NEPTIS STUDIES ON THE
TORONTO METROPOLITAN REGION
ECONOMIC INFLUENCES
ON POPULATION GROWTH
AND HOUSING DEMAND
IN THE GREATER GOLDEN
HORSESHOE
JANUARY 2006
WILL DUNNING INC.
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ECONOMIC INFLUENCES ON POPULATION GROWTH
AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
Will Dunning Inc.
Neptis is an independent Canadian foundation that conducts and publishes
nonpartisan research on the past, present and futures of urban regions.
By contributing reliable information. expert analysis and fresh policy ideas,
Neptis seeks to inform and catalyze debate and decision-making on regional
urban development.
NEPTIS FOUNDATION
50 Park Road
Toronto, Ontario
M4W 2N5
www.neptis.org
© 2006 Neptis
Foundation
NEPTIS
THE ARCHITECTURE
OF URBAN REGIONS
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Copyright © 2006 Neptis Foundation
First Impression
Library and Archives Canada Cataloguing in Publication
Economic influences on population growth and housing demand in the Greater Golden Horseshoe
[electronic resource] / Will Dunning Inc.
(Neptis studies on the Toronto metropolitan region)
ISBN 0-9739888-0-0
1. Population forecasting—Ontario. 2. Ontario—Population.
3. Housing—Ontario. I. Neptis Foundation II. Will Dunning Inc.
III. Series.
HB3530.O58E28 2006
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C2005-907599-6
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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Table of Contents
EXECUTIVE SUMMARY
1
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1
INTRODUCTION 3
1.1 Overview 3
1.2 Terminology 4
1.3 This Analysis Does Not Reflect the Effects of Policy Changes or Lifestyle Trends
5
2
ECONOMIC INFLUENCES ON THE HOUSING MARKET 6
2.1 Housing Market Cycles 6
2.2 The Economic Basis of the Housing Market Expansion in the Late 1990s 9
2.3 The Economic Basis of the Housing Market Peak and Decline after 2002 13
2.4 Implications for Long-Term Housing Demand in the GTA 14
3
ECONOMIC INFLUENCES ON MIGRATION AND POPULATION GROWTH
3.1 Overview of Economic Trends and Components of Population Growth 15
3.2 International Immigration 15
3.3 Emigration 19
3.4 Interprovincial Migration 19
3.5 Intraprovincial Migration 23
3.6 Simulations 26
3.7 Conclusions 33
4
ECONOMIC INFLUENCES ON DWELLING TYPE MIX 35
4.1 Existing Stock of Occupied Housing (Census Data) 35
4.2 Housing Starts Data for the GTA 35
4.3 Housing Starts Data for the Greater Golden Horseshoe 43
4.4 Comparing Housing Starts Data with the Census Data 44
4.5 Conclusions 44
5
PROJECTIONS 46
5.1 Projections of Population Growth 46
5.2 Projections of Household Formation and Housing Requirements 50
5.3 Projections of Employment Growth 56
5.4 Comparison with Other Projections 61
A
APPENDIX 71
A.1 Projections of Migration by Components for 16 Census Divisions in the Greater Golden Horseshoe 71
A.2 Projections of Population and Population Growth for 16 Census Divisions in the Greater Golden Horseshoe 73
A.3 Projections of Households and Household Growth for 16 Census Divisions in the Greater Golden Horseshoe 75
A.4 Projections of Employment and Employment Growth for 16 Census Divisions in the Greater Golden Horseshoe 77
A.5 Economic Influences on Household Formation Rates and Household Sizes 79
A.6 Charts of Headship Rates For 27 Census Metropolitan Areas by Age Group 89
15
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List of Maps and Figures
Map 1: Geographical Boundaries in the Greater Golden Horseshoe
4
Figure 1: Housing Starts in the GTA, 1987 to 2004 6
Figure 2: New Home Sales in the GTA, 1981 to 2004 7
Figure 3: New Home Sales and Housing Starts in the GTA, 1985 to 2004 8
Figure 4: Monthly New Home Sales in the GTA, 1995 to 2005 8
Figure 5: New Home Sales in the GTA, by Low-Rise or High-Rise, 1995 to 2005 9
Figure 6: Employment Growth in the GTA, 1988 to 2005 10
Figure 7: Employment-to-Population Ratio in the GTA, 1987 to 2005 10
Figure 8: Average Monthly Mortgage Payments in the GTA, in 1992 dollars, 1981 to 2003 11
Figure 9: GTA Employment Ratio vs. Canada-U.S. Exchange Rate, 1987 to 2004 13
Figure 10: Immigration to Canada and to the Inner Ring, 1987 to 2004 16
Figure 11: Inner Ring Share of Canada’s Immigration vs. Employment-to-Population Ratio, 1987 to 2004 17
Figure 12: Inner Ring’s Share of Canada’s Immigration vs. Average GTA House Prices, 1987 to 2004 17
Figure 13: Outer Ring’s Share of Canada’s Immigration vs. GTA House Prices, 1987 to 2004 18
Figure 14: GGH Share of Canada’s Immigration vs. Employment-to-Population Ratio, 1987 to 2004 19
Figure 15: Inner Ring Interprovincial Net Migration vs. Employment-to-Population Ratio, 1987 to 2004 20
Figure 16: Inner Ring Interprovincial Net Migration vs. GTA House Prices, 1987 to 2004 20
Figure 17: Outer Ring Interprovincial Net Migration vs. Employment-to-Population Ratio, 1987 to 2004 21
Figure 18: Outer Ring Interprovincial Net Migration vs. GTA House Prices, 1987 to 2004 22
Figure 19: Interprovincial Net Migration vs. Employment-to-Population Ratio, Greater Golden Horseshoe, 1987 to 2004 22
Figure 20: Interprovincial Net Migration vs. GTA House Prices, Greater Golden Horseshoe, 1987 to 2004 23
Figure 21: Inner Ring Intraprovincial Net Migration vs. Employment-to-Population Ratio, 1987 to 2004 23
Figure 22: Inner Ring Intraprovincial Net Migration vs. GTA House Prices, 1987 to 2004 24
Figure 23: Outer Ring Intraprovincial Net Migration vs. Employment-to-Population Ratio, 1987 to 2004 25
Figure 24: Outer Ring Intraprovincial Net Migration vs. GTA House Prices, 1987 to 2004 26
Figure 25: GTA Homeowner Apartment Starts vs. GTA Single House Prices, 1988 to 2004 41
Figure 26: Percentage of GTA Single-Detached Homeowner Starts vs. Real Median Single Detached House Prices, 1988 to 2004 42
Figure 27: Percentage of GTA Homeowner Semi-Detached and Row Housing Starts vs. Real Median Single Detached House Prices,
1988 to 2004 43
Figure 28: GGH Share of Net Immigration to Canada, 1987 to 2004 65
Figure 29: Coefficients for Owners’ Monthly Costs, by Age Group 80
Figure 30: Coefficients for Employment Ratio, by Age Group 81
Figure 31: Adjusted R-Squares for Analysis Models, by Age Group 81
Figure 32: Predicted vs. Actual Changes in Headship Rates, for 25 CMAs, by Age Group, 1996 to 2001 81
Figure 33: Predicted vs. Actual Changes in Headship Rates for Toronto CMA, by Age Group, 1996 to 2001 82
Figure 34: Number of Adults per Household vs. Owners’ Monthly Costs, for 25 CMAs 83
Figure 35: Number of Adults per Household vs. Employment-to-Population Ratio, for 25 CMAs 83
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List of Tables
Table 1: Estimated Sensitivities of Migration Components to Two Economic Factors 27
Table 2: Estimation of Potential Impacts of Population Change on the Employment-to-Population Ratio in the GTA 28
Table 3: Simulated Migration Rates, Based on Two Economic Factors 30
Table 4: Projections of Components of Migration, Annual Averages by 10-Year Period and Total Migration, 2001 to 2031 33
Table 5: Distribution of Dwellings in the Greater Golden Horseshoe, by Structural Type, 2001 35
Table 6: Housing Starts by Dwelling Type in the GTA, 1987 to 2004 (in units) 36
Table 7: Housing Starts by Dwelling Type in the GTA, 1987 to 2004 (percentages) 37
Table 8: Housing Starts by Dwelling Type in the GTA, Excluding Assisted Housing, 1987 to 2004 (percentages) 39
Table 9: Housing Starts by Dwelling Type in the GTA, Including Only Units Intended for Homeownership, 1987 to 2004 (percentages) 40
Table 10: Distribution of Housing Starts in the Greater Golden Horseshoe, by Structural Type, 1999 to 2004 43
Table 11: Components of Annual Population Growth in the Greater Golden Horseshoe 49
Table 12: Actual and Projected Population by Area, 2001 to 2031 49
Table 13: Household Headship Rates in the Greater Golden Horseshoe, 2001 51
Table 14: Households by Age Group in the Greater Golden Horseshoe, 2001 to 2031 52
Table 15: Projections of Households and Household Growth in the Greater Golden Horseshoe, 2001 to 2031 52
Table 16: Housing Demand in the GGH, by Type of Dwelling, 2001 to 2031 55
Table 17: Employment-to-Population Ratios by Age Group in the Greater Golden Horseshoe, 2001 57
Table 18: Distribution of the Adult Population by Age Group in the Greater Golden Horseshoe, 2001 to 2031 58
Table 19: Projections of Employment and Employment Growth in the Greater Golden Horseshoe, 2001 to 2031 59
Table 20: Simulation of Age-Specific Employment Rates (in the GGH) Required to Result in a 64.2% Employment Rate in 2031 60
Table 21: Comparison of Projections of Total Population Growth for the Greater Golden Horseshoe (Will Dunning Inc. and Hemson
Projections) 61
Table 22: Comparison of Projections of Total Population Growth for Central Ontario (Will Dunning Inc. and IBI Projections) 62
Table 23: Comparison of Projections of Annual Migration for the Greater Golden Horseshoe 63
Table 24: Comparison of Projections of Household Formation in the Greater Golden Horseshoe (Total Growth in Households by Period) 67
Table 25: Comparison of Projections of Employment and Employment Growth in the Greater Golden Horseshoe 68
Table 26: Estimation of Potential Employment Growth in the Inner Ring, using Hemson Population Projections 69
Table 27: Comparison of Projections of Total Employment Growth for Central Ontario (Will Dunning Inc. and IBI Projections) 70
Table A–1–1: Projections of Migration by Census Division in the Inner Ring 71
Table A–1–2: Projections of Migration by Census Division in the Outer Ring 72
Table A–2–1: Projections of Population and Population Growth by Census Division in the Inner Ring 73
Table A–2–2: Projections of Population and Population Growth by Census Division in the Outer Ring 74
Table A–3–1: Projections of Households and Household Growth by Census Division in the Inner Ring 75
Table A–3–2: Projections of Households and Household Growth by Census Division in the Outer Ring 76
Table A–4–1: Projections of Employment and Employment Growth by Census Division in the Inner Ring 77
Table A–4–2: Projections of Employment and Employment Growth by Census Division in the Outer Ring 78
Table A–5–1: Adults per Household in 1996 and 2001, for 25 CMAs 84
Table A–5-2: Estimation of Potential Surplus or Shortfall in Households as of 2001 Due to Incomplete Adjustment to Changed Economic
Conditions in Census Divisions of the GTA 86
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Executive Summary
Government planning and policy development at all levels depend on forecasts
for population and employment. Planning for infrastructure investment, land
development, and transportation also depend on forecasts about household size
and housing requirements.
In this report, Will Dunning develops
forecasts for population, employment,
household formation, and housing
demand for Ontario’s Greater Golden
Horseshoe in the context of economic
trends that affect the housing market,
immigration and migration, and the size
and structure of households.
Lake Superior
PETERBOROUGH
Lake
Simcoe
SIMCOE
NORTHUMBERLAND
DURHAM
DUFFERIN
The housing market is cyclical; periods of
intense activity are followed by periods in
which housing starts decrease. An analysis
of housing starts in the Greater Toronto
Area (GTA) since 1987 suggests that the
housing market peaked in 2003 and is
starting a period of decline. At the same
time, employment growth in the GTA appears to be slowing, partly because of the
weakening of the U.S. dollar, the prospect
of rising interest rates, and the retirement
or early retirement of baby boomers.
KAWARTHA
LAKES
YORK
PEEL
WELLINGTON
TORONTO
Lake
Ontario
HALTON
WATERLOO
0
20
40
km
HAMILTON
BRANT
NIAGARA
Upper-Tier Municipal Boundary
Greater Golden Horseshoe
HALDIMAND
Data Sources: National
Topographic Survey, 2001
Census Statistics Canada
Copyright Neptis Foundation 2006
Lake Erie
Outer Ring
Inner Ring
The Greater Golden Horseshoe
Trends in international immigration and in migration within Canada also affect
the region’s population and employment prospects, and are themselves affected by
employment rates. In the Inner Ring of the Greater Golden Horseshoe (the GTA
plus Hamilton), peaks in immigration generally coincide with peaks in employment growth.
Where people settle within the region is strongly influenced by housing prices.
People migrate into the region when employment growth is strong, and within the
region, choose the areas where housing prices are affordable to them. As housing
prices rise in the Inner Ring, people become more likely to choose housing in the
rest of the region (the Outer Ring).
Cycles in employment and the economy also affect the kind of housing that people
choose. During strong markets, the proportion of apartments rises relative to
houses. The share of single detached houses has fallen over the last decade and a
half; single detached houses now account for less than half of all housing starts
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in the GTA. The share of semi-detached and row houses has risen and fallen over
the same period; after increasing for several years, they are now losing share to
apartments. These changes relate to housing prices: as prices rise, more people
choose apartments. Also, the low interest rates of recent years have encouraged
many renters to buy condominium apartments.
Given long-term trends in employment and immigration, Dunning projects the
population of the Greater Golden Horseshoe at 10.48 million in 2031, compared
to 7.88 million in 2001. The figures represent an average growth rate of 86,700
people per year, but the rate of growth will fall over the period, from 109,600
people per year between 2001 and 2011, to 62,000 people per year between 2021
and 2031. This decrease largely is due to the aging of the population, as retirees
move elsewhere and mortality increases.
Within the region, the share of growth going to the Inner Ring will fall from almost
70 percent to just above 60 percent, if house prices in the Inner Ring remain at or
near present levels.
Over the next three decades, the forecasts suggest that the rate of household formation will slow and household size will decrease from 2.80 people per household
in 2001 to 2.53 people in 2031. These trends will affect the amount and type of
housing that is needed. Housing starts would fall from an average of 54,800 units
per year between 2001 and 2011 to 32,400 units per year between 2021 and
2031. If, at the same time, housing costs and interest rates rise beyond the trend
levels that have been assumed, the demand for apartments will increase relative to
single detached houses.
The aging of the population will also mean slower employment growth and a
lower employment rate. This will be true for the country as a whole, so the trend
is unlikely to be offset by migration from elsewhere in Canada, although it could
be affected by increased immigration of working-age adults from outside the
country.
Finally, Dunning compares his forecasts to those prepared by Hemson for the
Ontario government and those by the IBI Group for the Neptis Foundation. His
projections for both population and employment growth are considerably lower
than those by Hemson and IBI. Dunning predicts 1.1 million fewer people and
700,000 fewer jobs in the Greater Golden Horseshoe in 2031 than Hemson; and
500,000 fewer people and 800,000 fewer jobs than IBI. The differences stem from
differing assumptions about migration and employment growth. Hemson and
IBI generally assumed continued robust employment growth, whereas Dunning
assumes that sustainable long-term growth rates are lower. He incorporates a
falling employment rate due to the aging of the population, which in turn will lead
to lower migration into the region.
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1
Introduction
1.1
Overview
|3
Population and employment forecasts underpin government planning and policies for everything from economic development to transportation. These forecasts
are based on assumptions about immigration, migration, demographic change,
mobility within a region, and trends in the economy and in lifestyles. Not only
is it important to know how many people will live in a city-region, governments
also need to know where growth will occur, so that investment can be directed to
those areas.
The Province of Ontario, in establishing a growth plan for the Greater Golden
Horseshoe (the area surrounding the west end of Lake Ontario), needs accurate
forecasts, not only for population and employment, but also for matters such as
household formation and the type of dwellings that those households are likely to
choose.
This research report offers a series of forecasts, prepared in light of economic
trends that may affect population growth and household formation in the Greater
Golden Horseshoe over the long term. It also assesses the prospects for employment growth, considering that the aging of the population is likely to result in
reduced participation in the labour force.
This research begins with an overview of housing market cycles, and of economic
influences on migration, population growth, household formation rates, household size, and dwelling type choices. This information is used to develop four sets
of projections:
•
•
•
•
population growth;
household formation;
housing requirements;
employment growth.
The results are then compared to two other sets of projections for population
growth, housing demand, and employment growth, one by Hemson Consulting in
the Growth Outlook for the Greater Golden Horseshoe (January 2005), commissioned by the Province of Ontario, and the other by the IBI Group in the Torontorelated Region Futures Study (2003), commissioned by the Neptis Foundation.
Both of these studies projected population and employment growth to 2031.
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Map 1: Geographical Boundaries in the Greater Golden Horseshoe
Lake Superior
PETERBOROUGH
Collingwood
Lake
Simcoe
SIMCOE
KAWARTHA
LAKES
Lindsay
Barrie
Peterborough
DURHAM
Newmarket
DUFFERIN
YORK
WELLINGTON
Richmond
Hill
PEEL
Oshawa
Whitby
Pickering
TORONTO
Brampton
Lake
HALTON
WATERLOO
Guelph
NORTHUMBERLAND
Mississauga
Milton
Waterloo
o
Ontari
Oakville
Kitchener
0
20
BRANT
40
km
St. Catharines
HAMILTON
Upper-Tier Municipal Boundary
NIAGARA
Welland
HALDIMAND
Lower-Tier Municipal Boundary
Greater Golden Horseshoe (GGH) Outer Ring
Greater Golden Horseshoe (GGH) Inner Ring
Data Sources: National
Topographic Survey, 2001
Census Statistics Canada
Copyright Neptis Foundation 2006
5
1.2
Toronto Census Metropolitan Area (CMA)
Lake Erie
Terminology
Several geographical terms will be used in this report. For the sake of consistency,
definitions will be used that correspond to those used in the Province’s recently
released policy documents. These definitions are:
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•
The Greater Toronto Area (GTA) includes the City of Toronto and the
Regional Municipalities of Halton, Peel, York, and Durham.
•
The Inner Ring consists of the GTA plus the City of Hamilton.
•
The Outer Ring contains the remainder of the Greater Golden Horseshoe
— the Regional Municipalities of Niagara and Waterloo; the counties of
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Brant, Dufferin, Haldimand-Norfolk, Northumberland, Peterborough,
Simcoe, and Wellington, together with their associated separated cities;
and the City of Kawartha Lakes.
•
The Greater Golden Horseshoe (GGH) is made up of the Inner Ring and
the Outer Ring.
Some of the analysis makes use of Census Divisions (CDs). These correspond to
upper- and single-tier municipalities, with separated cities such as Guelph, Barrie,
Orillia, and Orangeville included with their associated counties.
1.3
This Analysis Does Not Reflect the Effects of
Policy Changes or Lifestyle Trends
The projections developed in this study do not include the potential impact of
changes in provincial government policy, such as the creation of the Greenbelt or
the implementation of the Growth Plan for the Greater Golden Horseshoe. More
generally, the projections do not reflect constraints on the supply of developable
land that might hinder population growth in some areas or shift it to other areas.
This would occur if land supply constraints lead to higher land prices in some areas,
which are passed along to consumers in the form of higher house prices. Rising
prices would cause some buyers to move to communities with lower housing costs.
For these reasons, actual growth for individual regions will vary compared to the
projections contained in Section 5. However, shifts away from some parts of the
Greater Golden Horseshoe will largely be offset by shifts towards other areas.
Growth for the GGH as a whole is expected to be close to the totals shown for
both the Inner and Outer Rings.
The research also excludes potential changes in federal government policy that
would affect population growth. For example, the federal government has recently
started to consider raising annual immigration targets. This change would increase the rate of population growth and result in expanded household formation
and increased demand for housing.
By focusing on economic influences on migration and household formation, this
research also does not factor in other trends that may affect population growth
and household formation, such as:
Dunning0112.indd Sec2:13
•
Changing attitudes and behaviour that might increase or decrease birth
rates, cause young people to stay in their parents’ homes for longer or
shorter periods, or affect marriage rates.
•
Changing lifestyles and medical science that affect life expectancy.
•
Changing attitudes of immigrants or the development of ethnic clusters
that might cause more or fewer immigrants to settle in central Ontario.
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2
|6
Economic Influences on the Housing Market
This section describes the cyclical nature of the housing market and identifies
where the Greater Golden Horseshoe is in that cycle at present.
2.1
Housing Market Cycles
Figure 1 summarizes CMHC data on housing starts in the Greater Toronto Area,
from 1987 to 2004. This period is more or less equivalent to one housing market
cycle. Over the entire period, GTA housing starts averaged 33,678 units per year.
They peaked at more than 50,000 units in 1987 and again in 2003.
Figure 1: Housing Starts in the GTA, 1987 to 2004
Housing Starts in the GTA - 1987 to 2004
60,000
50,000
40,000
30,000
20,000
10,000
0
1987
1990
1993
1996
1999
2002
Source: CMHC
Between these peaks, the market cycle was low from 1990 to 1996, when starts
averaged 20,444 units per year. Starts were actually bolstered during that period
by an aggressive program of assisted rental housing development, which represented an average of 4,039 starts per year. If those starts are excluded, unassisted
development averaged 16,405 units per year between 1990 and 1996. During the
recent period of market strength (1999 to 2004), housing starts averaged 45,098
units per year.
