Relevant Literature

We briefly discuss some of the recent studies that found contrary evidence to this prediction from the Ben Porath (1967) model. While examining the consequence of diseases for economic development based on the prediction from neoclassical growth models, Acemoglu and Johnson (2006, 2007) exploited cross-country variation in mortality reduction from global

epidemiological intervention in the 1940s, and reported that increased life expectancy did not affect average years of schooling.⁶⁹ Bloom, Canning, and Fink (2014) suggested that controlling for initial health is critical since countries with poor initial health endowment experienced most improvement from mortality reduction but did not exhibit a similar increase in completed years of schooling. In another cross-country study, Lorentzen, McMillan and Wacziarg (2008) failed to observe any statistically significant impact of life expectancy at birth on secondary schooling.

Both of these two studies examined the effect of life expectancy on the stock of schooling years in a country (Cohen and Leker 2014). Note that life expectancy at birth is a decisive factor

69 The explanation lies in the higher fertility in response to an improved health, at least in the initial stage of

development. Unexpectedly large cohorts will face depressed earnings from a crowding of more individuals into the market, particularly if different birth cohorts are not perfect substitutes in production. To the extent that the potential for crowding in is expected, individuals in cohorts with rising life expectancy will moderate their human capital investment decisions to reflect anticipated depreciated earnings per unit of human capital.

for schooling decision of younger cohorts and not relevant for people who have already

completed their schooling. In our birth-cohort framework, we avoid such aggregation by relating life expectancy at birth in period t with completed years of schooling of only cohort born in t.⁷⁰

In another influential study, Hazan (2009) included retirement into the Ben Porath model, and derived a necessary condition that increased life expectancy has to increase lifetime labor supply to raise lifetime earnings because increased schooling is not a rational decision otherwise.

As a supporting evidence, he noted that American cohorts born between 1840 and 1970 did not exhibit an increase in labor supply, from which he concluded that increases in life expectancy do not cause a rise in human capital investment through schooling. Hazan (2012) reinforces this view by studying cross-country data for the later part of the twentieth century, in which he finds positive and significant association between life expectancy at birth and schooling while such correlation goes away once life expectancy at age 5 or 10 replace the life expectancy at birth.

Note that although life expectancy at birth exhibits higher variation across countries due to high rate of child and infant mortality, life expectancies at higher ages are more likely to be

endogenous since parents make investment into children health. If such investments are not controlled in an empirical analysis, the life expectancy effects on schooling will be biased. In this study, we address this issue by choosing observations at the birth cohort level.

According to the Ben-Porath framework, the longer time spent in school in response to a higher life expectancy at birth can increase lifetime earnings because the individuals enter the labor market with an increased stock of human capital. The resulting gain in lifetime earnings from increased human capital stock can offset the reduced earnings from decreased labor supply, which suggests that increased labor supply does not need to be a necessary condition in Ben

70 In contrast to our birth-cohort strategy, Hansen (2013) adopted a school-cohort based strategy and their schooling measures are not constructed from completed years of schooling.

Porath model. Cervellati and Sunde (2013) revisited Hazan’s model and data. They argued that

Hazan adopted a special case of Ben Porath model, and the fall in expected lifetime labor supply by successive cohorts of US men born between 1840 and 1930 was actually due to the fact that the cohorts spent more time in school and delayed entry into the labor market. The decreased lifetime labor supply indicates to the possibility of increased leisure as well. The increased lifetime earnings in response to a rise in life expectancy at birth implies that individuals in successive cohorts can afford more leisure. Heckman (1976) theoretically demonstrated that increased human capital investment, decreased labor supply, and higher consumption of leisure is consistent in an extension of Ben-Porath model with endogenous leisure.

In a micro-empirical study, Bleakley (2010a) compared the cohort’s schooling across sites with different malarial intensity both before and after the malaria eradication campaign in several South American countries and Mexico. The impact on schooling is mixed, in fact, in one country he noted that cohorts born after the malaria eradication obtained less schooling. In another study, Cutler et al. (2010) reported that there was no statistically significant relationship between schooling and health improvement among post malaria eradication cohorts in India. Several arguments exist that would explain such an inconclusive findings on schooling (Costa 2014;

Bleakley et al. 2014). Better nutrition increases the number of healthy workers who are more productive in unskilled works as well as better performers in school as they learn faster. Now, whether improved health would have a positive impact on education actually depends on

whether the economy is brain or brawn based. In the later type, demand for physical labor is high which implies that marginal cost of time spent in school to be higher compared to a brain based economy. Consequently, improved health in such economy might not lead to higher average schooling in the population (Pitt et al. 2012).

There is a view that significant association between economic outcome and life

expectancy at birth in cross-country regression based studies is merely a correlation rather than causal effect because of some omitted or unobserved decisive factors. Some studies have argued that better educated individuals with higher income would be more knowledgeable to spend more in preventive health care and medical expenditure and health thus might be associated with income and education in the other direction. However, studies could not reach a conclusion on this. For example, Clark and Royer (2013) did not find any positive impact of British education reform on health although it reported such changes increased wages and educational attainment.