We examine whether state government responses to rising Medicaid costs cause reduced low income assistance, overall state budget cuts, or higher taxes. We segment Medicaid recipient groups into families, the disabled, and the elderly. Using GMM estimation, we instrument for endogenous program...

Measurement error in an independent variable is one reason why OLS estimates may not be consistent. However, as shown by Dagenais (1994), in some circumstances the OLS bias may be ameliorated somewhat given the presence of serially correlated disturbances, and OLS may prove superior to standard...

We suggest and compare different methods for estimating spatial autoregressive panel models with randomly missing data in the dependent variable. We start with a random effects model and then generalize the model by introducing the spatial Mundlak approach. A nonlinear least squares method is...

Most of the estimators suggested for the estimation of spatial autoregressive models are generally inconsistent in the presence of an unknown form of heteroskedasticity in the disturbance term. The estimators formulated from the generalized method of moments (GMM) and the Bayesian Markov Chain...

In this paper, we introduce the one-step generalized method of moments (GMM) estimation methods considered in Lee (2007a) and Liu, Lee, and Bollinger (2010) to spatial models that impose a spatial moving average process for the disturbance term. First, we determine the set of best linear and...

In this study, we evaluate the impact of the French Zones Franches Urbaines on economic activity. This public-funded place-based program, comparable to US enterprise zones, exempts businesses from taxes for a period of at least five years. For the purpose of this evaluation, we merged several...