 1 versus  As w e l l ,  the  demographic  i n c r e a s e s c a n be  investigated. The problem w i t h t h e  third  16 d e m o g r a p h i c e x p l a n a t o r y periods)  extension  variables  there w i l l  Toronto there w i l l to  are  be few r e m a i n i n g  F o r V a n c o u v e r and Ottawa t h e r e w i l l be 3 6 .  loaded  degrees  be o n l y  The r e s u l t s  be i n c l u d e d f o r  into of  from t h i s  all  x 2 the  freedom.  1 d.f.;  t h e model must be v i e w e d w i t h s k e p t i c i s m b u t  nevertheless  once  (8 v a r i a b l e s  and h o u s i n g m a r k e t v a r i a b l e s  regression,  is that  for  extension will  completeness.  C H A P T E R SUMMARY The c h a p t e r constructed for gentrification premise t h a t ,  has d e s c r i b e d t h e this  thesis  i n Canada. as the  r e g r e s s i o n model  to predict The model  literature  intra-urban  i s b a s e d on  claims,  gentrification  follows  a l o g i s t i c c u r v e so t h e r e  initial  d e m o g r a p h i c c h a n g e i n an i n n e r - c i t y  that  is gentrifying  literature city  and t h e  is correct,  rise  i s a l a g between  have f u t u r e p r i c e  neighbourhood  which  are  constructed  from  If  the  inner-  increases  o b s e r v i n g which ones a r e u n d e r g o i n g demographic The m o d e l ' s v a r i a b l e s  the  in housing p r i c e s .  t h e n one c a n p r e d i c t  neighbourhoods w i l l  the  by  change. 1961,  1971,  50  a n d 1981  Canada C e n s u s d a t a .  c o n s i d e r e d t o be a c c u r a t e . the data,  however,  On t h e w h o l e ,  the  data  is  The u n d e r l y i n g l i m i t a t i o n  is that  it  is available  only in  of  ten-year  periods. There are ability  of the model.  determine fact  four extensions to  whether  If  not,  of  predictive to  demographic changes i n p e r i o d 1 can housing p r i c e  increases  in  in  d e m o g r a p h i c c h a n g e s i n p e r i o d 1 may  m e r e l y be a c o r r e l a t e determinant  the  The e x t e n s i o n s a r e d e s i g n e d  be o b s e r v e d e f f e c t i n g  p e r i o d 2.  evaluate  to period 2 price  i n c r e a s e s and n o t  a  gentrification. The r e g r e s s i o n e q u a t i o n s  Regression Equations:  t h e model and e x t e n s i o n s a r e a s  for  follow:  MODEL: RENT2  i  = B + B-LAGEli + B U N V R S l + B P R F O C l + B F M L B R l BFJFMPROCIJ^ + BgNFMHSl^ + B y C H L D l ^ + BgNORLGl^ + BgRENTljL + B-^QRSTZDV^ + B-^iVANDUM^ + B 2 i i 0  2  i  3  i  4  0  T  T  D  U  +  i  M  +  1  E  VALUE 2  =B + B ^ G E l i + B U N V R S l + B P R F O C l + B F M L B R l BsFMPROCli + BgNFMHSlj^ + B C H L D l + BgNORLGl^ + B g V A L U E l i + Bj^oVSTZDVi + B-L-JVANDUMJL + B 2 i Ei Q  2  i  3  ?  i  4  i  +  i  0  T  T  D  U  M  +  1  EXTENSION 1: R E N T l i = B + B^AGElj^ + B U N V R S l + B P R F O C l + B F M L B R l BgFMPROCljL + BgNFMHSlj^ + B y C H L D l ^ + BgNORLGl-^ + 0  BgVANDUM^ +  2  i  B-J^QOTTDUM^ +  3  i  4  2  I  i  I  DUM  +  i  +  Ej^  VALUER =B + B-LAGEIJ^ + B U N V R S l + B P R F O C l + B F M L B R l BsFMPROCli + BgNFMHSli + B^CHLDl^ + BgNORLGl-^ + BgVANDUMi + B ° ' " ' i i Q  i  3  i  4  + E  10  51  EXTENSION 2: RENT 2 ^ = B + B A G E 2 + B UNVRS2 + B PRFOC2i + B FMLBR2 B FMPROC2 + B NFMHS2 + B C H L D 2 + BgNORLG2 + Q  1  5  i  2  i  i  6  3  i  y  4  i  BgRENTli + B-LQRSTZDV! + B^VANDUMi + B-^OTTDUMi E  VALUE 2 £  +  i  + B A G E 2 + B UNVRS2 + B PRFOC2JL + B F M L B R 2 B FMPROC2 + B NFMHS2 + B CHLD2JL + B NORLG2 +  =B  1  Q  5  i  2  i  i  6  4  3  i  7  Q  +  i  i  BgVALUEl^ + B^^oVSTZDVi + B^^VANDUM^ + B O T T D U M 1 2  E  +  i  i  +  I  i  EXTENSION 3: RENT 2 ^ = B + B^AGElj^ + B A G E 2 + B U N V R S l + B U N V R S 2 + B g P R F O C l i + B P R F O C 2 i + B F M L B R l + BgFMLBR2 + BgFMPROCli + B F M P R O C 2 + B-j^NFMHSl^ + B N F M H S 2 + B C H L D l + B C H L D 2 + B-j^NORLGli + B N O R L G 2 B ^ R E N T ^ + B^gRSTZDV^ + B^gVANDUM-^ + B O T T D U M + Q  2  i  3  6  ?  10  1 3  i  i  4  i  i  i  i  1 4  1 2  i  i  1 6  i  2Q  E  i  i  VALUE2j, = B + B ^ A G E ^ + B AGE2j, + B U N V R S l + B U N V R S 2 + B s P R F O C l i + B P R F O C 2 + B F M L B R l + Bg FMLBR2 ^ + BgFMPROCl^ + B F M P R O C 2 + B ^ N F M H S l i + B N F M H S 2 + BJ^-JCHLDIJL + B C H L D 2 + B ^ N O R L G l ^ + B N O R L G 2 B^^yVALUEljL + B-LgVSTZDVi + B-^gVANDUM^ + B O T T D U M + Q  2  6  3  i  ?  10  i  4  i  i  i  1 4  i  1 2  1 6  2Q  E  EXTENSION 4:  i  i  i  Run t h e r e g r e s s i o n s w i t h o u t t h e dummy v a r i a b l e s f o r each c i t y s e p a r a t e l y .  52  i  CHAPTER  5  DATA ANALYSIS  This  chapter presents the r e s u l t s of the  intra-urban  g e n t r i f i c a t i o n p r e d i c t i v e model a n d i t s e x t e n s i o n s were d e s c r i b e d multiple  i n C h a p t e r 4.  regression  analysis  whether t h e r e i s a c a u s a l , earliest and  Correlation a r e used t o  CORRELATION  analysis  investigate  (demographic  ANALYSIS  correlation analysis  of the three c i t i e s .  of the analysis.  variables  Part  2.  A of the table  a r e contemporaneous c o r r e l a t e s  Part  correlated  B shows w h i c h p e r i o d  to period  designed so t h a t  1 is a  shows w h i c h  to inner-city i n periods  1  2 p r i c e changes.  The t a b l e i s  t h e performance o f each v a r i a b l e  c a n be  the performance o f  c a n be a n a l y z e d b y r e a d i n g down t h e t a b l e .  Variables:  The s i g n s  of the correlations are  predominantly as expected—unexpected discussed  from  1 variables are  a n a l y z e d by r e a d i n g a c r o s s t h e t a b l e ; each c i t y  compiled  Table  h o u s i n g p r i c e change, i . e . , g e n t r i f i c a t i o n , and  transition)  escalations.  Appendix A c o n t a i n s m a t r i c e s and t a b l e s  summary  and  l a g g e d r e l a t i o n s h i p between t h e  phase o f g e n t r i f i c a t i o n  subsequent p r i c e  that  i n the multiple  regression  signs section  will  be  of this  chapter.  53  Table 1: Summary of C o r r e l a t i o n Analysis  A) Contemporaneous Correlates to G e n t r i f i c a t i o n . Period 1 and 2 3 Cities Per.1  Vancouver Per.1  Per. 2  Ottawa-Hull  Per.2  Per.1  Rnt Val Rnt Val Rnt Val Rnt Val Variables U n i v e r s i t y education 20-34 year olds  C1 C  -C1 C1  Female labour force Female prof, occupations  C C1  C1 C -C  •C1-C  -C  C1  8  5  C  C1  4  C  11  .05 8  C  CI  -C  -C C1  -C1-C  2 5 2 9 7  C -C  7 7  C 6  5 16 7  6 4  Tot  Rnt Val Rnt Val  -C  C1 C C C1  C1  2  13 9 Legend:  -C  C1 C1 C1 -C1  Per.2  Per.1  C1 C1  C  C1 C -C  C1  Sub-total T o t a l : .05 s i .01 s i  Per.2  Rnt Val Rnt Val  C1  C1 C1  Not r e l i g i o u s Non-family households Children per family P r o f e s s i o n a l occupations  Toronto  6 12 5  C = C o r r e l a t i o n at the .05 s i g n i f i c a n c e l e v e l C1= C o r r e l a t i o n at the .01 s i g n i f i c a n c e level  B) Period 1 Variables that are Correlated to Period 2 G e n t r i f i c a t i o n 3 Cities  Vancouver  Ottawa  Toronto  Rent Value  Rent Value  Rent Value  Rent Value  Variables U n i v e r s i t y education 20-34 year olds Not r e l i g i o u s Non-family households Children per family Professional occupations Female labour force  Total  P  P1L PL PL  -P1L  P1L P1L  P1 -PL  P  -P  P1L PL PL  Female prof, occupations Rent/Value 1971 rent/value z-score  P P1L PL  P1  P1 P -P -P1  Sub-total T o t a l : .05 s i .01 s i L  1  5 6 1 5  Legend:  2  2 4 3 1  2  1 3 1 2  4  .05  .01  L_  2 3 3 1 1 5 3 2  1 2 2 0 0 3 1 0  1 3 2 1 0 2 2 1  1 1  0 1  n/a n/a  5 9 5 4  P = C o r r e l a t i o n at the .05 s i g n i f i c a n c e l e v e l P1= C o r r e l a t i o n at the .01 s i g n i f i c a n c e level PL= Evidence of lag  Data compiled from Appendix A.  54  In  part A of Table  "university  1,  "children per  e d u c a t i o n " have t h e  contemporaneous c o r r e l a t i o n across the  table,  to  highest  family  nine of  sixteen  regressions.  O n l y two  perform p o o r l y :  reading is  1 1  to housing p r i c e s  regressions; "university  demographic v a r i a b l e s  of  "children per  one s e e s t h a t  of the  incidence By  contemporaneous c o r r e l a t e  so i n e i g h t  and  housing p r i c e s .  significant the  family"  in  education"  of  the  a  is  eight  "20-34 y e a r  olds"  and  "non-family households." Relevant were a b l e  to t h i s  to predict  shows how t h e  thesis  i s which demographic  gentrification.  demographic v a r i a b l e s  Part  B of  Table  performed as  alone,  however,  correlation.  correlated  to p r i c e s i n p e r i o d 2 but  increases.  demographic changes might the  demographics i n p e r i o d  p e r i o d 1 demographics might  caused p e r i o d 2 p r i c e  effect,  also to  Instead,  have been t h e  period  in period 1 is correlated  is  i n p e r i o d 1.  that are  correlated  actually  period  affect,  1  rather  in period  1.  is  this  type  of  P e r i o d 1 demographic  to p e r i o d 2 p r i c e s but  contemporaneous c o r r e l a t e s  if  than 1 and  demographics  to p r i c e s i n p e r i o d 2 but  Evidence of  i n p a r t B of Table  in  2.  A stronger case f o r p r e d i c t a b i l i t y  prices  of 1 was  prices  n o t have  o f p r i c e movements t h a t s t a r t e d  continued into  Lagged  convincing proof  predictive  p e r i o d 1,  If  i s not  1  lagged  period 1 predictors of period 2 g e n t r i f i c a t i o n . correlation  variables  are  not  to  correlation variables not  to p e r i o d 1 p r i c e s i n p a r t A of  55  the  t a b l e are  Table  1,  period  i n d i c a t e d by " L " .  one s e e s t h a t t h e  2 gentrification  occupations,"  "not  However, the  gentrification  rise  in prices  best period  1 predictors  were " 2 0 - 3 4 y e a r  religious,"  there i s  Reading a c r o s s p a r t  still  olds,  and " f e m a l e  doubt.  p r o c e s s might  It  The r i s e  n o t h a v e b e e n enough t o be s i g n i f i c a n t l y change i n demographics i n p e r i o d demographics might price  h a v e b e e n enough t o  increases that continued  words,  the  gentrification  by p r i c e movements r a t h e r contrary  t o what t h e  Table 2 are  the  1 but  into  2 helps resolve the differences  1 that  between  in  correlated  the  slight  in prices  change  turn might  to  the  in  be c o r r e l a t e d In  to  other  have been  t h a n by demographic  literature  that  with a  p e r i o d 2.  p r o c e s s might  force."  is possible  i n a neighbourhood i n p e r i o d  c a u s e d a change i n d e m o g r a p h i c s .  of  professional  labour  have s t a r t e d  B of  sparked  changes,  claims. issue.  the  The numbers  average  in  Table  inner-city  percent  c h a n g e i n h o u s i n g p r i c e s p e r room m i n u s t h e CMA  percent  change f o r  Table  2:  the  two  periods.  % Change i n H o u s i n g P r i c e s p e r R e l a t i v e t o t h e CMA Value  Rent 61-71 Vancouver Ottawa-Hull Toronto Data  -10 1 -1  room  71-81 35 38 29  c o m p i l e d from Canada C e n s u s ,  61-71  71-81  4 0 7 1961,  20 58 64 1971,  and  1981  The a v e r a g e the  three c i t i e s  change i n varies  inner-city  little  rents  in relation  and v a l u e s to  in  t h e CMA  c h a n g e d u r i n g p e r i o d 1.  I n n e r - c i t y neighbourhoods as a  whole d i d not  r e l a t i v e price gains u n t i l  2.  experience  Therefore,  Table  p e r i o d 1 demographic v a r i a b l e s  1 that are  to p r i c e s  correlated  in period  literature  1  (the  to prices "PLs")  c o n t e n d s : The i n i t i a l  neighbourhood i s demographic. whole g e n t r i f i c a t i o n initial  demographic  Cities:  i n p r i c e s and  By r e a d i n g down p a r t A o f T a b l e  incidence of  contemporaneous c o r r e l a t i o n  Ottawa f a r e d between  demographics i n p a r t correlates  gentrifying  have the  the  this  stimulus.  with a score of  correlations  not  the  a consequence of  t h a t Ottawa,  cities.  B of  2 but  s u p p o r t what  The r i s e  process i s  in part  in period  phase i n a  period  sixteen,  poorly,  though,  had t h e of  with  1,  the  the  three  predictive 1  t a b l e — t h e o n l y two  wrong s i g n .  The d a t a  sees  highest  p e r i o d 2 p r i c e s and p e r i o d B of  one  "PL"  indicates  that  t h e r e was a l a g between  demographic change and h o u s i n g  price  the  change i n Ottawa,  have a l l  occurred w i t h i n the  The h i s t o r y reflected  i n the  of Ottawa's data.  housing r e h a b i l i t a t i o n years,  l a g and t h e  same t e n - y e a r inner-city  Ottawa's until  1975.  downtown  events period.  For the  d i d not first  i n the  i n the  decade  (Ley,  is  undergo  few  rental  L a r g e - s c a l e condominium c o n s t r u c t i o n c l o s e occurred l a t e r  must  h o u s i n g market  inner-city  r i s i n g p r i c e s were p r e d o m i n a n t l y  sector.  two  if  1985).  