intertemporal and inter-industry effects of population
TRANSCRIPT
Intertemporal and Inter-Industry Effects of Population Ageing: A General Equilibrium
Assessment for Canada
Nabil Annabi, Maxime Fougère and Simon Harvey
November, 2008
Policy Research Directorate, Labour Market Research and Forecasting
2
The views expressed in this research are solely those of the
authors and do not necessarily reflect the views of HRSDC,
nor those of the Government of Canada.
2
33
Projected old-age dependency ratio (OADR) and population growth rate in Canada
Note: OADR = Population aged 65+ relative to the working-age population
4
Outline
Objective
Methodology– Model features– Data & Calibration
Simulation Results
Concluding Remarks
4
5
ObjectiveSimulate the inter-industry and labour market effects of population ageing using a multi-sectoral life-cycle overlapping-generations (OLG) model.
Account for both the supply and demand effects of population ageing.
– Supply effect: decline in the labour force growth.
– Demand effect: structural changes in final demand due to different consumption preferences of older generations.
Examine the impact on living standards by taking into account not only the change in the OADR but also the lower population growth rate.
6
Model Features
Extended version of Fougère, Mercenier and Mérette (2007) model.
– Calibration along a balanced-growth path: account for (Harrod-neutral) labour-augmenting technical progress.
– Assume the presence of unemployment on the labour market.
– Increased heterogeneity among households: incorporate earning profiles for 25 occupations (National Occupational Matrix, NOC).
– Increase the number of generations from 7 to 15: 4-years instead of 10-years model.
– Taking into account the difference in the effective age of retirement among occupations.
7
Model Features – cont’d.Households (generations) maximize an intertemporal utility function subject to a lifetime budget constraint.
– The representative household values consumption and bequests.
A representative competitive firm in each of the 14 industrial sectors using intermediate goods, hired labour and rented physical capital in the production process.
– The aggregate intermediate input is a CES function of goods produced across industries.
– Labour factor is composed of 25 occupations, combining 10 occupational groups and 5 qualification levels.
– Aggregate labour is also represented by a CES function of 3 types of labour with high, medium and low elasticity of substitution.
8
Figure 1. Nesting in Sectoral Production
CES : constant elasticity of substitutionL : low elasticity of substitution M : medium elasticity of substitution H : high elasticity of substitutionB,C,D: qualification levels in the NOC matrix
Production
Value AddedIntermediate Consumption
Cobb-Douglas
Prod. 1
Prod.14
… CES
Capital Labour
Cobb-Douglas
CES-L
……
… ………
Type 3
Prof. 7 Prof. 8 Prof. 9
CES-M
B C D B C D B DC
CES-H CES-H CES-H
…
9
Model Features – cont’d.Following Blanchflower and Oswald (1994), a “Wage curve” depicts a negative relation between the real wage rate and the occupation-specific unemployment rate.
– Local unemployment rate is considered as one of the determinants of the wage rate.
– Wages tend to be higher on a labour markets with lower unemployment rate.
– Wage-unemployment elasticities based on the estimates in Decaluwé, Lemelin, Bahan and Annabi (2005).
A consolidated government levies taxes to finance expenditures.
– Public education and health expenditures fixed per head in each age group budget shift in favour of health as population ages.
An intermediary represents the pay-as-you-go pension system.
10
Table 1. Base run statistics
Labour CapitalPrimary 3.3 34.4 34.4 65.3Man. & utilities 20.8 32.0 53.2 46.6Construction 14.8 66.8 77.3 22.6Transp. & stor. 2.2 24.4 65.0 34.8Communication 1.8 42.5 48.6 51.2Wholesaling & ret. 9.2 59.0 74.0 25.9Fin., ins., & RS serv. 10.8 55.7 29.6 70.1Serv. to firms 4.8 75.7 70.2 29.6Comput. & serv. 3.2 77.4 70.2 29.6Public. adm. 11.0 69.4 85.6 14.4Education 3.4 63.4 84.1 15.9Health 6.6 64.8 70.3 29.6Accom. & leis. 1.5 16.5 75.0 24.9Other serv. 6.7 73.4 79.4 20.6
Share in sectoral GDP at factor cost ofShare of sectoral
GDP at factor cost
Share of sectoral GDP at factor cost
in gross output
Source: Input-Output tables, Statistics Canada
Data & Calibration
11
Source: Labour force survey, Statistics Canada
Table 2. Labour demand by sector and occupation (share, %)
12
Table 2. cont’d.
Source: Labour force survey, Statistics Canada
13
Figure 2. Distribution of public expenditures on education and health per age group (share, %)
Source: Annabi, Harvey and Lan (2007), HRSDC.
14
Figure 3: Spending shares by sector and age group (%)
Source: Survey of Household Spending, Statistics Canada
15Source: Census 2001, Statistics Canada
Figure 4. Occupation-specific earnings profiles
16
Population ageing implies a slower labour force growth which causes a change in factors remunerations:
– rise in wage rates;– capital becomes relatively more abundant and its rental rate declines.
Combined change in wages and rental rate would affect production costs and market prices.
– Change in factors reallocation across sectors (subtit. of capital to labour)– Substitution in consumption.
On the other hand, changes in remunerations will affect household’s income:
– change in aggregate private demand and savings; – and ultimately investment.
Simulation Results: transmission channels
17
Population ageing would shift private demand in favour of the service goods.
– At the sectoral level, production would expand more in sectors with lower labour share in value-added (GDP at factor cost).
