This paper studies the spatial random effects and spatial fixed effects model. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We...

While interest in social determinants of individual behavior has led to a rich theoretical literature and many efforts to measure these influences, a mature social econometrics has yet to emerge. This chapter provides a critical overview of the identification of social interactions. We consider...

Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level. As a result, the need for economic forecasts at a sub-national level is rapidly increasing. The data available to compute regional forecasts is usually based on a pseudo-panel that...

This paper provides a systematic analysis of identification in linear social interactions models. This is both a theoretical and an econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game that...

This paper considers the estimation of binary choice panel data models with discrete endogenous regressors. We present a switching probit model which accounts for selectivity bias as well as for other forms of time invariant unobserved heterogeneity. Individual effects are allowed to be...

Involuntary job loss in administrative data is commonly identified by focusing on mass-layoffs or plant closures. However, such events usually do not happen without prior knowledge, which potentially leads to selection in the labor turnover of distressed firms. We find that workers separating...

This paper presents a generalized moments (GM) approach to estimating an R-th order spatial regressive process in a panel data error component model. We derive moment conditions to estimate the parameters of the higher order spatial regressive process and the optimal weighting matrix required to...

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...

This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster...