Headlights on tobacco road to low birthweight outcomes - Evidence from a battery of quantile regression estimators and a heterogeneous panelCreation-Date: 20080508
Low birthweight outcomes are associated with large 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 diffculty in estimating such effects is the unobserved heterogeneity among mothers and the fact that estimation of conditional mean effects seems inappropriate. Previous results, both in the medical and economic literature, suggest significant consequences for birthweight of prenatal smoking, yet the applied statistical approaches differ — a fact which does have an impact on the suggested magnitudes of the effects. The present paper provides a unified view on the estimation of relationships between prenatal smoking and birthweight outcomes with focus on quantile regression approaches. The estimations are based on a very detailed and extensive data set, and model performance is evaluated by means of Monte Carlo simulation. We thus contribute 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 models are thoroughly tested in a simulated environment, and recommendations are given regarding the appropriateness of the individual models; iii) the results are based on a detailed data set, which includes many relevant control variables for socio-economic, wealth, and personal characteristics.
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