This paper proposes a spatial panel model for German matching functions to avoid possibly biased and inefficient estimates due to spatial dependence. We provide empirical evidence for the presence of spatial dependencies in matching data. Based on an official data set containing monthly...

The standard LM tests for spatial dependence in linear and panel regressions are derived under the normality and homoskedasticity assumptions of the regression disturbances. Hence, they may not be robust against non-normality or heteroskedasticity of the disturbances. Following Born and Breitung...

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...

This paper analyzes how the distribution of marketing time of residential real estate evolves across time. Using real estate data from a large suburb in the Washington D.C. area we first show that the whole distribution of marketing time shifts to the right when a “hot” housing market in...

The willingness of households to pay for prevention against industrial risks can be revealed by real estate markets. By using very rich microdata, we study housing prices in the vicinity of hazardous industries near three important French cities. We show that the impact of hazardous plants on...

We examine spatially correlated interregional flows measured as binary choice outcomes. Since the dependent variable is not only binary and dyadic, but also spatially correlated, we propose a spatial origin–destination probit model and a Bayesian estimation methodology that avoids inconsistent...

This paper applies a locally weighted scatterplot smoothing (loess) method to estimate the spatially heterogeneous wages of demographic groups of workers across precisely defined US labor markets. We estimate a location choice model using data from the National Longitudinal Survey of Youth...

The residential sector accounts for 33% of electricity consumption in the U.S., with a total expenditure of $166billion in 2010. Increasing the energy efficiency of the durable housing stock can thus provide significant cost savings for consumers. One promising trend is the rise of homes labeled...

This paper uses quantile regression, while accounting for spatial autocorrelation, to examine the simultaneous space–time impact of foreclosures on neighborhood property values. We find that negative price externalities associated with neighborhood foreclosures are greatest (1) among...

This paper investigates spatio-temporal variations in ex-post credit risk in the United States, as a function of real estate prices, loan purchases made by government sponsored enterprises, and a set of local characteristics during the recent housing boom and bust.