Evidence from a battery of quantile regression estimators
Low birthweight outcomes are associated with considerable social and economic costs, and therefore the possible determinants of low birthweight are of great interest. One such determinant which has received considerable attention is maternal smoking. From an economic perspective this is in part due to the possibility that smoking habits can be influenced through policy conduct. It is widely believed that maternal smoking reduces birthweight; however, the crucial difficulty in estimating such effects is the unobserved heterogeneity among mothers and the fact that estimation of conditional mean effects seems potentially inappropriate. We provide a unified view on the estimation of relationships between prenatal smoking and birthweight outcomes with quantile regression approaches for panel data and emphasize their differences. This paper contributes to the literature in three ways: (i) we focus not only on one technique, but provide evidence from several approaches and highlight a variety of statistical issues; (ii) the performance of the methods are thoroughly tested in a simulated environment, and recommendations are given on their appropriate use; (iii) our results are based on a detailed data set, which includes many relevant control variables for socio-economic, wealth, and personal characteristics.
Empirical Economics, 2013, Vol 44, Issue 3, p. 1593-1633
Quantile regression; Low birthweight; Panel data; Unobserved heterogeneity; Quantile regression Low birthweight Panel data Unobserved heterogeneity SCHOOL PERFORMANCE CIGARETTE-SMOKING EXPOSURE CHILDREN HEALTH PREGNANCY MARKET