Housing starts fell by 7.6 percent in 2004, to 46,372. Although this number is
above the long-term average of 33,678 per year, it appears that the current housing
market cycle peaked in 2003 and that housing construction may now be slowing.
An additional perspective on the housing market cycle in the GTA is provided by
data on new home sales from the Greater Toronto Home Builders’ Association
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(GTHBA). Figure 2 summarizes annual total sales between 1981 and 2004. This
longer period represents about two market cycles, during which sales averaged
25,400 units per year. In the weak market period between 1990 and 1996, sales
averaged 13,200 units per year; during the strong period of 1999 to 2004, sales
averaged 43,200 units per year.
The GTHBA data show that sales of new homes peaked in 2002, per year earlier
than the peak shown in the CMHC data on housing starts. In the housing production process, the sale of a new house or apartment almost always occurs before
construction starts. The data from GTHBA therefore confirms the conclusion from
the CMHC data, that the recent housing market cycle has passed its peak.
Figure 2: New Home Sales in the GTA, 1981 to 2004
New Home Sales in the GTA - 1981 to 2004
60,000
50,000
40,000
30,000
20,000
10,000
0
1981
1984
1987
1990
1993
1996
1999
2002
Source: Greater Toronto Home Builders' Association
Figure 3 overlaps data on new home sales from the GTHBA and on housing starts
from CMHC. Since the GTHBA data excludes purpose-built rentals, the CMHC
data has been adjusted to exclude purpose-built rentals. The results reinforce the
conclusion that the current housing cycle has passed its peak.
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Figure 3: New Home Sales and Housing Starts in the GTA, 1985 to 2004
New Home Sales and Starts in the GTA
60,000
New Home Sales
50,000
Starts (excl. Rentals)
40,000
30,000
20,000
10,000
0
1985
1988
1991
1994
1997
2000
2003
Source: GTHBA / CMHC
Very recent data on new home sales shown in Figure 4 provides an even stronger
indication that the market cycle has peaked and is now in decline. The trend line
(the smooth black line) for seasonally adjusted sales is falling.
Figure 4: Monthly New Home Sales in the GTA, 1995 to 2005
Monthly New Home Sales in the GTA
80,000
70,000
60,000
50,000
40,000
30,000
20,000
10,000
0
1995
1997
1999
2001
2003
2005
Source: GTHBA / Will Dunning Inc.
Figure 5 separates new home sales into two components — low-rise sales (singledetached, semi-detached, and townhouses) and high-rise sales (apartment condominiums).*
* Before 2002, new home sales data were divided between freehold tenure versus condominium tenure
(which can include condominium townhouses); starting in 2002, the division is between low-rise
(which includes condominium townhouses) and high-rise (apartments only). To ensure comparable
data, the author estimated low-rise versus high-rise distribution for the pre-2002 data.
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Sales of low-rise homes fell sharply in the second half of 2004 and, despite the
recent partial recovery, the trend line is now at its lowest level since 1998. In
the high-rise market (which is centred in downtown Toronto) the trend remains
strong. This trend contrasts with the low-rise market, which is focused on the
municipalities outside Toronto.
Figure 5: New Home Sales in the GTA, by Low-Rise or High-Rise, 1995 to 2005
New Home Sales
60,000
Low-Rise
50,000
High-Rise
40,000
30,000
20,000
10,000
0
1995
2.2
1997
1999
2001
2003
Source: GTHBA / Will Dunning Inc.
2005
The Economic Basis of the Housing Market Expansion in the Late 1990s
2.2.1
Employment Growth
Figure 6 illustrates the effect of the employment rate on the GTA housing market
cycle. In the early 1990s, a weak employment situation (heavy job losses early in
the decade, followed by a halting recovery until the mid 1990s) resulted in low
housing demand.
Starting in 1994, the GTA economy began to recover rapidly from the recession.
Between December 1994 and December 2000, 492,000 jobs were created in the
GTA, representing an average of 82,000 jobs per year, or 3.5 percent per year. This
growth rate was faster than the population growth rate. The rate of job creation
has since slowed.
During this expansionary period, the number of people who had recently become
employed rose and resulted in an increasing number of people who were in a
position to buy homes. This trend resulted in expanding sales for new and resale
homes.
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Figure 6: Employment Growth in the GTA, 1988 to 2005
Employment Growth (Year Over Year) in the GTA
150
100
50
0
1988
-50
1990
1992
1994
1996
1998
2000
2002
2004
-100
-150
Source: Statistics Canada / Will Dunning Inc.
Employment can also be expressed as the percentage of adults who are employed:
the employment rate. Figure 7 shows that the employment rate for the GTA rose
during the late 1990s and peaked about 2001. It is difficult to see a conclusive
trend after 2001, but the period of strong growth appears to have ended.
Figure 7: Employment-to-Population Ratio in the GTA, 1987 to 2005
Employment-to-Population Ratio in the GTA
72
70
68
66
64
62
60
58
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
Source: Statistics Canada / Will Dunning Inc.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
2.2.2
| 11
Housing Affordability
Figure 8 shows data on the affordability of homeownership in the Greater Toronto
Area, using data on house prices reported by the Toronto Real Estate Board. The
graph shows the average monthly mortgage payment (in inflation-adjusted or
“real” dollars) for the period 1981 to 2003. Between 1995 and 1997, the average
monthly cost fell to the lowest level since the start of the data set in 1981. While it
rose slightly in 1999 and 2000, it remains at a quite low level compared to earlier
years. This represents good housing affordability. The persistence of the trend
during the second half of the 1990s and the early 21st century coincided with the
expanding numbers of recently employed people and contributed to rising levels
of housing demand from 1995 to 2002.
Figure 8: Average Monthly Mortgage Payments in the GTA, in 1992 dollars, 1981 to 2003
Monthly Mortgage Payments in the GTA
$3,000
$2,500
$2,000
$1,500
$1,000
$500
$0
1981
1984
1987
1990
1993
1996
1999
2002
Source: TREB / W ill Dunning Inc.
2.2.3
Factors that Drove the Economic Expansion
The rapid rate of job creation in the GTA between 1994 and 2000 can be attributed to a number of factors:
Dunning0112.indd Sec2:19
•
The economy was recovering from a harsh recession.
•
Low interest rates encouraged spending and investment by companies and
individuals.
•
The strong stock market encouraged job creation in the GTA in at least
three ways — by increasing activity and employment in the financial
services industry; by making it easier for companies to raise money and
expand; and by encouraging consumers to spend their increased wealth.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
•
The strong housing market resulted in job creation in the construction
industry.
•
Rising house prices created a wealth effect that encouraged consumer
spending.
•
The U.S. dollar was rising relative to the Canadian dollar. This made it
easier for Canadian companies to export goods to the United States. It
also improved Canadian competitiveness in services, encouraging U.S.
companies to buy services in Canada and U.S. tourists to visit Canada
while discouraging Canadians from visiting the U.S. and from buying U.S.
goods and services.
| 12
Figure 9 compares the GTA employment-to-population ratio to the exchange rate.
The data suggest that a change in the exchange rate affects employment, although
there is a time lag between shifts in the exchange rate and changes in employment.
Some key dates in this chart are:
Dunning0112.indd Sec2:20
•
Beginning in 1986, and up to mid-1992, the U.S. dollar weakened relative
to the Canadian dollar. Employment in the GTA peaked in 1989 (three
years after the exchange rates began to change) and then dropped sharply.
The shift in exchange rates was certainly not the only negative factor
— double-digit interest rates and the implementation of the Canada-U.S.
Free Trade Agreement also hammered the GTA economy.
•
In late 1991, the exchange rate changed direction and the Canadian dollar
weakened relative to the U.S. dollar. In early 1994, employment in the GTA
began to recover. Low interest rates also contributed to the recovery.
•
Through the second half of the 1990s, the U.S. dollar continued to
strengthen relative to the Canadian dollar, which contributed to the increase in the GTA’s employment-to-population ratio.
•
Since 2001, the GTA’s employment-to-population ratio has not increased
in a sustained way. This economic slowdown is most likely due, initially,
to the bursting of the stock market bubble in late 2000.
•
At the end of 2002, the exchange rates changed direction. Since then, the
U.S. dollar has weakened relative to the Canadian dollar. As of 2005, signs
are emerging that employment in the GTA has been affected, particularly
in the goods-producing sector. While total employment is growing, the
rate of growth is slower than that of adult population and the employment rate has fallen.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 13
Figure 9: GTA Employment Ratio vs. Canada-U.S. Exchange Rate, 1987 to 2004
GTA Employment Ratio Versus Canada/US Exchange Rate
75
$1.80
Emp-ratio
70
$1.60
$ CDN
65
$1.40
60
$1.20
55
$1.00
1987
1990
1993
1996
1999
2002
2005
Source: StatsCan, Bank of Canada, Will Dunning Inc.
Taken together, these data suggest that the GTA’s economic expansion of the late
1990s was the product of an unusual combination of factors. It is unlikely that this
expansion trend can continue in the long term.
2.3
The Economic Basis of the Housing Market Peak and Decline after 2002
The rate of employment growth began to decline in 2001. After averaging 3.5 percent per year between December 1994 and December 2000, the rate slowed to 2.8
percent per year between December 2000 and December 2002 — slower, but still
a healthy rate. During the period December 2002 to December 2004, however, the
rate fell to 1.3 percent per year, or about 38,000 new jobs per year. Since the end
of 2002, employment growth has been slower than the estimated growth rate for
the adult population (2.2 percent per year). The employment-to-population ratio
has therefore fallen and the unemployment rate has increased.
Also, between 2002 and 2004, the level of housing affordability was relatively flat.
Improved affordability had contributed to housing demand during the second half of
the 1990s and this source of stimulus is now absent, although short-term variations
in interest rates prompt short-term changes in sales figures. However, the period of
large improvements in affordability and large increases in sales is over.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
2.4
| 14
Implications for Long-Term Housing Demand in the GTA
The housing market performance of the late 1990s and early 21st century was
driven by an unusual combination of positive economic factors that could not
be sustained indefinitely. The rapid rate of job creation in the GTA levelled off in
2002, ending the run-up in the employment rate. As a result, the housing market is
slowing down. Both the short-term and the long-term outlook are uncertain. The
recent experience of strong growth cannot be used to predict future growth.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
3
Economic Influences on Migration
and Population Growth
3.1
Overview of Economic Trends and Components of Population Growth
| 15
For Canada as a whole, the rate of population growth is determined mainly by
immigration. Within particular areas of Canada, population growth is determined
by migration, which includes immigration, as well as movement to and from other
parts of Canada: to and from other provinces (interprovincial migration) and
within a single province (intraprovincial migration).
People move for many reasons, but one of the most important is economic opportunity. The cost of living in an area may also be a factor. Thus, during economic
cycles in which economic opportunities vary and costs of living vary, we can expect
to see cycles in migration and rates of population growth across Canada.
The analysis in this chapter covers the 16 Census Divisions of the Greater Golden
Horseshoe. It uses data on components of population change that are generated
by Statistics Canada once a year. Although more frequent data collection would
allow for a more sophisticated analysis, even with only 18 data points between
1987 and 2004, it is possible to find strong relationships between economic conditions and migration.
In this analysis, it is assumed that economic opportunities are reflected in the
employment-to-population ratio (using data for the Toronto Census Metropolitan
Area). The cost of living is represented by the “real” average house price (using the
average price reported by the Toronto Real Estate Board, adjusted for inflation).
3.2
International Immigration
3.2.1
Immigration to Canada
Immigration to Canada has varied widely over the years, as is shown in Figure 10.
Likewise, immigration to the Inner Ring has also varied. Variations in annual immigration to Canada probably have less to do with economic conditions than with
political considerations and variations in administrative processing. Therefore, it
is highly unlikely that the number of immigrants to Canada or the Inner Ring
could be forecast using an economic model.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 16
Figure 10: Immigration to Canada and to the Inner Ring, 1987 to 2004
Immigration - Canada Versus Inner Ring
140,000
300,000
120,000
250,000
100,000
200,000
80,000
150,000
60,000
Inner Ring
40,000
100,000
Canada
50,000
20,000
0
0
1987
1990
1993
1996
1999
2002
The pattern of immigration to the Inner Ring tends to follow that of the Canadian
figures. The next section examines the share of immigrants who arrive in the Inner
Ring, and the relationship between that share and economic variables.
3.2.2
Inner Ring
Figure 11 shows the relationship between the Inner Ring’s share of Canada’s immigration and the Toronto CMA employment-to-population ratio.* There appears
to be a loose relationship between the two variables. In the early 1990s, when the
employment ratio in the GTA was falling, the Inner Ring’s share of immigrants
also fell slightly. As the GTA employment rate rose during the second half of
the 1990s, the immigrant share also rose. However, there was a large jump in
the Inner Ring share during 2001 and 2002, followed by a setback in 2003 and
2004. It is unclear whether that setback was the result of the softening economy
in the GTA, or a correction from an unusually high level in the previous years, or
a combination of the two.
It appears that the share of immigration is influenced by economic cycles to some
extent. The peak in the Inner Ring’s share of Canada’s immigration generally coincides with the peak in the economic cycle. Therefore, it is likely that the Inner
Ring’s share of immigration will be influenced by future economic conditions.
* In this section, the employment rate for the Toronto CMA is used, rather then the GTA rate, because
the GTA rate is not available for the entire period. A CMA, or Census Metropolitan Area, is a
definition used by Statistics Canada to describe metropolitan areas of over 100,000 persons.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 17
Figure 11: Inner Ring Share of Canada’s Immigration vs.
Employment-to-Population Ratio, 1987 to 2004
Inner Ring Share of Canada's Immigration Versus Emp-Pop Ratio
55.0%
74.0
Immigration as % of Canada
CMA Emp-Pop Ratio
50.0%
70.0
45.0%
66.0
40.0%
62.0
35.0%
58.0
30.0%
54.0
1987
1990
1993
1996
1999
2002
Figure 11 shows that in the early years of the period, the employment rate was
very high, while the Inner Ring’s share of immigration was low. Thus, other factors may influence the share. The average (inflation-adjusted) house price may
help explain trends in immigration. Figure 12 compares the Inner Ring’s share of
Canada’s immigration to the average house price in the GTA to determine whether
rising house prices reduce the share.
Figure 12: Inner Ring’s Share of Canada’s Immigration
vs. Average GTA House Prices, 1987 to 2004
Inner Ring Share of Canada's Immigration
Versus GTA House Price
55.0%
Immigration as % of Canada
Real House Price
50.0%
$320,000
45.0%
$280,000
40.0%
$240,000
35.0%
$200,000
$160,000
30.0%
1987
Dunning0112.indd Sec2:25
$360,000
1990
1993
1996
1999
2002
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 18
Although during the first part of the period, that seems to be the case, subsequently
the share has risen when house prices are rising. As we will see later, the improving
job market increased the Inner Ring’s share of immigration to Canada, while rising
house prices tended to reduce the Inner Ring’s share.
3.2.3
Outer Ring
The Outer Ring tends to receive a small share of Canada’s immigrants, and that
share appears to be falling, as shown in Figure 13. There is no obvious relationship between the Toronto CMA employment ratio and the Outer Ring’s share of
immigration. Similarly, there is no clear relationship between house prices and the
Outer Ring’s share of immigration.
However, the 10 Census Divisions of the Outer Ring are far from homogeneous.
Some may be more sensitive to economic conditions. Moreover, some may benefit
when the GTA is strong economically and others may suffer. Therefore, each of
the Census Divisions was analyzed individually. These analyses indicate that when
GTA house prices rise, the Outer Ring may receive a very small increase in its share
of immigration.
Figure 13: Outer Ring’s Share of Canada’s Immigration
vs. GTA House Prices, 1987 to 2004
Hinterlands Share of Canada's Immigration
Versus GTA House Price
6.0%
Immigration as % of Canada
Real House Price
5.0%
$350,000
$300,000
4.0%
$250,000
3.0%
2.0%
$200,000
1.0%
0.0%
$150,000
1987
3.2.4
1990
1993
1996
1999
2002
Greater Golden Horseshoe
There appears to be a positive relationship between the Toronto CMA employment
ratio and the share of Canada’s immigration received by the GGH as a whole, as
shown in Figure 14. The share rose as the economy strengthened during the late
1990s, and fell as the employment ratio weakened between 2002 and 2004. Also,
as the GTA average house price increased in real terms, the GGH’s share of immigration tended to fall.
Dunning0112.indd Sec2:26
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 19
Figure 14: GGH Share of Canada’s Immigration vs.
Employment-to-Population Ratio, 1987 to 2004
Share of Canada's Immigration Versus Emp-Pop Ratio - 16 CDs
60.0%
Immigration as % of Canada
CMA Emp-Pop Ratio
55.0%
68.0
50.0%
66.0
45.0%
64.0
40.0%
62.0
35.0%
60.0
30.0%
58.0
1987
3.3
70.0
1990
1993
1996
1999
2002
Emigration
Data on emigration for the Census Divisions are available on a consistent basis
only from 1997 to 2004, which precludes a meaningful statistical analysis. Later
in this report, it is assumed that emigration, as a share of each area’s population,
is at the same rate as the average for the 1997–2004 period.
3.4
Interprovincial Migration
3.4.1
Inner Ring
Figure 15 shows net interprovincial migration for the Inner Ring (net migration
is equal to in-movements minus out-movements). There appears to be a strong
relationship between net interprovincial migration and the Toronto CMA’s employment ratio.
At the end of the 1980s, a plummeting employment ratio was mirrored by plummeting net interprovincial migration. Indeed, between 1990 and 1994, more
people left the area than arrived. The economic recovery during the second half
of the 1990s improved net interprovincial migration. Since 2000, it has dropped
again, and in 2004, more people left than arrived.
Dunning0112.indd Sec2:27
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 20
Figure 15: Inner Ring Interprovincial Net Migration vs.
Employment-to-Population Ratio, 1987 to 2004
Inner Ring Interprovincial Net Migration Versus Emp-Pop Ratio
30,000
72.0
Interprovincial - Net
25,000
70.0
CMA Emp-Pop Ratio
20,000
68.0
15,000
66.0
10,000
64.0
5,000
62.0
60.0
0
-5,000 1987
1990
1993
1996
1999
2002
58.0
-10,000
56.0
-15,000
54.0
The rapid deterioration in interprovincial migration between 2002 and 2004 occurred at a time when the employment-to-population ratio did not change very
much. Similarly, during the late 1980s, net interprovincial migration fell before the
employment rate did. Figure 16 indicates that rapid increases in GTA house prices
may have contributed to the fall in interprovincial migration in both the late 1980s
and more recently, and that falling prices may have contributed to a recovery of
interprovincial migration during the early to mid 1990s.
Figure 16: Inner Ring Interprovincial Net Migration vs. GTA House Prices, 1987 to 2004
Inner Ring Interprovincial Net Migration Versus GTA House Price
30,000
$350,000
Interprovincial - Net
25,000
Real House Price
20,000
$300,000
15,000
10,000
$250,000
5,000
0
-5,000 1987
1990
1993
1996
1999
2002
$200,000
-10,000
-15,000
Dunning0112.indd Sec2:28
$150,000
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 21
Interprovincial migration varies widely over time, and average figures can be
misleading. Thus, while net interprovincial migration to the Inner Ring averaged
about +2,500 people per year from 1991 to 2001, this period included several
years of strong economic growth and strong migration (averaging +9,600 people
per year between 1998 and 2001) and several years of weak economic conditions and negative migration (averaging –5,500 people per year between 1991 and
1994. Future interprovincial migration will depend upon economic conditions.
3.4.2
Outer Ring
Figure 17 shows that interprovincial net migration for the Outer Ring tends to
be positively related to the economic cycle in the Toronto Area. In other words,
economic strength in the GTA encourages people to move from other provinces to
the GTA and to surrounding areas.
Figure 17: Outer Ring Interprovincial Net Migration vs.
Employment-to-Population Ratio, 1987 to 2004
Outer Ring Interprovincial Net Migration Versus Emp-Pop Ratio
8,000
70.0
Interprovincial - Net
CMA Emp-Pop Ratio
6,000
68.0
4,000
66.0
2,000
64.0
0
62.0
1987
1990
1993
1996
1999
2002
-2,000
60.0
-4,000
58.0
Similarly, net interprovincial net migration is negatively related to GTA house
prices, as shown in Figure 18.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 22
Figure 18: Outer Ring Interprovincial Net Migration vs. GTA House Prices, 1987 to 2004
Outer Ring Interprovincial Net Migration Versus GTA House Price
$350,000
8,000
Interprovincial - Net
6,000
Real House Price
$300,000
4,000
$250,000
2,000
0
1987
1990
1993
1996
1999
2002
$200,000
-2,000
$150,000
-4,000
3.4.3
Greater Golden Horseshoe
Combining the data on interprovincial migration for all 16 Census Divisions of
the Greater Golden Horseshoe, it is seen once again that the Toronto CMA employment ratio is positively related to net migration and that GTA house prices are
negatively related to migration (see Figures 19 and 20).
