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The impact of population aging  on the provincial housing markets  in Canada Presentation to the CMHC Mario Fortin, Ph. D. Professor Département d’économique April 1 st , 2009
Background ,[object Object],[object Object],[object Object],[object Object]
Goal of the project ,[object Object],[object Object],[object Object],[object Object]
Aging in Canadian provinces ,[object Object],[object Object],[object Object],[object Object]
Ratio of 25-44 to 65+:   eastern and central Canada
Ratio of 25-44 to 65+:   Canada and western provinces
The financial approach to housing price ,[object Object],[object Object],[object Object],[object Object]
The structural approach to housing price ,[object Object],[object Object],[object Object],[object Object]
Housing price dynamics
Required data ,[object Object],[object Object],[object Object],[object Object],[object Object]
Change in stock :  Eastern and central  Canada
Change in stock : Canada  and western provinces
Real housing price : eastern and central Canada
Real housing price : Canada and western provinces
[object Object],[object Object],[object Object],[object Object],Evolution of the age-specific headship rate
The age-specific provincial headship rates ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],Historical changes in the headship rate
Steps to estimate the number of households  ,[object Object],[object Object],[object Object]
The number of households exceeds  the number of housing units ,[object Object],[object Object],[object Object]
Excess of housing units over the number of households
Excess of housing units over the number of households
Broad description of the model ,[object Object],[object Object],[object Object],[object Object],[object Object]
Provincial coefficients ,[object Object],[object Object],[object Object]
Impact of demography   ,[object Object],[object Object],[object Object]
Population and households forecasts   ,[object Object],[object Object],[object Object],[object Object]
Other economic hypothesis ,[object Object],[object Object],[object Object]
Projected growth in the number of households
Number of households and housing units
Projection of the Canadian average housing price
Projections of provincial housing price (scenario 2)
Conclusion ,[object Object],[object Object],[object Object]
Conclusion (continued) ,[object Object],[object Object],[object Object]

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Implications of Population Aging on Real Housing Prices

Hinweis der Redaktion

  1. Real price peaked in BC in 1994. After slowly receding for 7 years, is exploded after 2001 to reach the top value of 400 000$ in 2007. Alberta’s prices steadily declined after 1981 and took a serious upward momentum only in 2005 to pass beyond the Canadian average in 2006. Manitoba and Saskatchewan have since lowest and most stable prices. In 2007, prices in Saskatchewan have been growing very fastly. The Canadian average mimics the price behaviour of Ontario: peaks in 1988, virtually stable real prices until 2000, then a steady growth to reach the recent peak of almost 280 000$.
  2. - To proxy the demand/supply imbalance caused by aging, I calculated the ratio between population size in the age group 25-44 (prime age) and population size in the 65+ age group. In all regions the ratio was almost stable in the 80s but has started to decline between 1986 (Quebec) and 1990. - New Foundland had the youngest population in the 80s but is becoming the oldest place : the ratio falls rapidly. In Quebec, the ratio if falling almost as rapidly. It is now Ontario that has the youngest population in eastern and central Canada.
  3. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.
  4. To adapt the formula to housing it is necessary to add, uncluding depreciation f such that the formula becomes (1+  )/(i +  + f -  )
  5. Point A is the initial long-run equilibrium. Following an increase in housing demand, caused by (for example) a rise in Y or a fall in r, the price jumps to B in the short run. High price increases the profit in home building and the supply starts moving to the right. The final equilibrium is at point C where price equals cost. There is a final short run vertical supply curve (not shown on the graph) that intersects the final demand curve a point C.
  6. Not surprisingly, the lowest addition to housing stock is in New Foundland and the faster is in Ontario.
  7. Addition to the housing stock has been much faster in western provinces, particularly in Alberta and British Columbia. Annual variations in BC were extremely wide between 1990 and 1998. Starting in 1998 and for 5 years, the annual growth was lower in BC than the Canadian average, but construction has since picked up. At the opposite, Manitoba and particularly Saskatchewan has had very low construction.
  8. The lowest price are observed in the Atlantic provinces and New Foundland and the highest is in Ontario Real price peaked in 1988 in Ontario and Quebec. It picked up again significantly only after 2000 in both provinces and have now exceeded the previous peak.
  9. Real price peaked in BC in 1994. After slowly receding for 7 years, is exploded after 2001 to reach the top value of 400 000$ in 2007. Alberta’s prices steadily declined after 1981 and took a serious upward momentum only in 2005 to pass beyond the Canadian average in 2006. Manitoba and Saskatchewan have since lowest and most stable prices. In 2007, prices in Saskatchewan have been growing very fastly. The Canadian average mimics the price behaviour of Ontario: peaks in 1988, virtually stable real prices until 2000, then a steady growth to reach the recent peak of almost 280 000$.
  10. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.
  11. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.
  12. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  13. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  14. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  15. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  16. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  17. In the price equation : Change in real income has a positive impact (7%) while change in the interest rate a strong and highly significant impact on housing price : a one percentage point rise decreases housing price by 4.7%. Lag price is not significant but lagged real income, interest rate and stock are significant. In the stock equation : a 1% increase in real price increases by 0.0245% the change in the stock while the lagged stock has a coefficient of -0.045. In the Canadian system, population change has a positive but not significant impact on price.
  18. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.
  19. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.
  20. Alberta has by far the most favourable demographic ratio of all Canadian provinces. The oldest province is Saskatchewan.