to Part A  57  of  Table  1 shows t h a t t h e r e a r e  four  correlates  t o p e r i o d 2 Ottawa r e n t .  transition  started  the  If  gentrification  Ottawa,  then demographic t r a n s i t i o n ,  of  i n c r e a s e s must h a v e a l l  rent  2 years p r i o r lag,  to  however.  1975.  The d a t a  not  demographic  process off the  lag,  four  does not  Ottawa's.  between  a causal lagged  Residential  particularly mid 1970s. west-side  of  the  prices  redevelopment  Demographic t r a n s i t i o n  1985).  price  c h a n g e b o t h happened i n p e r i o d 2 ,  is  for  Ottawa.  L i k e Ottawa,  and  i n the  data  for  Vancouver i s  the  CMA i n p e r i o d 2 ,  the  inner-city  O t t a w a and T o r o n t o were t h r e e t i m e s Nevertheless,  the  data  happened i n V a n c o u v e r . is  not  some c o r r e l a t i o n  other  that there i s p r a c t i c a l l y  and  as  in  points  innermore in  Vancouver  A of Table  Part  the  as s t r o n g  does s u p p o r t  between  the  1981.  increases  that of  Part  d e m o g r a p h i c s and p e r i o d 2 p r i c e s . indicates  core,  was i n  i n Vancouver  than  that there  to  A r e a s o n f o r weak c o r r e l a t i o n  n e i g h b o u r h o o d s i n c r e a s e d 20 p e r c e n t a g e  actually  similar  city  area,  1971  city  2).  was  demographic change  V a n c o u v e r may be t h a t a l t h o u g h v a l u e s  (Table  this  neighbourhoods o c c u r r e d throughout  (Ley,  it  show  i n F a l s e Creek and  1970s  The c o r r e l a t i o n  period  one.  F a l s e Creek i n d u s t r i a l  inner-city  start  shows o n l y t h a t t h e r e was a  The c h r o n o l o g y o f V a n c o u v e r g e n t r i f i c a t i o n to  in  and t h e  occurred i n the  The O t t a w a d a t a  contemporaneous c o r r e l a t i o n demographics,  contemporaneous  what 1 shows  period 2 B of  no l a g g e d  the  table  correlation  58  b e t w e e n p e r i o d 2 p r i c e s and p e r i o d 1 d e m o g r a p h i c s .  Since  inner-city  p r i c e s d i d n o t move i n V a n c o u v e r u n t i l  the  1970s,  inner-city  reports  the  t o have s t a r t e d the mid-1970s does not  demographic change t h a t  i n the  price  show t h i s  early  Ley  1970s c o u l d h a v e  increase.  precipitated  The V a n c o u v e r d a t a ,  lagged r e l a t i o n s h i p .  mid  The d a t a  however, only  shows a c o n t e m p o r a n e o u s o n e . Gentrification either  Ottawa  transition  in Toronto started  or Vancouver.  The s t a r t  earlier of  from lower-income b l u e - c o l l a r h o u s e h o l d s ones i n t h e  in  p i c k e d up i n  House s a l e s a c t i v i t y  neighbourhoods but, was no s u b s t a n t i a l  just rise  of g e n t r i f i c a t i o n .  as the  for  however,  had f o r  the  was 139%  (Ley,  The t i m i n g  first  between  start  that there between  inner-city and The the  Don V a l e ' s  mean  i n Toronto enables  t h e s i s to d i s t i n g u i s h the  o f demographic t r a n s i t i o n  in housing p r i c e s .  i s very  little  In  fact,  contemporaneous  two o f t h e  and  Part A of  p e r i o d 2 changes i n d w e l l i n g v a l u e  demographics.  phase  CMA mean and The A n n e x ' s mean  of g e n t r i f i c a t i o n  model i n t h i s  subsequent r i s e  there  time equalled  By 1981,  was  1985).  intra-urban the  centre  early  (Cabbage Town)  m e t r o T o r o n t o mean s a l e s p r i c e . s a l e s p r i c e was 156% o f t h e  two  to  central  in prices during t h i s  By 1978,  example,  city  literature claims,  T o r o n t o n e i g h b o u r h o o d s , Don V a l e Annex,  in  demographic  m i d d l e - i n c o m e CBD w h i t e - c o l l a r 1969.  than  the lag  the  Table  1 shows  correlation and p e r i o d 2  only three  correlates  59  have the other  wrong s i g n .  hand,  variables  i s very  that  Lagged p r e d i c t i v e strong.  in period  There are  1 are  2 changes i n Toronto d w e l l i n g contemporaneous c o r r e l a t e s part B of Table In  other  Toronto  i n the  transition  words,  the  rise  in  2 value  the  The c o i n c i d e n c e o f  to  (the  of  not  2 are  "PLs" in  b o u n d a r y between the  lag  literature:  in  period Toronto  boundary  what h a s o n l y  future housing p r i c e  increases  in  fact  the  in gentrifying  B u t how l o n g i s t h e indicate before  T o r o n t o shows t h a t  increases  1970s.  change.  price  neighbourhoods. lag?  in central-city  i n the  which  demographic  precursor of housing  t h a t t h e r e was l i t t l e ,  1971  been  increases,  c a n be p r e d i c t e d by o b s e r v i n g  for  prices  1 and  neighbourhoods are b e g i n n i n g t o undergo demographic The d a t a  in  1970s.  demographics and  show s t a t i s t i c a l l y  gentrification,  is  not  house p r i c e s  i n the  with the model's time p e r i o d  e n a b l e s t h e model t o  transition  period  demographic  1960s,  l a g between  period  Lag:  the  demographic  in period  inner-city  1970s i s c o r r e l a t e d  occurs at  i m p l i e d by t h e  but  to period  because i t  i.e.,  value  on  1).  The model p i c k s up t h e  gentrification  four  lagged c o r r e l a t e s  that occurred i n the  2.  correlation,  Vancouver and Ottawa if  any,  demographic  neighbourhoods t h a t had  Since gentrifying  data change price  neighbourhoods  i n b o t h Ottawa and V a n c o u v e r h a d e s c a l a t e d h o u s i n g p r i c e s b y 1975  (Ley,  1985)  and s i n c e t h e r e was no  significant  d e m o g r a p h i c change i n t h e s e n e i g h b o u r h o o d s b e f o r e  1971,  the  60  l a g must h a v e b e e n between less  than  before  four years.  they  REGRESSION  0 and 4 y e a r s .  reached the  level  for  the  three  For each r e g r e s s i o n , a l l appropriate model.  increasing  t h a t t h e y were a t  cities  results  of  in  1975.  combined and  explanatory  h o u s i n g market  multiple separated.  demographic  variables  variables  were  included  V a r i o u s p e r f o r m a n c e and d i a g n o s t i c  measurements were r e c o r d e d .  T h e n , by r e p e a t e d l y  the v a r i a b l e  t-statistic  with the  remaining v a r i a b l e s (backward  probably  ANALYSIS  regressions  i n the  was  P r i c e s would have s t a r t e d  A p p e n d i c e s B and C c o n t a i n t h e  and t h e  It  lowest  had a t - s t a t i s t i c  stepwise r e g r e s s i o n ) ,  until  greater  sweeping all  than  1  a " B e s t M o d e l " was  determined. A "Best Model" i s the variables  combination of  i n a model t h a t y i e l d e d t h e  explanatory  highest  adjusted  Backward s t e p w i s e r e g r e s s i o n was i n c l u d e d i n t h e to determine  which group of e x p l a n a t o r y  R . 2  analysis  variables  in  each  errors  were  model b e s t p r e d i c t e d h o u s i n g p r i c e c h a n g e s . Generally, normal.  the  distributions  F o r most o f t h e  was l e s s t h a n  of  residual  " B e s t M o d e l " r e g r e s s i o n s , skewness  1 and k u r t o s i s was l e s s t h a n  2.  T h e r e were two T o r o n t o o b s e r v a t i o n s i n t h e whose r e s i d u a l e r r o r standard deviations census t r a c t  was c o n s i s t e n t l y g r e a t e r f r o m t h e mean.  adjacent  to  sample  than  5  One o b s e r v a t i o n was a  Cabbage Town i n T o r o n t o .  It  was  61  an extreme  outlier  when v a l u e was r e g r e s s e d on p e r i o d  period 2 explanatory a tract  adjacent  extreme  outlier  variables.  The s e c o n d o b s e r v a t i o n was  t o R o s e d a l e and F o r e s t H i l l .  It  was  an  when r e n t was r e g r e s s e d on p e r i o d 1 o r  period 2 explanatory  variables.  B o t h o b s e r v a t i o n s were  T o r o n t o a r e a s t h a t Ley i d e n t i f i e d  as s t r o n g  during the  all  1970s  (Ley,  1985).  In  i n c l u d e d t h e s e two v a r i a b l e s ,  regressions that  normality  of  residual  outlier  o b s e r v a t i o n was  ( s e e A p p e n d i x B, p a g e s 9 2 ,  93,  and 9 9 ) .  98,  Model" r e s u l t s presented i n the two o b s e r v a t i o n s  in  gentrifiers  was a c h i e v e d o n l y o n c e t h e  the  1 or  following  The  errors deleted  "Best  tables  are  with  deleted.  The r e g r e s s i o n r e s u l t s regressions with explanatory  a r e p r e s e n t e d i n two  parts:  demographic v a r i a b l e s  p e r i o d o n l y and r e g r e s s i o n s w i t h e x p l a n a t o r y  f r o m one  variables  from  both periods pooled.  E x p l a n a t o r y V a r i a b l e s from One P e r i o d : 4 are  summaries o f t h e  using explanatory B).  Table  variables; Table the  performance of  A of the  variables  regressions  overall  (Appendix  explanatory the  cities.  performance  c a n be a n a l y z e d a c r o s s  table  of  the  shows w h i c h " B e s t M o d e l "  had s i g n i f i c a n t  c o e f f i c i e n t s when r e g r e s s e d a g a i n s t dependent p r i c e v a r i a b l e s .  the  performances of  3 i s d e s i g n e d so t h a t the variables  for  f r o m one p e r i o d o n l y  T a b l e 4 compares t h e  Part  explanatory  variables  3 analyzes the  explanatory  cities.  "Best Model" r e s u l t s  T a b l e s 3 and  Part  regression  contemporaneous  B of the  table  shows w h i c h  62  Table 3: Summary of M u l t i p l e Regression A n a l y s i s  A) "Best Model" Regression C o e f f i c i e n t s f o r G e n t r i f i c a t i o n Regressed Against Contemporaneous Variables 3 Cities Perl  Per2  Rt VI Rt V! Explanatory V a r i a b l e s U n i v e r s i t y education 20-34 year olds Not r e l i g i o u s Non-family households Children per family Professional occupations Female labour force Female prof, occupations Multicol I inearity legend:  Vancouver Perl Rt  yi  Per2  Perl  Rt VI  Rt  C1  Yi  Toronto  Per2  Perl  Rt V i  Rt  -C2 C C -C2  C2  Ottawa  C C  C -C1 C -C2-C2 C2 C2 C C -C2 C C  C -C1 -C2-C1-C2-C2 C C1 C2 C C2 C -C2  n n n y  n y y n  Per2  yi  Total  Rt V i  .05 .01  C C1 -C1  -C -C1  5  1 0 2  -C C -C1 C C2 C C2 -C -C2 C -C  -C1-C2 C1 C1-C -C2-C -C2 -C C2-C  1 10 7 6 2  0 6 4 6 2  C1-C C C C  n n n n  2 1  n y y y  C = Variable included i n "Best Model", i . e . , regression c o e f f i c i e n t t - s t a t > 1 C1= Regression c o e f f i c i e n t s i g n i f i c a n t at the .05 l e v e l ; C2= s i g n i f i c a n t at .01  B) "Best Model" Regression C o e f f i c i e n t s f o r Period 2 G e n t r i f i c a t i o n Regressed Against Period 1 Variables 3 Cities Rent Value Explanatory V a r i a b l e s U n i v e r s i t y education 20-34 year olds Not r e l i g i o u s Non-family households Children per family Professional occupations Female labour force Female prof, occupations Rent/Value 1971 rent/value z-score Multicollinearity Legend:  -P  P2  Rent Value  Ottawa  Total  Toronto  Rent Value  Rent Value  .05 .01  P2L  -P2L -P1L P2L P1L  -P2L -P -PI -P1 y  Vancouver  y  P1L P1L  -P P1 -P  P2 P2 -P  -P1L  -P2  P  P2  -P P1 -P  P2L -P2L P2  P1L -P  -P1  n  -P1 -P  -P P  y  y  -P y  n  1 0 3 2 2 7 3 2 1 3  L  1 1 0 0 1 1 1 2 1 2 4 3 2 1 1 2 0 n/a 1 n/a  n  P = Variable included i n "Best Model", i . e . , regressionc o e f f i c i e n t t - s t a t > 1 P1= Regression c o e f f i c i e n t s i g n i f i c a n t at the .05 l e v e l ; P2= s i g n i f i c a n t at .01 PL= Evidence of lag  Data compiled from Appendix B.  63  period 1 explanatory  variables  had s i g n i f i c a n t  coefficients  when r e g r e s s e d a g a i n s t p e r i o d 2 p r i c e v a r i a b l e s . correlation  analysis, variables  that predict  As  in  period 2  p r i c e s when l a g g e d i n p e r i o d 1 b u t n o t when c o n t e m p o r a n e o u s i n p e r i o d 2 are  noted with " L " .  The p e r f o r m a n c e s o f t h e multiple  demographic v a r i a b l e s  regression in Table  correlation  3 are  analysis in Table  1.  consistent with those For both  r e g r e s s i o n and l a g g e d r e g r e s s i o n , t h e demographic v a r i a b l e s religious," force."  are  a strong performer Included  i n part B of Table  z-score variable.  It  inner-city  3 are  Table  3 shows e v i d e n c e t h a t t h e  average p r i c e  for  the  and N a r o f f ' s  the  1971  is  not  the  housing  inner-city.  z-score variable  This  is  a  especially  the  supports  finding that gentrifiers  prefer  the best housing deal  change i n average h o u s i n g p r i c e  is  b e t w e e n an  average  entire  The s e c o n d h o u s i n g m a r k e t e x p l a n a t o r y  correlation  the  two h o u s i n g  of p e r i o d 2 p r i c e change,  neighbourhoods t h a t o f f e r  little  and  olds"  difference  z - s c o r e i n the Vancouver model.  Melchert  labour  One h o u s i n g v a r i a b l e  census t r a c t ' s  and t h e  predictor  "20-34 y e a r  measures t h e  price  value  "not  in regression analysis.  variables.  