This paper analyzes spatial Probit models for cross sectional dependent data in a binary choice context. Observations are divided by pairwise groups and bivariate normal distributions are specified within each group. Partial maximum likelihood estimators are introduced and they are shown to be...

This paper is concerned with estimation and testing in data sets consisting of a small number (about 20–30) of curves observed at unevenly distributed spatial locations. Such data structures may be referred to as spatially indexed functional data. Motivated by an important space physics...

We describe the spreg command, which implements a maximum likelihood estimator and a generalized spatial two-stage least-squares estimator for the parameters of a linear cross-sectional spatial-autoregressive model with spatial-autoregressive disturbances. Copyright 2013 by StataCorp LP.

We present the spmat command for creating, managing, and storing spatial-weighting matrices, which are used to model interactions between spatial or more generally cross-sectional units. spmat can store spatial-weighting matrices in a general and banded form. We illustrate the use of the spmat...

We describe the spivreg command, which estimates the parameters of linear cross-sectional spatial-autoregressive models with spatial-autoregressive disturbances, where the model may also contain additional endogenous variables as well as exogenous variables. spivreg uses results and the...

This article investigates migration in postunification Germany, focusing on three particular issues: Do Germans migrate to improve their net wages or for higher levels of amenities? Is migration behavior in East Germany the same as for unified Germany? And finally, is there a difference between...

The best linear unbiased predictor (BLUP) is called a kriging predictor and has been widely used to interpolate a spatially correlated random process in scientific areas such as geostatistics. However, if an underlying random field is not Gaussian, the optimality of the BLUP in the mean squared...

We study the location patterns of business-oriented service and manufacturing industries in France. We develop a new test of localization considering space as continuous. Our test relies on a measure of divergence in the space of density distributions that allows us to assess whether or not the...