Another reason that population growth under GET and FT scenarios is higher than under the RTFR scenario is because increasing the education transition rate reduces the mortality rate and, as described above, life expectancy is higher among more educated people.
For instance, the population death rate by year 2051 is 14.4 per thousand under the RTFR Scenario, significantly higher than under the Constant Scenario (12.5%o), although the life expectancy is the same.
Through reducing fertility to the level of today's wanted fertility by the year 2021, the proportion of population in the labor force under the RTFR Scenario will quickly increase to above 59 percent by the year 2021 and will hit a peak of about 63 percent by the year 2041.
To test the robustness of the results of the cointegration analysis in the previous section, we conduct a sensitivity analysis by employing the RTFR and the CBR as alternative measures for TFR.
TABLE 1 Summary Statistics of Fertility Rate, HPs, FLFPRs, and FW and MW rates Variable Definition N Mean TFR Total fertility rate 35 1,676.20 RTFR Revised total fertility rate 35 1,677.91 CBR Crude birth rate 35 13.17 HP House price index 35 0.54 FLFPR Female labor force participation rate 35 0.47 FW Female daily wages 35 357.94 MW Male daily wages 35 536.26 Variable SD Minimum Maximum TFR 740.86 927 3,459 RTFR 739.71 901 3,459 CBR 4.14 6.90 19.70 HP 0.32 0.13 1.10 FLFPR 0.03 0.43 0.52 FW 140.58 186.75 622.49 MW 187.73 295.76 898.46 Notes: Data sources and variable constructions are given in Table A1.
Thus, for example, OWN has a greater total effect on RTFR and M than its structural coefficients would indicate, because its coefficient has the same (positive) sign in both equations.
(17) In this process, we substituted the right side of the migration equation for MLAG in equation (1.1) and the right side of the fertility equation for RTFR in equation (2.1).