Figure 19: Interprovincial Net Migration vs. Employment-to-Population Ratio,
Greater Golden Horseshoe, 1987 to 2004
Interprovincial Net Migration Versus Emp-Pop Ratio - 16 CDs
40,000
70.0
Interprovincial - Net
CMA Emp-Pop Ratio
30,000
68.0
20,000
66.0
10,000
64.0
62.0
0
1987
Dunning0112.indd Sec2:30
1990
1993
1996
1999
2002
-10,000
60.0
-20,000
58.0
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 23
Figure 20: Interprovincial Net Migration vs. GTA House Prices,
Greater Golden Horseshoe, 1987 to 2004
Interprovincial Net Migration Versus GTA House Price - 16 CDS
40,000
$350,000
Interprovincial - Net
Real House Price
30,000
$300,000
20,000
10,000
$250,000
0
1987
1990
1993
1996
1999
2002
$200,000
-10,000
-20,000
3.5
$150,000
Intraprovincial Migration
3.5.1
Inner Ring
The Inner Ring tends to lose population to other parts of Ontario. Figure 21
shows that net intraprovincial migration has been negative for the past 17 years.
Figure 21: Inner Ring Intraprovincial Net Migration vs.
Employment-to-Population Ratio, 1987 to 2004
Inner Ring Intraprovincial Net Migration Versus Emp-Pop Ratio
0
70.0
1987
1993
1996
1999
2002
-10,000
68.0
-20,000
66.0
-30,000
64.0
-40,000
62.0
-50,000
-60,000
Dunning0112.indd Sec2:31
1990
Intraprovincial - Net
CMA Emp-Pop Ratio
60.0
58.0
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 24
There is no clear relationship between the Toronto CMA employment rate and net
intraprovincial migration. In fact, at first glance it appears that the relationship
may be negative — the opposite of what might be expected:
•
During the late 1980s, while the employment rate was high, migration fell
sharply.
•
As the employment rate fell during the early 1990s, net intraprovincial
migration began to recover.
•
As the employment rate expanded during the second half of the 1990s,
migration did not improve further. In fact, intraprovincial net migration
may have started to fall in 1999, before the peak of the economic cycle.
The last available data point for the intraprovincial data is for July 2003. It is not
possible to review the relationship in the current economic environment.
Figure 22 shows net intraprovincial migration for the Inner Ring relative to house
prices. It appears that out-migration during the late 1980s may have been due to
rapid increases in house prices, the recovery of migration in the early 1990s to
price reductions, and the muted migration figures in the late 1990s to the resumption of price increases. As will be discussed later, when the employment rate and
house prices are analyzed in combination, employment has the expected positive
effect on net intraprovincial migration to the Inner Ring, although the effect is
weak. House prices have a strong negative effect on this component of population
growth for the Inner Ring.
Figure 22: Inner Ring Intraprovincial Net Migration vs. GTA House Prices, 1987 to 2004
Inner Ring Intraprovincial Net Migration Versus GTA House Prices
$350,000
0
1987
1990
1993
1996
1999
2002
-10,000
$300,000
-20,000
-30,000
Intraprovincial - Net
Real House Price
$250,000
-40,000
$200,000
-50,000
-60,000
Dunning0112.indd Sec2:32
$150,000
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
3.5.2
| 25
Outer Ring
Figure 23 shows a strong positive relationship between the Toronto CMA employment rate and intraprovincial migration. However, in 2001 there is a sharp
downward shift in the migration data. The cause of this shift is not clear.
Figure 23: Outer Ring Intraprovincial Net Migration vs.
Employment-to-Population Ratio, 1987 to 2004
Outer Ring Intraprovincial Net Migration Versus Emp-Pop Ratio
35,000
72.0
Intraprovincial - Net
30,000
70.0
CMA Emp-Pop Ratio
25,000
68.0
20,000
66.0
15,000
64.0
10,000
62.0
5,000
60.0
0
58.0
1987
1990
1993
1996
1999
2002
Figure 24 indicates a positive relationship between GTA house prices and net intraprovincial migration for the Outer Ring. As house prices rise in the GTA, the
Outer Ring gains population from intraprovincial migration.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 26
Figure 24: Outer Ring Intraprovincial Net Migration vs. GTA House Prices, 1987 to 2004
Outer Ring Intraprovincial Net Migration Versus GTA House Price
$350,000
35,000
Intraprovincial - Net
30,000
Real House Price
25,000
20,000
$300,000
$250,000
15,000
10,000
$200,000
5,000
0
$150,000
1987
3.6
1990
1993
1996
1999
2002
Simulations
Statistical analysis has been used to interpret the data for the three main components of migration (immigration, net interprovincial migration, and net intraprovincial migration). In this section, results from the statistical analysis are used to
simulate migration trends in the future, based on economic assumptions. These
simulations of the components of migration are used later in this report to project
population for the 16 Census Divisions of the Greater Golden Horseshoe.
Simulations were performed for each of the Census Divisions of the Greater
Golden Horseshoe, as well as for three aggregated areas (the Inner Ring, the Outer
Ring, and the GGH as a whole). In this section, only the results for the three
aggregated areas are discussed. Summaries of the simulations for each of the 16
Census Divisions are provided in Appendix A.1.
Table 1 shows the estimated sensitivities for the components to changes in the two
economic variables. The analysis indicates that:
•
Dunning0112.indd Sec2:34
A one-percentage-point increase in the Toronto CMA employment-topopulation ratio is estimated to result in increases in all three components of migration, for all three geographic areas, with one exception
— net intraprovincial migration for the Outer Ring has a weak negative
relationship to the employment ratio. This negative relationship, while
somewhat unexpected, reflects the fact that stronger employment in the
Toronto CMA could, depending on its nature, result in either more or less
movement to the Outer Ring from elsewhere in Ontario.
1/12/06 9:46:30 AM
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
•
A $10,000 increase in the real (that is, inflation-adjusted) GTA house price
is estimated to result in reduced in-migration for all three components of
migration for the Inner Ring and for the Greater Golden Horseshoe. This
is expected.
•
For the Outer Ring, rising house prices in the GTA are estimated to result
in increased immigration and net intraprovincial migration. This result
is expected, as it would reflect economic rationing in the GTA. However,
the estimates indicate that a GTA house price increase results in reduced
net interprovincial migration. This result is not expected. It may be that
when house prices increase in the GTA, prices also tend to increase in the
Outer Ring, which deters people from moving there from other provinces.
Alternatively, rising house prices in the GTA may lead people in other
provinces to assume that prices are rising elsewhere in Ontario, which
would generally discourage non-Ontarians from moving to the Outer
Ring.
| 27
Table 1: Estimated Sensitivities of Migration Components to Two Economic Factors
Inner Ring
(%)
Outer Ring
(%)
GGH
(%)
0.0313
0.1097
0.1410
–0.0800
0.0047
–0.0754
Immigration (% Share of Immigration to Canada)
Impact of 1% Increase in Toronto CMA Employment Ratio
Impact of $10,000 Increase in GTA Real House Price
Net Interprovincial Migration (as a % of Canada’s Population Excluding Ontario)
Impact of 1% Increase in Toronto CMA Employment Ratio
Impact of $10,000 Increase in GTA Real House Price
0.0169
0.0054
0.0223
–0.0206
–0.0055
–0.0261
0.0084
–0.0001
0.0083
–0.0512
0.0195
–0.0317
Net Intraprovincial Migration (as % of Ontario Population)
Impact of 1% Increase in Toronto CMA Employment Ratio
Impact of $10,000 Increase in GTA Real House Price
Source: Will Dunning Inc.
The results from this analysis were used to simulate how migration rates might be
affected by future trends in economic variables.
First, it is necessary to develop assumptions for the employment-to-population
ratio and real house prices. The employment ratio peaked in 2001, and it appears
to have fallen slightly during the past three years. During the last economic cycle
(which began with a peak in 1989 and ended with another peak in 2001), the
average employment rate in the Toronto CMA was 63.3 percent. In the analysis
that follows, it is assumed that at present the long-term average employment rate
is 63.3 percent, a reduction from the rate of 64.4 percent seen over the last 12
months (ending in October 2005). The 63.3 percent rate is assumed to hold over
the 2001 to 2011 period.
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In addition, demographic change may affect the employment rate over time. The
baby boomers are moving into middle age and retirement, and this change may
affect the percentage of the population that chooses to work (or is able to work).
This relationship can be investigated by combining detailed data on employmentto-population ratios by age group with data on the expected age structure of the
future population. Table 2 displays this analysis, using data on the GTA employment-to-population ratio from the 2001 census and combining it with projections of population by age group for the GTA from Hemson Consulting’s Growth
Outlook for the Greater Golden Horseshoe.
This analysis suggests that changes in the age structure of the population could
cause the employment-to-population ratio in the GTA to fall by 5.75 percentage points between 2001 and 2031. Since the analysis holds employment rates
constant for each age group, this change would be entirely due to demographic
change; the effects of economic cycles are ignored in this simulation.
Table 2: Estimation of Potential Impacts of Population Change on the Employment-to-Population Ratio in the GTA
Age Group
Hemson Population
Projections – GTA
2001
Emp-Pop Ratio,
2001 Census,
2031
GTA (%)
Implied
Employment in…
2001
2031
15-19
347,200
438,700
41.53
144,190
182,189
20-24
358,700
498,100
69.00
247,488
343,668
25-29
392,700
585,800
80.43
315,835
471,139
30-34
441,900
597,200
80.76
356,895
482,321
35-39
492,400
614,500
81.99
403,719
503,829
40-44
456,100
579,900
82.62
376,816
479,095
45-49
391,700
543,400
82.86
324,563
450,261
50-54
347,100
486,400
79.26
275,111
385,520
55-59
253,100
436,500
67.96
171,998
296,630
60-64
202,400
422,200
45.68
92,453
192,854
65+
585,100
1,450,300
9.76
57,130
141,610
4,268,400
6,653,000
2,766,197
3,929,116
64.81%
59.06%
Total
Total
Employment-toPopulation Ratio
Sources: Statistics Canada, Hemson Consulting Ltd, calculations by Will Dunning Inc.
Admittedly, it is likely that the age-specific employment rates will vary over time.
In the analysis that follows, an optimistic assumption is made: that demographic
change will cause the employment-to-population ratio to fall by one percentage
point in the 2011-to-2021 period and again in the 2021-to-2031 period — this is
only about one-half of the reduction indicated by this analysis of the 2001 census
data.
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| 29
The following assumptions were used in these simulations of migration rates:
•
The Toronto CMA employment-to-population ratio averages 63.3 percent during 2001 to 2011. This is the average rate over the last business
cycle.
•
For both 2011 to 2021 and 2021 to 2031, the average employment rate
is assumed to fall by one percentage point (to 62.3 percent between 2011
and 2021 and to 61.3 percent between 2021 and 2031). These reductions
are the consequence of the aging population.
•
For real house prices, it is assumed that between 2001 and 2011, the
average real house price is 5 percent higher than the 2001 figure ($221,833
versus the 2001 figure of $211,270; all figures are expressed in 1992
dollars). This assumed average figure for the 2001–2011 decade is lower
than the figure for 2004 ($243,611), and slightly lower than the average
for the past four years ($227,938). This assumption implies that prices
will fall in real terms during the next few years (in other words, that
actual prices would increase less rapidly than overall inflation).
•
For the subsequent two decades (2011 to 2021 and 2021 to 2031), the
average real house price is assumed to be unchanged, at $221,833. While
it is assumed that house prices will be unchanged in real terms, during
1980 to 2004 the average real rate of increase was 2.2 percent per year.
•
If house prices were assumed to increase in real terms, the consequence
would be even greater negative impacts on migration than is shown
below.
The simulation results are shown in Table 3 and discussed in detail below. The
table also shows the actual results for 2001 in comparison to the simulated results
for the same year.
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Table 3: Simulated Migration Rates, Based on Two Economic Factors
Inner Ring (%)
Outer Ring (%)
GGH (%)
2.97
51.38
Immigration (% Share of Immigration to Canada)
2001 Actual
48.41
2001 Simulated
44.44
3.50
47.95
3.96
–0.53
3.43
2011
42.16
3.53
45.69
2021
42.12
3.42
45.55
2031
42.09
3.31
45.40
Error in 2001
Net Interprovincial Migration (as a % of Canada’s Population Excluding Ontario)
2001 Actual
2001 Simulated
0.0464
0.0095
0.0559
0.0475
0.0126
0.0601
Error in 2001
–0.0010
–0.0032
–0.0042
2011
–0.0040
–0.0037
–0.0077
2021
–0.0209
–0.0091
–0.0300
2031
–0.0377
–0.0145
–0.0522
Net Intraprovincial Migration (as % of Ontario Population)
2001 Actual
–0.1126
0.1080
–0.0045
2001 Simulated
–0.1553
0.1520
–0.0033
Error in 2001
0.0427
–0.0440
–0.0012
2011
–0.2168
0.1655
–0.0514
2021
–0.2252
0.1656
–0.0597
2031
–0.2337
0.1657
–0.0680
Source: Will Dunning Inc.
Implications for immigration:
Dunning0112.indd Sec2:38
•
In 2001 the shares of immigration for the Inner Ring and the GGH were
somewhat higher than the simulated rate. In 2001 and 2002, the Inner
Ring and Greater Golden Horseshoe shares of immigration were elevated.
For the years on either side, the actual and simulated results are closer together. It is unclear at this point whether the 2001 and 2002 results were
temporary aberrations or represent permanent shifts in the relationships.
•
Based on the relationships estimated using 18 years of data, it appears that
the Inner Ring and the Greater Golden Horseshoe will experience gradual
erosion in their shares of Canada’s immigration. During the 2001-to-2031
period, the Inner Ring share would be similar to the rate seen in the mid1990s.
•
These projected rates can be used to project actual numbers of immigrants. The 2005 Hemson report Growth Outlook for the Greater Golden
Horseshoe (page 20) assumed that immigration to Canada will average
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| 31
218,000 people per year from 2001 to 2006, and just under 210,000 for
the remainder of the projection period. Using this assumption, and applying the projected shares shown above, it is possible to calculate anticipated
average annual immigration figures for the Inner Ring, Outer Ring, and
Greater Golden Horseshoe, as shown in Table 4. For the Inner Ring, immigration is projected to total almost 2.7 million over the 30-year period,
or slightly less than 90,000 people per year.
Implications for emigration:
•
The rates of emigration (as percentages of the populations of each area) are
assumed to remain at the 1997–2004 level. As the population increases,
therefore, the number of emigrants will also rise. For the entire 30-year
period, about 550,000 people are expected to leave the GGH for other
countries, an average of about 18,000 people per year.
Implications for net immigration (immigration minus emigration):
•
The total contribution to population growth in the Greater Golden
Horseshoe over the 30-year period would be about 2.33 million. Annual
net contributions from immigration would fall over time, as immigration
falls (slightly) and emigration increases. From 2001 to 2011, the contribution would be about 80,700 people per year; between 2021 and 2031 it
would be about 75,300 people per year.
Implications for net interprovincial migration:
Dunning0112.indd Sec2:39
•
The simulated migration rates for 2001 were close to the actual rates for
both the Inner Ring and the GGH, but less close for the Outer Ring.
•
The actual data indicate that net interprovincial migration has deteriorated with the economic slowdown in the GTA. In the Inner Ring,
net interprovincial migration has fallen from a peak of about 10,100 in
1999–2000 to less than zero (about –3,200) in 2003–2004. For the GGH,
the numbers have fallen from a peak of +13,100 in 1999–2000 to –4,400
in 2003–2004. Based on the assumption of a normal economic performance (on average) in the years up to 2031, the projections indicate that
central Ontario could lose population to other provinces.
•
In Table 4, the projected rates for net interprovincial migration are applied
to the projected population of the rest of Canada, to determine migration
for the period up to 2031. The results indicate that from 2001 to 2031,
the Greater Golden Horseshoe would lose about 187,000 people to other
provinces. The average annual rate of out-migration would be low from
2001 to 2011 (averaging –1,500 people per year) and would increase to
about –11,100 people per year from 2021 to 2031.
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| 32
Implications for net intraprovincial migration:
•
The Inner Ring simulation for 2001 overestimates net out-migration by
about 40 percent, although the simulations for both 2000 and 2002 are
more accurate. Similarly, for the Outer Ring, the simulation for 2001 is
about 40 percent above the actual amount. For the GGH as a whole,
where net out-migration was low, the simulation was quite close to the
actual amount.
•
Net intraprovincial migration for the GGH began to deteriorate in 1999,
before the economic slowdown, apparently as the consequence of rising
real house prices. Unfortunately, the last available data point is for July
2003, which precludes an evaluation of the consequences of the developing economic downturn and the continued real increases in house prices.
•
The analysis of the available data suggests increasing migration out of the
Inner Ring and into the Outer Ring. Over the 30-year period, the Inner
Ring would experience net intraprovincial out-migration of 922,000, or
about 31,000 people per year; in the Outer Ring, intraprovincial in-migration would total 930,000, or 31,000 people per year. For the entire
GGH, net intraprovincial migration would be close to nil — a total of
about 8,000 over the 30 years.
Combining these components, it is possible to project total net migration:
Dunning0112.indd Sec2:40
•
Total net migration is projected to add 2.15 million people to the population of the GGH during the coming 30 years, or an average of about
71,700 people per year. The contribution of net migration would fall over
time, from just over 80,000 people per year from 2001 to 2011, to about
63,500 people per year from 2021 to 2031.
•
About 55 percent of the total net migration would be to the Inner Ring
(about 1.17 million people); 45 percent (977,000 people) would go to the
Outer Ring.
•
In the Inner Ring, net migration would fall sharply during the 30-year
period, from an average of 48,800 people per year between 2001 and
2011 to an average of 30,000 people per year between 2021 and 2031.
On the other hand, for the Outer Ring, net migration would increase
slightly over time, from about 31,300 people per year between 2001 and
2011 to 33,600 people per year between 2021 and 2031.
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| 33
Table 4: Projections of Components of Migration, Annual Averages
by 10-Year Period and Total Migration, 2001 to 2031
Inner Ring
Outer Ring
GGH
2001–2011
89,775
7,521
97,296
2011–2021
88,445
7,185
95,629
Immigration
2021–2031
88,379
6,954
95,333
2,665,989
216,596
2,882,585
2001–2011
–13,291
–3,277
–16,568
2011–2021
–14,728
–3,792
–18,520
2021–2031
–15,750
–4,253
–20,003
–437,688
–113,216
–550,905
2001–2011
–785
–718
–1,503
2011–2021
–4,289
–1,870
–6,158
2021–2031
–8,001
–3,082
–11,082
–130,741
–56,693
–187,434
2001–2011
–26,866
27,813
947
2011–2021
–30,798
31,326
528
Total Over 30 Years
Emigration
Total Over 30 Years
Net Interprovincial Migration
Total Over 30 Years
Net Intraprovincial Migration
2021–2031
–34,607
33,939
–668
–922,717
930,790
8,073
2001–2011
48,833
31,340
80,173
2011–2021
38,629
32,849
71,479
2021–2031
30,022
33,559
63,580
1,174,842
977,476
Total Over 30 Years
Total Net Migration
Total Over 30 Years
2,152,318
Source: Will Dunning Inc.
3.7
Conclusions
This section of the report has developed projections of migration for the 16 Census
Divisions of the Greater Golden Horseshoe using an analysis model that relates
the components of migration to two economic variables that are expected to have
considerable influence on individual choices: employment opportunities and house
prices.
The economic assumptions used in this research are based on historic experience.
Under these assumptions, economic opportunities (measured by the employmentto-population ratio) in the study area will be less attractive than they were during
the late 1990s and early 2000s, but comparable to the average seen over the last
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| 34
business cycle. House prices are assumed to be relatively stable, albeit at a level
that has been boosted by a recent strong market cycle. The assumed average real
price is about 10 percent higher than the average seen during the second half of
the 1990s.
Both of these economic assumptions are expected to have negative consequences
for migration tendencies in the future as compared to the second half of the
1990s.
The projections are sensitive to these assumptions:
•
If it is assumed that over the entire projection period (2001–2031) the
employment rate will be higher than it was during the past business cycle,
then projected migration would be higher.
•
If it is assumed that house prices will be lower (in inflation-adjusted dollars), then the projections of migration would also increase.
•
On the other hand, if house prices increase beyond the level that is assumed here, then migration would be less than expected.
The projections developed here have limitations, largely because of the small
amount of data that is available, which limits the complexity of the analysis.
Therefore, the projections are not definitive, either in terms of the outcomes or
in terms of the specifics of the analysis. However, this analysis suggests that projections of migration and population growth should take account of economic
influences.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
4
Economic Influences on Dwelling Type Mix
4.1
Existing Stock of Occupied Housing (Census Data)
| 35
Census data provide a baseline perspective on dwelling types, although since the
census data show the total stock, they do not necessarily indicate the choices being made today or in the future — they represent the consequences of choices
made over many decades.* As shown in Table 5, the existing stock of occupied
housing in the GGH is slightly more than one-half (53.7 percent) in the form of
single-detached houses, about 30 percent in apartments, and about 15 percent in
semi-detached and row houses (townhouses) combined.
Table 5: Distribution of Dwellings in the Greater Golden Horseshoe, by Structural Type, 2001
Inner Ring
(%)
Outer Ring
(%)
GGH
(%)
Single-detached house
47.5
70.1
53.7
Semi-detached house
8.1
4.7
7.2
Row house
8.0
5.8
7.4
Apartment, detached duplex
2.0
2.3
2.1
25.4
6.1
20.1
8.7
10.3
9.1
Dwelling Type
Apartment, building that has five or more storeys
Apartment, building that has fewer than five storeys
Other single-attached house
0.2
0.4
0.3
Movable dwelling
0.1
0.4
0.1
Source: Statistics Canada, 2001 Census Profiles; calculations by Will Dunning Inc.
4.2
Housing Starts Data for the GTA
Housing market activity is cyclical. Within that cycle of activity there is also a
cycle in terms of the mix of housing by dwelling types. This section explores the
variation in the mix of housing starts by dwelling type over the past 18 years in
the GTA.
Table 6 shows annual housing starts by type from 1987 to 2004 and averages for
four sub-periods:
•
•
•
•
the “boom” years of 1987 to 1989;
the recessionary period of 1990 to 1995;
the beginning of the recovery during 1996 to 1998;
the strong market period of 1999 to 2004.
* In theory it is possible to compare census data for 1996 and 2001 to estimate the growth of the
housing stock by dwelling type. However, in the census data there appear to be large losses in two
dwelling types – apartments in detached duplexes and apartments in buildings with less than five
storeys – and it appears that the data may have been collected inconsistently in the two censuses.
Therefore, this comparative approach has not been used.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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Table 6: Housing Starts by Dwelling Type in the GTA, 1987 to 2004 (in units)
Year
Single Detached
Semi-Detached
Row/Town
House
Apartment
Total
1987
31,005
832
3,079
16,675
51,591
1988
22,817
459
3,092
17,373
43,741
1989
19,538
208
2,732
16,988
39,466
1990
8,518
236
2,396
10,081
21,231
1991
10,731
249
3,627
7,146
21,753
1992
9,814
954
3,114
9,417
23,299
1993
8,998
924
2,577
5,001
17,500
1994
11,962
1,467
3,227
3,723
20,379
1995
7,878
914
3,686
5,386
17,864
1996
11,408
1,664
4,727
3,286
21,085
1997
16,433
2,811
6,177
3,427
28,848
1998
14,220
3,388
6,316
4,939
28,863
1999
17,584
5,091
6,354
9,512
38,541
2000
19,474
5,760
6,958
10,369
42,561
2001
19,147
5,766
5,806
13,901
44,620
2002
25,319
5,358
7,235
10,375
48,287
2003
22,772
5,024
6,867
15,545
50,208
2004
21,593
3,668
6,744
14,367
46,372
1987–1989
24,453
500
2,968
17,012
44,933
1990–1995
9,650
791
3,105
6,792
20,338
1996–1998
14,020
2,621
5,740
3,884
26,265
1999–2004
20,982
5,111
6,661
12,345
45,098
Entire Period
16,623
2,487
4,706
9,862
33,678
Averages
Source: Canada Mortgage and Housing Corporation
Table 7 shows the percentage shares of housing starts by year and for the subperiods. The data indicate that over the entire period, single detached houses have
accounted for just under half (49.4 percent) of housing starts in the GTA; semidetached houses have accounted for less than one-tenth of starts (7.4 percent); 14.0
percent of starts have been townhouses, and 29.3 percent have been apartments.
The shares have varied during the period.
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Table 7: Housing Starts by Dwelling Type in the GTA, 1987 to 2004 (percentages)
% Shares by Dwelling Type
Year
Single Detached
(%)
Semi-Detached
(%)
Row/Town
House (%)
Apartment
(%)
Total Units
1987
60.1
1.6
6.0
32.3
51,591
1988
52.2
1.0
7.1
39.7
43,741
1989
49.5
0.5
6.9
43.0
39,466
1990
40.1
1.1
11.3
47.5
21,231
1991
49.3
1.1
16.7
32.9
21,753
1992
42.1
4.1
13.4
40.4
23,299
1993
51.4
5.3
14.7
28.6
17,500
1994
58.7
7.2
15.8
18.3
20,379
1995
44.1
5.1
20.6
30.2
17,864
1996
54.1
7.9
22.4
15.6
21,085
1997
57.0
9.7
21.4
11.9
28,848
1998
49.3
11.7
21.9
17.1
28,863
1999
45.6
13.2
16.5
24.7
38,541
2000
45.8
13.5
16.3
24.4
42,561
2001
42.9
12.9
13.0
31.2
44,620
2002
52.4
11.1
15.0
21.5
48,287
2003
45.4
10.0
13.7
31.0
50,208
2004
46.6
7.9
14.5
31.0
46,372
1987–1989
54.4
1.1
6.6
37.9
44,933
1990–1995
47.4
3.9
15.3
33.4
20,338
1996–1998
53.4
10.0
21.9
14.8
26,265
1999–2004
46.5
11.3
14.8
27.4
45,098
Entire Period
49.4
7.4
14.0
29.3
33,678
Averages
Source: Canada Mortgage and Housing Corporation; calculations by Will Dunning Inc.
During about half of this 18-year period, assisted rental housing development contributed many units. Since the mix of dwelling types constructed under the assisted
housing programs may not reflect the housing type preferences of the population,
Table 8 shows the shares of housing by type, excluding assisted housing units.
If assisted housing units are excluded, over the last 18 years, single detached
houses have accounted for just over half (52.6 percent) of housing starts in the
GTA; apartments for slightly over one-quarter; semi-detached houses less than
one-tenth (7.9 percent), and row housing units slightly more than one-tenth (13.9
percent). The shares have shifted over time.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
Dunning0112.indd Sec2:46
•
The share of apartments has been higher in the strong market periods
(1987–1989 and 1999–2004) and lower in weaker markets (1990–1995
and 1996–1998).
•
The share for single detached houses has fallen over the past decade and a
half. During the recent strong housing market, singles have accounted for
less than one-half of starts.
•
Semi-detached houses were a small minority of starts until 1992, when
the share began to increase. It peaked in 2000 and has since declined.
That declining share coincides with increased apartment activity.
•
Similarly, the share for row housing units was higher in the second half of
the 1990s than in the first half. In recent years, row houses have lost share
as apartment activity has expanded.
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| 39
Table 8: Housing Starts by Dwelling Type in the GTA, Excluding Assisted Housing, 1987 to 2004 (percentages)
% Shares by Dwelling Type
Year
Single Detached
(%)
Semi-Detached
(%)
Row/Town
House (%)
Apartment
(%)
Total Unassisted
Units
1987
63.5
1.7
5.0
29.8
48,796
1988
55.3
1.1
6.9
36.6
41,228
1989
53.8
0.6
5.9
39.7
36,318
1990
45.4
1.3
11.2
42.1
18,757
1991
70.0
1.6
13.0
15.3
15,322
1992
71.5
7.0
12.1
9.5
13,724
1993
68.8
7.1
15.8
8.3
13,079
1994
67.3
8.3
16.7
7.8
17,771
1995
49.6
5.8
22.6
22.0
15,879
1996
56.2
8.2
23.2
12.4
20,303
1997
57.0
9.7
21.4
11.9
28,848
1998
49.3
11.7
21.9
17.1
28,863
1999
45.6
13.2
16.5
24.7
38,541
2000
45.8
13.5
16.3
24.4
42,561
2001
42.9
12.9
13.0
31.2
44,620
2002
52.6
11.1
15.0
21.2
48,119
2003
45.4
10.0
13.7
30.9
50,176
2004
46.8
8.0
14.6
30.6
46,124
1987–1989
58.1
1.2
5.9
34.9
42,114
1990–1995
61.3
5.0
15.2
18.5
15,755
1996–1998
53.9
10.1
22.0
14.0
26,005
1999–2004
46.6
11.4
14.8
27.3
45,024
Entire Period
52.6
7.9
13.9
25.7
31,613
Averages
Source: Canada Mortgage and Housing Corporation; calculations by Will Dunning Inc.
If all purpose-built rental units are excluded, and only homeowner units counted,
a similar pattern emerges:
Dunning0112.indd Sec2:47
•
The share for single detached houses has fallen, and is below 50 percent
in the most recent period.
•
The share of apartments has been highest during strong markets.
•
Semi-detached and row houses gained market share during the 18-year
period, but this trend has been reversed as apartments have gained market
share.
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| 40
Table 9: Housing Starts by Dwelling Type in the GTA, Including Only Units
Intended for Homeownership, 1987 to 2004 (percentages)
Shares by Dwelling Type
Year
Single Detached
(%)
Semi-Detached
(%)
Row/Town
House (%)
Apartment
(%)
Total Ownership
Units
1987
66.1
1.8
4.6
27.6
46,927
1988
59.5
1.2
7.3
32.0
38,316
1989
56.2
0.6
6.0
37.2
34,775
1990
51.9
1.4
9.8
36.9
16,414
1991
71.1
1.6
13.1
14.1
15,097
1992
74.7
7.3
12.6
5.5
13,135
1993
70.4
7.2
16.2
6.2
12,788
1994
67.5
8.3
16.7
7.5
17,714
1995
49.7
5.8
22.6
21.9
15,859
1996
56.6
8.3
23.2
11.9
20,148
1997
57.5
9.8
21.6
11.1
28,596
1998
49.6
11.8
22.0
16.7
28,684
1999
46.2
13.4
16.4
24.0
38,045
2000
46.2
13.7
16.2
24.0
42,158
2001
43.9
13.2
12.8
30.1
43,642
2002
54.2
11.5
14.8
19.6
46,756
2003
47.5
10.5
14.0
28.1
47,989
2004
48.0
8.2
14.8
29.0
44,969
1987–1989
61.1
1.2
5.9
31.8
40,006
1990–1995
63.6
5.2
15.2
15.9
15,168
1996–1998
54.3
10.2
22.1
13.4
25,809
1999–2004
47.8
11.6
14.8
25.8
43,927
Entire Period
54.2
8.1
13.9
23.7
30,667
Averages
Source: Canada Mortgage and Housing Corporation; calculations by Will Dunning Inc.
The data indicate that market shares by dwelling type vary during the housing
cycle, but do not show the mechanism that causes the variation. Figure 25 plots
the percentage of the GTA’s homeowner starts that are apartments against an
estimate of the median price (adjusted for inflation) for single detached houses
(using data from the Toronto Real Estate Board). During periods of high or rising
house prices, the share for apartments tends to rise. In the late 1980s, a high price
for single houses was associated with a high share for apartments. As the price of
single houses fell during the first half of the 1990s, the share for apartments was
lower. Since the mid 1990s, a rising price for singles has once again been associated with a rising market share for apartments.
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Figure 25: GTA Homeowner Apartment Starts vs. GTA Single House Prices, 1988 to 2004
% of GTA Home Owner Starts that are Apartments, Versus The
Median "Real" Single Detached Price
$350,000
40.0%
% Apartrment
30.0%
$300,000
Real Median
20.0%
$250,000
10.0%
$200,000
$150,000
0.0%
1988
1991
1994
1997
2000
2003
Source: CMHC, TREB, W ill Dunning Inc.
As house prices rise, more consumers choose to buy lower-cost apartments rather
than expensive single detached houses. However, this is not the entire story. The
share of apartments has been boosted by low interest rates, which have allowed
thousands of renters to move from rental apartments to condominium apartments.
There is also an investment component in the condominium market, which is
unlikely to be affected by the price of single detached houses. Many new condominium apartments are purchased by investors who offer them for rent. These
apartments are leased on month-to-month or annual leases, similar to conventional rentals; some are available as furnished, short-term accommodation, and
have more in common with hotels than with conventional rentals. For investment
buying, the motivation is the expected return on investment. That return has two
parts – the cash flow generated by the rents (minus costs) and capital gains (due to
rising property values).
Although there is no precise data on the extent of investment activity in the new
condominium market, informed observers believe that at present at least 25
percent of new condominium apartments are purchased by investors. The investor
share varies over time and by location. There is undoubtedly a cyclical element to
this investment activity, since investment vehicles come into and fall out of favour.
Investment in condominiums was in favour during 2004 and 2005, but recent
high levels of investment could be followed by a downturn precipitated by rising
vacancies and weaker rents. This would contribute to a downturn in the sales cycle
for condominium apartments.
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| 42
As shown in Figure 26, the share for singles has a weaker relationship to prices.
During the early 1990s, the share rose as prices fell. But, from 1995 to 1997, the
share fell, despite the reduced prices. Over the past seven years, as prices have increased in real terms, the share for singles has been below 50 percent in all but one
year. During the first half of the 1990s, the share for singles exceeded 60 percent
for four years and 70 percent for three years. This was during a period when the
apartment market was suffering from the over-building of the 1980s, and when
total housing starts were quite low. Actual starts of singles averaged only 10,376
units per year during those four years, well below the 18-year average of 16,623
units per year.
Figure 26: Percentage of GTA Single-Detached Homeowner Starts
vs. Real Median Single Detached House Prices, 1988 to 2004
% of GTA Home Owner Starts that are Single-Detached, Versus
The Median "Real" Single Detached Price
$350,000
80.0%
% Single
Real Median
70.0%
$300,000
60.0%
$250,000
50.0%
$200,000
40.0%
$150,000
1988
1991
1994
1997
2000
2003
Source: CMHC, TREB, W ill Dunning Inc.
The loss of share by singles in the mid 1990s is also due to the increasing share for
semi-detached and row units. Figure 27 shows the combined share for these two
dwelling types, which increased from 1989 to 1998, but fell again as apartments
gained share.
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| 43
Figure 27: Percentage of GTA Homeowner Semi-Detached and Row Housing
Starts vs. Real Median Single Detached House Prices, 1988 to 2004
% of GTA Home Owner Starts that are Semis or Rows, Versus
The Median "Real" Single Detached Price
40.0%
$350,000
30.0%
$300,000
20.0%
$250,000
10.0%
% Semi + Row
Real Median
0.0%
1988
1991
1994
1997
2000
$200,000
$150,000
2003
Source: CMHC, TREB, W ill Dunning Inc.
4.3
Housing Starts Data for the Greater Golden Horseshoe
Canada Mortgage and Housing Corporation collects data on housing starts in
municipalities with 10,000 or more people. This survey captures most, but not all,
housing starts in the GGH. Table 10 shows the data, summarized for the Inner
Ring, Outer Ring, and GGH.
From 1999 to 2004, slightly more than half (53.7 percent) of housing starts in
the GGH were single detached houses, slightly more than one-fifth (22.1 percent)
were apartments, about 10 percent were semi-detached houses, and 15 percent
were row houses.
Table 10: Distribution of Housing Starts in the Greater Golden
Horseshoe, by Structural Type, 1999 to 2004
Dwelling Type
Single-detached
Inner Ring (%)
Outer Ring (%)
GGH (%)
46.5
74.4
53.7
Semi-detached
11.3
3.9
9.2
Row
14.8
14.0
15.1
Apartment
27.4
7.7
22.1
Source: Canada Mortgage and Housing Corporation; calculations by Will Dunning Inc.
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4.4
| 44
Comparing Housing Starts Data with the Census Data
Comparing the CMHC housing starts data with data from the 2001 Census for
the GGH leads to the following observations:
4.5
•
The share of single detached houses is similar in the two data sets, at 53.7
percent in the CMHC data and 54.1 percent in the census data (which
includes attached houses and mobile homes).
•
The share for semi-detached houses is slightly higher in the CMHC data
(9.2 percent) than the census data (7.2 percent).
•
For row houses, the share has increased considerably in the CMHC data
(15.1 percent) compared to the census data (7.4 percent).
•
For apartments, the CMHC starts data shows a 22.1 percent share, which
is considerably lower than the 31.3 percent in the census data (including
the three categories of apartments).
Conclusions
It is sometimes stated that as many as 75 percent of potential home buyers would
prefer to buy a single detached house. That is undoubtedly correct. However,
in housing, as in most aspects of life, “You can’t always get what you want.”
People make compromises. Increases in house prices can cause economic rationing
— people live in the housing they can afford, rather than in the housing they say
they would prefer.
In future, the actual mix of housing in the GTA, the Inner Ring, the Outer Ring,
and the GGH will continue to be influenced by pricing, as well as by interest
rates.
Dunning0112.indd Sec2:52
•
If pricing in future is similar to current pricing (in real, inflation-adjusted
terms), and interest rates remain at current levels, then the mix of housing
will probably resemble the current mix — single detached houses would
account for less than half of new housing construction in the Inner Ring
and about three-quarters in the Outer Ring.
•
If, on the other hand, prices rise in real terms (for example, if the cost of
land increases), the share for singles would be expected to fall. Increasing
mortgage interest rates would have a similar effect.
•
If prices fall in real terms, or interest rates fall, then the share for single
detached houses would increase — although based on past experience, the
share is unlikely to exceed 60 percent for the Inner Ring and 65 percent
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| 45
for the entire GGH. Furthermore, this trend would occur in a weak economic and housing market situation in which total starts would be low.
Therefore the actual number of single detached houses would not be very
large.
Changing tastes may also affect the housing mix. For example, apartments
have become increasingly accepted as a form of homeownership. And for many
home-owners, a condominium apartment is the preferred housing form, irrespective of the relative costs of low-rises versus high-rises. This is an evolving trend,
which is likely to result in further shifts in the housing mix.
Demographic change, combined with changing tastes, also affects the future mix
of housing. For example, many of today’s empty nesters and retirees are making
different housing choices from those of their parents, and future generations will
show further changes. There is also a possibility that new housing forms (or the
rejuvenation of old forms, such as walk-up apartments) could alter the mix of
housing.
Although it is difficult to draw definitive conclusions about the future mix of housing, we need to use assumptions in order to make projections. In the next section,
the shares seen in recent CMHC housing starts data (for 1999 to 2004) are used
to project future housing requirements.
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5
Projections
5.1
Projections of Population Growth
| 46
Population projections were developed for each of the 16 Census Divisions in
the Greater Golden Horseshoe, for the 2001-to-2031 period. A summary of the
projections is provided here. The details are shown in Appendix A.2.
5.1.1
Method
The projections use a “cohort-survival” method, the most commonly used approach for developing long-term projections of population. The model employs
the following steps:
1. Starting in the base year of the analysis, data are obtained on population by
single year of age, by sex. In this case, the data are for July 1, 2001. The database can be drawn either from the 2001 census, or from Statistics Canada’s
post-censal estimates. The main difference between these two data sets is that
the census data do not include 100 percent of the population, as some people
are missed by the census (and some people are counted more than once)
whereas the post-censal estimates are adjusted for “net under-coverage” and
are presumed to count 100 percent of the population.* In the 2001 census
data, the population for the GGH is estimated at 7.53 million; in the 2001
inter-censal estimates, the population is 4.6 percent larger, or 7.88 million.
2. The annual number of births is estimated by applying fertility rates to the
estimates of the female population (by age group) at the start of each year. The
rates used were the 2001 fertility rates for Ontario, as estimated by Statistics
Canada. For each Census Division, the division of the births between males
and females is based on the actual male-female shares of the newborn population in the Census Division as of 2001.
3. Each year, as the population ages by one year, each age group is moved up to
the next bracket. In the process, “survival rates” (the percentage of people in
each age-sex group who are still alive one year later) are applied, to account
for deaths. Survival rates are derived from Statistics Canada data for Ontario
as of 1995-1997.
4. Adjustments are made for migration — adding the projected number of immigrants, subtracting the projected number of emigrants, and adding (or subtracting) net interprovincial and net intraprovincial migration. In Section 3 of
this report, a method was developed for projecting each of these components
of migration, and a summary table showed factors for each of the components, for three aggregated areas: the Inner Ring, Outer Ring, and GGH. In
* The projections performed by Hemson in its Growth Outlook for the Greater Golden Horseshoe
used the census data and a similar cohort-survival model. At the end of the exercise, the Hemson
model added an adjustment for under-coverage. In all likelihood, the Hemson approach would
generate results similar to those developed in this report, if similar assumptions were used for the key
input variables.
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| 47
developing the following projections, the sets of factors were projected individually for each of the 16 Census Divisions in the study area. The migration
components have been measured and projected in the following way:
•
Immigration is the percentage of Canada’s immigrants who move into
the Census Division each year. The Hemson report (page 20) assumes
that immigration to Canada will average 218,000 people per year during
2001 to 2006, and just under 210,000 for the remainder of the projection period. The same assumptions are used here. After total migration is
estimated for each Census Division, the migrants are distributed by age
and sex using the actual distribution (for the respective Census Divisions)
for immigrants who arrived from 2001 to 2003. The assumption that the
level of immigration will be stable for a 25-year period is quite strong.
For example, in fall 2005, the federal government started to argue for
increased immigration targets. It has been suggested that annual immigration could be as high as one percent of Canada’s population, which would
result in annual figures of more than 300,000.
•
Emigration is expressed as a percentage: the number of net emigrants
from the Census Division divided by its population at the start of the
year. Given the lack of data for analysis, it has been assumed that for each
Census Division, the rate is equal to the average seen over the 1997-to2004 period. The age-sex distribution is based on the actual distribution
(for the respective Census Divisions) of emigrants from 2001 to 2003.
•
Net interprovincial migration is expressed as a percentage: net interprovincial migration to or from the Census Division, divided by the population
of Canada excluding Ontario at the start of the year. Long-term population projections are needed for Ontario and Canada. The projections used
here are from Statistics Canada, “Projection 2: medium-growth and medium inter-provincial.” These projections cover the 2001-to-2026 period.
The projections have been extended to 2031 in this analysis. In applying
the projections of net migration, the age-sex distribution is based on the
actual distribution (for the respective Census Divisions) of interprovincial
in-migrants in 2001–2003.
•
Net intraprovincial migration is expressed as a percentage: net intraprovincial migration to (or from) the Census Division divided by the population of Ontario at the start of the year. The age-sex distribution is based
on the actual distribution (for the respective Census Divisions) of net
intraprovincial in-migrants in 2001–2002.
5. This process was followed for each year of the 2001-to-2031 projection
period.