negative  family,"  between t h e s e r e s u l t s  market e x p l a n a t o r y  individual  strongest  " p r o f e s s i o n a l o c c u p a t i o n s , " and " f e m a l e  a n a l y s i s ones i s t h a t  of  contemporaneous  four  "children per  The o n l y d i f f e r e n c e  correlation  during  (1987) .  variable  i n p e r i o d 1.  between p e r i o d 1 i n n e r - c i t y  There  is  the  is  housing  64  p r i c e c h a n g e s and p e r i o d 2 c h a n g e s . price  increases i n the  until  the  This indicates  Canadian i n n e r - c i t y  d i d not  1970s w h i c h i s c o r r o b o r a t e d by T a b l e  a s s o c i a t e d w i t h i n c r e a s e d female p a r t i c i p a t i o n force  (Smith,  1987;  Berry,  non-conforming households (Ley, that  i n p a r t B o f T a b l e 3,  analysis,  "female  coefficients  labour  have a n e g a t i v e  It  in  is  1 for  f o r c e " and " n o t  the in  interesting correlation  religious"  s i g n when r e g r e s s e d a s  variables  period  against period 2 p r i c e s ,  sign i n part A of  as p e r i o d 2 e x p l a n a t o r y  is  and an i n c r e a s e  1985).  as i n T a b l e  have a p o s i t i v e  1 lagged explanatory  1985)  occur  2.  The l i t e r a t u r e c o n t e n d s t h a t g e n t r i f i c a t i o n  labour  that  variables  the  table  against  yet  when r e g r e s s e d  contemporaneous  period 2 prices. T h e most e x t r e m e religious."  switch in signs i s  as a contemporaneous v a r i a b l e its  seems t h a t  t-statistic i n the  proportion of  rise,  to  its  t-statistic  regressed against  -2.5  ( A p p e n d i x B,  Once m o d e r a t e  higher  first  is  Toronto's  page 9 9 ) .  It before  inner-city  r e n o v a t i o n s were made t o  wave o f g e n t r i f i e r s  +4.8;  period 2  stage of g e n t r i f i c a t i o n , rise,  "not  variable  non-conformist individuals r e l a t i v e  h o u s i n g by t h e to  is  earliest  housing p r i c e s started  CMA r o s e .  Toronto  As a l a g g e d p e r i o d 1 e x p l a n a t o r y  regressed against period 2 value,  value,  for  to  the  the  and p r i c e s  started  s o c i o - e c o n o m i c g r o u p s were a t t r a c t e d  neighbourhood.  T h i s s c e n a r i o conforms t o the  gentrification"  reported  i n the  literature  to  the  "staged  (Berry,  1985;  65  Ley,  1985; M e l c h e r t  affluent  and N a r o f f ,  of the switching  explanation Table cities. from R  2  I f one assumes t h a t  " s e c o n d wave" h o u s e h o l d s a r e g e n e r a l l y more  conforming than l e s s a f f l u e n t riddle  1987).  "first  wave" o n e s , t h e n t h e  sign i s explained.  o f f e r e d here should  R s and F s  t e s t ) o f t h e r e g r e s s i o n s t h a t had f r o m one p e r i o d  4:  (F-statistic  2  explanatory  only.  Comparison o f " B e s t M o d e l " A d j u s t e d R s ( F - s t a t f r o m R^ t e s t i n P a r e n t h e s e s ) 2  VALUE  RENT  Cities  Vancouver Ottawa-Hull Toronto  data.  4 summarizes t h e r e g r e s s i o n p e r f o r m a n c e s o f t h e  Table  3  the  be s u b s t a n t i a t e d w i t h  I t compares t h e a d j u s t e d  variables  Of course,  Indp. V a r i a b l e s i n : Period 1 Per.2  Indp. V a r i a b l e s i n : Period 1 Per.2  Rent2  Valu2  .14 (3.6)  Rentl  2  .38 (20.)  Rent2  2  .30 (5.9)  2  .18 (4.4)  .56 (9.2)  .28 (2.9)  .64 (6.7)  .80 (16.6)  .39 (3.0)  .72 (13.)  .41 (3.7)  50 (5.9)  .27 (4.3) Note:  z  1 2  .35 . 39 ( 9 . 5 ) ^ (6.6)  .52 (20.)  2  Valul  2  2  2  .06 (3.8) .72 (13.) .53 (6.) .17 (6.5)  2  Valu2  1  .15 (3) 84 (21)  2  2  46 (3.7) .29 (4.9)  2  2  1  2  = s i g n i f i c a n t a t .05 l e v e l = s i g n i f i c a n t a t .01 l e v e l  Data compiled  from Appendix B  66  If period  period  1 demographic change  2 price escalation in gentrifying inner-city  neighbourhoods, p e r i o d two  i s the determinant of  requirements:  1 d e m o g r a p h i c v a r i a b l e s must  First,  period  1 demographic  must p r e d i c t p r i c e c h a n g e s i n p e r i o d p r e d i c t p r i c e changes i n p e r i o d columns  1,  variables  2 b e t t e r than they  i.e.,  the R s  i n columns  T h i s would e s t a b l i s h t h a t p e r i o d  demographics a r e not merely the a f f e c t o f p e r i o d movements t h a t  and Fs i n  2  1 a n d 4 o f t h e t a b l e must e x c e e d t h o s e  and 5 r e s p e c t i v e l y .  satisfy  continued  into period  2.  2  1  1 price  Second, p e r i o d  1  d e m o g r a p h i c v a r i a b l e s must p r e d i c t p r i c e c h a n g e s  i n period  2 better than period  i . e . , the  R s 2  2 d e m o g r a p h i c v a r i a b l e s do,  and F s i n c o l u m n s  t h o s e i n columns that period  1 and 4 o f t h e t a b l e must e x c e e d  3 and 6 r e s p e c t i v e l y .  2 p r i c e c h a n g e s were e f f e c t e d b y  demographics i n p e r i o d  1 r a t h e r t h a n by  demographics i n p e r i o d  2.  T a b l e 4 shows t h a t t h e s e two fulfilled  This  convincingly  The p r e d i c t i v e , c a u s a l demographic change  lagged  requirements are  when v a l u e i s r e g r e s s e d r e l a t i o n s h i p between  i n the l a t e  1960s  f o r Toronto.  lagged  and d w e l l i n g  i n t h e e a r l y 1970s  analysis  i s consistent with the conclusion  i n Toronto m u l t i p l e  Future housing p r i c e increases  As s t a t e d  value  regression  from c o r r e l a t i o n c a n be  by o b s e r v i n g w h i c h n e i g h b o u r h o o d s a r e b e g i n n i n g change as t h e f i r s t  indicate  contemporaneous  increase  analysis:  would  predicted demographic  wave o f g e n t r i f i e r s move i n .  i n t h e d i s c u s s i o n on c o r r e l a t i o n a n a l y s i s ,  67  the  model  i s successful  f o r Toronto but not f o r Vancouver  a n d O t t a w a b e c a u s e t h e l a g between inner-city  the s t a r t  of Toronto  d e m o g r a p h i c t r a n s i t i o n and s u b s e q u e n t h o u s e  p r i c e e s c a l a t i o n coincides with the time period the  model.  c h a n g e was  The s t a r t  i n t h e same t i m e p e r i o d  p r i c e c h a n g e was Why but  o f V a n c o u v e r and O t t a w a  s o t h e l a g was  d o e s t h e model work w e l l  not f o r Toronto rents?  demographic  i n t h e model  not  f o r T o r o n t o house  To answer,  increase values rents  i n t h e 1970s.  i n t h e 1970s rose  answer, rent  i n rents  by o n l y  however,  increases,  predict period  First,  rose 29%.  2 rents  rents  rent controls  C h a p t e r 3.  1 demographics should b e t t e r than p e r i o d  b y 64% b u t the  attenuated be a b l e  to  2 demographics  4.  2 o f t h e answer m i g h t be t h a t T o r o n t o i n n e r - c i t y  greater  responding t o increased maintenance—recall Increased  2 to late  t h a n CMA  period  1  rents.  revenues, would  have  t h e economic d i s c u s s i o n i n  maintenance would have  h o u s i n g i n t h e e a r l y 1970s; h i g h e r  improved the  socio-economic  would t h e n have been a t t r a c t e d t o t h e c i t y the  Toronto  Rent c o n t r o l s a r e n o t e n t i r e l y  d e m o g r a p h i c s and i n c r e a s e d  increased  l i m i t e d the  T a b l e 2 shows t h a t  s t a r t e d t o respond e a r l y i n p e r i o d  Landlords,  The a n s w e r i s  r e l a t i v e t o t h e CMA  which i s not the case i n Table Part  prices  one must move f r o m  because even i f c o n t r o l s had period  as housing  detected.  objective analysis to subjective conjecture. p r o b a b l y a t w o - p a r t one.  boundary i n  r e i n f o r c i n g r e l a t i o n s h i p between  centre.  groups Due  demographic change  to and  68  h o u s i n g p r i c e c h a n g e , what t h e model d e t e c t s c o r r e l a t i o n with than period rent  r e i n f o r c e d the  no  period  excessive  there  when t h e  explanatory  because p e r i o d  1 demographic  qualified.  As  noted  was  against  the  two  dependent v a r i a b l e  (Ott  i n Appendix  Model" r e g r e s s i o n s  The  period  variables  f r o m w h i c h t i m e p e r i o d had significant  1 and  A. Table 2  explanatory demographic  regression  t-statistics.  i n d i c a t e s w h i c h t i m e p e r i o d had of the  2  and  of period  t a b l e shows w h i c h  demographic v a r i a b l e from b o t h p e r i o d s  object  than  from b o t h P e r i o d s P o o l e d :  "Best  be  significant  greater  C o r r e l a t i o n t a b l e s are  was the  When a significant,  greater  the  t-  t a b l e i s to determine which  t i m e p e r i o d s ' d e m o g r a p h i c s had period  explanatory  to  (Appendix C).  c o e f f i c i e n t s with  1  2  considered  variables  i n f l u e n c e on  there  M u l t i c o l l i n e a r i t y was  housing p r i c e s against pooled  two  3,  the  5 i s a summary o f t h e  of the  thus  i n some o f  Explanatory Variables  The  stated  i n Table  c o r r e l a t i o n b e t w e e n any  1983).  statistic.  had  multicollinearity  e i t h e r ' s c o r r e l a t i o n with  table  changes,  2 that  period  v a r i a b l e s i n a r e g r e s s i o n was  Hildebrand,  2  m u l t i c o l l i n e a r i t y when T o r o n t o p e r i o d  regressions.  excessive  stronger  demographics  from m u l t i p l e r e g r e s s i o n  slightly  v a r i a b l e s but  2  a  1.  h o u s i n g p r i c e s were r e g r e s s e d  other  period  demographic change i n p e r i o d  conclusions  f a r must be was  s p a r k e d by  in period  The  2 r e n t s by  1 demographics i s probably  increases,  started  period  as  the  stronger  2 p r i c e changes.  69  Table 5:  A)  Summary: H u l t i p l e Regression of Period 2 Gentrif i c a t i o n against Pooled Period 1 and 2 Demographic Explanatory Variables  A l l 8 Demographic Explanatory Variables Included  Demographic Variables U n i v e r s i t y education 20-34 year olds Not r e l i g i o u s Non-family households Children per family  3 Cities  Vancouver  Ottawa  Toronto  Rent Value  Rent Value  Rent Value  Rent Value  1>2 2>1 1>2 1>2  2 2 2 1  1>2  2 1>2  1 2  1 2>1  2>1 1>2  2>1  7  PI  1 2 2  2 1>2 1  2>1  1>2 1  1>2 1  1  1>2  1  2>1 2 1  Dominating Period:  P1  P1  P1  Housing Market Variables Rent/Value 1971 rent/value z-score  1  2  Professional occupations Female labour force Female prof, occupations  1>2  Explanatory Variables Not r e l i g i o u s Children per family Professional occupations Female labour force Dominating Period:  Legend:  P2  1>2 2>1  P2  P1  1 1  B)  2  1  1  1  1  Best 4 Demographic Explanatory Variables Only 3 Cities  Vancouver  Ottawa  Toronto  Rent Value  Rent Value  Rent Value  Rent Value  2 2  2  2 1  1 1>2  P2  P2  P1  PI  2 1  2 1>2 1>2  1  PI  P1  1 = Only period 1 beta c o e f f i c i e n t s i g n i f i c a n t at the .05 l e v e l 2 = Only period 2 beta c o e f f i c i e n t s i g n i f i c a n t at the .05 l e v e l 1>2 = Period 1 and 2 beta c o e f f i c i e n t s both s i g n i f i c a n t at the .05 l e v e l but period 1 t - s t a t i s t i c > period 2 t - s t a t i s t i c 2>1 = Period 1 and 2 beta c o e f f i c i e n t s both s i g n i f i c a n t at the .05 level but period 2 t - s t a t i s t i c > period 1 t - s t a t i s t i c  Data compiled from Appendix C.  Part A of the  table i s regressions  that  include a l l  e i g h t demographic v a r i a b l e s from both p e r i o d s . l a r g e number o f e x p l a n a t o r y degrees of models—a  variables l e f t  freedom—especially  i n the  few  run.  The  multiple regression analyses. of the  second  regressions  The  f o u r most c o n s i s t e n t c o r r e l a t e s  t o h o u s i n g p r i c e s t h r o u g h o u t c o r r e l a t i o n and  set  Vancouver  used f o u r demographic v a r i a b l e s o n l y .  v a r i a b l e s c h o s e n were t h e  the  remaining  O t t a w a and  s e c o n d s e t o f r e g r e s s i o n s was  regressions  Because  are  The  one  period  r e s u l t s from the  summarized  in part  B of  second the  table. Conclusions do  corroborate  t h o s e f r o m c o r r e l a t i o n and  multiple regression analysis. a significant increases Naroff's  price  negative  conclusion  not  literature's  one-period  the value  z-score  was  2 house p r i c e  supports Melchert  that g e n t r i f i e r s prefer  result  period  2.  and  neighbourhoods 2  Second, p e r i o d  house  of demographic t r a n s i t i o n This  claim that there  demographic t r a n s i t i o n rising  This  but  i n T o r o n t o c e n t r a l n e i g h b o u r h o o d s were  predominantly the 1,  cities.  a good h o u s i n g buy.  increases  period  First,  p r e d i c t o r of period  f o r a l l three  that offer  5 are tenuous a t best  drawn f r o m T a b l e  fact  supports  during  the  i s a l a g between t h e  start  i n a g e n t r i f y i n g neighbourhood  of  and  housing p r i c e s .  