In this broad and illuminating work, experts on public finance discuss innovations in state and local tax policy that have been implemented or considered over the course of the last three decades. The authors provide original work that analyzes whether state and local governments have...

We study the factors affecting the employment probability of temporary assistance for needy families (TANF) recipients using recent quarterly panel data from Atlanta, Georgia. A central focus of our study is to determine whether the TANF recipient's proximity to job opportunity and the...

This article develops a modeling approach for a count data set for recreational boating trips that shows a frequency of zero counts significantly higher than that expected for Poisson distributed data. As alternatives to the Poisson regression, the authors consider several parametric and...

This paper motivates, exposits, and develops the variable augmentation specification test (VAST) approach from the perspective of generalized linear exponential family, which includes several parametric families widely used in applied econometrics and statistics. The approach is equivalent to...

This paper empirically investigates whether the quantity deficit in the children of the mother’s preferred gender is compensated through their favorable treatment in terms of investment in schooling (what we call a compensating hypothesis) in an environment where schooling opportunities are...

Unlike the substance abuse studies in developed countries, tobacco consumption and its adverse effects in developing countries are poorly studied. The objective of this paper is to identify which factors influence individuals' decision to smoke cigarettes, chew tobacco and their knowledge about...

This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the unknown density of the unobserved heterogeneity. The semi-parametric hurdle model nests Poisson and negative binomial...