This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990-2003. This is done using maximum likelihood estimation taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four...

Hedonic regressions with house value as the dependent vaqriable are widely used to study the value of public services and amenities. This paper builds on the theory of household bidding and sorting to derive a bid function envelope, which provides a form for these regressions. This approach uses...

This paper exploits the significant recent variation in United States house prices to empirically examine the effect on housing equity constraints and nominal loss aversion on household mobility. The analysis uses unique, detailed data from 1985-1996 on household characteristics, mobility, and...

This paper studies racial and ethnic discrimination in discrete choices by real estate brokers using national audit data from the 2000 Housing Discrimination Study. It uses a fixed effects logit model to estimate the probability that discrimination occurs and to study the causes of...

This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error...

This paper examines the consequences of model misspecification using a panel data model with spatially autocorrelated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include...

This paper considers the problem of prediction in a panel data regression model with spatial autocorrelation in the context of a simple demand equation for liquor. This is based on a panel of 43 states over the period 1965-1994. The spatial autocorrelation due to neighboring states and the...

Wavelet analysis is a new mathematical tool developed as a unified field of science over the last decade. As spatially adaptive analytic tools, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent/strong dependence, seasonality...

This paper develops the adaptive elastic net GMM estimator in large dimensional models with many possibly invalid moment conditions, where both the number of structural parameters and the number of moment conditions may increase with the sample size. The basic idea is to conduct the standard GMM...

This paper suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi, Egger and Pfaffermayr (2013) by the inclusion of a spatial lag...