C o m p a r i s o n Between M o d e l s : determine i f p e r i o d statistically  One  final  test  1 demographic changes can  shown t o p r e d i c t p e r i o d  to  be  2 housing  price  71  increases test.  i s t h e "complete and reduced  The t e s t  determines  model  comparison"  whether t h e a d d i t i o n a l  explanatory v a r i a b l e s i n a complete r e g r e s s i o n t h a t a r e not i n a reduced significant increment  affect  to R  2  form o f t h e e q u a t i o n  on t h e u n a d j u s t e d  model.  There a r e t h r e e models period  2 housing  M o d e l 1:  The t e s t  i s an F - t e s t .  i n this thesis that  predict  explanatory  from p e r i o d 1 o n l y . explanatory  from p e r i o d 2 o n l y .  period 2 p r i c e s regressed against  explanatory  from p e r i o d s 1 and 2 combined.  M o d e l s 1 and 2 a r e r e d u c e d  forms o f Model  contains a l lthe period 1 explanatory 1 plus period 2 explanatory  Similarly,  the additional  period 2 p r i c e s regressed against  variables  Model  i . e . , whether t h e  2  period 2 p r i c e s regressed against  variables M o d e l 3:  have a  price increases:  variables M o d e l 2:  R ,  i s s i g n i f i c a n t when a d d i n g  v a r i a b l e s t o t h e reduced  equation  3.  Model 3  variables that are i n  v a r i a b l e s n o t i n Model  Model 3 c o n t a i n s a l l t h e p e r i o d 2  1.  explanatory  v a r i a b l e s t h a t a r e i n Model 2 p l u s p e r i o d 1 e x p l a n a t o r y v a r i a b l e s n o t i n M o d e l 2. Table  6 shows t h e F - t e s t s t a t i s t i c s  i n c r e m e n t a l R s between t h e two r e d u c e d 2  c o m p l e t e one when p e r i o d 2 v a l u e explanatory  f o r the models and t h e  i s regressed  against the  v a r i a b l e s (see Appendix D f o r F - s t a t i s t i c  calculations).  I f lagged  p e r i o d 1 demographic v a r i a b l e s  are p r e d i c t o r s o f p e r i o d 2 housing  price  increases but  72  T a b l e 6:  F - S t a t Comparison o f Value2 R e g r e s s i o n R^s: Complete v s Reduced Models (.05 s i g n i f i c a n c e l e v e l s i n p a r e n t h e s e s )  3Cities  Vancver  Ottawa  Toronto  Model 3 v s Model 2  1.70 (2.05)  .56 (239)  .94 (239)  6.04 (2.25)  Model 3 v s Model 1  2.31 (2.05)  .75 (239)  .99 (239)  1.10 (2.25)  Data from Appendix D  contemporaneous p e r i o d t h e n two c o n d i t i o n s increase  2 demographic v a r i a b l e s  i n T a b l e 6 s h o u l d b e met:  i n the unadjusted R  2  when p e r i o d  v a r i a b l e s a r e added t o Model 2 ( p e r i o d  are not, F i r s t , the  1 demographic  2 demographic  v a r i a b l e s o n l y ) t o make M o d e l 3 ( p e r i o d  1 and 2 demographic  v a r i a b l e s combined) must b e s i g n i f i c a n t ,  i.e.,  the F-stats  in the f i r s t  row o f T a b l e 6 must b e s i g n i f i c a n t .  the  i n the unadjusted R  increase  2  when p e r i o d  v a r i a b l e s a r e added t o M o d e l 1 ( p e r i o d  the F-stats  2 demographic  1 demographic  v a r i a b l e s o n l y ) t o make M o d e l 3 must b e i.e.,  Second,  insignificant,  i n t h e s e c o n d row o f T a b l e 6 must b e  insignificant. The T o r o n t o d a t a i n T a b l e 6 c o r r o b o r a t e s t h e conclusion  from c o r r e l a t i o n and m u l t i p l e  analysis.  The i n c r e a s e i n t h e u n a d j u s t e d R  period  2  from adding  2 demographic e x p l a n a t o r y v a r i a b l e s t o p e r i o d  v a r i a b l e s when p r e d i c t i n g p e r i o d is  regression  not significant.  2 housing p r i c e  The c o n v e r s e , however,  1  increases  i s significant  73  (adding  1 variables to period  period  In  1 d e m o g r a p h i c v a r i a b l e s a r e much  words, p e r i o d  p r e d i c t o r s of period  2 Toronto dwelling  2 demographic v a r i a b l e s  than period  2 ones).  value  other  stronger increases  are.  CHAPTER SUMMARY This  chapter  presents  the  r e s u l t s of the  g e n t r i f i c a t i o n model—and extensions—that  The  conclusions are  from the  consistent with  gentrification city  statistical  the  c o r r e l a t e d with  ( d e f i n e d i n t h e model as  increases  not  i n the  non-conformist  r e l i g i o u s ) i n the  negatively  city  correlated to  c h i l d r e n per  are  o f f e r a good h o u s i n g Third,  the  statistical  occupations,  i n the  to the  attracted to  analysis of  i s a two-staged process.  second stage i s the  by  of  and  Naroff's  neighbourhoods  buy.  gentrification  the  number  Melchert  supports the  start  female  CMA.  gentrification  the  of  Gentrification is  study corroborates  finding that gentrifiers  inner-  i n d i v i d u a l s (proxied  increases  this  is positively  proportion  centre.  family r e l a t i v e  Second, t h i s  that  in  First,  increased  CMA)  professional/technical/administrative f o r c e , and  analysis in  literature.  housing p r i c e s r e l a t i v e to the  labour  i s described  4.  Chapter  chapter  intra-urban  literature's  Toronto claim The  that  first  stage  is  o f demographic change i n a c e n t r a l n e i g h b o u r h o o d ; affect  of the  first  stage:  rising  74  housing  prices.  Fourth, analysis  and  o f paramount i n t e r e s t  to this thesis,  i n t h i s c h a p t e r shows s t a t i s t i c a l l y — a t  T o r o n t o — w h a t t h e l i t e r a t u r e has future housing  price  o b s e r v i n g which c i t y  o n l y been a b l e t o  The from  single  final  the data.  Toronto, of  and  c e n t r e neighbourhoods are  CBD  B a s e d on t h e c h r o n o l o g y  years—probably  starting  childless  i s extrapolated  of events  in  Vancouver, t h e l a g between t h e  d e m o g r a p h i c change i n a g e n t r i f y i n g  the s t a r t of housing  imply:  e m p l o y e e s b e g i n t o move i n .  conclusion of t h i s chapter  O t t a w a , and  for  i n c r e a s e s c a n be p r e d i c t e d by  demographic change as young, w e l l - e d u c a t e d , couples  least  the  price  l e s s than  start  neighbourhood  and  i n c r e a s e i s between 0 t o 4 4 years.  75  CHAPTER 6  SUMMARY/ CAVEATS, AND CONCLUSION  SUMMARY T h i s t h e s i s uses c o r r e l a t i o n and m u l t i p l e a n a l y s i s t o show t h a t gentrifying  future housing p r i c e  regression  increases i n  c i t y - c e n t r e n e i g h b o u r h o o d s c a n b e p r e d i c t e d by  o b s e r v i n g which o f these neighbourhoods a r e b e g i n n i n g t o undergo  demographic  change,  the f i r s t  phase o f  gentrification. Chapter 2 reviewed t h e g e n t r i f i c a t i o n Gentrification  i s a post-1970  literature.  u r b a n phenomenon.  neighbourhoods t h a t had t r a d i t i o n a l l y  Inner-city  been t h e domain o f  lower-income, b l u e - c o l l a r households l i v i n g  i n filtered,  i n e x p e n s i v e h o u s i n g became p o p u l a r among h i g h e r - i n c o m e groups.  As a consequence,  theprice  o f h o u s i n g was b i d up  i n t h e s e n e i g h b o u r h o o d s a n d t h e h o u s i n g s t o c k was rehabilitated. The  consensus i n t h e l i t e r a t u r e  "gentry" aret y p i c a l l y and c h i l d l e s s c o u p l e s .  t h e young,  i sthat  t h e new u r b a n  upwardly mobile  singles  T h e o r i e s t o e x p l a i n why i n n e r - c i t y  n e i g h b o u r h o o d s became f a v o u r e d b y t h i s g r o u p c a n b e c a t e g o r i z e d as f o l l o w s : demographic, amenities,  and h o u s i n g market.  i n t h e l i t e r a t u r e t o have neighbourhoods  economic,  Demographic  urban  reasons  listed  s t i m u l a t e d demand f o r i n n e r - c i t y  i n t h e 1970s i n c l u d e t h e m a t u r a t i o n o f t h e  baby boom c o h o r t , t h e r e d u c t i o n o f h o u s e h o l d s i z e , a n d  76  urban sprawl. with  The g r o w t h i n CBD employment  t h e d e c r e a s e and s u b u r b a n i z a t i o n  employment made t h e p r o x i m i t y desirable  i n conjunction  of manufacturing  of inner-city  f o r w h i t e - c o l l a r workers.  neighbourhoods  Changing l i f e  e s p e c i a l l y t h e i n c r e a s e i n c h i l d l e s s two-income favoured  city  families,  neighbourhoods c l o s e t o urban a m e n i t i e s .  1970s h o u s i n g  influenced  The  m a r k e t a n d a w i d e n i n g r e n t g a p made  reinvestment  profitable.  styles,  Government p o l i c y  inneralso  gentrification.  Chapter 3 d i s c u s s e d g e n t r i f i c a t i o n w i t h i n an economic framework.  On t h e demand s i d e , t h e r e c e n t  i n n e r - c i t y housing  by h i g h e r  d e s i r a b i l i t y of  income g r o u p s b i d s up t h e  price  o f housing  i n c e n t r a l neighbourhoods.  On t h e s u p p l y  side,  p r o f i t maximizing l a n d l o r d s i n these g e n t r i f y i n g  neighbourhoods respond t o t h e p r i c e - i n d u c e d marginal  increase  b e n e f i t s o f maintenance by i n c r e a s i n g t h e f l o w o f  maintenance c a p i t a l . gentrifying  As a r e s u l t ,  the housing  constructed  t h i s thesis to predict intra-urban g e n t r i f i c a t i o n i n  Canada.  T h e model i s b a s e d on t h e p r e m i s e t h a t ,  literature curve  claims,  so there  gentrification  the rise  i s a l a g between t h e i n i t i a l  correct,  i n housing  S-  demographic i s gentrifying  prices. I f the literature i s  t h e n one c a n p r e d i c t w h i c h  neighbourhoods w i l l  as t h e  follows a l o g i s t i c  change i n an i n n e r - c i t y neighbourhood t h a t and  stock i n  neighbourhoods i s r e h a b i l i t a t e d .  C h a p t e r 4 d e s c r i b e s t h e r e g r e s s i o n model for  i n the  inner-city  have f u t u r e p r i c e i n c r e a s e s by  77  observing  w h i c h ones a r e  c h a n g e as t h e start  young, w e l l - e d u c a t e d ,  childless  s a m p l e f o r t h e model i s 95  comprising Toronto.  the  inner-cities  of Vancouver, Ottawa-Hull,  than the  as  CMA  r e l a t i v e to the  CMA  i s regressed  v a r i a b l e s and  two  change d u r i n g  change d u r i n g  against  the  the  the p e r i o d  from the  literature.  the  the  is positively  The value  to  demographic to  the  1971. intra-urban The  a n a l y s i s are  gentrification  consistent  (defined  increases  f o r c e , and  in  in  the  to  the  not  non-conformist  r e l i g i o u s ) i n the  i s negatively correlated to  Second, M e l c h e r t  city  family r e l a t i v e to the and  Naroff's  i s s u p p o r t e d by the  this  centre.  increases  in  the  CMA.  finding that  gentrifiers  i n n e r - c i t y neighbourhoods t h a t o f f e r a good  Third,  change  f r o m 1971  i n C h a p t e r 4.  c o r r e l a t e d with  ( p r o x i e d by  number o f c h i l d r e n p e r  deal  in  i n n e r - c i t y housing p r i c e s r e l a t i v e  female l a b o u r  Gentrification  prefer  to  and  of p r o f e s s i o n a l / t e c h n i c a l / a d m i n i s t r a t i v e  occupations, individuals  period  r e s u l t s of the  First,  increased  proportion  the  1961  statistical  model as CMA)  dwelling  change i n e i g h t  g e n t r i f i c a t i o n model d e s c r i b e d  with  increase  housing market v a r i a b l e s r e l a t i v e  Chapter 5 presents  conclusions  an  increase.  a c e n s u s t r a c t ' s a v e r a g e r e n t and  CMA  workers  census t r a c t s  G e n t r i f i c a t i o n i s defined  housing p r i c e s greater  1981  CBD  t o move i n . The  in  s t a r t i n g t o have demographic  housing  analysis.  statistical  analysis supports—at  least  in  78  Toronto—the  literature's claim that g e n t r i f i c a t i o n  two-staged process.  The f i r s t  stage i s the s t a r t  is a  of  demographic change i n a c e n t r a l n e i g h b o u r h o o d ; t h e s e c o n d stage i s the a f f e c t of the f i r s t  stage:  rising  housing  prices. Of paramount in  interest to this  C h a p t e r 5 shows t h a t  be p r e d i c t e d — i n  thesis, the analysis  future housing p r i c e increases  Toronto a t l e a s t — b y  observing which  c e n t r e neighbourhoods a r e s t a r t i n g demographic change young, w e l l - e d u c a t e d ,  c h i l d l e s s c o u p l e s and s i n g l e  e m p l o y e e s b e g i n t o move i n .  w i t h t h e b o u n d a r y between p e r i o d  t h e model.  CBD  Toronto  1 and p e r i o d  (start  of price escalation)  o f demographic t r a n s i t i o n and seem t o o c c u r i n p e r i o d  2.  B a s e d on t h e c h r o n o l o g y o f e v e n t s i n T o r o n t o , and  2  Ottawa and V a n c o u v e r l a g s a r e n o t d e t e c t e d  because both events start  as  o f demographic  change and house p r i c e e s c a l a t i o n i n c e n t r a l  in  city  The model w o r k s w e l l f o r  T o r o n t o b e c a u s e t h e l a g between t h e s t a r t  coincides  can  V a n c o u v e r , t h e l a g between  the s t a r t  Ottawa,  o f demographic  c h a n g e i n a g e n t r i f y i n g n e i g h b o u r h o o d and t h e s t a r t housing p r i c e increase  i s between  of  0 to 4 years.  