The long-run determinants of fertility: one century of demographic change 1900–1999

Abstract

We examine the long-run relationship between fertility, mortality, and income using panel cointegration techniques and the available data for the last century. Our main result is that mortality changes and growth of income contributed to the fertility transition. The fertility reduction triggered by falling mortality, however, is not enough to overcompensate the positive effect of falling mortality on population growth. This means that growth of income per capita is essential to explain the observed secular decline of population growth. These results are robust to alternative estimation methods, potential outliers, sample selection, different measures of mortality, the sample period, the inclusion of education as an explanatory variable, and the use of different data sets. In addition, our causality tests suggest that fertility changes are both cause and consequence of economic development.

Assortative mating and differential fertility by phenotype and genotype across the 20th century

“…Just as observations have been made regarding the changing patterns of spousal assortment, demographers have documented declines in fertility rates during the 20th century (23). Economic models suggest that the most powerful social (distal) correlates of fertility are child survival and female education, both of which are negatively related to fertility in developed countries (24)(25)(26)(27)(28). Meanwhile, twin and molecular genetics studies find that fertility is also influenced by genetic factors (29), although somewhat less so than…”

The Political Economy of Public Investment When Population is Aging A Panel Cointegration Analysis

“…Under these assumptions the error term ε it becomes non-stationary potentially resulting in distorted t-statistics that falsely indicate statistical significance (Entorf, 1997;Granger and Newbold, 1974;Phillips, 1986). If public investment and the elderly voter share by contrast are cointegrated (which means both variables are non-stationary but a linear combination of them is stationary) some favorable properties apply such as the robustness of panel cointegration estimators against omitted variables and reverse causation (Herzer et al, 2012).…”

“…Bronzini and Piselli, 2009;Herzer et al, 2012). Granger causality is not restricted to be unidirectional, in fact, both variables might be actually endogenous.…”

“…Moreover, results from an error correction model suggest long-run Granger causality running exclusively from aging to public investment. The use of a reduced-form model is justified, because cointegration relationships are invariant to model extensions (Herzer et al, 2012;Lütkepohl, 2007). Adding control variables typically considered in the literature indeed leaves our results broadly unchanged.…”

Mortality versus morbidity in the demographic transition

“…Angeles (2010) finds, using data on TFR and NFR, that net fertility fell due to falling child mortality and income growth had little explanatory power. Using data on the crude birth rate, Herzer et al (2012) find the reverse, that mortality declines alone were insufficient to reduce net fertility, economic growth was necessary. In our model income has no effect on fertility.…”