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5.1.1
| 48
Projections
Using population estimates adjusted for “net under-coverage,” the population of
the GGH is assumed to be about 7.88 million in 2001. For 2031, the projections
indicate a total population of 10.48 million, an increase of 2.60 million (33.0
percent) over 30 years. Over the 30-year period, these projections indicate average annual growth of 86,700 people per year (1.0 percent per year). The rate of
population growth is projected to decelerate rapidly over the period:
•
From 2001 to 2011, population growth averages 109,600 people per year
(1.3 percent).
•
From 2011 to 2021, the growth rate is reduced to 88,600 people per year
(0.9 percent).
•
From 2021 to 2031, the growth rate is 62,000 people per year (0.6 percent).
Table 11 summarizes the components of population growth for the Inner Ring, the
Outer Ring, and the GGH.
Dunning0112.indd Sec2:56
•
Slight increases in the number of births provide increasing contributions
to growth for all three of the areas.
•
Mortality rises sharply (the consequence of an increasingly older population), tripling the annual number of deaths in the GGH.
•
Immigration falls slightly during the period.
•
Emigration increases slightly.
•
Interprovincial net migration is an increasingly negative factor over the
30-year period. This change is due to the lower employment rate in the
GGH and increased housing costs. It can be further interpreted as the
consequence of the aging population and the increased rate of retirements
over the 30-year period. Since some retirees leave Ontario to return to
their original homes or to move to areas with a lower cost of living or a
more congenial climate, the aging of the population helps drive increased
out-migration to other provinces.
•
Intraprovincial net migration will deteriorate slightly during the 30 years,
again, partly as the consequence of departures by retirees.
•
Overall, the primary cause of the slowdown in population growth is the
anticipated increase in mortality.
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| 49
Table 11: Components of Annual Population Growth in the Greater Golden Horseshoe
Births
Deaths
Immigration
Emigration
Net Interprovincial
migration
2001–11
36,147
–8,638
89,775
–13,291
–785
–26,866
76,343
2011–21
38,229
–18,682
88,445
–14,728
–4,289
–30,798
58,177
2021–31
39,177
–31,263
88,379
–15,750
–8,001
–34,607
37,935
2001–11
10,665
–8,720
7,521
–3,277
–718
27,813
33,285
2011–21
11,677
–14,124
7,185
–3,792
–1,870
31,326
30,403
2021–31
11,954
–21,430
6,954
–4,253
–3,082
33,939
24,082
2001–11
46,812
–17,357
97,296
–16,568
–1,503
947
109,627
2011–21
49,906
–32,806
95,629
–18,520
–6,158
528
88,579
2021–31
51,130
–52,693
95,333
–20,003
–11,082
–668
62,017
Period
Net Intraprovincial
migration
Total
growth
Inner Ring
Outer Ring
GGH
Source: Will Dunning Inc.
Over the 30 years, the projections indicate a shift in the shares of population and
population growth:
•
In 2001, the Inner Ring had about 74.1 percent of the GGH population,
and the Outer Ring had about 25.9 percent.
•
During 2001–2011, the Inner Ring receives 69.6 percent of the GGH’s
population growth. In 2011–2021, the Inner Ring’s share of growth falls
to 65.7 percent. During 2021–2031, the Inner Ring share of growth falls
again to 61.2 percent. Over the entire period, the Inner Ring is projected
to receive 66.3 percent of the GGH population growth and the Outer
Ring 33.7 percent.
•
By 2031, the Inner Ring’s share of the GGH population is projected to be
72.1 percent, versus 74.1 percent in 2001.
Table 12: Actual and Projected Population by Area, 2001 to 2031
Inner Ring
Outer Ring
GGH
2001
5,835,242
2,043,436
7,878,678
2011
6,598,668
2,376,282
8,974,950
2021
7,180,434
2,680,311
9,860,745
2031
7,559,786
2,921,130
10,480,916
Total Growth
1,724,544
877,694
2,602,238
66.3%
33.7%
Share of GGH Growth
Source: Will Dunning Inc.
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5.1.2
| 50
Conclusions
As we have seen, economic cycles affect rates of population growth, through variations in the components of migration. These projections of population growth for
2001 to 2031 incorporate those findings. Under neutral assumptions for economic
prospects, changes in migration tend to reduce population growth in the Greater
Golden Horseshoe. However, the changes in migration are expected to be relatively minor. More fundamentally, the aging of the population, and the consequent
expected increase in mortality, is expected to be the primary factor resulting in
slower population growth in the GGH.
The next two sections further analyze the implications of population growth, by
generating estimates of housing demand and employment growth. These two factors are the major drivers of land requirements for the study areas.
5.2
Projections of Household Formation and Housing Requirements
The projections of population from 2001 to 2031 were used to estimate the
total number of households and household growth for 2011, 2021, and 2031.
Estimates were developed for each of the 16 Census Divisions in the Greater
Golden Horseshoe study area. In this section, results are summarized for three
aggregated areas (the Inner Ring, the Outer Ring, and the GGH). More details are
provided in Appendix A.3.
5.2.1
Method
The method in this section is quite simple:
1. The 2001 census provides data on the number of households by the age of
the primary household maintainer (or household head). This data is used to
estimate household headship rates by age group as of 2001 for each of the
Census Divisions.
2. The age-specific headship rates are applied to the population projections (for
the same age groups), to estimate the number of households by age group for
2001, 2011, 2021, and 2031. Then the age groups are combined to estimate
the total number of households as of 2001, 2011, 2021, and 2031.*
3. The amounts of growth in households are calculated for each period. These
indicate the requirements for new housing.
4. Finally, these requirements are allocated to dwelling types, using the shares
seen in recent CMHC housing starts data (for 1999 to 2004).
* Since the census data are not adjusted for net under-coverage, but the population projections use
adjusted population estimates for 2001 and subsequent years, it was necessary to create revised
estimates of the total number of households for 2001. For example, in the 2001 census data, the
number of households in the GGH is estimated at 2,704,495. Using the population data adjusted for
net under-coverage, the number of households, at July 2001 is 3.9 percent higher, at 2,809,807.
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This method assumes that age-specific headship rates will not change over the 30year period. However, headship rates do vary over time. As part of this research
project, attempts were made to interpret headship rates as a function of economic
variables. While the research found some relationships, the results were weak and
could not be used in projections. Therefore, constant headship rates were used.
The research on headship rates is described in Appendixes A.5 and A.6.
5.2.2
Projection of Household Formation
Household formation varies by age group, as seen in Table 13, which shows the
headship rates by age groups for the Inner Ring, the Outer Ring, and the GGH.
Headship rates are lowest for young adults, and rise in each of the subsequent age
groups. The data also indicates that headship rates are lower in the Inner Ring
than in the Outer Ring, which is not surprising, given that housing costs are higher
in the Inner Ring.
Table 13: Household Headship Rates in the Greater Golden Horseshoe, 2001
Age Group
Inner Ring (%)
Outer Ring (%)
GGH (%)
15–24
6.4
8.7
7.0
25–34
38.4
44.4
39.7
35–44
51.9
52.9
52.1
45–54
55.3
55.4
55.3
55–64
55.8
56.4
56.0
65–74
57.8
61.3
58.8
59.0
62.6
60.1
75 +
Source: Statistics Canada, 2001 Census; calculations by Will Dunning Inc.
For each of the 16 Census Divisions, the headship rates are applied to the projections of population, to derive the total number of households at 10-year intervals.
Table 14 shows the summarized results for the GGH. The projections suggest that
the number of households will increase by almost one-half (47.6 percent), to about
4.15 million in 2031, compared to 2.81 million in 2001.
Table 14: Households by Age Group in the Greater Golden Horseshoe, 2001 to 2031
Age Group
2001
2011
2021
2031
15–24
73,474
78,888
74,177
72,229
25–34
466,534
489,383
526,863
500,912
35–44
720,249
708,519
730,835
771,624
45–54
605,545
793,476
774,422
791,067
55–64
390,681
601,680
779,329
757,954
65–74
308,658
373,680
563,411
722,421
75 +
244,665
311,705
375,020
531,516
Total
2,809,807
3,357,330
3,824,056
4,147,722
Source: Will Dunning Inc.
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Table 15 summarizes the results for the Inner Ring, the Outer Ring, and the GGH
as a whole. The number of households is projected to increase by 1.34 million
between 2001 and 2031, an average of about 44,600 households per year. Of this
growth, 62.5 percent would be in the Inner Ring and 37.5 percent in the Outer
Ring. By 2001, the Outer Ring would have 30.5 percent of the GGH households,
up from 27.2 percent in 2001.
Table 15: Projections of Households and Household Growth
in the Greater Golden Horseshoe, 2001 to 2031
Inner Ring
Outer Ring
GGH
2001
2,046,711
763,097
2,809,807
2011
2,406,214
951,116
3,357,330
2021
2,695,414
1,128,642
3,824,056
2031
2,882,649
1,265,073
4,147,722
2001-2011
359,503
188,019
547,522
2011-2021
289,200
177,526
466,726
2021-2031
187,236
136,430
323,666
Total
835,939
501,976
1,337,915
2001-2011
35,950
18,802
54,752
2011-2021
28,920
17,753
46,673
2021-2031
18,724
13,643
32,367
Total
27,865
16,733
44,597
Number of Households
Total Household Formation
Annual Household Formation
Number of Adults per Household
2001
2.29
2.15
2.25
2011
2.27
2.11
2.22
2021
2.23
2.03
2.17
2031
2.21
1.99
2.14
2001
2.85
2.68
2.80
2011
2.74
2.50
2.67
2021
2.66
2.37
2.58
2031
2.62
2.31
Total Population per Household
2.53
Source: Will Dunning Inc.
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The rate of growth is expected to slow during the 30-year period:
•
From 2001 to 2011, household formation would average about 36,000
per year in the Inner Ring and 18,800 per year in the Outer Ring for a
GGH total of 54,800 per year.
•
From 2011 to 2021, household formation would fall to less than 29,000
per year in the Inner Ring. The reduction in the Outer Ring would be
less sharp, falling to about 17,800 per year. For the GGH as a whole,
household formation would fall by about 15 percent, to 46,700 per year.
•
From 2021 to 2031 there would be a sharper drop in household formation, to about 18,700 per year in the Inner Ring, 13,600 per year in the
Outer Ring, and a total of 32,400 per year for the GGH.
Average household size is expected to fall during the 30-year period. By 2031,
there would be an average of 2.53 people per household, about 10 percent lower
than the 2001 average of 2.80 people per household.
The distribution of activity by area does not take into account the impacts of land
use policies or land supply constraints. Thus the geographic distribution among
the Census Divisions is imprecise. The totals for the Inner Ring, Outer Ring, and
GGH are the most important result of these projections.
5.2.3
Projection of Housing Requirements by Dwelling Type
Housing requirements by dwelling types were based on the preceding projection
of household growth. The analysis has shown that dwelling type mix varies in
relation to housing cost. As the median real cost of single detached dwellings
increases in the GTA, the share of apartments increases as homebuyers seek lowercost options.
If we assume that housing costs remain the same over the 30-year projection period
as in the recent past, we would expect the following projected demand for about
1.34 million units:
•
About 762,000 single detached units would be required (57.0 percent of
the total).
•
About 114,000 units would be semi-detached (8.5 percent).
•
About 194,000 units would be townhouses (14.5 percent).
•
About 267,000 units would be apartments (20.0 percent).
In this analysis, housing demand was apportioned to the shares recorded in the
CMHC housing starts data for the 1999–2004 period. These shares were applied
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separately for the Inner Ring and for the Outer Ring and then added to estimate
total housing demand by dwelling type for the GGH. The resulting shares for each
area by decade are shown in Table 16.
The actual distribution will depend on many factors, including housing costs and
interest rates. Given that during the past half-decade, interest rates have been at
the lowest level in a generation, over the 30-year projection period, housing affordability is more likely to deteriorate than to improve. In response, households
will choose less expensive options, resulting in a reduced share for single detached
houses and increased shares for row houses and apartments. Consequently, this
projection represents a likely maximum scenario for single-detached production.
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Table 16: Housing Demand in the GGH, by Type of Dwelling, 2001 to 2031
Inner Ring
Outer Ring
GGH
Shares by Dwelling Type, 2001 (CMHC Housing Starts 1999-2004)
Single detached
46.5%
74.4%
53.7%
Semi-detached
11.3%
3.9%
9.2%
Row
14.8%
14.0%
15.1%
Apartment
27.4%
7.7%
22.1%
2001–2011 Allocation by Dwelling Type (Annual)
Single detached
16,728
13,990
30,718
Semi-detached
4,075
732
4,807
Row
5,305
2,640
7,945
9,842
1,440
11,282
35,950
18,802
54,752
13,209
26,666
Apartment
Total
2011–2021 Allocation by Dwelling Type (Annual)
Single detached
13,457
Semi-detached
3,278
691
3,969
Row
4,268
2,493
6,760
Apartment
7,918
1,360
9,277
28,920
17,753
46,673
Total
2021–2031 Allocation by Dwelling Type (Annual)
Single detached
8,712
10,151
18,864
Semi-detached
2,122
531
2,653
Row
2,763
1,916
4,679
Apartment
Total
5,126
1,045
6,171
18,724
13,643
32,367
Total Housing Demand over 2001–2031
Single detached
388,970
373,502
762,473
Semi-detached
94,754
19,541
114,295
Row
123,357
70,485
193,842
Apartment
228,857
38,448
267,305
Total
835,939
501,976
1,337,915
Shares of Total Housing Demand over 2001–2031
Single detached
46.5%
74.4%
57.0%
Semi-detached
11.3%
3.9%
8.5%
Row
14.8%
14.0%
14.5%
Apartment
27.4%
7.7%
20.0%
100.0%
100.0%
Total
100.0%
Source: Will Dunning Inc.
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5.2.4
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Conclusions
Earlier projections indicated that population growth would decline between 2001
and 2031 period, partly because of reduced net migration, but primarily because
of increased mortality. This section has extended that analysis, to estimate the
requirement for new housing.
Not surprisingly, slower population growth results in a reduced need for new
housing. From 2001 to 2011, the average annual requirement is projected to be
very high, at an average of about 54,800 units per year. From 2011 to 2021, the
annual requirement (46,700 units) would be about 15 percent lower. From 2021
to 2031, the annual requirement (32,400 units) would be 41 percent lower than
the 2001–2011 requirement.
If recent trends continue, it is projected that 57 percent of the new housing across
the GGH will be in the form of single detached units, 8.5 percent semi-detached,
14.5 percent row houses, and 20 percent apartments. If housing costs and interest
rates increase, however, the share of new single detached units would decrease in
favour of attached or multi-residential forms. Other factors (demographic change,
the evolution of tastes, and the creation of new housing types) will affect the mix
of housing. The combined impact of these factors cannot be predicted.
5.3
Projections of Employment Growth
Using the projections of population for the period 2001 to 2031, estimates of the
total employment and employment growth that might result in 2011, 2021, and
2031 were developed for each of the 16 Census Divisions in the GGH. Results are
summarized here for three aggregated areas (the Inner Ring, the Outer Ring, and
the GGH). More details are provided in Appendix A.4.
5.3.1
Method
The method in this section is similar to that used to project household growth:
1. The 2001 census provides data on employment by age group.
2. This data is used to estimate employment rates by age group as of 2001 for
each of the Census Divisions.
3. Age-specific employment rates are applied to the population projections for
the same age groups, to estimate employment by age group for 2001, 2011,
2021, and 2031.
4. The age groups are combined to estimate total employment for 2001, 2011,
2021, and 2031.*
* Since the census data are not adjusted for net under-coverage, but the population projections use
adjusted population estimates for 2001 and the subsequent years, it was necessary to estimate
employment for 2001, which differs from the total employment estimated by the census. For
example, in the 2001 census data, total employment in the GGH is estimated at 3,833,750. Using
population data adjusted for net under-coverage, the employment estimate for July 2001 is 6.1
percent higher, at 4,066,852.
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5.3.2
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Projections
Employment rates vary by age group, as can be seen in Table 17, which shows
employment rates by age groups for the Inner Ring, the Outer Ring, and the GGH.
Not surprisingly, employment rates are lowest for people aged 65 years and older.
The rates are below-average for young adults (15 to 19 and 20 to 24) and for the
pre-retirement and early-retirement age groups (50 to 54, 55 to 59, and 60 to 64).
Employment rates are highest for adults in the prime working ages of 25 to 49.
Table 17: Employment-to-Population Ratios by Age Group
in the Greater Golden Horseshoe, 2001
Age Group
Inner Ring (%)
Outer Ring (%)
GGH (%)
15–19
48.0
57.7
44.3
20–24
74.0
76.7
73.8
25–29
83.7
86.0
83.3
30–34
83.9
86.2
83.1
35–39
85.5
85.9
84.9
40–44
85.6
86.2
86.0
45–49
86.6
86.7
85.2
50–54
82.3
84.7
81.6
55–59
66.6
73.7
70.0
60–64
40.9
48.8
48.9
8.6
11.4
10.6
68.2
69.3
69.8
65+
All Ages
Source: Statistics Canada, 2001 Census; calculations by Will Dunning Inc.
As Table 18 shows, during the 30-year period, the age distribution of the adult
population will change. Of greatest importance for this exercise is the large increase in the share of the population aged 65 and over, which rises from 14.7
percent in 2001 to 24.3 percent in 2031. There are smaller increases in the shares
in the early-retirement age brackets of 55 to 59 and 60 to 64. The shares fall for
all of the age groups under 55 years. The percentage in the prime working ages (25
to 49) falls from 49.5 percent in 2001 to 39.6 percent in 2031.
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Table 18: Distribution of the Adult Population by Age Group
in the Greater Golden Horseshoe, 2001 to 2031
Age Group
2001 (%)
2011 (%)
2021 (%)
2031 (%)
15–19
8.3
7.9
6.5
6.3
20–24
8.3
7.9
7.1
6.5
25–29
8.8
8.2
8.0
6.9
30–34
9.8
8.5
8.2
7.6
35–39
11.2
8.9
8.5
8.4
40–44
10.6
9.4
8.5
8.4
45–49
9.2
10.1
8.4
8.3
50–54
8.1
9.2
8.5
7.9
55–59
6.1
7.7
8.9
7.7
60–64
4.9
6.7
7.9
7.7
14.7
15.6
19.4
24.3
100.0
100.0
100.0
100.0
65 +
All Ages
Source: Statistics Canada inter-censal population estimates for 2001; calculations by Will Dunning Inc.
This evolving age distribution has significant implications for total employment in
the GGH. Table 19 summarizes the projections of employment for the Inner Ring,
Outer Ring, and GGH. These projections indicate that employment growth will
decelerate sharply between 2001 and 2031, from an average of about 64,000 jobs
per year between 2001 and 2011, to 31,500 jobs per year between 2011 and 2021,
and just 8,800 jobs per year between 2021 and 2031. The percentage of adults
employed in the GGH is projected to fall sharply, from 64.2 percent in 2001 to
57.6 percent in 2031.
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Table 19: Projections of Employment and Employment Growth in the Greater Golden Horseshoe, 2001 to 2031
Inner Ring
Outer Ring
GGH
2001
3,024,896
1,041,956
4,066,852
2011
3,468,059
1,238,572
4,706,631
2021
3,674,432
1,346,782
5,021,213
2031
3,719,781
1,389,847
5,109,628
2001–2011
443,164
196,616
639,779
2011–2021
206,372
108,210
314,582
2021–2031
45,349
43,066
88,415
2001–2011
44,316
19,662
63,978
2011–2021
20,637
10,821
31,458
2021–2031
4,535
4,307
8,841
2001–2011
1.4%
1.7%
1.5%
2011–2021
0.6%
0.8%
0.6%
2021–2031
0.1%
0.3%
0.2%
2001
64.4%
63.6%
64.2%
2011
63.5%
61.8%
63.1%
2021
61.2%
58.7%
60.5%
2031
58.5%
55.2%
57.6%
Change 2001-2031
(Percentage points)
–6.0%
-8.4%
-6.7%
Total Employment
Total Growth in Employment
Annual Average Growth in Employment
Annual Average % Change in Employment
Employment rate
Source: Will Dunning Inc.
5.3.3
Conclusions
These projections indicate that the aging of the population will slow employment
growth in the Greater Golden Horseshoe. The projections are based entirely upon
demographic change, not on an economic forecast, as they assume that for each
age group, the percentage of people who are employed remains at the 2001 level.
In order for employment growth to be stronger than projected, it would be necessary for the age-specific employment rates to increase. However, in 2001, the
GGH economy was at or close to a cyclical peak, so it is hard to imagine that
the age-specific employment rates could increase for most age groups. If delayed
retirement causes employment growth, very large increases in the employment
rates would be required if the overall employment rate in 2031 is to be equal to
the 2001 GGH rate of 64.2 percent. Table 20 illustrates one scenario that results
in a 64.2 percent employment rate in 2031. In this scenario, the employment rate
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among people aged 65 and over must more than triple to 30 percent. There must
also be increases in employment rates among the pre-retirement age groups. For
example:
•
In the 50-to-54 group, the employment rate must be 83 percent, similar to
the rate for the 40 to 49 age groups.
•
In the 55-to-59 age group, the rate must increase by more than onetenth.
•
In the 60-to-64 age group, the employment rate must increase by about
one-third.
This scenario would require an extraordinary shift in behaviour and social convention, or else a profound shift in retirement incomes (reduced public and private
pensions and the loss of personal savings or home equity) that forces a high percentage of the older population to delay planned retirements. If these doomsday
scenarios do not come to pass, demographic change will likely result in a sharp
slowdown in employment growth from 2001 to 2031.
