One important goal of this study is to develop a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first...

This paper provides a method for the analysis of the spatial and temporal diffusion of shocks in a dynamic system. We use changes in real house prices within the UK economy at the level of regions to illustrate its use. Adjustment to shocks involves both a region specific and a spatial effect....

The main aim of this paper is to assess whether there is a statistically significant environmental impact of cities within European countries. Second, starting from the estimated environmental impact of cities within European countries, the paper investigates whether cross-country variation can...

The U.S. Environmental Protection Agency (USEPA) maintains networks of pollution monitors for two basic purposes: to check and enforce the attainment of national ambient air quality standards (NAAQS) and to provide useful data for studying pollution and its effects. These purposes imply...

This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a...

The purpose of this paper is to apply recent advances in the econometrics of panel data to a problem that has a clear spatial dimension. We model the dynamic adjustment of real house prices using data at the level of US States. In the last decade, in most OECD countries there has been a...

The geographic distance between a household and financial institutions may constitute a significant obstacle to achieving the benefits of modern financial institutions. We measure the impact of improved distance-related access to microcredits in Uzbekistan. Residents living closer to...

This paper introduces dynamics in the R&D to innovation and innovation to productivity relationships, which have mostly been estimated on cross-sectional data. It considers four nonlinear dynamic simultaneous equations models that include individual effects and idiosyncratic errors correlated...

I study the effects of service offshoring on white-collar employment, using highly disaggregated occupational data for the U.S.. I present a structural model of the firm's behavior that allows tractable derivation of labor demand elasticities for highly detailed occupations. I estimate the model...

This paper proposes a method to implement maximum likelihood estimation of the dynamic panel data type 2 and 3 tobit models. The likelihood function involves a two-dimensional indefinite integral evaluated using "two-step" Gauss-Hermite quadrature. A Monte Carlo study shows that the quadrature...