1. A New Empirical Evidence of the Relationship Between Population Aging and Economic Growth
Chong-Bum AN
Department of Economics, Sungkyunkwan University
&
Seung-Hoon JEON
National Assembly Budget Office (NABO)

2. Motivation
To explore how population aging affects economic growth in 25 OECD countries.

3. Backgrounds The demographic changes in OECD countries.
 Fertility rates in almost all OECD countries have declined to
the rate below 2.1, which is a critical level for maintaining
a stable population.
 Life expectancy has dramatically increased from 66 in 1960s
to 77 now.
 The share of the old-aged population is expected to double over the next 50 years in the major industrialized countries. (UN)
Such a drastic demographic change could have a significant impact on Economic growth.

4. Previous Researches Rostow(1990):
Using data for the year 1965 from 76 countries
Birth rates and death rate are negatively correlated with per capita GNP.
 Population aging increases per capita GNP in 76 countries.
Bloom et al. (1999):
Asia Countries.
Demographic variables had placed a large role in East Asia’s economic success.
Cutler et al. (1990) :
United States.
Demographic changes could improve American standards of living in the near future, but lower them slightly over the very long term.
Turner et al.(1998), McMorrow and Roeger(1999), and Kotlikoff et al.(2001):
the standard of living, which is approximated by GDP per capita, grows less
if demographic pressures were absent.

5. Previous Researches These results imply that
1) Demographic changes may have a positive impact
on the less developed countries, in which the population
aging is not that serious,
2) Demographic changes may have a negative impact
on the developed countries, in which the population
aging is very serious.
 We may observe that population aging and economic growth have the invert-U shaped relationship.

6. Population Aging in OECD Countries
<Table 1>
In most countries except Mexico and Turkey,
the share of the aged is over 7% in (Aging Society)
In 15 Countries among the aging society,
the share is over 14% (aged society)
We can find that most of OECD countries were aging or aged
society and became aging society during the period

7. Population Aging in OECD Countries
<Table 2> Changes in the Old Age Dependency Ratio:
the population aged 65 and over as a percentage of the working-age population of aged
In average, the old age dependency ratio increases from in 1960 to in 2000.

8. Estimation Method Panel Data Analysis Nonparametric Kernel Fit
 While using the Nonparametric Kernel Fit with the panel data set, it seems better to interpret the result as a relationship between changes in Aging and GDP per capita rather than as a relationship between the levels of aging and GDP per capita
Nonparametric kernel regression has the problem not to control the other time-variant variables that affect the dependent variable.
 Thus, when we interpret the results, we have to consider the results from panel data analysis and results from nonparametric kernel regression simultaneously.

9. Estimation Method
Simultaneous Equation Estimation using Panel Data Analysis
 In order to explore the channel of the population aging to Economic Growth, we estimate the simultaneous equations model by two stage least squares.
 Step 1: Regress on the full set of group dummy variables and all Xs. Compute predicted values.
 Step 2: For the jth equation, regress on the group dummy variables, the Xs that appear in that equation, and the predictions of the other endogenous variables.

10. Results of the Panel Data Analysis 1
Spec. 1
Spec. 2
Spec. 3
FEM
REM
OAGDEP
0.1017
***
0.0998
0.2376
0.2209
0.4575
0.3962
(0.0032)
(0.0031)
(0.0188)
(0.0179)
(0.0627)
(0.0600)
OAGDEP2
(0.0005)
(0.0036)
(0.0035)
OAGDEP3
0.0002
(0.0000)
(0.0001)
R-square
0.7971
0.5031
0.8075
0.5248
0.8101
0.5291
LM-test
66.58***
61.32***
60.96***
Hanuman
8.22***
83.74***
***
Note: standard errors in ( ).  *: 10%, **: 5%, ***: 1% significance level

11. Results of the Panel Data Analysis 1
linear specification between OAGDEP and LPGDP in spec.1 appears a significantly positive relationship.
The quadratic specification in spec.2 results in a significant the inverted-U shape.
The cubic specification in spec. 3 is also significant and the cubic term has a positive sign.
 It is very difficult to interpret these results and to show the shape of the relationship between OAGDEP and LPGDP.
 Thus we employ the nonparametric kernel regression, to find the shape of the relationship between OAGDP and LPGDP.