Table 20: Simulation of Age-Specific Employment Rates (in the GGH)
Required to Result in a 64.2% Employment Rate in 2031
% of Adult
Population
in 2031
GGH
Employment Rate
in 2001 (%)
Alternative GGH
Employment Rate in
2031 (%)
Required Change
in Employment
Rate (%)
15–19
6.32
44.5
44.5
0.0
20–24
6.49
70.8
70.8
0.0
25–29
6.90
80.8
80.8
0.0
30–34
7.61
81.2
81.2
0.0
35–39
8.41
82.4
82.4
0.0
40–44
8.39
83.1
83.1
0.0
45–49
8.27
83.1
83.1
0.0
50–54
7.95
78.9
83.0
4.1
55–59
7.69
66.5
75.0
8.5
7.66
43.6
60.0
16.4
24.31
9.1
30.0
20.9
64.2
64.2
Age Group
60–64
65 +
All Ages
Source: Will Dunning Inc.
It might be argued that the reduction in the employment rate will result in increased
migration to the GGH by working-age adults. However, since the entire country
will be experiencing the same demographic changes, there is no reason to believe
that this change alone will cause increased movement to the GGH from other
areas of Canada. Migration to the GGH will be determined by economic costs and
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opportunities. Only a considerable change in economic conditions would cause
increased migration by adults from the rest of the country. However, a change in
immigration policy might result in increased immigration by working-age adults.
5.4
Comparison with Other Projections
This report has projected migration and population growth, household formation,
housing demand, and employment growth. In this section, these projections are
contrasted with those in Hemson Consulting’s Growth Outlook for the Greater
Golden Horseshoe, commissioned by the provincial government, and IBI Group’s
Toronto-Related Region Futures Study, funded by the Neptis Foundation.
5.4.1
Population Growth
Table 21 compares the preceding projections for population growth with those
in the Hemson report. Over the 30-year period, the population projections in
this report (WDI) total about 1.1 million less than the Hemson projections. The
difference amounts to an average of about 36,900 people per year. Most of the
difference in the projections is in the Inner Ring, where the WDI projections are
1.09 million lower than the Hemson projections. For the Outer Ring, the projections are quite similar.
The projections differ for all three of the decades in the projection period. In the
first decade, the WDI projections are about 200,000 less than the Hemson projections. In the third decade, the difference between the two projections is more than
500,000. The differences between the two are largely due to expectations about
migration. The following section compares the migration assumptions.
Table 21: Comparison of Projections of Total Population Growth for the Greater Golden Horseshoe
(Will Dunning Inc. and Hemson Projections)
Inner Ring
Period
Outer Ring
GGH
WDI
Hemson
WDI
Hemson
WDI
Hemson
2001–2011
763,426
1,050,000
332,846
250,000
1,096,272
1,300,000
2011–2021
581,766
920,000
304,029
330,000
885,794
1,250,000
2021–2031
379,352
840,000
240,820
320,000
620,172
1,160,000
1,724,544
2,810,000
877,694
900,000
2,602,238
3,710,000
Total
Difference:
WDI – Hemson
–1,085,456
–22,306
–1,107,762
Source: Will Dunning Inc; Hemson Consulting Ltd., The Growth Outlook for the Greater Golden Horseshoe
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Table 22 compares the WDI population projections with those in the Neptis-sponsored Toronto-Related Region Futures Study by IBI. In the IBI projections, the first
period covers 11 years (2000–2011), so the IBI projections were reduced pro rata
to allow for comparisons. Also, the IBI projections did not include two Census
Divisions included in the WDI and Hemson projections, Brant and HaldimandNorfolk. Therefore, the WDI projections have been adjusted to exclude them.
The WDI projection of total population growth (2.57 million) is about 500,000
less than the IBI projection. There is a large negative difference in the projections
for the Inner Ring of about –600,000. For the eight Census Divisions in the Outer
Ring, the WDI projections are about 100,000 higher than the IBI projections.
The projections are quite similar for the first decade of the projection period (for
all areas combined), but there are increasing differences in the second decade
(about 160,000) and third decade (about 360,000).
Table 22: Comparison of Projections of Total Population Growth for
Central Ontario (Will Dunning Inc. and IBI Projections)
Inner Ring
Period
Outer Ring
Total
WDI
IBI
WDI
IBI
WDI
IBI
2001–2011
763,426
830,485
315,365
225,704
1,078,792
1,056,189
2011–2021
581,766
770,040
292,014
265,999
873,780
1,036,039
2021–2031
379,352
725,537
235,826
249,294
615,177
974,831
1,724,544
2,326,062
843,205
740,997
2,567,749
3,067,059
Total
Difference:
WDI – IBI
–601,518
+102,208
–499,310
Source: Will Dunning Inc.; IBI Group/Dillon Consulting, Toronto-Related Region Futures Study
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Migration
Table 23 contrasts the assumptions for the components of migration. A summary
of the results (by component of migration) follows the table.
Table 23: Comparison of Projections of Annual Migration for the Greater Golden Horseshoe
Inner Ring
Period
Outer Ring
GGH
WDI
Hemson
WDI
Hemson
WDI
Hemson
2001–2011
76,484
90,100
4,244
3,600
80,728
93,700
2011–2021
73,716
79,600
3,393
4,500
77,109
84,000
2021–2031
72,629
78,000
2,701
4,300
75,331
82,300
2,228,300
2,477,000
103,380
124,000
2,331,680
2,600,000
Net International Migration
Total
Difference:
WDI – Hemson
–248,700
–20,620
–268,320
Net Interprovincial Migration
2001–2011
–785
2,500
–718
200
–1,503
2,700
2011–2021
–4,289
3,100
–1,870
300
–6,158
3,400
2021–2031
–8,001
3,100
–3,082
300
–11,082
3,400
–130,741
87,000
–56,693
8,000
–187,434
95,000
Total
Difference:
WDI – Hemson
–217,741
–64,693
–282,434
Net Intraprovincial Migration
2001–2011
–26,866
–18,800
27,813
17,800
947
–1,000
2011–2021
–30,798
–24,600
31,326
23,600
528
–1,000
2021–2031
–34,607
–27,000
33,939
27,000
–668
0
–922,717
–704,000
930,790
684,000
8,073
–20,000
Total
Difference:
WDI – Hemson
–218,717
246,790
28,073
Total Net Migration
2001–2011
48,833
73,800
31,340
21,600
80,173
95,400
2011–2021
38,629
58,100
32,849
28,400
71,479
86,400
2021–2031
30,022
54,100
33,559
31,600
63,580
85,700
1,174,842
1,860,000
977,476
816,000
2,152,318
2,675,000
Total
Difference:
WDI – Hemson
–685,158
161,476
–522,682
Source: Will Dunning Inc.; Hemson Consulting Ltd., Growth Outlook for the Greater Golden Horseshoe
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5.4.2.1
| 64
NET INTERNATIONAL MIGRATION
Over the 30 years of the projections, the Hemson assumptions for net immigration (i.e., immigration minus emigration) are, in total, about 268,000 higher than
those in this report. The Hemson report indicates that from 1991 to 2001, net
international immigration to the GGH was 80,500 people per year. In the WDI
projections, the average over the 30-year period (for the GGH) is about 77,700
people per year, or 3.5 percent lower than the 1991–2001 average. In the Hemson
projections, the average over the 30 years is 86,700 people per year, about 7.7
percent higher than the 1991–2001 average.
This report argues that the economic cycle in the GTA has peaked and that a
return of the employment ratio to a “normal” level should result in the GGH
receiving a lower share of Canada’s immigration than it did in the late 1990s
and early 21st century. Recent data shows that the GGH share of immigration is
falling in response to the changing economic environment. During the past two
years (2002–2004), net immigration to the GGH averaged 91,600 people per year;
during the previous two years (2000–2002), the average was higher, at 119,200
people per year. These projections assume that net immigration will decline further
because of the softening of the economy and higher house prices.
The differences between the two sets of projections may be partly due to emigration. In this analysis, it is assumed that emigration increases over time with the
growth in the population. From 2021 to 2031, emigration is expected to be about
7,000 people per year above current levels. Rising emigration is certainly a factor
in the decline of net immigration. The Hemson report does not specify assumptions for emigration and therefore it is not possible to compare the approaches or
estimates.
Immigration to Canada is assumed (by both Hemson and this report) to be about
210,000 people per year over the 30 years. If emigration is about 60,000 people
per year over the period, net immigration to Canada will be about 150,000 people
per year. Using an average net immigration assumption of about 86,700 people
per year, the Hemson analysis assumes that the GGH will receive about 58 percent
of Canada’s net immigration. It is questionable whether such a high share can
be sustained, when the GGH accounts for only about 28 percent of the national
population. Moreover, during the past 18 years, the GGH share of Canada’s net
immigration has averaged 52.3 percent. The assumption in this report is that
GGH net immigration will average 77,700 people per year over the next 30 years,
or about 52 percent of Canada’s net immigration. This is in line with the historic
average.
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| 65
Figure 28: GGH Share of Net Immigration to Canada, 1987 to 2004
GGH Share of Net Immigration to Canada
65%
60%
55%
50%
45%
40%
35%
30%
1987
5.4.2.2
1990
1993
1996
1999
2002
NET INTERPROVINCIAL MIGRATION
The Hemson report assumes that net interprovincial migration to the GGH will be
positive during the projection period, averaging about +3,200 people per year; the
projections in this report (WDI), however, assume that this component of migration will be negative, averaging about –6,200 people per year over the 30 years.
The Hemson report shows an average of +2,400 people per year for the 1991–2001
period. Annual data show that net interprovincial migration to the GGH has declined for four consecutive years, and was about –4,400 people per year in 2004.
Thus, the assumption in this report for the 2001–2011 period (–1,500 people per
year) is higher than the most recent actual figure (–4,400 people per year).
The assumptions of long-term negative net interprovincial migration are based
on an analysis of past trends, which indicate that increased house prices, combined with a “normal” employment rate (lower than in recent years, in which
the economic cycle has been at a peak), result in relatively weak interprovincial
migration. Over the 30 years, these assumptions for net interprovincial migration
are 282,000 people per year lower than the Hemson projections.
5.4.2.3
NET INTRAPROVINCIAL MIGRATION
There is little difference between the projections, as the Hemson projections assume a small net loss (–20,000 people over 30 years) for this component, while the
projections in this report assume a small net gain (+8,100).
5.4.2.4
TOTAL NET MIGRATION
Combining the three components of net migration, the assumptions in this report
result in total net migration of 2.15 million people over the 30-year period. While
this is a substantial source of population growth — averaging 71,700 people per
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 66
year — it is lower than the Hemson assumption of 2.67 million net migrants
(89,200 people per year).
The WDI projections are also lower than the 1991–2001 average, which the
Hemson report shows as 82,700 people per year. The lower migration assumption in this analysis is based on the assumption that a “normal” employment rate
combined with high house prices will deter in-migration and encourage out-migration. The deterioration in the WDI assumptions is also partly due to growth in
emigration (the consequence of a rising population), while total immigration to
Canada is assumed to be flat.
5.4.3
Housing Demand
The projections in this report indicate that household formation could total about
1.34 million from 2001 to 2031, or about 44,600 households per year. This is
372,000 households (22 percent) lower than the Hemson projection of 1.71 million households (57,000 households per year).
For the Inner Ring, the WDI projections average 27,865 new households per year
during 2001 to 2031, substantially below the average of 42,000 households per
year projected by Hemson.
In contrast to these two sets of projections, from 1987 to 2004, housing starts in
the GTA averaged 33,678 units per year (see section 2 of this report); from 1999
to 2004, GTA starts were higher, averaging 45,098 units per year.
•
The WDI projections are below the 1987–2004 long-term average, reflecting that demographic change will tend to slow housing activity.
•
The Hemson projections, on the other hand, are close to the 1999–2004
average, suggesting that long-term housing activity will remain at levels
seen in recent years, which represent the peak of a market cycle.
•
Thus, the WDI projections are based on an assumption that over the 30
years, economic and housing market conditions will be similar to the
long-term average; the Hemson projections appear to depend on the continuation of peak economic and housing market conditions for 30 years.
Looking at each of the three decades separately:
Dunning0112.indd Sec2:74
•
From 2001 to 2011, the WDI projection (548,000 households) is about
50,000 (9 percent) lower than the Hemson projection.
•
From 2011 to 2021, the difference between the projections increases to
about 135,000 households (22 percent).
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
•
| 67
From 2021 to 2031, the difference expands again, to about 185,000
households (37 percent).
These differences are mainly due to different expectations for population growth
and partly due to differences in household sizes. In the Hemson projections, in
2031 the average household size is 2.62 people; in the WDI projections, the average is 2.53 people. If the average household size were the same in both projections,
the total number of households projected by WDI would be even lower.
Table 24: Comparison of Projections of Household Formation in the Greater
Golden Horseshoe (Total Growth in Households by Period)
Inner Ring
Period
Outer Ring
GGH
WDI
Hemson
WDI
Hemson
WDI
Hemson
2001–2011
359,503
460,000
188,019
140,000
547,522
600,000
2011–2021
289,200
430,000
177,526
170,000
466,726
600,000
2021–2031
187,236
370,000
136,430
140,000
323,666
510,000
Total
835,939
1,260,000
501,976
450,000
1,337,915
1,710,000
Difference:
WDI – Hemson
–424,061
+51,976
–372,085
Source: Will Dunning Inc.; Hemson Consulting Ltd The Growth Outlook for the Greater Golden Horseshoe
5.4.4
Employment Growth
Given its population projections and the associated age distribution, this report
has estimated that employment growth will decline over the 30-year period. This
is partly due to the slowdown in population growth, but mostly due to the shifting
age structure of the population: over time, an increasing share of the adult population will be retired, and the percentage of adults available for employment will
fall. The analysis showed that if employment rates by age group remain at 2001
levels, the percentage of adults (in the GGH) who are employed would fall from
64.2 percent in 2001 to 57.6 percent in 2031.
Table 25 compares projections of employment and employment growth in this report and the Hemson report. The Hemson report projects the creation of 700,000
more jobs than this report does.
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| 68
Table 25: Comparison of Projections of Employment and Employment Growth in the Greater Golden Horseshoe
Inner Ring
Period
Outer Ring
GGH
WDI
Hemson
WDI
Hemson
WDI
Hemson
2001
3,024,896
2,940,000
1,041,956
870,000
4,066,852
3,810,000
2011
3,468,059
3,630,000
1,238,572
1,010,000
4,706,631
4,640,000
2021
3,674,432
4,030,000
1,346,782
1,130,000
5,021,213
5,160,000
2031
3,719,781
4,320,000
1,389,847
1,240,000
5,109,628
5,560,000
2001–2011
443,164
690,000
196,616
140,000
639,779
830,000
2011–2021
206,372
400,000
108,210
120,000
314,582
520,000
2021–2031
45,349
290,000
43,066
110,000
88,415
400,000
694,885
1,380,000
347,891
370,000
1,042,776
1,750,000
Total Employment
Growth in Employment
Total
Difference:
WDI – Hemson
–685,115
–22,109
–707,224
Source: Will Dunning Inc; Hemson Consulting Ltd., The Growth Outlook for the Greater Golden Horseshoe
Hemson took a different approach to projecting employment growth: rather than
applying employment rates directly, Hemson applied age-specific labour force
participation rates to project the size of the labour force and then subtracted an
estimate of unemployment to estimate the number of employed persons. This
approach should yield results similar to the approach used by WDI (if similar assumptions are used). However, Hemson used different assumptions. The Hemson
report notes some adjustments to the labour force participation rates:
Dunning0112.indd Sec2:76
•
Hemson assumes that participation rates will continue to rise from the
levels in the 2001 Census. However, the economic cycle probably peaked
at about the same time as the 2001 census, and the employment rate has
since declined; therefore, an assumption of further growth in the labour
force participation rate seems questionable. Hemson also assumes that
labour force participation rates will return to 1980s levels. Again, this
is questionable, since the economic cycle has peaked. Moreover, labour
force activity was boosted in the late 1980s by a “bubble” housing market
and economy, and by extremely high housing costs, which forced people
to work more than they might have otherwise. Finally, demographic
change since the 1980s (more people at retirement ages and more early
retirements) will lower labour force participation. Thus it appears unlikely
that labour force participation will return to 1980s levels.
•
Hemson assumes that women over 40 will continue to have rising participation rates.
•
Hemson assumes that there will be “a small increase” in the participation
rate of people over 65.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 69
A simulation was conducted using the Hemson population projections for the
Inner Ring. Table 26 shows the Hemson population estimates for 2001 and 2031.
The actual 2001 employment rates for the Inner Ring (by age group, using census
data) were applied to project total employment and employment growth by age
group. This analysis projects total employment growth of about 1.21 million jobs
from 2001 to 2031, or about 12 percent less than the Hemson projection that
Inner Ring employment will expand by 1.38 million jobs. If the same 12 percent
factor also applies to the projections for the Outer Ring, total employment growth
in the GGH would be 1.54 million jobs, about 210,000 lower than the Hemson
projection of 1.75 million jobs.
This factor explains about one-third of the difference (707,000 jobs) between the
WDI and Hemson projections. The rest of the difference (close to 500,000 jobs) is
due to different projections of population growth.
Table 26: Estimation of Potential Employment Growth in the Inner Ring, using Hemson
Population Projections (Assuming no Change in Age-Specific Employment Rates)
Hemson Population
Projections: Inner Ring
2001
2031
Emp-Pop
Ratio
– 2001
15–19
382,100
477,100
20–24
393,400
25–29
426,700
30–34
Age Group
Implied Employment in…
2001
2031
Change
41.78%
159,643
199,334
39,691
541,300
69.11%
271,876
374,089
102,213
629,300
80.26%
342,489
505,105
162,616
478,800
641,400
80.56%
385,719
516,709
130,990
35–39
535,300
661,000
81.80%
437,860
540,679
102,819
40–44
498,200
624,900
82.50%
411,016
515,544
104,528
45–49
428,800
586,300
82.65%
354,391
484,560
130,169
50–54
380,200
526,900
78.85%
299,779
415,448
115,670
55–59
278,400
473,800
67.43%
187,735
319,500
131,765
60–64
223,400
459,300
44.89%
100,289
206,190
105,901
65 +
656,000
1,586,200
9.38%
61,538
148,798
87,260
4,681,300
7,207,500
3,012,336
4,225,958
1,213,622
Total Adults
Sources: Statistics Canada, Hemson Consulting Ltd, calculations by Will Dunning Inc.
Table 27 compares the WDI employment growth projections with the projections
in the Neptis-sponsored Toronto-Related Region Futures Study by IBI, with the
adjustments already described. In this comparison, the WDI projection of total
employment growth (1.04 million jobs) is very far below the IBI projection (1.83
million jobs), with a difference of almost –800,000 jobs. This difference is only
partly due to the difference in population projections. A difference in method is
responsible for more than half the difference:
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
•
In the WDI analysis, age-specific employment rates were applied to the
population. Given the changing composition of the population (an increasing share of the population in retirement ages), the average employment rate falls.
•
In the IBI analysis, it was assumed that employment would rise relative
to the population, and thus, the changing age-structure of the population
was not considered.
| 70
The differences between the two sets of projections are large for all three decades (about 223,000 jobs in the first decade, 243,000 in the second decade, and
320,000 in the third decade).
Table 27: Comparison of Projections of Total Employment Growth for
Central Ontario (Will Dunning Inc. and IBI Projections)
Inner Ring
Period
Outer Ring
Total
WDI
IBI
WDI
2001–2011
443,164
709,314
187,694
144,661
630,858
853,975
2011–2021
206,372
413,409
109,879
146,296
316,251
559,705
2021–2031
45,349
284,227
49,907
131,197
95,256
415,424
694,885
1,406,950
347,479
422,154
1,042,365
1,829,104
Total
Difference:
WDI – IBI
–352,065
IBI
WDI
–74,675
IBI
–786,739
Source: Will Dunning Inc.; IBI Group/Dillon Consulting, Toronto-Related Region Futures Study
5.4.5
Conclusions
The projections prepared by WDI are considerably lower than the projections by
Hemson Consulting Ltd and by IBI Group. The differences are primarily due to
different expectations about migration. The WDI analysis concluded that based
on a “normal” economic environment (in which the employment-to-population is
ratio is similar to the average rate seen over the past business cycle), net migration
is highly likely to fall from recent levels, which have been bolstered by the peaking
of an economic cycle. Furthermore, the aging of the population will, in the long
term, cause the employment rate to decline, which will further reduce migration
levels. This long-term decline in migration can be interpreted as the consequence
of increased retirement, which will cause some people to leave the Inner Ring, to
return to their original communities, or to move to other communities with lower
costs of living or what they perceive to be different qualities of life.