CAVEATS A f u n d a m e n t a l a s s u m p t i o n on w h i c h t h e m o d e l thesis  i s based i s that  r e l a t i v e t o t h e CMA r e l a t i o n s h i p between  rising  i n n e r - c i t y housing  indicates gentrification. rising  in this  The  prices assumed  p r i c e s and g e n t r i f i c a t i o n  may  79  not  always h o l d t r u e .  from the  statistical  qualified The  Furthermore, the analysis in this  because of the  limitations  major l i m i t a t i o n  periods.  Although  there  conclusions  t h e s i s must of the  i s that the data i s a mini  price  information  i s excluded.  d e m o g r a p h i c s and  number o f p e r i o d s e x a m i n e d w h i l e per  of the  dwellings  CMA  centre.  i s not  u s e d as  suburbs are  The  proper  years,  housing post-1970  by  The  i n c r e a s i n g the the  number  i s by  reported  third  attenuate  the  One  of  i n the  l a r g e r than  inner-city  per  to  that  dwellings  in  the  different  square f o o t .  census so p r i c e p e r  Dwelling room i s  model. the  data  i n Canada i n 1975.  r e s p o n s e by  of p r i c e  would expect  the p r i c e per  problem with  were i n s t i t u t e d  i s the use  m e a s u r e when c o m p a r i n g  a s u b s t i t u t e i n the  The  a  prices.  p r i c e s of the  as a whole.  i n the  sized dwellings size  a l l of the  decreasing  of the data  room f o r c o m p a r i n g h o u s i n g  city  five  period.  Another l i m i t a t i o n  those  ten-year  neighbourhood  neighbourhood housing  r e l a t i o n s h i p w o u l d be b e t t e r a n a l y z e d  years  is in  Gentrification,  phenomenon, i s a r e l a t i o n s h i p b e t w e e n  be  data.  census every  much o f t h e d e m o g r a p h i c i n f o r m a t i o n and  drawn  i s that rent controls Rent c o n t r o l s  r e n t s t o demographic  probably  change.  CONCLUSION Although data  t h e model i s h a n d i c a p p e d by  the  three  l i m i t a t i o n s d e s c r i b e d a b o v e , t h e model d o e s work.  80  First,  i t produces the a n t i c i p a t e d  correlations  between  d e m o g r a p h i c v a r i a b l e s and r i s i n g h o u s i n g p r i c e s gentrified  inner-city  and O t t a w a - H u l l .  i n the  neighbourhoods o f Toronto, Vancouver,  S e c o n d — f o r Toronto a t l e a s t — t h e  d e t e c t s t h e l a g between  the s t a r t  and t h e s t a r t  prices.  of r i s i n g  o f demographic  I m p r o v i n g t h e f r e q u e n c y and q u a l i t y  model  transition  of the data  will,  u n d o u b t e d l y , hone t h e m o d e l ' s s e n s i t i v i t y  t o changing  d e m o g r a p h i c s and c h a n g i n g h o u s i n g p r i c e s .  W i t h more  f r e q u e n t d a t a , t h e l a g i n V a n c o u v e r and O t t a w a detected.  As w e l l ,  should  a more a c c u r a t e e s t i m a t e o f t h e  be  lag's  l e n g t h c o u l d be made. Nevertheless,  t h e i n t r a - u r b a n model p r e s e n t e d  t h e s i s does s t a t i s t i c a l l y  show what t h e l i t e r a t u r e  f a r o n l y been a b l e t o imply: S i n c e t h e r e the s t a r t city  has so  i s a l a g between  in a gentrifying  n e i g h b o u r h o o d and t h e c o n s e q u e n t r i s e  prices, will  o f demographic t r a n s i t i o n  i n this  inner-  i n housing  one c a n p r e d i c t w h i c h i n n e r - c i t y n e i g h b o u r h o o d s  gentrify  and h a v e f u t u r e p r i c e  i n c r e a s e s by  observing  w h i c h ones a r e u n d e r g o i n g demographic change as young, e d u c a t e d , CBD t o move i n . statistically  employed s i n g l e s and c h i l d l e s s The l a g g e d r e l a t i o n s h i p i n the Toronto  couples  well  begin  i s demonstrated  model.  81  REFERENCES  A p g a r , W.; K a i n , J . 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" C a n a d i a n a n d U.S. C i t i e s : B a s i c D i f f e r e n c e s , P o s s i b l e E x p l a n a t i o n s , and t h e i r Meaning f o r P u b l i c P o l i c y , " The R e g i o n a l S c i e n c e A s s o c i a t i o n Papers, ( P h i l a d e l p h i a , R e g i o n a l S c i e n c e As.) Hamnett, C. ( 1 9 8 4 ) . " G e n t r i f i c a t i o n a n d R e s i d e n t i a l L o c a t i o n Theory: A Review and Assessment", Geography and t h e U r b a n E n v i r o n m e n t . ( J o h n W i l e y & Sons L t d ) H e n d e r s o n , V. (1977) E c o n o m i c T h e o r y a n d t h e C i t i e s . York: Academic Press) C h a p t e r 6 L a n g , M. ( 1 9 8 2 ) . G e n t r i f i c a t i o n Amid U r b a n (Cambridge: B a l l i n g e r P u b l i s h i n g )  (New  Decline,  L a s k a , Seaman, a n d McSeveney, ( 1 9 8 2 ) . " I n n e r - C i t y Reinvestment: Neighbourhood C h a r a c t e r i s t i c s and S p a t i a l P a t t e r n s O v e r Time", U r b a n S t u d i e s ( E s s e x : Longman) 82  9  L e y , D. ( 1 9 8 3 ) . A S o c i a l G e o g r a p h y o f t h e C i t y . H a r p e r & Row) L e y , D. ( 1 9 8 5 ) . G e n t r i f i c a t i o n (CMHC)  i n Canadian  (New  Inner  York:  Cities,  L e y , D. (1986) . " A l t e r n a t i v e E x p l a n a t i o n s f o r I n n e r - C i t y Gentrification: A Canadian Assessment," A n n a l s o f t h e A s s o c i a t i o n o f American Geographers. Vol.76, No.4 L e y , D. ( 1 9 8 7 ) . " G e n t r i f i c a t i o n : A T e n Y e a r O v e r v i e w " , Magazine. (Winnipeg: P o l i s P u b l i s h i n g ) V o l . 9 , N o . l  City  L o n d o n ; L e e ; L i p t o n ; (1986) " D e t e r m i n a n t s o f G e n r i f i c a t i o n i n t h e U n i t e d S t a t e s " , Urban A f f a i r s Q u a r t e r l y (London: Sage P u b l i c a t i o n s ) L o n d o n , B.; P a l e n , J . e d s ( 1 9 8 4 ) . G e n t r i f i c a t i o n . D i s p l a c e m e n t , and N e i g h b o u r h o o d R e v i t a l i z a t i o n , S t a t e U n i v e r s i t y o f New York) Lowry, I . (1960) " F i l t e r i n g and H o u s i n g C o n c e p t u a l A n a l y s i s , " Land E c o n o m i c s . Wisconsin: U n i v e r s i t y of Wisconsin)  (Albany:  Standards: (Madison,  A  M e l c h e r t ; N a r o f f ; (1987) " C e n t r a l C i t y R e v i t a l i z a t i o n : P r e d i c t i v e M o d e l " , AREUEA J o u r n a l Vol.15, No.l  A  f  M i l l s , (1972) S t u d i e s i n t h e S t r u c t u r e o f t h e U r b a n Chapter 3 Muth, (1969) C i t i e s Chicago Press)  and H o u s i n g ,  Economy  (Chicago: U n i v e r s i t y  O t t ; H i l d e b r a n d ; (1983) S t a t i s t i c a l ( B o s t o n : Duxbury P r e s s )  of  T h i n k i n g f o r Managers,  S m i t h , N. (1982) " G e n t r i f i c a t i o n and Uneven E c o n o m i c G e o g r a p h y . V58 N2  Development,"  S m i t h , N.; W i l l i a m s , P., e d s . ( 1 9 8 6 ) . G e n t r i f i c a t i o n C i t y . ( B o s t o n : A l l e n & Unwin)  of  the  S m i t h , N. (1987) "Of y u p p i e s and h o u s i n g : g e n t r i f i c a t i o n , s o c i a l r e s t r u c t u r i n g , and t h e u r b a n dream", S o c i e t y and S p a c e (London: P i o n L t d . ) S h o r t , J . (1984) An (Boston: Routledge Vancouver  I n t r o d u c t i o n t o Urban & Kegan P a u l )  R e a l E s t a t e Board,  Geography,  (1981) " M o n t h l y  Warner, Sam B a s s (1962) S t r e e t c a r S u b u r b s Harvard U n i v e r s i t y Press)  Statistics"  (Cambridge:  83  APPENDIX A Table 7: C o r r e l a t i o n Matrix, 3 C i t i e s Combined  loi- *» 01 r-. in  e u cc  oowmm  m  2  . . .  — t  —OOOO  u_ *o -r  OOM^-W oO'-N'-n  a) _j 2 Ii. <j  .«- o.o o.o .o *- c*> r*."*f m  CM  O < M O  O U_  O T  O  — O O O O O O  cc  .  a.  .  .  .  —  otvimo^Ncoco  o LL cc  —ooooooo . . .  a. CM o  o^fT-rvnonoico o^wovnw^-  _j  --oooooooo  x ( _ > —  OO wtnw»-0(n^n  Q _l  — O O O O O O O O O  x u  CM o*-C•DMWo>i nini-eoo (x/) on--' ONCMOO' -cy  2 —oooooooooo 1 1. . . . . . . . Z •-c owM^otoinoKflinoin n o (\in-oon •-(vjO'-ty  x  ZE u. z  —ooooooooooo . . . . . . .  wooi'HosvcooW'-now OO-ONOWnNi-ONyn _l CC'-OOOOOOOOOOOO  o z  — CD  .  .  .  .  omsofoim'-NONOino o ftiw—^t(\in'-mon^''~r-  cr o z  —ooooooooooooo . . . .  .  orKOOO' -rinNorowoioo) OOf'-ONM' -^OWONP)'-  C\J  LU C3 •<  - O O O O O O O O O O O O O O . . . . . . .  OMmOinOffl'-CT-fNinQCVJN ui o  --o o o o o o o o o o o o o o o  •<  CM c ccn  ow'jN^ninioainoO' -iocouif oc\ i'womooc\inor-c\imO' «»roc\*  > z  — •cn c r >  —oooooooooooooooo • . . . . . .  om--no)' -o)t*>^ci)(\J<DU)«)'#N(\i<D>oO'-^^-oo-ciD'-ni'-inO'—ooooooooooooooooo . . . , .  z  *- l U  Ovjnwoooi^o'^iO'-oiO'-innfvj m  13  O CM * - O O — O O O r- w r~  13 _J  O —  O O  - - O O O O O O O O O O O O O O O O O O  <£  .  .  .  .  c -wcnv<j)(\it-«»-iD' -0(\i<o UJu o«<ofn(\iin' oo-owo<vNoO'-«tnoN -N''(no _ t •< • . >  t  =3  O O O O O O O O O O O O O O O O O O O  >  —  » — z  o  — f^'"'f^*u>»-'o^tcMm — racum — -  _  -  <-a o o o o o o o o o o o o o o o o o o o U crl Oi oi'n-O' corxj'— iDOOOOrocuroo* forocooi'-Mcivio0*"~' cKDn O —-inrnO* —O I— JOO— -  -  Z ' - O O O O O O O O O O O O O O O O O O O O O UJ * . . . .  cr CM «- LU iu </i co cjjocotn — OJCJOCCCCUOOO t-t-DDaa-NjjjiOQOOmajooNN zz_i_i>>a)uia:a:22jJiLU i _» ce cc v- • tutu<<zzoc)OOu.u.iiQ:a:22a.a.(/iui ca:>>3D<<zzz2uuio.iLinm.o:> CM •- *- CV  --N - W  T-CM--CU*-CM>->  APPENDIX A Table 8: C o r r e l a t i o n C o e f f i c i e n t s f o r Rent and Value. 3 C i t i e s Combined ( t - s t a t i s t i c s i n parentheses)  ALL 3 CITIES:  n = 95 i n n e r - c i t y census t r a c t s  Indep. Var. i n Per. 2  Independent Variables i n Period 1 Cor. Hiqher With RENT2 RENT2 RENT1 UNVRS1 AGE1 N0RLG1 NFMHS1 CHLD1 PRF0C1 FHLBR1 FPR0C1 RSTZDV RENT1  Cor. Hiqher With RENT1 RENT2 RENT1 .18 .05 .12 .03 -.08 .21 -.03 .06  -.16 (-1.6) -.05 (-0.5)  n/a n/a  .42 ( 1.8) .34 ( 0.5) ( 1.2) .56 ( 0.3) .15 (-0.1) -.40 ( 2.0)' .52 (-0.3) .23 ( 0.5) .34 n/a n/a  ( 4.4)" ( 3.5)"  UNVRS2 AGE2  ( 6.5)" ( 1.4) (-4.2)" ( 5.8)"  N0RLG2 NFHHS2 CHLD2 PRF0C2 FHLBR2 FPR0C2  ( 2.3)' ( 3.4)" n/a n/a  Independent Variables i n Period 1 Cor. Higher With VALUE2 VALUE2 VALUE1 UNVRS1 NFHHS1 AGE1 NORLG1 CHLD1 PRFOC1 FMLBR1 FPR0C1 VSTZDV VALUE1  RENT2  ( 2.2)' .03 ( 0.3) ( 2.0)' .10 ( 1.0) ( -1.8) -.16 (-1.6) ( 3.2)" .16 ( 1.5) ( 2.0)' .09 ( 0.9) .21 ( 2.0)' .11 ( 1.0) -.06 ( -0.6) n/a -.02 (-0.2) n/a  .24 ( 2-4)' .09 ( 0.9)  .22 .21 -.19 .31 .21  = S i g n i f i c a n t at the .05 l e v e l = S i g n i f i c a n t at the .01 l e v e l  .33 ( 3.4) .14 ( 1.3) .18 ( 1.7)  VALUE2 UNVRS2 NFMHS2 AGE2 NORLG2 CHLD2 PRFOC2 FMLBR2 FPROC2  n/a n/a  ( 3.1V ( 1.8) ( 0.5) (-0.2) (-4.1)'  Indep. Var. i n Per. 2  Cor. Higher With VALUE1 VALUE2 VALUE1 .16 ( 1-5) -.09 (-0.9)  .31 .18 .06 -.03 -.39  n/a n/a  -.03 -.04 .05 -.22 -.22 -.04 -.20 -.10  (-0-3) (-0.4) ( 0.5) (-2.2) (-2.1) (-0.4) (-1.6) (-1.0)  APPENDIX A Table 9: C o r r e l a t i o n Matrix. Vancouver  O D IO O O1 f"^ — 'V C D Il —OOOO O O" O —UO OC O lv  Q l C ^Q L— L C X CD ^ u _ c vj CJ O u _ cr Q_ *O UCL CM  1  lO  —o o oo o  o "i (CDonvO)»o Nin(D f^  —oooooo . . .  Ocn — omunmcD —o o o oo o o OrifOiifiWOOn  Q ^  —oooooooo O o o o w o j i n T f m u j o oon--^-nooinv  — Q — I X CM X 2  —ooooooooo •• . . . o - c o t n i n u i N ' j i n — in  CO o cu — m o O  —- T n n  —oooooooooo  u_ . . . .... 2 •C ~O OOOCOi o O*-t o r * . m— • o"iwnomo - if^OM x  2  —ooooooooooo  L L O— . ."Of^OCDMlOlflcyoirl .. . . . CM O O O OJCMO—(MCn-srO —m _ J CC —•OO OOO O •OO .O .O.OO .O. 2  —  OOf^cN-CvirnflonoiDn  _»  CC o z  —ooooooooooooo . . . . . .  C M a i o <: L U  o  OJ/l < cc  > z  .  .  .  .  . . .  — oooooooooooooo OOUl-DOWWl/lrlifi'-MOnw  *-o o o o o o o o o o o o o o o •  ocoowN.nvr~o^oi^ifi(0(ono o — twryn«-rnr- o 10 ^ m o to --oooooooooooooooo  — tC /C i  0<OOOinK(\j(0--r-.r)cOiflOa)--ri-<f om^OrKMi-n-ONTT'-ioinri  L—U  owoir-'q-air-ncocniaoicor-. w v N n »i o^O 0 vt\jnri(D-inuiniooO(\J  ID  > z 3 1 3  _J < >  CM  3 _ -«j  —ooooooooooooooooo . . . r_  ,_  ,  —oooooooooooooooooo . . . . . . . .  OCDO>Or*1(M'-'».