July 2016

IZA DP No. 10072: The Demand for Season of Birth

revised version published in: Journal of Applied Econometrics, 2019, 34, 707-72

We study the determinants of season of birth of the first child, for white married women aged 25-45 in the US, using birth certificate and Census data. We also analyze stated preferences for season of birth using our own Amazon Mechanical Turk survey. The prevalence of quarters 2 and 3 is significantly related to mother's age, education, and smoking status during pregnancy. Moreover, those who did not use assisted reproductive technology present a higher prevalence of these births. The frequency of April to September births is also higher and more strongly related to mother's age in states where cold weather is more severe, and varies with mother's occupation, exhibiting a particularly strong positive association with working in "education, training, and library" occupations. Remarkably, this relationship between season and weather disappears for mothers in "education, training, and library" occupations, revealing that season of birth is a matter of choice and preferences, not simply a biological mechanism. We find that the average willingness to pay for season of birth of mothers who report to have chosen season of birth is 19% of financial wealth while for those who report not to have chosen it is only 2% and not statistically different from zero, with the former always targeting an April to September birth. In addition, the average willingness to pay for season of birth is higher among individuals, and parents, in "education, training, and library" occupations. We also document that the top-3 reasons for choosing season of birth are mother's wellbeing, child's wellbeing, and job requirements, while those in "education, training, and library" occupations rank job requirements as the most important reason. Finally, we present evidence that babies born between April and September have on average better health at birth even conditional on the observable maternal characteristics which predict selection.