The consequences of falling migration will be slower population growth, which
leads to decreased household formation and housing demand, and reduced employment growth.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A
Appendix
A.1
Projections of Migration by Components for 16 Census
Divisions in the Greater Golden Horseshoe
| 71
Table A–1–1: Projections of Migration by Census Division in the Inner Ring
Durham
Halton
Peel
Toronto
York
Hamilton
2001–2011
1,530
1,957
17,060
57,843
8,175
3,210
2011–2021
1,478
1,861
17,189
56,261
8,606
3,051
Immigration
2021–2031
1,446
1,792
17,559
55,494
9,151
2,936
44,545
56,099
518,079
1,695,978
259,319
91,967
2001–2011
–922
–1,223
–2,350
–5,933
–2,102
–761
2011–2021
–1,090
–1,395
–2,956
–5,787
–2,715
–786
2021–2031
–1,250
–1,540
–3,540
–5,396
–3,228
–796
–32,614
–41,584
–88,455
–171,154
–80,447
–23,434
2001–2011
608
734
14,710
51,910
6,074
2,449
2011–2021
388
466
14,234
50,474
5,890
2,264
2021–2031
197
252
14,019
50,098
5,923
2,140
11,931
14,515
429,625
1,524,824
178,872
68,533
2001–2011
–349
109
237
–672
38
–148
2011–2021
–706
–183
–469
–2,369
–223
–338
Total
Emigration
Total
Net Immigration
Total
Net Interprovincial
2021–2031
–1,079
–496
–1,224
–4,162
–502
–538
–21,338
–5,703
–14,556
–72,034
–6,868
–10,242
2001–2011
8,126
4,369
7,493
–62,953
16,822
–724
2011–2021
9,077
4,647
8,776
–67,308
14,744
–735
2021–2031
9,950
4,846
10,055
–70,568
11,836
–726
271,528
138,619
263,245
–2,008,290
434,024
–21,844
2001–2011
8,385
5,211
22,440
–11,715
22,934
1,577
2011–2021
8,759
4,930
22,541
–19,203
20,411
1,192
2021–2031
9,068
4,602
22,850
–24,632
17,258
876
262,121
147,432
678,314
–555,500
606,028
36,448
Total
Net Intraprovincial
Total
Total Net Migration
Total
Source: Will Dunning Inc.
Dunning0112.indd Sec2:79
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Dunning0112.indd Sec2:80
292
2021–2031
–155
2021–2031
137
2021–2031
–128
2021–2031
529
2021–2031
539
2021–2031
17,431
582
2011–2021
Total
622
2001–2011
Total Net Migration
15,187
509
2011–2021
Total
480
2001–2011
Net Intraprovincial
–2,483
–82
2011–2021
Total
–39
2001–2011
Net Interprovincial
4,727
155
2011–2021
Total
180
2001–2011
Net Immigration
–4,481
–150
2011–2021
Total
–143
2001–2011
Emigration
9,207
305
2011–2021
Total
323
2001–2011
Immigration
Brant
27,371
994
914
829
30,635
1,140
1,023
900
–2,209
–94
–74
–53
–1,054
–52
–36
–18
–3,394
–129
–113
–97
2,340
77
78
79
Dufferin
37,769
1,352
1,260
1,165
34,077
1,256
1,139
1,013
–1,879
–94
–62
–32
5,571
189
184
184
–2,133
–74
–72
–67
7,704
264
256
251
HaldimandNorfolk
55,363
1,619
1,847
2,070
47,628
1,641
1,598
1,523
–7,808
–450
–257
–74
15,543
428
506
621
–21,080
–706
–709
–693
36,623
1,134
1,215
1,314
Niagara
32,333
1,073
1,084
1,076
33,243
1,146
1,115
1,062
–2,147
–111
–71
–33
1,237
37
40
47
–2,072
–73
–70
–64
3,310
111
110
111
Northumberland
Table A–1–2: Projections of Migration by Census Division in the Outer Ring
38,865
1,319
1,299
1,269
43,868
1,608
1,466
1,312
–5,834
–276
–193
–114
831
–13
26
70
–4,432
–155
–149
–139
5,263
142
174
209
Peterborough
282,164
9,955
9,432
8,829
296,907
10,915
9,923
8,853
–15,135
–785
–500
–228
391
–174
9
205
–20,846
–819
–696
–570
21,236
645
704
774
Simcoe
43,085
1,492
1,443
1,373
47,118
1,679
1,578
1,455
–3,950
–178
–131
–85
–84
–8
–4
4
–1,794
–66
–60
–53
1,711
58
57
57
Kawartha
Lakes
160,953
5,630
5,475
4,991
153,474
5,614
5,234
4,500
–7,453
–387
–246
–112
14,931
403
487
603
–14,653
–567
–494
–405
29,584
970
981
1,007
Source: Will Dunning Inc.
282,143
9,586
9,513
9,115
228,653
8,411
7,741
6,713
–7,797
–579
–253
52
61,286
1,754
2,025
2,349
–38,332
–1,508
–1,280
–1,046
99,618
3,262
3,305
3,395
Waterloo Wellington
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.2
| 73
Projections of Population and Population Growth for 16 Census
Divisions in the Greater Golden Horseshoe
Table A–2–1: Projections of Population and Population Growth by Census Division in the Inner Ring
Durham
Halton
Peel
Toronto
York
Hamilton
2001–2011
526,987
390,235
1,056,167
2,592,460
759,320
510,073
2011–2021
632,368
453,014
1,365,417
2,584,667
1,029,850
533,353
2021–2031
735,735
507,535
1,669,774
2,455,240
1,267,651
544,498
Total
827,747
549,563
1,954,071
2,234,967
1,449,481
543,956
Total Population
Total Population Growth
2001–2011
105,381
62,779
309,250
–7,793
270,530
23,280
2011–2021
103,368
54,521
304,358
–129,427
237,801
11,145
92,012
42,027
284,297
–220,272
181,830
–542
300,760
159,328
897,904
–357,493
690,161
33,883
–779
27,053
2,328
2021–2031
Total
Average Annual Population Growth
2001–2011
10,538
6,278
30,925
2011–2021
10,337
5,452
30,436
–12,943
23,780
1,114
2021–2031
9,201
4,203
28,430
–22,027
18,183
–54
10,025
5,311
29,930
–11,916
23,005
1,129
Total
Average Annual % Growth
2001–2011
1.84%
1.50%
2.60%
–0.03%
3.09%
0.45%
2011–2021
1.53%
1.14%
2.03%
–0.51%
2.10%
0.21%
2021–2031
1.19%
0.80%
1.58%
–0.94%
1.35%
–0.01%
Total
1.52%
1.15%
2.07%
–0.49%
2.18%
0.21%
Source: Will Dunning Inc.
Dunning0112.indd Sec2:81
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136,542
142,618
145,135
2011–2021
2021–2031
Total
2,517
2021–2031
28,560
8,963
9,755
9,842
81,582
72,619
62,864
53,022
Dufferin
608
252
542
2011–2021
2021–2031
Total
0.58%
0.44%
0.18%
0.40%
2001–2011
2011–2021
2021–2031
Total
Average Annual % Growth
767
2001–2011
1.45%
1.17%
1.45%
1.72%
952
896
975
984
Average Annual Population Growth
16,264
6,076
2011–2021
Total
7,671
2001–2011
Total Population Growth
128,871
2001–2011
Total Population
Brant
0.51%
0.20%
0.49%
0.86%
608
248
594
981
18,226
2,477
5,939
9,810
127,730
125,253
119,314
109,504
Haldimand–
Norfolk
0.07%
–0.22%
0.08%
0.36%
305
–975
347
1,543
9,143
–9,752
3,465
15,429
435,675
445,427
441,961
426,532
Niagara
0.67%
0.16%
0.72%
1.13%
590
156
665
950
17,706
1,557
6,649
9,500
97,728
96,171
89,522
80,022
Northumberland
0.53%
0.29%
0.56%
0.74%
751
435
811
1,006
22,527
4,354
8,113
10,060
153,205
148,851
140,738
130,678
Peterborough
1.82%
1.43%
1.82%
2.21%
9,382
8,917
9,652
9,577
281,471
89,173
96,524
95,773
673,290
584,116
487,592
391,819
Simcoe
Table A–2–2: Projections of Population and Population Growth by Census Division in the Outer Ring
1.02%
0.56%
1.06%
1.44%
849
525
920
1,101
25,460
5,246
9,200
11,014
97,278
92,032
82,832
71,818
Kawartha
Lakes
1.69%
1.04%
1.68%
2.37%
4,254
3,176
4,450
5,137
127,628
31,760
44,500
51,368
322,449
290,689
246,189
194,821
Wellington
Source: Will Dunning Inc.
1.83%
1.44%
1.84%
2.23%
11,024
10,452
11,381
11,238
330,710
104,524
113,808
112,378
787,059
682,535
568,727
456,349
Waterloo
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.3
| 75
Projections of Households and Household Growth for 16
Census Divisions in the Greater Golden Horseshoe
Table A–3–1: Projections of Households and Household Growth by Census Division in the Inner Ring
Durham
Halton
Peel
Toronto
York
Hamilton
2001–2011
178,034
138,319
2011–2021
229,848
170,098
324,919
979,173
231,374
194,892
447,974
1,006,486
337,828
213,979
2021–2031
282,014
199,309
569,717
981,253
435,348
227,772
Total
325,172
221,227
680,068
912,317
510,304
233,561
Total Households
Total Household Growth
2001–2011
51,814
31,779
123,055
27,312
106,454
19,088
2011–2021
52,166
29,211
121,743
–25,233
97,520
13,793
43,159
21,918
110,351
–68,936
74,956
5,788
147,139
82,908
355,149
–66,857
278,930
38,669
2021–2031
Total
Average Annual Household Growth
2001–2011
5,181
3,178
12,306
2,731
10,645
1,909
2011–2021
5,217
2,921
12,174
–2,523
9,752
1,379
2021–2031
4,316
2,192
11,035
–6,894
7,496
579
Total
4,905
2,764
11,838
–2,229
9,298
1,289
Average Number of People Per Household
2001–2011
2.96
2.82
3.25
2.65
3.28
2.62
2011–2021
2.75
2.66
3.05
2.57
3.05
2.49
2021–2031
2.61
2.55
2.93
2.50
2.91
2.39
Total
2.55
2.48
2.87
2.45
2.84
2.33
Source: Will Dunning Inc.
Dunning0112.indd Sec2:83
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Dunning0112.indd Sec2:84
54,219
59,184
61,730
2011–2021
2021–2031
Total
2,546
2021–2031
14,288
4,175
5,143
4,969
32,108
27,932
22,789
17,820
Dufferin
497
255
449
2011–2021
2021–2031
Total
476
418
514
497
2.67
2.52
2.41
2.35
2001–2011
2011–2021
2021–2031
Total
2.54
2.60
2.76
2.98
2.27
2.37
2.52
2.73
538
322
564
726
16,125
3,219
5,644
7,262
56,171
52,952
47,308
40,046
Haldimand–
Norfolk
Average Number of People Per Household
596
2001–2011
Average Annual Household Growth
13,473
4,965
2011–2021
Total
5,963
2001–2011
Total Household Growth
48,257
2001–2011
Total Households
Brant
2.23
2.29
2.41
2.54
929
149
1,053
1,584
27,863
1,494
10,529
15,839
195,644
194,149
183,620
167,781
Niagara
2.18
2.26
2.41
2.66
488
226
539
700
14,645
2,256
5,392
6,998
44,785
42,529
37,137
30,140
Northumberland
2.28
2.33
2.42
2.55
532
328
573
694
15,949
3,283
5,726
6,940
67,249
63,966
58,240
51,300
Peterborough
2.42
2.47
2.59
2.76
4,557
4,205
4,821
4,646
136,714
42,046
48,212
46,455
278,716
236,670
188,458
142,002
Simcoe
Table A–3–2: Projections of Households and Household Growth by Census Division in the Outer Ring
2.06
2.16
2.35
2.60
656
473
729
766
19,687
4,733
7,293
7,660
47,313
42,580
35,287
27,626
Kawartha
Lakes
2.12
2.22
2.41
2.75
2,707
2,118
2,855
3,148
81,199
21,175
28,547
31,477
152,005
130,830
102,283
70,806
Wellington
Source: Will Dunning Inc.
2.39
2.46
2.56
2.73
5,401
5,150
5,607
5,446
162,033
51,502
56,075
54,456
329,352
277,850
221,775
167,319
Waterloo
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.4
| 77
Projections of Employment and Employment Growth for 16
Census Divisions in the Greater Golden Horseshoe
Table A–4–1: Projections of Employment and Employment Growth by Census Division in the Inner Ring
Durham
Halton
Peel
Toronto
York
Hamilton
2001–2011
278,120
215,532
577,771
1,299,771
408,031
245,670
2011–2021
343,679
254,723
749,838
1,295,871
562,642
261,305
2021–2031
384,436
277,033
894,066
1,190,845
670,331
257,721
Total
410,465
285,451
1,010,967
1,037,081
734,241
241,575
Total Employment
Total Employment Growth
2001–2011
65,560
39,191
172,067
–3,900
154,611
15,635
2011–2021
40,757
22,310
144,227
–105,027
107,689
–3,584
26,029
8,418
116,902
–153,764
63,910
–16,146
132,346
69,919
433,196
–262,691
326,210
–4,095
17,207
–390
15,461
1,563
2021–2031
Total
Average Annual Employment Growth
2001–2011
6,556
3,919
2011–2021
4,076
2,231
14,423
–10,503
10,769
–358
2021–2031
2,603
842
11,690
–15,376
6,391
–1,615
Total
4,412
2,331
14,440
–8,756
10,874
–137
Average Annual % Growth
2001–2011
2.1%
1.7%
2.6%
0.0%
3.3%
0.6%
2011–2021
1.1%
0.8%
1.8%
–0.8%
1.8%
–0.1%
2021–2031
0.7%
0.3%
1.2%
–1.4%
0.9%
–0.6%
Total
1.3%
0.9%
1.9%
–0.7%
2.0%
–0.1%
2001
68.1%
69.3%
70.3%
60.7%
68.1%
59.5%
2011
65.8%
67.5%
67.8%
60.2%
66.3%
58.2%
2021
62.6%
64.7%
65.2%
57.5%
63.3%
55.4%
2031
59.2%
61.5%
62.6%
54.5%
60.1%
51.9%
Employment Rate
Source: Will Dunning Inc.
Dunning0112.indd Sec2:85
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70,122
70,273
68,567
2011–2021
2021–2031
Total
2021–2031
13,565
2,624
4,458
6,483
42,210
39,586
35,128
28,645
Dufferin
15
–171
133
2011–2021
2021–2031
Total
0.0
–0.2
0.2
2011–2021
2021–2031
Total
63.0
61.6
58.6
55.9
2001
2011
2021
2031
Employment Rate (%)
0.8
2001–2011
Average Annual % Growth
553
2001–2011
61.9
65.1
68.1
70.7
1.3
0.6
1.2
2.1
452
262
446
648
Average Annual Employment Growth
3,975
150
–1,705
2011–2021
Total
5,531
2001–2011
Total Employment Growth
64,592
2001–2011
Total Employment
Brant
47.4
53.1
59.4
63.2
–0.2
–0.9
–0.3
0.6
–119
–514
–182
339
–3,564
–5,136
–1,819
3,391
51,879
57,014
58,833
55,442
Haldimand–
Norfolk
49.8
53.8
57.8
60.0
–0.4
–0.9
–0.5
0.4
–705
–1,860
–1,040
784
–21,158
–18,599
–10,395
7,836
188,511
207,110
217,505
209,669
Niagara
44.1
48.4
54.6
59.2
0.0
–0.7
–0.4
0.9
–13
–258
–157
377
–380
–2,582
–1,570
3,772
38,168
40,750
42,320
38,548
Northumberland
48.7
51.6
55.1
56.8
0.2
–0.2
–0.1
0.8
115
–135
–38
518
3,450
–1,351
–383
5,183
64,527
65,877
66,260
61,076
Peterborough
55.9
58.9
62.0
64.4
1.6
0.9
1.4
2.4
3,986
2,797
3,804
5,357
119,573
27,966
38,037
53,570
318,820
290,854
252,817
199,247
Simcoe
Table A–4–2: Projections of Employment and Employment Growth by Census Division in the Outer Ring
42.0
47.2
53.1
56.2
0.4
–0.5
0.2
1.6
144
–191
63
561
4,326
–1,910
625
5,611
37,259
39,168
38,543
32,932
Kawartha
Lakes
53.5
60.3
64.7
68.5
1.3
0.0
1.3
2.6
1,651
–34
1,908
3,080
49,538
–342
19,078
30,802
155,662
156,004
136,926
106,124
Wellington
Source: Will Dunning Inc.
63.4
66.2
67.7
67.7
1.8
1.1
1.7
2.7
5,952
4,410
6,003
7,444
178,564
44,099
60,028
74,437
424,245
380,146
320,118
245,680
Waterloo
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.5
Economic Influences on Household
Formation Rates and Household Sizes
This section analyzes household formation rates
to determine the extent to which changes in
economic variables affect household formation
rates.
In economic analysis, the usual approach is a
“time series analysis” — examining data over
many years to find the relationship between
economic change over time and changes in
household formation rates. However, since data
on household formation rates are available only
at five-year intervals, there is not enough data to
conduct a meaningful time series analysis.
As an alternative, an analysis was conducted
at two specific points (the 1996 census and the
2001 census), to see how economic variations
from location to location relate to variations in
household formation rates. An attempt was made
to draw inferences about how economic variations affect headship rates over time. However,
this analysis of household formation rates does
not lead to strong conclusions for future household formation.
Although a subsequent analysis of household
sizes led to stronger conclusions about how
economic change affects household sizes, those
results are not strong enough to predict future
household sizes.
A.5.1
2001 census data, the age groups for household maintainers are 15–24, 25–34, 35–44,
45–54, 55–65, 65–74, and 75 and over. In
the 1996 data, the oldest age category is 65
years and over. To permit comparison between the 1996 and 2001 data, in the 2001
census data, the two oldest categories (65–74
and 75 and over) were combined into a 65and-over grouping.
3. Data were obtained on population for each
corresponding age group.
4. The number of households in each age
group, divided by the population in each
age group, provides the household formation rate by age group for each of the 25
CMAs. These household formation rates
are also referred to as “headship rates.”
The census variables that were selected for
analysis (for each CMA) were:
•
Homeowner’s average monthly major
payment: expected to have a negative
impact — higher costs should result in
lower household formation rates.
•
Average monthly gross rent payment:
expected impact is negative — higher
costs should result in lower household
formation rates.
•
Employment-to-population ratio for
persons aged 15 years and older: expected impact is positive — a higher
employment rate should result in higher
household formation rates.
•
Average annual income for persons aged
15 years and older: expected impact is
positive — higher income should result
in higher household formation rates.
•
Average value of owner-occupied
dwellings: expected impact is negative
Method
The analysis was conducted using data from the
1996 and 2001 censuses.
1. Analysis was conducted for the 25 Census
Metropolitan Areas (CMAs) available in
both the 1996 and 2001 census.
2. Census data provide the number of households by the age of the “primary household
maintainer.” The data are aggregated into
age groups in 10-year increments. In the
Dunning0112.indd Sec2:87
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
— higher costs should result in lower
household formation rates.
•
Percentage of the population aged five
and over that immigrated from another
country within the past five years: possible negative impact on household
formation rates, if recent immigrants
live in larger household groupings for
cultural or economic reasons. However,
the impacts of recent immigration may
be partially found in other economic
variables, such as the income variable
or the employment-to-population ratio.
Thus, an impact from this variable
should not necessarily be expected.
Combinations of these variables were tested
(using multiple regression analysis) to determine
the extent to which the variables can explain
headship rates across the 25 CMAs. Each of the
age groups was tested separately, using data for
2001.
A.5.2
Findings for Household Formation Rates
The review of the data found some relationships between headship rates and economic
indicators. The scatter plot charts in Appendix
A.6 show the headship rates in relation to some
economic variables. The charts strongly suggest
a relationship between housing costs and household formation rates. The relationship between
household formation rates and the employmentto-population ratio is less obvious; however,
when the employment ratio is tested statistically
in combination with housing cost variables, it
appears that housing costs and the employment
ratio act in combination to influence household
formation rates.
| 80
The model that provides the most robust results
overall (using the 2001 data) analyzes headship
rates as a function of average homeowners’
monthly costs and the employment-to-population ratio. The inclusion of other variables resulted in less strong results.*
Not only did this specification provide the strongest results, but the estimated effects also had
the expected directions:
•
Owners’ cost has the expected negative
effect — higher costs result in lower
headship rates for all age groups.
•
The employment-to-population ratio
has the expected positive effect — higher
ratios result in higher headship rate for
all age groups.
In addition, the estimated impacts for the two
variables are strongest for the youngest age
groups, weakest for the age groups in the middle,
and slightly stronger for the older age groups.
This pattern makes sense. Figures 29 and 30
show the estimated factors (“coefficients”) for
the effect of the two economic variables on
headship rates, by age group.
Figure 29: Coefficients for Owners’
Monthly Costs, by Age Group
Coefficients for Owners' Monthly Cost, By Age Group
15-24
25-34
35-44
45-54
55-64
65 +
0.00000
-0.00005
-0.00010
-0.00015
-0.00020
-0.00025
-0.00030
* The other housing cost variables were highly correlated with the owners’ cost variables, and therefore their inclusion did not
improve the results.
Dunning0112.indd Sec2:88
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
Figure 30: Coefficients for Employment
Ratio, by Age Group
•
For the three younger age groups, the
economic analysis predicts relatively
large increases in the headship rates,
because homeowners’ costs fell during
the period (in inflation-adjusted dollars) and the employment-to-population ratios increased in most of the
CMAs (due to economic expansion in
most areas of the country). In actuality,
however, headship rates for the younger
age groups changed very little or fell.
Therefore, the predictions generated for
the younger age groups were far off the
mark.
•
For the three older age groups, the
predictions were more accurate, as
increases were predicted and increases
actually occurred.
Coefficients for Employment Ratio, By Age Group
0.0050
0.0045
0.0040
0.0035
0.0030
0.0025
0.0020
0.0015
0.0010
0.0005
0.0000
15-24
25-34
35-44
45-54
55-64
65 +
The analysis indicates the reliability of the estimates. In Figure 31, the “Adjusted R-Square”
statistics are shown for each of the age groups. If
the model did a perfect job of explaining variations in headship rates, the Adjusted R-Square
would be equal to 1.00. Figure 31 shows that
the reliability statistics range from 0.26 to 0.67.