<fl'lTj'TfiOfslsrnc\Jr-0) ,  —ooooooooooooooooooo . . . . . n . , ,  oin-Ou>iD^owin«-^ o)(DOiM O><oi—cu — 00<MOJOOOJ*Ow OLOOO"*OWO O ( CVJ — t> z —oo a ooo ooo o oo o o o o oo o o L U CC — rty OCK1 —c\j W cu — co>> C M UOfU 7 /W O -D^att'-NjJlIQQOOmCOOONN MaL > t)l^(/el\)( i^1 Nt»Nrd»-O WC^ 00>c0U <U DC iPCUU DO h -'—I-— zzj_j>>iuuj(rmi_i-iii.u j_icrair-t— LUUJ<<ZZ(JC3OOLLU-XXCCCCa20.CLC/lCn >•  ( M •— •— CM  — C\J  —  ao:>>D3«<<zzz2uuo.aij.iJ.iLu.ir> woiflN'-iow«-oo -'-wwfononioinpi>,  f1 l  2*-000000000000000000000  APPENDIX A Table 10: C o r r e l a t i o n C o e f f i c i e n t s f o r Rent and Value. Vancouver ( t - s t a t i s t i c s i n parentheses)  VANCOUVER: n = 20 i n n e r - c i t y census t r a c t s  Indep. Var. i n Per. 2  Independent Variables i n Period 1 Cor. Higher With RENT2 RENT2 RENT1 N0RLG1  .02 -.17 .27 -.02  NFMHS1 CHLD1 FMLBR1 UNVRS1 AGE1 PRF0C1 FPROC1 RSTZDV RENT1  Cor. Higher With RENT1 RENT1 RENT2 ( 0.7) -.10 (-0.4) (-0.7) .05 ( 0.2) ( 1.2) -.52 (-2.6)' (-0.1) .02 ( 0.1)  .57 ( 3.1)" -.20 (-0.9) .12 .31 .09 -.38 -.51  ( 0.5) ( 1.1) ( 0.4) (-1.7) (-2.5)'  ( 1.8) .32 ( 1.4) (-1.2) -.17 (-0.7) (-1.7) -.23 (-1.0) ( 3.9)" .57 ( 2.9)" (-4.0)" n/a ( 1.2) n/a  = S i g n i f i c a n t at the .05 level = S i g n i f i c a n t at the .01 level  ( 0.1) ( 0.1) (-0.1) (-0.6)  n/a n/a  .38 ( 1.7) .30 ( 1.3) .07 ( 0.3) .40 ( 1.8) .58 ( 3.0)"  Indep. Var. i n Per. 2  Cor. Hiqher With VALUE1 VALUE1 VALUE2 .03 .02 -.03 -.14  -.17 (-0.8) -.39 (-1.8) -.22 (-0.9)  n/a n/a  n/a n/a  Cor. Hiqher With VALUE2 VALUE2 VALUE1  .39 -.27 -.37 .67 -.69 .26  N0RLG2 NFHHS2 CHLD2 FMLBR2 UNVRS2 AGE2 PRF0C2 FPR0C2  .06 ( 0.3) .06 ( 0.3) .06 ( 0.2) n/a n/a  Independent Variables i n Period 1  FPR0C1 NORLG1 CHLD1 PRF0C1 UNVRS1 AGE1 NFMHS1 FMLBR1 VSTZDV VALUE1  RENT2  -.64 -.18 -.39 -.19  (-3.5)" (-0.8) (-1.8) (-0.8)  n/a n/a  VALUE2 FPR0C2 N0RLG2 CHLD2 PRF0C2 UNVRS2 AGE2 NFHHS2 FMLBR2  .12 ( 0.5) -.11 (-0.5) -.14 (-0.6) .36 .20 .24 .56 .47  ( ( ( ( (  1.7) 0.8) 1.0) 2.9)' 2.3)  APPENDIX A Table 11: C o r r e l a t i o n Matrix. Ottawa-Hull  cc *- o o o  — o oo oo -oo oo oo *-ooooooo • - 0 0 0 0 0 0 0 0  -ooooooooo -oooooooooo —ooooooooooo ft — o o o o o o o o o o o o  • ro — o -ooooooooooooo •oooooooooooooo •ooooooooooooooo -oooooooooooooooo -ooooooooooooooooo — oooooooooooooooooo — ooooooooooooooooooo -oooooooooooooooooooo -ooooooooooooooooooooo OJ — — OJ »— CM — CM — CM— CM — CM>-;> CM — LU LU C/l CO OOWWNUUIKEUOQO ht-DDiriE-WJJlIQaOOlDIDOONN z z - i J > > w i u o : Q : 2 2 J J i L U . j j a : a : r - i u j u j < < z z o c 3 0 0 i L U . i i a : i r 2 3 Q . a w u ) CCC>>3D<<ZZZZUUCLQ.U.U.U.U.a:>  APPENDIX A Table 12: C o r r e l a t i o n C o e f f i c i e n t s f o r Rent and Value. Ottawa-Hull ( t - s t a t i s t i c s i n parentheses)  OTTAWA-HULL: n = 20 i n n e r - c i t y census t r a c t s  Independent Variables i n Period 1 Cor. Higher With RENT2 RENT2 RENT1 UNVRS1 N0RLG1 NFMHS1 CHLD1 PRFOC1 FMLBR1 FPROC1 AGE1 RSTZDV RENT1  Cor. Higher With RENT1 RENT2 RENT1 -.32 -.15 -.01 .11 -.48 -.14 -.43  -.58 (-3.0)" -.31 (-1.4) -.24 (-1.0)  Indep. Var. i n Per. 2  .23 ( 1.0) n/a n/a  (-1.4) (-0.7) (-0.0) ( 0.5) (-2-3)' (-.06) (-2.0)  .81 ( 5.9)" .85 ( 6.7)" .47 ( 2.3)' -.51 ( •2.5)' .71 ( 4.2)" .64 ( 3.5)" .49 ( 2.4)'  n/a n/a  UNVRS1 N0RLG1 CHLD1 PRF0C1 FMLBR1 FPR0C1 AGE1 NFMHS1 VSTZDV VALUE1  ( 1.8) ( •2.3)' ( 1.7) ( 0.0)  .34 ( 1.5) .38 ( 1.8) n/a n/a  = S i g n i f i c a n t at the .05 level = S i g n i f i c a n t at the .01 level  (-0.1) .53 (-0.5) .38 ( 0.7) -.29 ( 1.5) .62 .49 (-1.9) ( 1.6) .66  ( 2.4)' ( 1.3) ( -0.2) ( •2.7)' ( 2.9)"  ( 1.7) ( 2.8)' .22 ( 1.0)  ( 2.7)' ( 1.7) (-1.3) ( 3.3)" ( 2.3)' ( 3.7)"  VALUE2 UNVRS2 N0RLG2 CHLD2 PRF0C2 FHLBR2 FPROC2 AGE2 NFHHS2  n/a n/a  .49 .28 -.05 -.54 .56 .36 .56  Indep. Var. i n Per. 2  Cor. Higher With VALUE1 VALUE2 VALUE1 -.02 -.12 .16 .34 -.41 .35  .39 -.48 .36 .01  UNVRS2 N0RLG2 NFHHS2 CHLD2 PRFOC2 FHLBR2 FPR0C2 AGE2  n/a n/a  Independent Variables i n Period 1 Cor. Higher With VALUE2 VALUE2 VALUE1  RENT2  n/a n/a  .05 -.19 -.05 .06 -.51 .06 .06 -.15  ( 0.2) (-0.8) (-0.2) ( 0.2) (-2.5) ( 0.3) ( 0.3) (-0.7)  APPENDIX A T a b l e 13: Correlation Matrix. Toronto *— o co n cn u o o *- •o ••• • cc-ooo  Q_ •  ca -J a  1  •  —. OO.OO.  u_  C C CD  o wiPiinn o wrnwon  —  — ) 3 u _ cj O u _ c c o_  —o oo oo . . .  o CM -*r — r- *r n —. o o o.o o . o  o  ootyws'-oj'-  CL  — ooooooo . . . oin on o o io in  o u_ cc  Q —J  O^-V- V T C M C M —  — •  o orin o^O^ioif)  o -J X  — ooooooooo  3_ u  — oooooooooo  OJ  — oooooooo  x  CU 0(Df' "'~0)i-***(0 txo O' -W'iO -m^wocynn T  CJ  N  -  — —O fu<— o^*-c— O '*C *-M iocn CO OCMO*— OO C M —O— 2* — o o o o o o o o o o o 2 WOOi ont-c»' -rsmoi (Own OO* m *r » —m » — N»-wifl« -J C C — O O O O O O O OOOOO o . . . ,  2  -  2  —  o<nN^"Cnmnow(oO'-<\i  _J C C o 2 C M LU a <f  — ooaooooooooooo oojincu*— (\JIO-—mcyoci'-cvi^'ci —ooooooooooooooo  LU o  CM co  ocnr«.inN'f-o)f^v-'-NO)ina3ui O'-^TQifl'-fi'-voajWfn'-'Trnfu  cc >  — co 2  cc > z  *» O O O O O • OOOOOOOo  •— LU Z3  —oooooooooooooooo  • ' ' Oinrnoj^w-rxntfjOooi' -fT-co' o — — mm — --ootDto T\ic\i(o-- >- CM  —ooooooooooooooooo •• • •  o — CM — — QCV — CMO - — rnroocM-OO  O U D C O - c ^ i n - C M C M O T — C O ' - - O C O C M — LOCO  _j  — ooooaooooooooooooo  < OJ LU => _i < >  . . . . . OOaD(OCO'-KPl(Or-.1f^O)CDtCOO)r-.inO  o — — ocooTmoo<''iCMro — rooj*- — mo — o• o o• o o o o o o o o o o o o o o o o OOOcO'-( i--innrn'jio^O^O)'-fJV'j ,  — t— 2 LU  cc  O rn n ro — in o ^ oj O — n n t o » - » - N f n T - t w  —oooooooooooooooooooo .  .  .  .  O0)0>C0^MDOC0^lvm»J.-C0NnWONfU'-  wo»-'-np)fu^wnooow^'rWOOnoow  z — ooooooooooooooooooooo  M' L— OJC/l — C M C MOU— MQ— M — CM>> C MC — U U— JC O OO W— W'-W IKUC U QC i - K D D i r t i i ' - w j j i T Q Q o o m m o o N N 22_J_J>>LULUCCCC33-l_IU.U._J_ICCCCI-ti r i r > > D 3 < < z z z z u u n o_ u_ u. u. LL <x >  ujuj<<zzauoou.iLXic:Q:Z2Q.a.(A(/)  APPENDIX A Table 14: C o r r e l a t i o n C o e f f i c i e n t s f o r Rent and Value. Toronto ( t - s t a t i s t i c s i n parentheses)  TORONTO: n = 55 i n n e r - c i t y census t r a c t s  Indep. Var. i n Per. 2  Independent Variables i n Period 1 Cor. Higher With RENT2 RENT2  RENT1  .33 ( 2.6)' .38 ( 3.0)" .16 ( 1.2) .53 ( 4.6)"  UNVRS1 AGE1 N0RLG1 CHLD1 PRF0C1 FMLBR1 FPR0C1 NFMHS1 RSTZDV RENT1  Cor. Higher With RENT1 RENT1 RENT2  N0RLG2 CHLD2 PRFOC2 FHLBR2  .30 ( 2.3)' .31 ( 2.3)'  FPR0C2 NFMHS2  .07 ( 0.5) -.03 (-0.2) -.02 (-0.2) n/a .19 ( 1.4) n/a  n/a n/a  .18 .38 .47 -.34 .39 .34 -.00 -.10  ( 1.3) .16 ( 1.2) ( 3.0)" .10 ( 0.8) ( 3.9)" .05 ( 0.4) (-2.6)' -.09 (-0.6) ( 3.1)" .18 ( 1.4) ( 2.6)' -.30 (-2.3)' (-0.0) n/a (-0.8) n/a  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  n/a n/a  ( 2.1)' ( 1.5) (-0.3) (-3.2)" ( 2.0)' (-0.1)  .07 ( 0.5) .03 ( 0.2)  Indep. Var. i n Per. 2  Cor. Higher With VALUE1 VALUE2 VALUE1 -.06 (-0.4) .19 ( 1.4)  .27 .20 -.04 -.41 .27 -.02  n/a n/a  Independent Variables i n Period 1  NFHHS1 FPR0C1 UNVRS1 AGE1 N0RLG1 CHLD1 PRF0C1 FMLBR1 VSTZDV VALUE1  UNVRS2 AGE2  ( 3.7)" (-2.6)' ( 5.1)" ( 1.1)  .38 ( 3.0)" .45 -.24 (-1.8) -.34 .48 ( 4.0)" .57 -.03 (-0.2) .14  Cor. Higher With VALUE2 VALUE2 VALUE1  RENT2  .12 ( 0.9) .22 ( 1.7)  n/a n/a  VALUE2 NFMHS2 FPR0C2 UNVRS2 AGE2 NORLG2 CHLD2 PRFOC2 FMLBR2  -.07 (-0.5) -.17 (-1.3) -.08 (-0.6) .01 -.33 -.27 -.18 -.28  ( 0.1) (-2.6)' (-2.0)' (-1.3) (-2.1)'  APPENDIX B Table 15: M u l t i p l e Regression of Rent. 3 C i t i e s Combined ( t - s t a t i s t i c s i n parentheses)  ALL 3 CITIES:  n = 95 i n n e r - c i t y census t r a c t s  Explanatory V a r i a b l e s i n Period 2  Explanatory Variables i n Period 1 RENT2 UNVRS1  0.09 ( 0.9)  AGE1  - 0.14 (-0.4) - 0.03 (-0.4) 0.15 ( 0.7) -10.01  N0RLG1 NFMHS1  RENT1  PRF0C1 FMLBR1 FPR0C1 RSTZDV RENT1 VANDUM OTTDUM CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  UNVRS2  ( 1.0) 0.09  AGE2  ( 0.9) 0.04 ( 2.0)' 0.01  ( 1-3) (-1-1) 45.81 - 0.19 ( 2.1)' ( 0.0) 4.70 - 6.66 ( 0.4) (-1.7) .11  RENT2  Best RENT1  0.03  ( 0.1) -17.78 (-0.2) (-1.3) 1.42 0.18 ( 3.2)" ( 1.3) - 0.77 0.16 (-1.3) ( 0.8) - 0.69 - 0.04 (-2.5)' (-0.4) -16.55 n/a (-1.8) n/a - 0.46 (-1.3) 22.81 - 6.28  CHLD1  Best RENT2  .35  0.06 ( 3.0)"  NORLG2 NFHHS2  -21.22 (-2.0)' 0.21 1.38 ( 3.0)" ( 4.2)"  CHLD2 PRF0C2 FMLBR2  - 0.60 (-2.6)" -17.80 (-2.4)' - 0.48 (-1.5) 18.31  FPROC2 n/a  RSTZDV  n/a  RENT1 VANDUM2  ( 1.1) 40.40 ( 2.3)' 14.05 - 7.59 ( 1.5) (-3.4)" .14 3.59 < .01 0.76 0.34  .38 20.23 < .01  Best RENT2  - 0.10 (-0.7) - 0.29 (-0.9) - 0.06 (-0.7) - 0.21 (-1.6) -224.1 (-4.1)" 0.54  - 0.10 (-1.5) - 0.18 (-1.4) -195.8  (-4.3)" 0.42 ( 3.3)" ( 2.9)" 0.90 - 0.85 (-1.3) (-1.1) 0.16 - 0.20 (-1.6) (-1-8) 0.15 ( 0.0) 0.48 - 0.52 (-1.8) (-1.8) 3.39  OTTDUM CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  ( 0.2) 23.63 ( 1.4) 36.88 ( 3.1)"  21.78 ( 1-3) 37.70 ( 3.8)"  .20 2.99 < .01  .23 (.30*) 4.47 (5.89*) < .01 (<.01*)  1.15 2.11  1.32 (0.79*) 2.70 (0.22*)  ' = S i g n i f i c a n t at the .05 l e v e l " = S i g n i f i c a n t at the .01 l e v e l * n = 94, observation #82 deleted  92  APPENDIX B Table 16: M u l t i p l e Regression of Value. 5 C i t i e s Combined ( t - s t a t i s t i c s i n parentheses)  ALL 3 CITIES:  n = 95 i n n e r - c i t y census t r a c t s  Explanatory Variables i n Period 2  Explanatory Variables i n Period 1 VALUE2 UNVRS1  - 0.34 (-1.3) 0.41 ( 0.5) - 0.02 (-0.1) - 1.33  AGE1 N0RLG1 NFMHS1 CHLD1 PRFOC1 FMLBR1 FPROC1 VST2DV VALUE 1 VANDUM OTTDUM CONSTANT  Best VALUE2 Best VALUE1  0.06  - 0.39  ( 1.7) - 0.04 (-0.4) - 0.02 (-0.8) 0.03  (-2.4)' ( 0.4) -187.78 -14.86 (-1.6) (-1.1) 1.44 0.06 ( 1.3) ( 0.4) 3.21 - 0.06 ( 2.0)' (-0.3) 0.37 - 0.03 ( 0.5) (-0.3) -42.67 n/a (-1.9) - 0.21 n/a (-0.2) -37.50 4.53 (-0.8) ( 0.8) 2.27 1.67 ( 0.0) 81.76 ( 2.7)"  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  VALUE1  .14  ( 0.2) - 3.66  (-1.7)  0.05  VALUE2 UNVRS2  ( 2.2)' AGE2 NORLG2  - 1.23 (-2.7)" -189.69 (-2.0)' 2.02  NFMHS2 -12.67 (-1.4)  CHLD2 PRF0C2  ( 3.2)" 2.83 ( 2.0)'  FMLBR2 FPR0C2  -45.89  n/a  VSTZDV  n/a  VALUE1  (-2.2)'  VANDUM OTTDUM 75.22  (-0.9) .00  ( 3.5)" .18 4.43 < .01 1.80 7.22  - 2.05  CONSTANT  (-0.9) .06 3.75 < .05  - 0.01 (-0.0) 0.88 ( 1-0) - 0.66 (-3.3)" - 0.38 (-1.1) -343.1 (-2.6)" 0.54 ( 1.1) - 5.76 (-3.2)" - 0.48 (-1-7) -45.72 (-2.4)' - 0.26 (-0.3) -84.97 (-2.0)' 29.70 ( 0.7) 122.4 ( 4.1)"  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  Best VALUE2  .18  1.01 ( 1.2) 0.62 (-3.6)"  -331.1 (-2.9)" 0.45 ( 1.3) - 6.05 (-3.5)" - 0.44 (-1.7) -42.54 (-2.4)'  -89.56 (-2.2)'  124.5 ( 4.7)" .21 (.15*) 4.09 (3.00*) < .01 (<.01*) 1.24 (0.34*) 4.20 (0.60*)  ' = S i g n i f i c a n t at the .05 l e v e l " = S i g n i f i c a n t at the .01 level * n = 94, oberservation #60 deleted  93  APPENDIX B Table 17: M u l t i p l e Regression of Rent. Vancouver ( t - s t a t i s t i c s i n parentheses)  VANCOUVER: n = 20 i n n e r - c i t y census t r a c t s  Explanatory Variables i n Period 2  Explanatory Variables i n Period 1 RENT2 UNVRS1  0.57 ( 1.4) 0.06 ( 0.1) - 0.35 (-0.5) 0.81 ( 0.9) 88.64 ( 0.6) 1.81 ( 1.1) - 0.57 (-0.3) - 0.69 (-0.7) 0.10 ( 0.0) - 1.05  AGE1 N0RLG1 NFMHS1 CHLD1 PRFOC1 FMLBR1 FPR0C1 RSTZDV RENT1 CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  (-1.1) - 2.45 (-0.1) .30  RENT1 - 0.05  Best RENT2 0.55  (-0.4) 0.06 ( 0.3)  AGE2 NORLG2 - 0.40 (-1.6) -126.7  (-1.0) -113.50 (-2.2)' - 0.45 (-0.8) 0.22  (-3.4)" 1.03 - 0.63 ( 2.3)' (-1.9)  .04  NFMHS2 CHLD2 PRFOC2 FMLBR2  ( 0.3) 0.39 ( 1.2) n/a  - 5.41 (-0.5)  UNVRS2  ( 3.3)"  - 0.10 (-0.4) • 0.35  n/a  RENT2  Best RENT1  1.28 (-2.8)' 7.07 (-0.5) .56 9.22 < .01 - 0.17 - 1.56  0.45 (1.8) n/a  RSTZDV  n/a  RENT1  9.98 (-2.1)' .28 2.85 < .10  FPROC2  CONSTANT  - 0.17 (-0.4) - 0.81 (-1.2) - 0.52 (-1.3) - 1.46 (-1.4) -190.1 (-1.5) 0.35 ( 1-1) 0.13 ( 0.1) 0.15 ( 0.3) -14.64 (-0.5) - 1.27 (-1.6) 36.58 ( 1.6)  Adjusted R2 .51 F-score 3.01 p-value < .10 Residuals: Skewness -0.08 Kurtosis -2.31  Best RENT2  - 0.75 (-1.5) - 0.53 (-1.9) - 1.20 (-2.1)' -221.0 (-3.1)" 0.43 ( 3.2)"  - 1.70 (-4.0)" 32.98 ( 2.4)' .64 6.67 < .01 -0.14 -1.72  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  94  APPENDIX B Table 18: M u l t i p l e Regression of Value. Vancouver ( t - s t a t i s t i c s i n parentheses)  VANCOUVER: n = 20 i n n e r - c i t y census t r a c t s  Explanatory Variables i n Period 1 VALUE2 UNVRS1  - 0.02  NORLG1  (-0.0) - 0.18 (-0.3) 0.02  NFMHS1  ( 0.2) 1.19  AGE1  VALUE1  PRFOC1 FMLBR1 FPROC1 VSTZDV VALUE1 CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  ( 0.1) 5.95 ( 0.1) .71  ( 0.3) 0.00 ( 0.0) - 0.06 (-0.4) 0.02  UNVRS2  - 1.58  AGE2  (-2.5)' - 0.15 (-0.2)  N0RLG2 1.57  NFMHS2  ( 2.5)' -47.63 (-2.2)' 3.38 0.50 ( 3.6)" ( 2.4)' 7.10 1.08 ( 4.8)" ( 3.7)" - 1.13 - 0.52 (-1.4) (-4.1)" -74.98 n/a (-3.9)" n/a  3.60  7.07  ( 0.5) .63  VALUE2  Best VALUE2 Best VALUE1  0.02  ( 1-0) ( 0.1) -64.24 -52.92 (-0.3) (-1.5) 2.98 0.49 ( 1.4) ( 1.3) 6.93 0.96 ( 2.5)' ( 2.0) - 0.83 - 0.52 (-0.6) (-2.3)' -77.85 n/a (-2.3)' 0.09 n/a  CHLD1  Explanatory V a r i a b l e s i n Period 2  ( 0.5) .80 16.63 < .01 0.12 - 2.08  3.86  CHLD2 PRFOC2 FMLBR2 FPROC2 VSTZDV VALUE1 CONSTANT  ( 1.2) .72 13.22 < .01  1.62 (-3.4)"  - 0.13 (-0.2) 0.96 ( 0.5) -553.3 (-3.2)" 0.81 ( 1.5) - 1.09 (-0.5) - 0.07 (-0.1) -115.1 (-3.6)' 2.82 ( 1.9) 77.77 ( 2.4)'  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  Best VALUE2  .78  -534.7 (-4.5)" 0.59 ( 2.0)  -119.6 (-8.2)" 3.70 ( 4.5)" 86.11 ( 4.2)" .84 21.31 < .01 -0.30 -1.65  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  95  APPENDIX B Table 19: M u l t i p l e Regression of Rent. Ottawa-Hull ( t - s t a t i s t i c s i n parentheses)  OTTAWA-HULL: n = 20 i n n e r - c i t y census t r a c t s  Explanatory V a r i a b l e s i n Period 2  Explanatory Variables i n Period 1 RENT2 UNVRS1 AGE1 NORLG1 NFMHS1 CHLD1 PRFOC1 FMLBR1 FPROC1 RSTZDV RENT1 CONSTANT  - 0.25  0.07  (-0.9) - 2.18 (-1.8) 0.49 ( 2.3)'  ( 0.8) 0.08 ( 0.2) 0.05 ( 0.8) 0.07  - 0.68 (-1.3) -98.09 (-0.9) - 4.87 (-2.4)' - 1.26 (-0.6) 2.00 ( 2.2)' 28.05 ( 1.3) - 0.25 (-0.2) -33.48 (-0.8)  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  RENT1  .31  ( 0.4) 50.78 ( 1.7) 0.42 ( 0.7) 0.47 ( 0.8) 0.17 (-0.6) n/a  Best RENT2  UNVRS2 2.03 (-2.0) 0.38 ( 2-5)' 0.76  N0RLG2  - 0.22 (-0.5) - 0.24 (-0.3) 0.17  NFMHS2  ( 1-1) - 0.23  AGE2 0.08 ( 2.8)'  (-1.9)  4.62 (-2.4)'  1.69 ( 2.1)' 27.93 ( 1-5)  n/a 5.58"  2.50 (-0.1)  ( 0.4) .65  RENT2  Best RENT1  .39 3.00 < .05 0.01 - 2.15  43.16 ( 1.7) 0.21 ( 1.4) 0.55 ( 1.4)  CHLD2 PRFOC2 FMLBR2 FPR0C2  n/a  RSTZDV  n/a  RENT1 CONSTANT  2.19 ( .72 13.44 < .01  (-1.1) -257.5 (-1.9) 0.05 ( 0.0) 3.10 ( 1.3) 0.04 ( 0.6) 15.98 ( 0-8) - 0.48 (-1-0) 57.30 ( 2.0)  0.3) Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  .19  Best RENT2  - 0.19 (-1.3) -202.8 (-2.1)'  1.87 ( 1.2) 0.35 ( 1.5)  - 0.42 (-1.0) 58.46 ( 2.7)' .41 3.66 < .05 0.10 -1.73  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  96  APPENDIX B Table 20: M u l t i p l e Regression of Value. Ottawa-Hull ( t - s t a t i s t i c s i n parentheses).  