Introduction
Demographic Dividend Models
Revisiting the Empirics of Age Structure, Education, and Income
The Modeling Set-Up
The Empirical Evidence
(1) | (2) | (3) | (4) | (5) | (6) | |
---|---|---|---|---|---|---|
Δlnk
it
| 0.419* | 0.582** | 0.589** | 0.564** | 0.559** | 0.492** |
[0.160] | [0.165] | [0.126] | [0.133] | [0.102] | [0.111] | |
ΔlnL
it
| –– | 0.797* | 1.479* | 1.961** | 1.609** | 1 |
[0.376] | [0.658] | [0.485] | [0.510] | (imposed) | ||
ΔlnN
it
| –– | 0.89 | 0.37 | 0.187 | 0.348 | −1 |
[0.997] | [1.052] | [1.081] | [0.979] | (imposed) | ||
\( \ln {\tilde{y}}_{it-1} \)
| –– | –– | −0.043 | −0.064 | −0.110* | −0.178* |
[0.0479] | [0.0437] | [0.0479] | [0.085] | |||
ln(L
it
/ W
it
) | –– | –– | 0.302 | 0.557* | 0.519†
| 0.178* |
[0.326] | [0.271] | [0.288] | [0.085] | |||
ln(W
it
/ N
it
) | –– | –– | 0.871 | 1.391* | 0.995 | 0.178* |
[0.790] | [0.623] | [0.619] | [0.085] | |||
Δs
it
| –– | –– | –– | 0.131 | 0.400* | 0.717* |
[0.170] | [0.177] | [0.306] | ||||
s
it – 1
| –– | –– | –– | –– | 0.0405** | 0.0671* |
[0.0128] | [0.0335] | |||||
Test for Accounting Effect: Growth Rates (p value) | –– | .1538 | .3767 | .0503 | .1350 | –– |
Test for accounting effect: Levels (p value) | –– | –– | .5035 | .0201 | .1941 | –– |
Test for Accounting Effect: Growth Rates and Levels (p value) | –– | –– | .7144 | .0505 | .3918 | –– |
Sargan Test (p value) | –– | –– | .1323 | .2457 | .5433 | .2665 |
AR(1) Test (p value) | –– | –– | .0032 | .0017 | .0026 | .0522 |
AR(2) Test (p value) | –– | –– | .1768 | .2548 | .2918 | .1741 |
Observations | 521 | 521 | 521 | 521 | 521 | 521 |
Number of Countries | 105 | 105 | 105 | 105 | 105 | 105 |
Within-Country SD | Effect on Yearly Income Growth | ||
---|---|---|---|
Full Sample | (ΔlnL
it
– ΔlnN
it
) | 2.93 % | 0.59 % |
(ΔlnL
it
– ΔlnW
it
) | 2.00 % | 0.40 % | |
(ΔlnW
it
– ΔlnN
it
) | 1.95 % | 0.39 % | |
ln(L
it
/ N
it
) | 4.98 % | 0.18 % | |
ln(L
it
/ W
it
) | 2.79 % | 0.10 % | |
ln(W
it
/ N
it
) | 3.30 % | 0.12 % | |
Δs
it
| 0.081 | 1.17 % | |
s
it
| 0.689 | 0.92 % | |
Δlnk
it
| 13.73 % | 1.35 % | |
High-Income Countries: OECD (N = 23) | (ΔlnL
it
– ΔlnN
it
) | 2.86 % | 0.57 % |
(ΔlnL
it
– ΔlnW
it
) | 2.82 % | 0.56 % | |
(ΔlnW
it
– ΔlnN
it
) | 1.40 % | 0.28 % | |
ln(L
it
/ N
it
) | 4.31 % | 0.15 % | |
ln(L
it
/ W
it
) | 3.39 % | 0.12 % | |
ln(W
it
/ N
it
) | 2.19 % | 0.08 % | |
Δs
it
| 0.065 | 0.93 % | |
s
it
| 0.560 | 0.75 % | |
Δlnk
it
| 4.50 % | 0.44 % | |
High-Income Countries: Non-OECD (N = 3) | (ΔlnL
it
– ΔlnN
it
) | 6.56 % | 1.31 % |
(ΔlnL
it
– ΔlnW
it
) | 1.56 % | 0.31 % | |
(ΔlnW
it
– ΔlnN
it
) | 5.41 % | 1.08 % | |
ln(L
it
/ N
it
) | 6.85 % | 0.24 % | |
ln(L
it
/ W
it
) | 2.58 % | 0.09 % | |
ln(W
it
/ N
it
) | 4.81 % | 0.17 % | |
Δs
it
| 0.131 | 1.88 % | |
s
it
| 0.855 | 1.15 % | |
Δlnk
it
| 12.04 % | 1.18 % | |
Low-Income Countries (N = 30) | (ΔlnL
it
– ΔlnN
it
) | 2.10 % | 0.42 % |
(ΔlnL
it
– ΔlnW
it
) | 1.12 % | 0.22 % | |
(ΔlnW
it
– ΔlnN
it
) | 1.88 % | 0.38 % | |
ln(L
it
/ N
it
) | 2.78 % | 0.10 % | |
ln(L
it
/ W
it
) | 1.51 % | 0.05 % | |
ln(W
it
/ N
it
) | 2.36 % | 0.08 % | |
Δs
it
| 0.091 | 1.31 % | |
s
it
| 0.685 | 0.92 % | |
Δlnk
it
| 13.08 % | 1.29 % | |
Lower Middle-Income Countries (N = 32) | (ΔlnL