The higher figures indicate a higher level of reliability, while the lower figures indicate results
that are probably unreliable.
| 81
Figure 32: Predicted vs. Actual Changes in Headship
Rates, for 25 CMAs, by Age Group, 1996 to 2001
Predicted Versus Actual Changes in Headship Rates
1996 to 2001, for 25 CMAs, By Age Group
1.60%
Figure 31: Adjusted R-Squares for
Analysis Models, by Age Group
1.40%
Average Predicted Change
1.20%
Average Actual Change
1.00%
0.80%
Adjusted R-Squares for Analysis Models, By Age Group
0.60%
0.80
0.40%
0.70
0.20%
0.00%
0.60
-0.20%
0.50
15-24
25-34
35-44
45-54
55-64
65 +
-0.40%
0.40
0.30
0.20
0.10
0.00
15-24
25-34
35-44
45-54
55-64
65 +
The next step was to use these analysis results to
simulate how the headship rates “should” have
changed during 1996 to 2001, given the changes
that occurred in the economic variables. In other
words, for each of the 25 CMAs, for each of the
age groups, the predicted changes in headship
rates were compared to the changes that actually occurred. Figure 32 shows that:
Dunning0112.indd Sec2:89
The results for the Toronto CMA are of particular interest. Figure 33 compares the predicted
increases in headship rates with the actual increases, and shows that the Toronto CMA
estimates were completely inaccurate: while
increased headship rates are predicted for all age
groups, the rates actually fell for five of the six
age groups. The magnitudes of the errors were
especially large for the two youngest age groups.
The reduction in headship rates for the 15–24
and 25–34 age groups is undoubtedly related
to the rapid rent increases that occurred after
the introduction of the Tenant Protection Act in
1/12/06 9:46:59 AM
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
June 1998. Unfortunately, in the analysis of all
25 CMAs, rents were not found to significantly
affect headship rates, as the effects of owners’
costs were overwhelming statistically. Thus, it
is not possible to test the extent to which rent
increases might have reduced headship rates in
Toronto.
Figure 33: Predicted vs. Actual Changes in Headship
Rates for Toronto CMA, by Age Group, 1996 to 2001
Predicted Versus Actual Changes in Headship Rates
1996 to 2001, for Toronto CMA, By Age Group
2.50%
2.00%
Toronto CMA - Predicted Change
1.50%
Toronto CMA - Actual Change
1.00%
0.50%
0.00%
-0.50%
15-24
25-34
35-44
45-54
55-64
65 +
A.5.3
| 82
Analysis of Household Sizes
The analysis of household formation rates (by
age group) was inconclusive. Modelling cannot
predict changes in household formation rates by
age group, especially for the younger groups.
However, analysis might generate useful results
on a less-detailed basis for each of the CMAs
as a whole, rather than for specific age groups.
Thus, an additional analysis was conducted to
examine for each of the CMAs the average number of adults per household.
The data set used is not the same as the average
number of people per household — this analysis
excludes people under the age of 15, in order to
concentrate on the people who could potentially
head their own households.
-1.00%
-1.50%
-2.00%
-2.50%
In conclusion, this analysis did not generate
results that could be used to confidently predict
future headship rates. However, the analysis
does support a theory that economic variables
do affect household formation rates, and therefore that changes in future economic conditions
are likely to influence headship rates. The directions of the influences are:
•
•
A rising cost of homeownership is likely
to reduce household formation and a
falling cost to increase household formation.
This analysis used the same set of explanatory
variables as before. The anticipated effects of
the variables are the opposites of those expected
for the headship rate analysis:
•
Homeowner’s average monthly major
payment: expected to have a positive
impact — higher costs should result in
more adults per household.
•
Average monthly gross rent payment:
expected to have a positive impact
— higher costs should result in more
adults per household.
•
Employment-to-population ratio for
persons aged 15 years and older: expected impact is negative — a higher
employment rate should result in fewer
adults per household.
•
Average annual income for persons aged
15 years and older: expected impact is
negative — higher incomes should result in fewer adults per household.
•
Average value of owner-occupied dwellings: expected to have a positive impact
A rising employment-to-population
ratio is likely to increase household
formation and a falling ratio to reduce
household formation.
If conclusions can be drawn about the likely
directions of these economic variables in future,
then conclusions could also be drawn about the
directions of headship rates.
Dunning0112.indd Sec2:90
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
— higher costs should result in more
adults per household.
•
Percentage of the population aged five
and over that immigrated from another
country within the past five years. There
may be a positive impact on household
sizes, if recent immigrants tend to live in
larger household groupings for cultural
or economic reasons.
In addition, data on the distribution of the adult
population by age was included, since different
age groups may have different household sizes.
Various combinations of the data were tested.
The model that best explains variations in the
number of adults per household uses average
owners’ costs and the employment-to-population ratio, as well as data on age distributions:
the two economic variables that were most influential in this analysis also produced the most
reliable results in the headship rate analysis.
Figures 34 and 35 show the relationships between household sizes and the two key economic
variables. In Figure 34, there is a clear relationship between the owners’ costs and the number
of adults per household, and the relationship is
quite strong, as indicated by the clustering of
most of the data points close to the trend line
and the relatively high R-Square figure of 0.545.
Moreover, the relationship has the expected
direction — higher housing costs are associated
with larger household size.
| 83
Figure 34: Number of Adults per Household
vs. Owners’ Monthly Costs, for 25 CMAs
Number of Adults Per Household Versus
Owners' Monthly Cost, For 25 CMAs
2.40
2.30
2
R = 0.545
2.20
2.10
2.00
1.90
1.80
$500
$600
$700
$800
$900
$1,000
$1,100
Monthly Cost (1996 Dollars)
In Figure 35, the relationship between household
size and the employment-to-population ratio is
weak, as the R-Square is just 0.11, and the direction is the opposite of what was expected — in
this chart a higher employment ratio appears to
result in larger household sizes, whereas the opposite is expected.
Figure 35: Number of Adults per Household vs.
Employment-to-Population Ratio, for 25 CMAs
Number of Adults Per Household Versus
Employment-to-Population Ratio, For 25 CMAs
2.40
2
R = 0.114
2.30
2.20
2.10
2.00
1.90
1.80
50
55
60
65
70
75
Employment-to-Population Ratio - %
However, when the two variables are analyzed in
combination, the direction on the employment
variable changes to the expected downward
slope, and both of the two economic variables
are found to be statistically significant in explaining variations in household size across the
25 CMAs.* Also, the two variables have roughly
equal force in causing variations of household
* The reason that the employment-to-population ratio appears to have the wrong effect when it is looked at alone is that many of
the CMAs with low employment ratios also have low housing costs, which are associated with low household sizes. When the two
variables are analyzed in combination, the employment ratio has a negative effect.
Dunning0112.indd Sec2:91
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 84
Table A–5–1: Adults per Household in 1996 and 2001, for 25 CMAs
Adults Per Household
Change from 1996 to 2001
Census Metropolitan Area
1996
2001
Actual
Change
Predicted
Change
Error
St. John’s
2.32
2.20
–0.12
–0.16
–0.043
Halifax
2.09
2.03
–0.06
–0.12
–0.056
Saint John
2.13
2.06
–0.07
–0.16
–0.088
Chicoutimi–Jonquière
2.15
2.07
–0.09
–0.22
–0.130
Québec
2.01
1.94
–0.07
–0.21
–0.144
Sherbrooke
1.97
1.91
–0.06
–0.20
–0.136
Trois-Rivières
1.99
1.94
–0.06
–0.20
–0.141
Montréal
2.01
1.98
–0.03
–0.15
–0.119
Ottawa–Hull
2.08
2.06
–0.02
–0.16
–0.139
Oshawa
2.19
2.20
0.01
–0.12
–0.133
Toronto
2.29
2.30
0.02
–0.09
–0.109
Hamilton
2.12
2.11
–0.01
–0.08
–0.071
St. Catharines–Niagara
2.08
2.05
–0.03
–0.12
–0.093
Kitchener
2.13
2.15
0.01
–0.10
–0.113
London
2.03
2.01
–0.02
–0.12
–0.106
Windsor
2.11
2.09
–0.01
–0.03
–0.020
Greater Sudbury
2.08
2.01
–0.07
–0.16
–0.092
Thunder Bay
2.07
2.01
–0.05
–0.14
–0.091
Winnipeg
2.03
2.01
–0.02
–0.13
–0.114
Regina
2.02
2.02
0.00
–0.11
–0.110
Saskatoon
2.00
2.02
0.01
–0.10
–0.109
Calgary
2.11
2.15
0.03
–0.11
–0.142
Edmonton
2.10
2.11
0.01
–0.12
–0.130
Vancouver
2.16
2.16
0.01
–0.07
–0.079
Victoria
1.96
1.95
–0.01
–0.13
–0.117
Average
2.09
2.06
–0.028
–0.133
–0.105
Source: Will Dunning Inc., using data from Statistics Canada 1996 and 2001 Census of Canada
sizes. This finding indicates that housing costs
and employment opportunities have equal impacts on household sizes and therefore on the
rate of household formation.
The next step is to assess the extent to which the
results from the 2001 data can be used to predict
the actual changes that occurred between 1996
and 2001.
Dunning0112.indd Sec2:92
Table A.5-1 presents the results from that analysis. In general, the table shows that:
•
Household sizes (as measured by the
number of adults per household) tended
to fall from 1996 to 2001, as the averages fell in 18 of the 25 CMAs. The
analysis indicates that the reduction in
household size is due to improvements
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
in both the monthly cost of owner-occupied housing (which fell in 17 CMAs)
and the improved job market (the employment-to-population ratio increased
in 24 CMAs).
•
•
Actual reductions in household sizes
tended to be much less than the amounts
predicted by the analysis of 2001 census
data. On average (using a simple, unweighted average of the 25 CMAs) the
expected reduction was –0.133 persons;
the actual reduction was –0.028, or just
one-fifth of the expected decline.
In two of the 25 CMAs, the predicted
changes were close to the actual changes — with differences of plus or minus
0.05 or less. In 16 of the CMAs, the
differences were large — plus or minus
0.10 or more.
lationships within families, especially) that are
involved. Since the changes in the economic
variables were quite large during the five-year
period, it is possible that while the process of
adjusting household sizes began, it was far from
complete by the time of the 2001 census, and
that further adjustment would continue over the
following years.
This idea can be explored further by applying
the analysis to the five Census Divisions of the
Greater Toronto Area, to estimate the amount of
adjustment that occurred during 1996 to 2001
as well as after the 2001 census, and to compare
the actual changes to what is predicted by the
analysis.
The analysis suggests the following:
•
As a consequence of the economic
changes (falling costs for homeownership and the rising employment rate), as
well as demographic change (the shift of
the population into the mid-age ranges),
the average household size “should”
have fallen by a fairly large amount
from 1996 to 2001 (by 0.095 persons
per household). However, the average
number of adults per household actually increased fractionally (by 0.014 per
household).
•
Based on the actual populations in 2001,
and based on the predicted household
sizes in 2001, there should have been
1,869,010 households in this combined
area. The actual number of households
(based on the same population figures)
was 1,780,495.
•
Therefore, there is a large estimated
shortfall of about 88,500 households
as of 2001. If household formation had
been affected to the extent predicted by
the model, housing demand in the GTA
would have been almost 90,000 units
In the Toronto CMA, the predicted change was
a significant reduction (0.109 persons) in the
average number of adults per household (implying an increased rate of household formation).
But in actuality, there was a marginal increase in
household size, despite the favourable economic
situation.
Once again, the analysis indicates that household
formation (in this case measured as the number
of adults per household) is affected by housing
costs and employment opportunities, and the
influences of these two economic variables are
in the expected direction. However, once again,
the economic variables do not do a good job of
explaining changes that occurred between 1996
and 2001.
Among the possible explanations is that this approach assumes that adjustments of household
formation rates will occur instantaneously when
economic conditions change. However, responses to economic change are likely to be gradual,
considering the range of personal choices (re-
Dunning0112.indd Sec2:93
| 85
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
| 86
Table 6.5-2: Estimation of Potential Surplus or Shortfall in Households as of 2001 Due to
Incomplete Adjustment to Changed Economic Conditions in Census Divisions of the GTA
Adults Per Household in
2001
Actual
Predicted
Number
of Adults in
2001
Durham
2.279
2.120
391,335
171,725
184,635
–12,910
York
2.570
2.461
573,540
223,185
233,019
–9,834
Toronto
2.171
2.092
2,047,660
943,075
978,793
–35,718
Peel
2.499
2.362
771,655
308,845
326,688
–17,843
Halton
2.231
2.199
298,220
133,665
135,612
–1,947
GTA
2.293
2.184
4,082,410
1,780,495
1,869,010
–88,515
CD
Number of
Households in
2001
Implied
Potential
Households
Surplus
(Shortfall) in
Households
Source: Will Dunning Inc., using data from Statistics Canada 1996 and 2001 Census of Canada
higher than actually occurred during the
1996 to 2001 period, or about 18,000
units per year higher. This leaves a large
backlog of potential housing demand
that could come into effect after the
2001 census. This backlog of demand
would be in addition to newly created
demand each year. The consequence
would be a high level of housing activity for many years to come.
number of vacant units is estimated to
have increased by 18,229 units.
•
Subtracting the change in vacancies
from the number of completed units,
the number of occupied dwelling units
(households) is estimated to have increased by 144,347, or about 40,300
units per year.
•
The adult population of the GTA has expanded, according to Statistics Canada’s
Labour Force, by 368,500. This would
result in a total adult population of
4,450,910 as of December 2004.
•
Thus, as of December 2004, it is estimated that the average number of adults
per household in the GTA is 2.312. This
is an increase of 0.020 adults per household from the 2001 census figure.
Table 6.5-2 shows the analysis of that shortfall.
Three and a half years have passed since the
2001 census, and if the “expected” adjustment
is occurring, it may be possible to find evidence
of the adjustment, by estimating the extent to
which household sizes in the GTA have changed
in the interval.
Much has changed since the 2001 census. As of
December 2004:
Dunning0112.indd Sec2:94
•
Housing completions have added an
estimated 162,576 new dwellings.
•
Vacancies have increased. Using CMHC
data on vacancies in the conventional
apartment stock and adding an estimate
of vacancy change in the rental stock
not covered by CMHC’s survey, the
Thus, while we were looking for evidence that
household size in the GTA is falling, this analysis suggests that it has actually continued to
increase.
In terms of the economic variables:
•
The monthly cost of homeownership has
increased. According to the Consumer
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
Price Index, the cost of owned accommodation in the Toronto CMA
increased by 10.5 percent during May
2001 to December 2004. The overall inflation rate was 6.7 percent. Therefore,
the cost of homeownership increased by
3.5 percent in inflation-adjusted terms.
This should tend to increase household
sizes.
•
The employment-to-population ratio
has fallen. In both the Toronto CMA
and the GTA, the seasonally adjusted
employment rate fell by about 0.9 from
May 2001 to December 2004. This
should also increase household size.
Combining these economic effects with anticipated shifts in the age structure of the population, the average number of adults per household
in the GTA should have increased by a small
amount — 0.007 adults per household — and the
average number of adults per household should
be about 2.299. The actual increase was larger
than predicted (0.020 people, almost triple the
predicted amount) and the average household
size is larger than predicted, at an estimate of
2.312 versus the predicted 2.299.
A.5.4
Conclusions
This section explored the relationship between
two measures of household formation (age-specific headship rates and the average number of
adults per household) and economic conditions.
The analysis indicates that housing costs (as
measured by the monthly cost of homeownership) and employment opportunities (measured
by the employment-to-population ratio) affect
the rate of household formation. Demographic
change (change in the age distribution of the
population) is also important. However, the
analysis explains only part of the actual change
in household formation.
Dunning0112.indd Sec2:95
| 87
From 1996 to 2001, economic conditions
were favourable — the labour market strongly
improved and homeownership costs fell (after
adjustment for inflation). This should have resulted in higher rates of household formation
and smaller household sizes. However, improvements in household formation were much less
than expected, both on a national basis and for
the GTA (where household formation rates fell
and household size increased).
Since the 2001 Census, economic conditions in
the GTA have deteriorated — the employmentto-population ratio has fallen and the real cost
of homeownership has increased. The analysis
predicts that this should result in reduced household formation and an increase in the number
of adults per household. It appears that the expected increase in household size has occurred,
but that the increase is larger than expected.
Thus, despite an earlier supposition that the
process of adjustment was ongoing, and that
household formation rates might continue to
increase, it appears that housing demand has
encountered a turning point, and that household
formation rates are more likely to weaken than
to strengthen, at least in the mid-term.
Simulations derived from the analysis models
do not do a good job of explaining the actual
changes that occurred from 1996 to 2001. This
result is not entirely surprising, as household formation rates have defied demographic and economic predictions for the past three decades.
While this analysis cannot exactly predict the
amount of change in household size, it does provide a basis for understanding the relationship
between household size and economic conditions, and therefore provides an indication of
the direction of change:
•
If housing costs rise in real terms from
2001 to 2031 (as they could), household
formation rates are likely to fall.
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
•
Dunning0112.indd Sec2:96
Increasing employment opportunities
increase household formation rates. If
employment opportunities remain at
the same level as they were over the past
business cycle, household formation
rates are unlikely to increase.
| 88
In conclusion, from 2001 to 2031, household
formation rates are not likely to rise from 2001
levels. In the body of the report, projections of
household formation assume that, over the projection period, household formation rates (by
age group) will be at the 2001 rates.
1/12/06 9:47:03 AM
| 89
ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.6
Charts of Headship Rates For 27 Census Metropolitan Areas by Age Group
A.6.1
Charts of Headship Rates For 27 Census Metropolitan Areas by Age Group Versus Owners’ Cost
25-34 - Headship versus Owners' Cost
15-24 - Headship versus Owners' Cost
55.0%
25.0%
20.0%
R2 = 0.339
52.0%
15.0%
49.0%
10.0%
46.0%
5.0%
43.0%
40.0%
0.0%
$600
R2 = 0.5182
$700
$800
$900
$1,000
$1,100
$1,200
$600
$700
$800
$900
$1,000
$1,100
$1,200
Owners' Monthly Cost
Owners' Monthly Cost
35-44 - Headship versus Owners' Cost
45-54 - Headship versus Owners' Cost
60.0%
65.0%
58.0%
62.0%
R2 = 0.3366
56.0%
59.0%
54.0%
56.0%
52.0%
53.0%
50.0%
R2 = 0.2566
50.0%
$600
$700
$800
$900
$1,000
$1,100
$1,200
$600
$700
Owners' Monthly Cost
$800
$900
$1,000
$1,100
$1,200
Owners' Monthly Cost
55-64 - Headship versus Owners' Cost
65-74 - Headship versus Owners' Cost
70.0%
65.0%
62.0%
R2 = 0.4578
67.0%
59.0%
64.0%
56.0%
61.0%
53.0%
58.0%
R2 = 0.6667
55.0%
50.0%
$600
$700
$800
$900
$1,000
$1,100
$1,200
$600
$700
$800
$900
$1,000
$1,100
$1,200
Owners' Monthly Cost
Owners' Monthly Cost
75 and Over - Headship versus Owners' Cost
75.0%
70.0%
R2 = 0.0475
65.0%
60.0%
55.0%
50.0%
$600
$700
$800
$900
$1,000
$1,100
$1,200
Owners' Monthly Cost
Dunning0112.indd Sec2:97
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ECONOMIC INFLUENCES ON POPULATION GROWTH AND HOUSING DEMAND IN THE GREATER GOLDEN HORSESHOE
A.6.2
| 90
Charts of Headship Rates For 27 Census Metropolitan Areas by Age Group Versus
Employment-to-Population Ratios
25-34 - Headship Rate versus Employment Rate
15-24 - Headship Rate versus Employment Rate
55.0%
25.0%
R2 = 0.0000
20.0%
52.0%
15.0%
49.0%
10.0%
46.0%
5.0%
43.0%
0.0%
50.0
R2 = 0.0099
40.0%
55.0
60.0
65.0
70.0
75.0
50.0
55.0
60.0
65.0
65.0%
60.0%
58.0%
62.0%
R2 = 0.0124
R2 = 0.0028
56.0%
59.0%
54.0%
56.0%
52.0%
53.0%
50.0%
50.0%
55.0
60.0
65.0
70.0
75.0
50.0
55.0
60.0
65.0
70.0
75.0
Employment-to-Population Ratio
Employment-to-Population Ratio
55-64 - Headship Rate versus Employment Rate
65-74 - Headship Rate versus Employment Rate
65.0%
70.0%
62.0%
67.0%
R2 = 0.0862
R2 = 0.1255
59.0%
64.0%
56.0%
61.0%
53.0%
58.0%
50.0%
50.0
75.0
45-54 - Headship Rate versus Employment Rate
35-44 - Headship Rate versus Employment Rate
50.0
70.0
Employment-to-Population Ratio
Employment-to-Population Ratio
55.0%
55.0
60.0
65.0
70.0
75.0
Employment-to-Population Ratio
50.0
55.0
60.0
65.0
70.0
75.0
Employment-to-Population Ratio
75 and Over - Headship Rate versus Employment
Rate
75.0%
70.0%
2
R = 0.0026
65.0%
60.0%
55.0%
50.0%
50.0
55.0
60.0
65.0
70.0
75.0
Employment-to-Population Ratio
Dunning0112.indd Sec2:98
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