OTTAWA-HULL: n = 20 i n n e r - c i t y census t r a c t s  Explanatory Variables i n Period 1 VALUE2 UNVRS1 AGE1 NORLG1 NFMHS1 CHLD1 PRFOC1 FMLBR1 FPR0C1 VSTZDV VALUE1 CONSTANT  Adjusted R2 F-score p-value  VALUE1  Explanatory Variables i n Period 2 VALUE2  Best VALUE2 Best VALUE1  - 0.49  0.02  UNVRS2  (-0.8) - 1.26 (-0.5) - 0.36 (-0.9) - 1.34 (-1.2) -17.00 (-0.1) 6.57  ( 0.3) 0.01  AGE2  ( 1.5) 1.01 ( 0.2) - 0.49 (-0.3) -34.45 (-0.8) - 2.32 (-0.8) 216.96 ( 2.3)' .30  ( 0.0) - 0.05 (-1.3) 0.02  0.33 (-2.2)' 0.91 (-1.7)  ( 0.2) 21.87  11.33 ( 1.2) .37  3.91 ( 3.5)"  N0RLG2 NFMHS2  19.56  ( 1.1) 0.47 ( 1.2) 0.73 ( 1.8) - 0.06 (-0.4) n/a n/a  0.04 (-2.0)  ( 1.2) 0.38 ( 3.9)" 0.74 ( 3.1)"  CHLD2  0.14 ( 0.1) - 0.23 (-0.2) - 0.65 (-2.0) 0.24 ( 0.5) -123.7  PRFOC2 FMLBR2 FPROC2  - 2.66 (-1.3) 160.26 ( 5.2) .50 5.85 < .01  Residuals: Skewness Kurtosis  0.87 0.03  n/a  VSTZDV  n/a  VALUE1  9.68  CONSTANT  ( 2.4)' .53 6.35 < .01  Best VALUE2  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  (-0.5) 2.06 ( 1.1) -17.43 (-3.4)" - 1.28 (-1.0) -20.42 (-0.6) - 4.64 (-1-9) 30.31 ( 0.5) .29  0.58 (-2.8)'  -189.1 (-1.0) 1.91 ( 1.8) -14.43 (-4.4)" - 1.16 (-1.3)  - 3.83 (-2.0) 54.21 ( 1.5) .46 3.74 < .05 0.07 -1.78  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  97  APPENDIX B Table 21: M u l t i p l e Regression of Rent. Toronto ( t - s t a t i s t i c s i n parentheses)  TORONTO: n = 55 i n n e r - c i t y census t r a c t s  Explanatory V a r i a b l e s i n Period 2  Explanatory Variables i n Period 1 RENT2 UNVRS1 AGE1  0.03 ( 0.3)  N0RLG1  - 0.65 (-1.3) 0.16  NFMHS1  ( 1.5) 0.04  CHLD1 PRF0C1 FMLBR1 FPR0C1 RSTZDV RENT1 CONSTANT  Adjusted R2 F-score p-value  ( 0.1) -88.12 (-1.4) 0.87 ( 1-7) - 0.90 (-1.2) - 0.13 (-0.4) -14.55 (-1.2) - 0.10 (-0.2) 6.25 ( 0.4) .20  RENT1  Best RENT2  RENT2  Best RENT1  0.05  0.05  UNVRS2  ( 1-3) 0.33 - 0.70 ( 2.0)' (-1.6) 0.00 0.18 ( 1-7) ( 0.1)  ( 1.4) 0.32 ( 2.5)'  AGE2  - 0.03 (-0.1) - 0.02  N0RLG2  (-0.0) - 0.16  NFMHS2  (-1.3) - 0.02  0.02 ( 0.2) 0.67 ( 0.0) 0.28 ( 1.6) 0.04 ( 0.2) 0.12 (-0.9) n/a  -99.56 (-1.9) 0.77 ( 2.5)' - 0.90 (-1.3)  -16.02 (-1.6)  n/a 9.84 (-2.3)' .33  8.75 ( 0.8) .27 4.28 < .01  Residuals: Skewness Kurtosis  0.78 0.50  CHLD2 0.28 ( 2.0)'  PRFOC2 FMLBR2 FPR0C2  - 0.1 (-1.0) n/a  RSTZDV  n/a  RENT1  -10.15 (-3.1)" .39 9.48 < .01  CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  (-0.1) -154.6 (-2.0)' 0.56 ( 1-8) - 1.57 (-1.5) - 0.23 (-1-6) 0.39 ( 0.0) - 0.09 (-0.2) 32.75 ( 2.3)' .14  Best RENT2  0.16 (-1.7)  -144.1 (-2.5)' 0.52 ( 2.6)' - 1.53 (-1.9) - 0.22 (-1.8)  32.38 ( 2.5)' .23 (.35*) 4.25 (6.63*) < .01 (<.01*) 1.83 (1.20*) 4.69 (2.05*)  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level * n = 54, observation #82 deleted  98  APPENDIX B Table 22: M u l t i p l e Regression of Value. Toronto ( t - s t a t i s t i c s i n parentheses)  TORONTO: n = 55 i n n e r - c i t y census t r a c t s  Explanatory V a r i a b l e s i n Period 2  Explanatory Variables i n Period 1 VALUE2 UNVRS1 AGE1 N0RLG1 NFMHS1 CHLD1 PRF0C1 FMLBR1 FPR0C1 VSTZDV VALUE1 CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  0.30 ( 0.1) - 0.59 (-0.7) 0.67 ( 3.6)" - 0.18 (-0.4) -237.18 (-2.2)' - 0.27 (-0.3) 3.71 ( 2.6)' 0.16 ( 0.3) - 2.79 (-0.1) - 0.58 (-0.8) 53.75 ( 2.4)' .46*  VALUE1  UNVRS2  0.02 ( 0.5) 0.07 ( 0.5) 0.01 (-0.4) 0.06 ( 0.7) 0.31 (-0.0) 0.04 ( 0.2) 0.72 (-3.0)" 0.12 ( 1.0) n/a  AGE2 NORLG2  0.58 ( 4.8)"  NFMHS2 -177.83 (-2.9)"  CHLD2 PRF0C2  4.14 ( 3.7)"  n/a  0.72 (-3.1)" 0.18 ( 2.7)" n/a n/a  9.13 (-2.2)' .09  VALUE2  Best VALUE2 Best VALUE1  54.29 - 7.72 ( 3.3)" (-2.3)'  .32 (.52*) 9.54 (20.4*) <.01 (<.01*) 3.21 (0.29*) 16.10 (-.29*)  .17 6.47 < .01  FMLBR2 FPR0C2 VSTZDV VALUE1 CONSTANT  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  0.49 ( 1.0) 0.26 ( 0.2) - 0.74 (-2.3)' - 0.05 (-0.1) -490.6 (-2.7)"  Best VALUE2  0.74 (-2.5)'  -503.6 (-3.1)" -67.95  - 0.67 (-1.4) (-0.8) - 6.41 - 6.55 (-2.8)" (-2.6)' 0.00 ( 0.0) -43.73 -43.37 (-1.8) (-1.6) - 0.05 (-0.1) 156.3 157.2 ( 3.4)" ( 4.3)" .24  .30 4.85 < .01  (.29*)  1.42 (0.07*) 4.73 (-.36*)  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t a t the .01 level * n = 54, observation #60 deleted  99  APPENDIX C Table 23: M u l t i p l e Regression of Rent and Value. Period 2. Against Period 1 and Period 2 Explanatory Variables Pooled. 3 C i t i e s Combined ( t - s t a t i s t i c s i n parenthesis)  ALL 3 CITIES:  n = 95 i n n e r - c i t y census t r a c t s  RENT2  Best RENT2  VALUE2  Best VALUE2 - 0.47 (-2.1)  UNVRS1  - 0.02 (-0.2)  - 0.47 (-1.6)  UNVRS2 AGE1 AGE2 N0RLG1 N0RLG2 NFMHS1 NFMHS2 CHLD1 CHLD2 PRF0C1 PRF0C2 FMLBR1 FMLBR2 FPROC1 FPR0C2 RSTZDV VSTZDV RENT1 VALUE1 VANDUM OTTDUM CONSTANT  -  - 0.13 (-0.3) 1.10 ( 1.3) 1.94 ( 2.1) - 0.07 (-0.5) - 0.53 (-2.5) - 1.31 (-2.4) - 0.76 (-2.0) -294.8 (-2.4) -186.4 (-1.2) 0.33 ( 0.3) 0.66 ( 1.2) 2.71 ( 1-4) - 2.17 (-1.0) 0.85 ( 1.2) - 0.29 (-0.9) n/a -68.12 (-2.9) n/a  Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  0.15 0.10 0.35 0.01 0.01 0.23  (-1.0) (-0.3) (-1.0) (-0.2) ( 0.1) ( 1.1) (-1.7) (-0.6) (-3.4) ( 2.7) ( 3.0) (-0.4) (-0.5) (-2.4)  - 0.24 -27.55 -200.0 1.19 0.58 - 0.26 - 0.45 - 0.65 - 0.24 (-2.1) - 5.09 (-0.5) n/a - 0.81 (-2.4) n/a 15.02 ( 0.9) 34.34 ( 1.6) 22.61 ( 1.6) 26 2.68 < . 01  0.18 ( 1.1)  -136.7 (-3.3) 1.23 ( 4.2) 0.40 ( 3.6)  - 0.68 (-3.2) - 0.20 (-2.0) n/a - 0.80 (-2.9) n/a 26.01 ( 1.6) 23.68 ( 2.2)  - 0.48 -79.31 2.52 127.2  (-0.5) (-1.8) ( 0.1) ( 3.1)  1.07 ( 1.4) 2.09 ( 2.4) - 0.53 - 1.49 - 0.73 -294.9 -167.8  (-3.0) (-3.0) (-2.1) (-2.8) (-1.3)  0.25 2.87 - 2.19 0.99  ( 1.0) ( 1.8) (-1.1) ( 2.0)  n/a -68.12 (-3.1) n/a -79.14 (-2.0) 127.3 (3.8)  .31 (.36*) 6.38 (7.46*) <.01 (<.01*)  .24 2..50 < ..01  .29  (.27") (3.30 )  3.70 <.01 c<.or)  0.96 (0.52*) 1.35 (-.73*)  1..04 2..18  1.18 C0.45 ) 2.99 co.ir) <  i i i  A  A  * n = 94, observation #82 deleted n = 94, observation #60 deleted A  100  APPENDIX C Table 24: M u l t i p l e Regression of Rent and Value. Period 2. Against Selected Period 1 and 2 Explanatory Variables Pooled. 3 C i t i e s Combined ( t - s t a t i s t i c s i n parenthesis)  ALL 3 CITIES:  n = 95 i n n e r - c i t y census t r a c t s  RENT2 N0RLG1 N0RLG2 CHLD1 CHLD2 PRF0C1 PRF0C2 FMLBR1 FMLBR2 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  - 0.03 - 0.03 -50.45 -125.3  Best RENT2  (-0.5) (-0.4) (-1.5) (-2.5)'  0.22 ( 0.9) 0.31 ( 3.3)" - 0.14 (-0.3) - 0.31 (-0.4) 26.26 ( 2.3)' .19 3..74 < ,.01  -45.14 (-1.5) -109.9 (-2.5)' 0.22 ( 1.2) 0.30 ( 3.3)"  24.46 ( 2.4)' .21 (.26*) 7.55 (9.24*) <.01 (<.01*) 1.23 (0.88*) 1.94 (-.25*)  ' = S i g n i f i c a n t at the .05 l e v e l " = S i g n i f i c a n t at the .01 l e v e l * n = 94, observation #82 deleted n = 94, observation #60 deleted A  VALUE2 - 0.10 - 0.27 -53.44 -281.0 0.80  (-0.6) (-1.6) (-0.6)  (-2.1)' ( 1.2) 0.21 ( 0.8) 2.13 ( 1.6) - 3.45 (-1.8) 80.33 ( 2.7)" .13 2..82 < ,.01  Best VALUE2  - 0.24 (-1.5) -293.8 (-2.2)' 0.62 ( 1.1) 1.86 ( 1.5) - 3.44 (-1.9) 127.3 ( 3.8)" .15 (.17 ) 4.38 (4.82 ) A  A  <.01 (<.or) 1.74 (0.44") 9.34 (2.41 ) A  APPENDIX C Table 25: M u l t i p l e Regression of Rent and Value. Period 2. Against Period 1 and P e r i o d 2 Explanatory Variables Pooled. Vancouver ( t - s t a t i s t i c s i n parenthesis)  VANCOUVER: n = 20 i n n e r - c i t y census t r a c t s  RENT2  Best RENT2  UNVRS1  - 0.53 (-0.5)  UNVRS2  - 1.16 (-5.2)  NFMHS2  - 1.06 (-1.1) 4.17 ( 2.3) 4.29 ( 1-7) - 1.80 (-2.0) - 0.32 (-0.3) 3.01 ( 1.8) - 3.93 (-1.3)  CHLD1 CHLD2 PRFOC1 PRF0C2 FMLBR1 FMLBR2 FPROC1 FPROC2 RSTZDV VSTZDV RENT1 VALUE1  151.7 ( 0.3) 64.44 ( 0.2) 1.95 ( 0.6) 0.93 ( 1.4) 1.27 ( 0.4) 4.68 ( 0.9) - 1.28 (-0.7) - 0.26 (-0.2) -12.90 (-0.2) n/a 0.12 ( 0.1) n/a  151.5 ( 2.8)  AGE1 AGE2 N0RLG1 NORLG2 NFMHS1  CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  76.10 ( 1.2)  3.72 ( 6.0) 4.19 ( 5.0) - 1.71 (-4.6) 2.93 ( 7.4) - 2.58 (-5.0)  1.73 ( 2.9) 0.71 ( 5.4) 3.91 ( 5.9) - 1.57 (-3.9)  n/a 50.93 ( 4.1)  .50 2..05 < ..10  .90 16.45 < .01  0..01 -3..00  -0.24 -2.37  VALUE2  Best VALUE2  - 1.31 (-1.0)  - 0.75 (-2.5)  - 1.31 (-2.1)  - 1.40 (-4.0)  -  - 0.80 (-1.5) - 0.69 (-1.8)  0.23 1.34 1.06 0.57 0.67  (-0.1) (-0.5) (-1.1) (-0.5)  ( 0.5) 0.65 ( 0.2) 76.62 ( 0.4) -308.2 (-1.2) 6.04 ( 2.8) 1.43 ( 1.8) 5.01 ( 1.9) 1.72 ( 0.6) - 2.29 (-1.6) - 0.75 (-0.8) n/a -135.5 (-2.7) n/a 161.5 ( 2.3) .85 7.41 < ,.15  1.11 ( 2.3)  -393.3 5.34 1.55 4.42  (-3.7) ( 6.0) ( 4.9) ( 3.8)  - 2.41 (-3.3) - 1.15 (-3.7) n/a -132.2 (-7.3) n/a 128.0 ( 4.3) .94 26 .55 < ,.01 0..05 -2,.62  102  APPENDIX C Table 26: M u l t i p l e Regression of Rent and Value. Period 2. Against Selected Period 1 and 2 Explanatory Variables Pooled. Vancouver ( t - s t a t i s t i c s i n parenthesis)  VANCOUVER: n = 20 i n n e r - c i t y census t r a c t s  RENT2  Best RENT2  N0RLG1 NORLG2 CHLD1  - 0.27 ( -0.5) - 0.66 ( -1.5) 173.6 ( 1.6)  - 0.57 ( -1.6) 177.4 ( 1.9)  CHLD2 PRF0C1 PRF0C2 FMLBR1  11.54 1.68 0.23 - 0.21 1.86  FMLBR2 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  ( 0.1) ( 1.6) ( 0.9) ( -0.1) ( 1.2) 45.81 ( 1.6) .27 1.87 < .20  1.55 ( 2.7)' 0.27 ( 1.8) 1.59 ( 1.3) 24.46 ( 2.4)' .41 3.63 < .05 -0.13 -1.52  VALUE2 0.81 ( 1.1) 0.18 ( 0.3) -147.3 ( -1.0) -138.9 ( -0.7) 1.07 ( 0.7) - 0.05 ( -0.2) 9.83 ( 4.3)" 4.70 ( 2.2)'  Best VALUE2 0.81 ( 1.4) -195.9 ( -1.7) -224.0 ( -1.5)  34.92 ( 0.9)  8.82 ( 6.1)" 4.60 ( 2.6)' 42.89 ( 1.5)  .68 6.07 < .01  .73 11.46 < .01 -0.02 -1.89  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  103  APPENDIX C Table 27: M u l t i p l e Regression of Rent and Value. Period 2. Against Period 1 and Period 2 Explanatory Variables Pooled. Ottawa-Hull ( t - s t a t i s t i c s i n parenthesis)  OTTAWA-HULL: n = 20 i n n e r - c i t y census t r a c t s  UNVRS1 UNVRS2 AGE1 AGE2 N0RLG1 N0RLG2 NFMHS1 NFMHS2 CHLD1 CHLD2 PRFOC1 PRFOC2 FMLBR1 FMLBR2 FPR0C1 FPR0C2 RSTZDV VSTZDV RENT1 VALUE1 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  RENT2  Best RENT2  VALUE2  - 1.36 (-6.3) 1.43 ( 4.9) - 2.19 (- 1.6) 5.52 ( 8.8) 2.86 ( 7.1) - 0.91 (-4.8) - 4.68 (- 7.3) 1.45 ( 4.0) -105i.3 (- 0.5) -249i.5 (- 2.2) -35.30 (-9.7) - 2.97 (- 4.8) -11. 89 (-6.6) -25. 72 (-7.7) 12.32 ( 8.9) - 2.73 (-7.0) -12. 14 (-0.4) n/a 7.74 ( 8.6) n/a -2401.1 (-3.6)  - 1.,43 (-14 ) 1.36 ( 9.7) - 2.,75 (-6.7) 5.,46 (14.7) 2.,99 (17.3) - 0..84 (-14 > - 4.,89 (-18 ) 1.,59 (12.8)  n/a 7.,68 (15.2) n/a -217.9 (-8.3)  - 0.16 (- 0.2) 2.30 ( 0.5) 5.20 ( 0.2) 3.31 ( 0.3) 0.19 ( 0.1) - 0.87 (- 0.6) - 2.22 (- 1.0) - 0.38 (-0.1) -909.7 (-0.3) -42.84 (-0.1) - 4.99 (- 0.3) - 2.68 (- 0.7) - 6.35 (-0.5) -17.45 (-0.8) 1.97 ( 0.4) 1.26 ( 0.4) n/a -160.6 (- 0.5) n/a 0.43 ( 0.1) -102.6 (-0.1)  .95 21..29 < ,.30  ,98 59..60 < .,01  ,26 1.,37 < ..60  .84 8..04 < ..05  0,.01 -3 .00  0..01 -2..94  0..01 -3..00  0,.04 -2,.77  -290.7 -35.,91 - 3.,16 -11. 76 -25.48 12.,66 - 2..79  (-6.8) (-18 ) (-11 ) (-13 ) (-15 ) (18.5) (-13 )  Best VALUE2  2.42 3.57 2.72 0.39 - 0.89 - 2.29  ( 4.0) ( 1.3) ( 2.1) ( 1.1) (-4.3) (-3.3)  -766.3 (-4.5) - 6.18 (- 1.3) - 3.01 (-2.5) - 7.97 (-3.3) -18.99 (-3.7) 2.40 ( 1.6) 1.23 ( 1.6) n/a -144.7 (-4.7) n/a -98.36 (-0.9)  104  APPENDIX C Table 28: M u l t i p l e Regression of Rent and Value. Period 2. Against Selected P e r i o d 1 and 2 Explanatory Variables Pooled. Ottawa-Hull ( t - s t a t i s t i c s i n parenthesis)  OTTAWA-HULL: n = 20 i n n e r - c i t y census t r a c t s  RENT2 NORLG1 NORLG2  0.08 ( 0.6) - 0.01 (-0.0)  CHLD1  -65.30 (-0.6) -155.2 (-1.2)  CHLD2 PRFOC1 PRFOC2 FMLBR1 FMLBR2 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  - 1.15 0.37 - 0.71 - 1.14 4.99  (-1.3) ( 0.8) (-0.5) (-0.5) ( 0.1)  .27  Best RENT2  VALUE2  Best VALUE2  - 0.17 (-0.8)  -225.7 (-3.0)" - 0.80 (-2.6)'  54.87 ( 4.0)" .44 8.35 < .01  - 0.30 (-1.5) -83.84 (-0.4) -292.6 (-1.4) 2.02 0.52 - 4.44 - 6.13 100.1  ( 1.4) ( 0.6) (-1.7) (-1.5) ( 1.2)  .51 3.45 < .05  - 0.27 (-1.9) -356.8 (-2.3)' 1.25 ( 1.8) - 5.67 (-3.6)" - 6.83 (-2.3)' 42.89 ( 1.5) .58 6.37 < .01 0.33 -1.35  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level  105  APPENDIX C Table 29: M u l t i p l e Regression of Rent and Value. Period 2. Against Period 1 and P e r i o d 2 Explanatory Variables Pooled. Toronto ( t - s t a t i s t i c s i n parenthesis)  TORONTO: n = 55 i n n e r - c i t y census t r a c t s  RENT2 UNVRS1 UNVRS2  0.01 ( 0.1) - 0.17 (-0.8)  AGE1 AGE2 N0RLG1  - 0.53 (-1.0) 0.25 ( 0.4) 0.09 ( 0.7) - 0.03 (-0.2) 0.05 ( 0.2) 0.05 ( 0.1) -67.76 (-1.0) -70.03 (-0.7) 1.04 ( 1.8) 0.63 ( 1.9) - 0.75 (-0.8) - 1.14 (-0.9) - 0.30 (-0.7) - 0.25 (-1.7) - 3.67 (-0.3) n/a - 0.47 (-0.9) n/a 4.24 ( 0.2)  N0RLG2 NFMHS1 NFMHS2 CHLD1 CHLD2 PRF0C1 PRF0C2 FMLBR1 FMLBR2 FPROC1 FPR0C2 RSTZDV VSTZDV RENT1 VALUE1 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  Best RENT2  VALUE2 - 0.28 (-0.6) 0.17 ( 0.3) - 0.37 (-0.3) 0.20 ( 0.1) 0.76 ( 2.1) - 0.21 (-0.5) - 0.22 (-0.3) - 0.50 (-0.4)  -48.11 (-1.1)  Best VALUE2  0.85 ( 3.3)  n/a - 0.41 (-1.1) n/a - 3.50 (-0.3)  -351.2 (-1.8) -428.6 (-1.4) - 1.16 (-0.7) - 0.60 (-0.7) 1.01 ( 0.3) - 4.18 (-1.2) 0.35 ( 0.3) 0.04 ( 0.1) n/a -75.86 (-2.2) n/a - 0.20 (-0.1) 147.3 ( 2.3)  ,20 1.,75 < .,10  .33 (.36*) 5.53 (6.13*) <.01 (<.01*)  ,24 1.,96 < ,,05  .40 (.42") 6.02 (6.86") <.01 (<.01")  0.,68 -0. 