Mankiw, N. Gregory, David Romer, and David N. Weil, “A Contribution to the Empirics of Economic Growth,” Quarterly Journal of Economics, Vol. 107 (May 1992), pp. 407 -37.
Sarel, Michael (1994a). “On the Dynamics of Economic Growth” (Ph.D. dissertation; Cambridge, Massachusetts: Harvard University, 1994).
Sarel, Michael, (1994b), “On the Dynamics of Economic Growth,” IMF Working Paper 94/138 (Washington: International Monetary Fund, November 1994).
Summers.Robert, and Alan Heston, “The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950–1988.” Quarterly Journal of Economics, Vol. 106 (May 1991), pp. 327–68.
Michael Sarel is an Economist in the Research Department. He graduated from the Hebrew University of Jerusalem and received a Ph.D. from Harvard University. This paper draws on the author’s Ph.D. dissertation (Sarel (1994a, Chapter 3)). The author thanks Robert Barro and the participants in the Macro– Growth Seminar at Harvard for helpful comments on an earlier draft.
The PWT–5.5 database is an updated version of the PWT–5.0 database, published by Summers and Heston (1991).
The set of countries for which we have information before 1960 is much smaller. It does not include many less developed countries, and in particular many African countries.
Alternatively, we could use directly the GDP per person data from the PWT–5.5 database. The two measures are almost identical. For consistency, we decided to use the United Nations’ database for all demographic data.
This may happen if these people require the time resources or the physical resources of people in other age groups. These resources could otherwise be used in production.
Another way to look at this problem is the following: The three factors that affect population dynamics are fertility, mortality, and migration. We assume that these three factors respond only to income per person and not to the rate of growth. A 5–year period is short enough to assume that changes in income per capita caused by differences in growth rates are small enough and recent enough to affect any one of these three factors. If there is reverse causality, the estimated productivity of the different age groups will be affected. For example, if life expectancy responds immediately to changes in income, the model will overestimate productivity at old age.
This significant difference is evident in Figure 1. It is important to note that the relevant source for this conclusion is Figure 1. and the standard error that it calculates using the variance–covariance matrix, and not the estimated coefficients in Table 2 The estimated coefficients of al and a2 in Table 2 have low r–statistics because of the negative correlation between the two coefficients. The magnitude of this correlation depends on the particular choice of the reference age group we previously made.
The effective labor supply is a relative measure and should be compared with the value 1, which is the effective labor supply that corresponds to the average demographic distribution in the sample.
Both databases described in this section. the “effective labor supply” (ELS) database and the “adjusted for demographic dynamics” (ADD) database, are in ASCII IBM format and are available upon request.