12. Non Parametric Kernel Regression

13. Non Parametric Kernel Regression
<Figure 1> shows that S-shaped relationship between changes of OAGDP and LPGDP.
Excluding the incipient stage, whose number of observations is very small, the changes of OAGDEP and LPGDP have the inverted-U shaped relationship, i.e. LPGDP increases at decreasing rate with changes of OAGDEP grow.
 This result explains why all specifications in panel data analysis are significant.

14. Panel Data Approach 2
We investigate the shape of the relationship between population aging and economic growth
 under the model of Log GDP per capita (LGDP),
in which saving rate (CSAVE), labor force participation rate (P1564R),
government expenditure per GDP(GOV), import and export per GDP(OPEN)
and Old age dependency ratio (OAGDEP) are used as explanatory variables.

15. Panel Data Approach 2 Variables Dependent variable (LGDP) :
log GDP per capita expressed in 1996 Purchasing Power Parities(PPP)
- Saving rate (CSAVE) : Current saving per GDP
Labor Supply(P1564R) : Labor Supply is proxied by the rate of the
working-age population (age 15 to 64) to the total population.
- Government expenditure (GOV) : Government share of GDP
- Indicators of the openness (OPEN) : import and export per GDP.
Indicators of the Aging (OAGDEP) : Old age dependency ratio is used
for the indicators of the aging.

16. Panel Data Approach 2 Spec. 1 Spec. 2 Spec. 3 CSAVE P1564R GOV OPEN
OAGDEP
OAGDEP2
OAGDEP3
0.0127
(0.0010)
0.0465
(0.0023)
(0.0013)
0.0047
(0.0004)
0.0713
***
0.0118
0.0419
(0.0024)
0.0054
0.1416
(0.0115)
(0.0003)
0.0114
(0.0011)
0.0420
0.1914
(0.0384)
(0.0022)
0.0001
(0.0000)
0.9326
0.9340
0.9347
Note: standard errors in ( ).  *: 10%, **: 5%, ***: 1% significance level

17. Panel Data Approach 2 All the variables have reasonable signs.
 The signs of the saving rate, labor supply and the openness
are positive.
 The sings of the government expenditure per GDP is negative.
The linear specification in spec.1 appears a significantly positive relationship.
The quadratic specification in spec.2 results in a significant the inverted-U shape.
The GDP per capita increase at the decreasing rate as old age dependency rate goes up.
 i.e. the growth rate of the GDP per capita decreases
as old age dependency ratio goes up.

18. Simultaneous Equations Estimation
PGDP
SAVING
P1564R
GOV.
OPEN
OAGDEP
OAGDEP2
OAGDEP3
0.0011
(0.0004)
0.0024
(0.0015)
(0.0016)
0.0101
0.2460
( ) *
***
(0.1029)
(0.0377)
0.0892
(0.0102)
(1.1097)
(0.0630)
(0.0012)
(0.0601)
1.7147
(0.1922)
0.0051)
Adj. R square
0.9015
0.6690
0.6434

19. Simultaneous Equations Estimation
These estimation results show us how population aging affects economic growth.
First, we can find the direct channel. The old age dependency ratio affects the log GDP per capita directly in the shape of invert U-shape.
Second, the old age dependency ratio affects the log GDP per capita via labor supply.
 The old age dependency ratio and labor supply together present the invert
U-shape relationship.
 Labor supply and log GDP per capita show the positive linear relationship.
 Thus the relationship between old age dependency ratio and log GDP per
capita has the invert U-shape relationship.
The channel of the old age dependency ratio to log GDP per capita via saving rates is not significant.

20. Concluding Remarks
we investigated the shape of the relationship using the panel data analysis method and nonparametric kernel fit.
 Estimation results reported in <table 4>, <figure 1>, and <table 5> showed that the GDP per capita increased at the decreasing rate as old age dependency rate rose. (i.e. the growth rate of the GDP per capita decreased.)
Simultaneous Equations Estimation
 The old age dependency ratio affects the log GDP per capita directly in the shape of invert U-shape.
 The old age dependency ratio affects the log GDP per capita via labor supply.