40  1.08 (0.74*) 1.55 (-.17*)  1.02 1.,61  1.48 (0.04") 4.60 (-.54")  1.23 ( 3.0) 0.53 ( 3.4)  - 0.34 (-1.1) - 0.21 (-1.9)  -321.1 -419.2 - 1.43 - 0.61  (-2.5) (-2.3) (-1.6) (-1.9)  - 4.90 (-1.9)  n/a -71.89 (-2.8) n/a 120.6 ( 2.9)  * n = 54, observation #82 deleted " n = 54, observation #60 deleted  106  APPENDIX C Table 30: M u l t i p l e Regression of Rent and Value. Period 2. Against Selected Period 1 and 2 Explanatory Variables Pooled. Toronto ( t - s t a t i s t i c s i n parenthesis)  TORONTO: n = 55 i n n e r - c i t y census t r a c t s  RENT2 N0RLG1  Best RENT2  0.03 ( 0.3) - 0.04 (-0.4)  N0RLG2 CHLD1 CHLD2 PRF0C1  -51.84 (-1.1) -56.49 (-0.8) 0.61 0.27 - 0.40 - 0.43  PRF0C2 FMLBR1 FMLBR2 CONSTANT Adjusted R2 F-score p-value Residuals: Skewness Kurtosis  0.58 ( 2.0)' - 0.13 (-0.4) -66.16 (-1.6)  ( 1.7) ( 1.9) (-0.5) (-0.5)  0.79 ( 3.5)" 0.30 ( 3.0)"  5.54 ( 0.3)  24.46 ( 2.4)'  .26 3.35 < .01  .31 (.35*) 9.21 (10.5*) <.01 (<.01*) 2.64 (0.84*) 8.71 (0.36*)  ' = S i g n i f i c a n t at the .05 level " = S i g n i f i c a n t at the .01 level * n = 94, observation #82 deleted n = 94, observation #60 deleted A  VALUE2  Best VALUE2 0.62 ( 2.4)'  -191.0 (-1.5) -403.8 (-2.0)'  -237.1 (-2.1)' -350.0 (-1.9)  - 1.08 (-1.1) - 0.16 (-0.4) 3.37 ( 1.6) - 4.63 (-1.8)  - 1.13 (-1.1)  129.7 ( 2.9)" .32 4.20 < .01  3.91 ( 2.0)' - 4.69 (-1.8) 110.9 ( 3.0)" .34 (.54") 5.65 (11.2 ) <.01 (<.01 ) A  A  2.50 (0.30 ) 10.60 (-.94 ) A  A  APPENDIX D Table  31:  C a l c u l a t i o n o f F - s t a t i s t i c f o r C o m p a r i s o n Between R e d u c e d and C o m p l e t e M o d e l V a l u e R^s  Model R k Model R k Model R  Ottawa  Toronto  3Cities  Vancver  .40 20  .98 18  96 18  .59 8  .29 12  .89 10  66 10  .37 4  .25 12  .86 10  67 10  .55 4  95  20  20  55  3:  2  2:  2  1:  2  n F-stat: Model 3 vs 2 (.05 s i g )  1.70 (2.05)  .56 (239)  .94 (239)  6.04 (2.25)  Model 3 vs 1 (.05 s i g )  2.31 (2.05)  .75 (239)  .91 (239)  1.10 (2.25)  Note: F - s t a t i s t i c (  ?2 __t?2.  calculated  C" R)/( C" R> o (l-R )/(n-k -l) R  R  k  2  c  Where:  as  follows:  k  ~  F  kC-kR,n-kC-l  c  R C R k n  2  i s unadjusted = c o m p l e t e model = r e d u c e d model = number o r e x p l a n a t o r y = observations  variables  APPENDIX E  SUMMARY, HOUSING VARIABLES V=VANCOUVER, H=QTTAHA-HULL, T=T0R0NTO  Obsrvtn  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40  1961 Tract VCMA V28 V34 V36 V54 V32 V30 V52 V24 V22 V20 V18 V16 V14  71-81 Rent  -18 -26 -17 7 -11 24 2 9 1 -29 -10 -2 -15 -26 -16 11 28 -2 -3 112  -51 -4 -10 16 4 31 -2 1 1 -32 18 -4 -17 -0 -11 -17 15 0 -5 23  29 -40 86  -14 -7 16 -44 8 -58 -17 71 -31 92 33 121 145 156  moo  68 74 99 75 48 21 13 607 110 58 27 41 -68 22 3 -2 -3 -21 11 -16  31 27  HCMA H12 H28 H26 H24 H22 H30 H34 H20 H14 H16 N18 H4 H70 H72  H102 H106 H104 H108  -20 -245 99 239 -31 125 -6 -6 88 98 207 -315 -230  26 -27  60 69 7 119 -6 -20 112  48 134 86 1 35 -7  61-71 Value  -13 -22 9 2 -12 -5 -9 -5 -84 -16 14 31 1  5 96 82 131 14  12 3 243  61-71 Rent  -2 -67 55 -56 -5 -15 6 -19 -8 -12 -11 -2 -20 -27 -56 17 -24 -5 5 -13  -16 4 -16 105 -49  Vi2 V10 V8 V50 V6 V2 V4  H74  71-81 Value  -14 -19 21 8 99 8 -84  1971 1971 Rent Value Stzd Dv Stzd Dv  -.3 .7 1.5 -.9 -.5 -.7 -.2 -.6 1.6 -.4 -.4 .9 -.6 -.7 -1.2 .0 -1.2 -.7 2.3 1.3  -.1 1  J  c  -.8 3.2 -.6 .3 .1 1.9 .7 -.8 -.6 -.4 .2 -.3 -.2 -.9 -.4 -.9 -.6 .6  -.8 .0 .1 -.4 -.8 -.9 -.8 -.7 2.2 -.6 n • i.  .7 -.1 -.8 -.8 -.4 -.5 .2 2.6 1.7  -.1 -.1 .1 3.6 -.7 -.3 -.6 1.2 .5 .2 -.0 -.4 .4 -.0 -.4 -1.0 -1.1 -.1 -1.1 -.0  APPENDIX E  43 44 45 46 47 48 49 50  TCMA T30 TUB T116 T114 T102 T74 T62 T60 T44 T46  51 52 53 54  T24 T28 T26 T20  55 56  T22 T40  57 58 59 60 61  91 92 93  T42 T56 T58 T72 T96 T98 T100 T112 T110 T122 T120 T108 T106 T94 T70 T54 T38 T18 T16 T10 T8 T12 T14 T36 T52 T68 T66 T92 T88 T86 T152 T232 T298 T230 T228 T296 T180  94 95  T182 T138  41 42  62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90  26 33  46 -54  -18 94 16 78 185 45 -54  -8 96 343 67 426 280 -77  -22 1 -47 -28 50  -40  -33 5 8 193 34 17 2 81 101 88 3 14 42 31 -14 -16 210 44 -37 1 15 87 102 40 -32 36 -15 287 -8 36 1 12 -24 -8 1 -3 41 -7 -23 -36 -22  11 -66 -57 72 -76 -69 -97 95 -60 1060 248 -148 325 10 -26 -56 -82 2 39 122 216 74 -81 -87 -102 45 -98 -116 -25 31 216 79 57 142 63 181 266 -80 -86 -80 143 68 -26 116 282  -30 0 -3 -12 -19 7 85 20 -9 11 -11 -18 16 -23  -27 -84  .7 -.4  1.2 -.9  -6 22 -84 -84 -84 -84 -9 16 -28 -27 -10 -24  -.6 -1.0 -.8 .5  -1.0 -1.0 -1.2 3.4 -.4 .1 -.5  -31  -2  -23 3 25 25 11 34 22 -1 -14 -15 -10 -28 -14 52 -19 5 22 4 -19 -19 -5 -20 -2 -11 1 95 -4 -1 -9 15 -17 -17 -12 -14 -24 -22 23 -13  -0 -84 -84 -84 -84  -1.2 -1.0  -12 -6  -84 -84 -84 23 24 20 8 8 37 -17 -84 33 11 13 -26 -4 30 -2 -15 3 28 68 30 -10 12 -24 -17 -10 15 7 J  -25 -2 -12 -37 -55  0  . i.  -.5 -.9 -1.0 -.4 -.8 _  T • L.  -.9  -.7 -.2 .3 2.9 1.7 .9 -.4 -.9 -.7 -.6 -.8 -.7 .7 1.5 1.3 .6 -.6 -.9 -.9 c J  -1.1 -.7 -.7 C • J  1.9 .0 2.6 -.1 .5 .3 .0 -.1 -.1 -.6 -.2 1.9 .4 .4 2.3  -.6 -.4 -.9 -.4 -.5 -.8 -.4 .1 -.1 1.3 -1.1 .4 3.2 -.8 -.7 -.6 -.8 c  -. J  -.6 .5 1.6 1.5 .8 -.7 -.8 -.9 -.4 -.5 -.6 .0 -.4 .7 1.1 2.2 .2 -.4 .3 1.2 -.7 -.6 -.3 .3 .7 -.4 .1 -.1  APPENDIX E SUMMARY TABLE, DEMOGRAPHIC VARIABLES, 1961 - 1971 VANCOUVER, H=OTTAWA-HULL, T=TQR0NT0  1961 srvtn  1 2  Tract VCMA V28 V34  Age  -18 -16 -1 -6 -6 -5  No Religion  Soee Unvrsty  Nonfaly Hsehds  -28 -16 14 31 20 15  9 -7 10  -18 64 39 57 -4 15  I  P/A/t Labour  Feiale Labour  Chldrn  .0 .0  -1 7  -.4 -.1 .1 .2  0 -8 -10 2  ZPAT FaLabr  -7 -12 -6 19 -10 4  22 32 5 39 -6 17  3 4 5 6 7  V36 V54 V32 V30 V52  -13  6  73  17  .0  B  5  45  8 9 10 11 12 13 14 15 16 17 18 19 20  V24  -26 12 14 35 48  37 11 83  64 -23 14  19 -24  -2 -18 -14  -16 12 17  -6 74 229  -.2 .0  12 -6 -2  12 39 53  3 7 22 -2 4 47  V12 V10 V8 V50 V6 V2 V4  94 79 9 37 33 28 -41 -38 22 14  16 24 9 -20  .1 -.1 .1  94 24 53 182 142 -23 34  12 19 30 -37 -16 -7 -23  .1 .1 -.1 .3 -.1 -.0 -.1  -3 6 8 25 37 -15 -18  -14 -36 -1 -41 -46 3 16  9 -29 12 -44 -95 -2 -43  21 22 23 24 25 26 27 28 29 30 31  HCMA H12 H28 H26 H24 H22 H30 H34 H20 H14 H16 H18  14 -3 31 66 -58 68 -46 52 100 47 23 -41 -37 176 -56  23 -65 -47 -14 37 118 -15 29 16 8 1  2 -4 -14 -24 9 130 38 -25 8 -15 97 24 56 70 70 67 19 75 116 140  -.6 .0 .1 -.2 .1 -.2 .0 -.1  12  -17 -19 -11 16 -14 45 -20 47 -3 -19 -8  -20 -8 -2 1 28 173 -23 100 15 -28 24 -12 -28 15 -44 -71 -58 7 -15 112  32 33 34 35 36 37 38 39 40  V22 V20 V18 V16 V14  H4 H70 H72 H74 H100 H102 H106 H104 H108  29 103 -38 11 -52 -47 26 36  37 9 31 38 0 22 -0 26 25 -14 -15 -4 2 -1 -7 -11 -15 -5 -1 25  87 55 211 120 1153  38 78 50  -72 -87 38 26 -104 -11 -54 -20 493  7  _ T -.2 • X.  -.1 -.2 -.2 -.4 -.2 .1 -.1  T  -.4 -.9  -10 -13 -5 8 -7 -16 -11 -27 7 -1 6 4 12 -7 5 15 12 49  -31 -45 -13 -47 -54 -44 -4 -19 106  111  APPENDIX E 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95  TCHA T30 TUB T116 T114 T102 T74 T62 T60 T44 T46 T24 T28 T26 T20 T22 T40 T42 T56 T58 T72 T96 T98 T100  -7 -11 -10 -1  -18 93 35 28  15 58 276 137  -17 41 15 67  -.1 -.0 .1 -.0  -17 -9 -7 -14  5 6 54 9  -14 50 304 371 -17  290 132 456 142 11 37 -14 176 79  69 -33 -31 -38 -12  -.1 -.4 .1 .3 .1  5 -39 35 15 -11  9 -25 -17  .1 .1 .1 -.0 -.0 -.0 .2 -.0  -10 -9 13 -6  -.0 -.1 -.2 -.8 -.3 .0 .1 .1 T  -6 -34 -4 7  83 43 36 74  -20 -12  61 85  -18 -17 -6 -10 -20 -9 -10 -17 -10 -15 -19 4 -3 -7 -12 -4 -17 -11 -6 2 -2 -10 -2 -14 -6  11 8 -11 -6 -11 74 7 85 62 -11 -13 -6 13 -20 -21 -8 13 14 48 4 6 16 -0 -17 -8 -24  -11 8 -8 -3 15 10  -16 -22 15 3 -14 -8  -13 -11 -7 -15 9 1 1 -3 4 13 105 41 70 26 -0  Tl 12  •J  T110 T122 T120 T108 T106 T94 T70 T54 T38 T18 T16 T10 T8 T12 T14 T36 T52 T68 T66 T92 T88 T86  1 -0 5 3 55 -7 24 57 -16 -7 -8  T152 T232 T298 T230 T228 T296 T180 T182 T138  28 -20 -14  0  C J  -59 -18 -1 6 17 21 8 11 22 29  -5 31 21 8 28 -19  -44 -15 -69 78 11 -54 -40 77 162 267 96 40 3 360 93 -30 -59 -81 -51 43 50 52 309 -79 -76 -80 1 -77 -80 -42 -7 50 100 29 182 -3 84 102 -36 -63 -44 107 11 -29 65 31  -1 97 -6 75 213 58 51 153 111 240 94 29 -26 6 129 120 -36 16 118 90 16 119 12 69 85 -31 21 -3 58 -43 -36 34 -32 -29 83 103 -12 -28 19 50 -40 -39  -25 -1 -29 -31 66 63 4 -24 14 -11 -17 15 19 -15 -35 1 40 -11 -12 32 -34 -19 -13 18 161 -47 -22 14 -10 -25 -20 -38 40 -22 3 19 20 3 8 -9 18 25 73  .0  .3 .2 -.1 .1 -.4 -.2 .2 .2 •Tt -.1 0  • L.  .3 .2 .2 -.2 -.4 -.2 .2 -.1 .1 .0 .2 .1 .2 -.1 -.1 -.1 -.3 -.1  -15 -4 -17 -6  -7  \i  11 24 13 21 60 -27 120 88 5 -29 -23 36 59 20 -2 -1 52  42 19 48 44 122 -75 99 94 IB -37 -1 30 -4 1 37 -19 39 112 1 19 3 64 76 28 27 13 12 -28 125 -24 -0 50 15 -24 10 24 29 -5 -15 29 -13 6 -6 7 12 -4 -25 -25 -17 -5 -1 17 2 -45 -28  112  APPENDIX  E  SUMMARY TABLE, DEMQ6RAPHIC VARIABLES, 1971 - 1981 VANCOUVER, H=OTTAHA, T=T0R0NT0  srvtn 1 2 7 0  4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40  1961 Tract VCMA V28 V34 V36 V54 V32 V30 V52 V24 V22 V20 V18 V16 V14 V12 V10 V8 V50 V6 V2 V4 HCMA H12 H28 H26 H24 H22 H30 H34 H20 H14 H16 HIS H4 H70 H72 H74  moo  H102 K106 H104 H108  Age  1 Na Soee Nonfaly Religion Unvrsty Hsehds Chldrn  14 -11 -IB -2 1 13 14 11 -4 30 -10 -14 -5 -62 40 5 26 17 -20 -10  135 10 -24 18 9 48 12 30 27 3 -21 -30 2 10 16 13 -30 -38 -8 -25  47 -42 -11 -19 57 102 40 19 -3 38 -37 -7 131 5 46 93 17 58 -10 -1  -8 1 7 17 2 -2 9 -6 -12 11 26 -4 -33 22 0 25 -13 33 -13 -25  -24 4 4 7 27 -23 13 8 -43 89 39 -20 -19 5 -10 14 4 3 -14 -12  -127 58 62 -9 206 58 97 -25 65 514 382 286 114 -80 49 91 313 75 155 -77  -95 5 17 -14 135 -52 13 70 38 115 163 175 63 -16 -41 206 48 75 -32 -43  433 -28 -25 -36 -5 8 -14 -38 -20 17 24 27 10 81 IB 19 18 40 66 76  Fenale Labour  .1 .0 •1 .1 .1 .1 .1 .1 .2 i  .0 .2 -.1 .2 ,2 .0  • L. n  .6 .1 .3  .0 .4 .2 7  • -j  .1 .3 •3 .0 .1 .1 .0 .1 .1 -.1 .1 -.2 • T4.  .0 .0 .0  P/fl/t Labour  XPAT FflLabr  0 -19 -0 13 8 -3. -8 5 -14 -0 -4 -17 11 3 -3 0 10 -20 -20 -27  48 -66 0 -19 44 33 42 32 -17 32 -21 10 253 -15 91 78 132 291 -4 9  55 -18 8 -2 35 18 68 20 -13 32 2 74 210 -12 101 44 27 ERR 6 67  10 0  12 20 44 3 127 -30 20 60 36 116 82 72 59 41 -16 161 121 40 -28 -45  4 12 55 4 56 -27 13 64 28 60 41 25 55 35 35 176 159 52 -40 -62  r -J  -17 -4 -12 -7 4.4.  -3 1 -16 4 -!  7 -5 13 -8 1 4. 1  4.  113  APPENDIX E  41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 783 84 85 86 87 88 89 90 91 92 93 94 95  TCMA T30 TUB TU6 T114 T102 T74 T62 T60 T44 T46 T24 T2B T26 T20 T22 T40 T42 T56 T58 T72 T96 T98 T100 T112 T110 T122 T120 T108 T106 T94 T70 T54 T38 T18 T16 T10 T8 T12 T14 T36 T52 T68 T66 T92 TB8 T86 T152 T232 T29B T230 T22B T296 T180 T182 T138  -77 26 10 38 11 49 18 9 -13 5 -6 -6 -3 13 -8 -1 -12 17 -35 -2 -24 7 25 3 -12 7 -4 -16 -12 -27 -42 -24 -8 -2 -5 26 68 -13 -2 -13 -20 -25 -23 -7 6 6 2 -5 -7 -16 10 • -4 -11 -15 -31  12 96 261 216 122 -29 -18 -17 50 35 3 -90 7 71 22 93 197 51 -32 -25 -24 53 54 143 153 269 364 158 34 -52 -86 -26 288 32 171 131 76 76 104 109 -7 -6 -47 -62 50 31 -36 -28 7 -10 31 32 42 -52 -65  -14 160 63 426 12 99 47 -17 -32 9 -2 -60 9 49 -74 121 75 89 -63 _TT  -52 37 289 157 224 313 65 5 16 -35 7 -6 63 6 15 126 14 21 67 2 -15 14 -22 -28 22 -1 -19 -16 12 57 45 -10 -17 -26 -46  -14 -3 18 14 27 -15 6 -12 -17 -15 61 -39 33 14 -10 21 13 30 -28 -25 -21 -25 7 -8 -14 19 -9 38 -18 -23 -29 -15 2 -6 1 116 -0 -3 -6 -5 -17 -33 -22 -37 -18 -12 -7 -13 -9 6 3 -16 -9 15 21  .4 .0 .0 -.2 -.3 -.1 -.4 .1 .1 .0 .1 .2 .1 .1 i  • t.  .1 .3 _ T  • L.  .1 .1 .1 ".I -.4 .1 .2 -.0 .3 .1 .1 .2 .1 .2 .1 .1 .1 -.0 .2 .2 .2 .1 .2 .2 .3 .0 .1 .2 .1 .1 .2 .2 .1 .2 .3 .2 .4  -19 -6 2 17 33 25 -16 -2 -5 7 3 -7 -1 -11 -9 16 -1 4 2 -28 -21 -14 11 -0 4 -3 -13 3 -10 -14 -13 -12 5 1 -1 -7 15 4 -8 -8 -12 -13 -8 -1 -3 -2 -1 7 5 9 -2 -13 -12 -4 -9  -19 143 72 250 44 65 87 31 15 132 2 -102 10 77 -37 79 88 89 18 -17 -48 23 253 282 221 192 42 125 5 -20 8 33 41 54 77 143 71 122 113 39 12 36 -19 -18 43 6 -10 198 39 88 34 10 -2 7 -45  -29 187 89 182 35 27 48 42 26 103 -21 -106 101 102 -36 106 100 69 18 -22 -53 -5 254 239 223 150 20 300 8 16 19 17 67 3 48 123 9 99 87 28 36 29 -16 1 32 24 21 621 75 37 65 11 -8 66 -25  114  

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