– Demand effect is expected to mitigate the long-run negative impact on the (labour intensive) service industries compared to the rest of the economy.
Lastly, the profession used intensively in the more expanding industries will benefit the most in terms of remuneration rate.
– The decline in population growth rate will be accompanied by a decrease in the unemployment rate which will further increase pressures on wages.
Transmission channels - cont’d.
18
Macro effects
19
Figure 5: Macro effects (Annual average % growth rate)
Simulation results.
20
Figure 6: Impact on factors remunerations (% change from 2006)
Simulation results.
21
Figure 7: Impact on the unemployment rate (Percentage point change from 2006)
Simulation results.
22
Figure 8: Impact on GDP and GDP per capita(Annual average % growth rate)
Simulation results.
Note: The exogenous labour productivity growth is set equal to the 1996-2006 historical average of 1.9% per year.
23
Inter-industry effects
24
Figure 9: Base run sectoral labour share and long-run impact on market price
Simulation results.
25
Figure 10: Long-run impact on sectoral production and market price
Simulation results.
26
Figure 11: Long-run impact on factors reallocation(% change from 2006)
Simulation results.
Note: Data sorted by increasing change in production.
-20
-10
0
10
20
30
40
50
60
70Production (detrended) Labour demand Capital demand (detrended)
27
Labour market effects
28Simulation results.
Management & skill level A Skill level B
Figure 12: Impact on unemployment by occupation and skill level (level, %)
29Simulation results.
Figure 12: Impact on unemployment by occupation and skill level –cont’d.
Skill level DSkill level C
30
Table 3: Impact on unemployment and wages by occupation
Simulation results.
Management - 1.9 -84 17Bus., fin. & adm. A 1.7 -88 16
B 3.0 -87 16C 4.2 -86 15
Nat. & app. sciences A 1.7 -65 13B 3.7 -62 12
Health occupations A 0.2 -50 12B 1.2 -75 15C 1.8 -67 14
So. scien., edu., gov. A 2.6 -65 13B 2.8 -75 16
Art, culture, rec. & sports A 2.9 -72 16B 6.0 -55 10
Skill level
Base run unemployment rate
(2006)
Unemployment rate (% change from
2006)Wage rate
31
Table 3: Impact on unemployment and wages by occupation – cont’d.
Simulation results.
Sales and services B 3.6 -69 12C 5.5 -67 11D 6.3 -57 9
Trades, tra.& equip.oper. B 5.2 -44 10C 5.5 -55 10D 9.9 -27 7
Occup. in prim. ind. B 5.8 -71 15C 5.8 -74 13D 22.0 -36 6
Processing, man. and ut. B 3.0 -67 11C 7.5 -49 8D 11.1 -43 7
Skill level
Base run unemployment rate
(2006)
Unemployment rate (% change from
2006)Wage rate
32
Lower labour productivity growth– Average growth is much lower, however, the long-run drop in growth
rates remain similar to that under the baseline scenario;– The decline in unemployment rate is larger leading to higher pressure on
wages.
Higher intertemporal elasticity of substitution – Average growth rates are lower, but the difference with respect to the
baseline is small;– Slower growth in investment which mitigates the relative scarcity of
labour, resulting in lower pressure on wages.
Higher elasticities of substitution in the CES (labour) nesting– The macro and sectoral effects are similar to the baseline scenario;– Small differences in real wages at the occupational level.
Sensitivity tests
33
Concluding remarksAt the aggregate level, population ageing lowers effective labour supply and decreases saving and investment in physical capital.
– The unemployment rate decreases by 2.7 percentage points in the long run, leading to an increased pressure on wages (+12% on average).
– In the long run, GDP and GDP per capital growth rates would fall by nearly 1.5 and 1 percentage point, respectively.
At the sectoral level, production costs would increase more in the labour intensive sectors
– Production would expand more in sectors with lower labour share in value-added (GDP at factor cost) Primary Industries, and Finance, Insurance and Real Estate.
– Demand effect would mitigate some of the long-run negative effects on labour-intensive service industries Health, Accomodation and Leisure, Other servicesand Transport and Storage industries.
34
Concluding remarks – cont’d.
Real wage pressures will rise across all occupational groups.
– Wage pressures in Management occupations, Business, Finance and administration, health, social science, and education as well as in Occupations in Primary industries would be well above average.
– Wage pressures in Processing, Manufacturing, Sales and Trades could be below average.
Under various assumptions about the model parameters, the sensitivity tests show that the conclusions remain similar to those under the baseline scenario.
35
( )15
1 1, 1 , 1 15 15, 1
1 1Max , 0, 01 1t t
g
t g t g g g t g g gTC Rbeq gU TC RBeqθ θ θβ β β
θ ρ− −+ − + − ≠ =
=
⎛ ⎞= + = >⎜ ⎟− +⎝ ⎠
∑
1, 1 , ,
, , , ,
, ,
(1 ) int
(1 ) (1 )
(1 )
kg t g t t t g t
w wt t gj t t g t g t g t
ct g t g t
Lend Lend R Lend
cr Linc Pens Inh Beq
Pc TC
τ
τ τ
τ
+ + − = −
+ − − + − + −
− +
( ), , , , , , , , , , , , , ,1qual supgj t itype iprof iqual t itype iprof iqual t itype iprof iqual gj gj itype iprof iqual gj t
itypeiprofiqual
Linc w u L EP AAR= −∑
s.t
Annex 1: Household’s optimization program
36
Annex 2: Spending shares by sector and age group
Calibration data.