it
– ΔlnN
it
) | 3.33 % | 0.67 % |
(ΔlnL
it
– ΔlnW
it
) | 2.07 % | 0.41 % | |
(ΔlnW
it
– ΔlnN
it
) | 2.07 % | 0.41 % | |
ln(L
it
/ N
it
) | 5.05 % | 0.18 % | |
ln(L
it
/ W
it
) | 2.18 % | 0.08 % | |
ln(W
it
/ N
it
) | 3.93 % | 0.14 % | |
Δs
it
| 0.088 | 1.26 % | |
s
it
| 0.766 | 1.03 % | |
Δlnk
it
| 12.30 % | 1.21 % | |
Upper Middle-Income Countries (N = 17) | (ΔlnL
it
– ΔlnN
it
) | 2.51 % | 0.50 % |
(ΔlnL
it
– ΔlnW
it
) | 1.83 % | 0.37 % | |
(ΔlnW
it
– ΔlnN
it
) | 1.36 % | 0.27 % | |
ln(L
it
/ N
it
) | 7.69 % | 0.27 % | |
ln(L
it
/ W
it
) | 4.31 % | 0.15 % | |
ln(W
it
/ N
it
) | 4.26 % | 0.15 % | |
Δs
it
| 0.058 | 0.84 % | |
s
it
| 0.687 | 0.92 % | |
Δlnk
it
| 10.61 % | 1.04 % |
-
Our model considers convergence in terms of output per worker, not output per person of working age, as is the case in most of the other studies. Because we had access to new data on labor force participation, this seemed the more appropriate specification in the spirit of the underlying economic growth model.
-
As a consequence of the availability of these labor force data, we explicitly included the labor force participation rate as a variable in the model. To our knowledge, this has not been done by earlier studies. This also has implications for what is defined to be the translation effect and productivity effect. If the model is specified only in terms of persons of working ages, an underlying increase in, for example, female labor force participation shows up as an increase in productivity of persons in working age. In our model, this effect can be directly measured and is interpreted as part of the translation effect.
-
Unlike earlier empirical studies on the demographic dividend, we explicitly include data on investment in our models. In the framework of the estimation of aggregate production functions, statistical tests for the existence of translation effects—such as those performed in the demographic dividend literature—would be based on misspecified models if the physical capital component is not included.3 Although potential effects of changes in the age structure on physical capital accumulation cannot be ruled out (following the rationale described in, for example, Lee and Mason 2010, 2011), our results indicate that these alone are not sufficient to explain the size of the effects that had been hitherto attributed to the demographic dividend.
-
Many of the earlier studies also included life expectancy at birth as an explanatory variable in the equations. We also did this initially, but because its effect consistently turned out to be insignificant, we decided to not include it in the table of results presented here.
-
Unlike many of the earlier studies that did include indicators of the level of education in the form of mean years of schooling of the adult population, we include both the level of the education variable and its change over time. As the results presented earlier show, this makes an important difference with respect to the importance of the education variable to economic growth. As described earlier, our analysis also uses a new and more internally consistent set of education data as provided by the IIASA-VID reconstructions.