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 suggest and compare different methods for estimating spatial autoregressive panel models with randomly missing data in the dependent variable. We start with a random effects model and then generalize the model by introducing the spatial Mundlak approach. A nonlinear least squares method is...

The purpose of this article is to analyze if spatial dependence is a synchronic effect, as it has usually been defined. It is known that in many socio-economic phenomena spatial dependence can be not only contemporary but also time-lagged. In this paper, we use two Moran-based space-time...

Using national level input-output matrices, we propose a strategy to identify pecuniary externalities operating through the markets for intermediate goods at the local level. Then, controlling for common shocks in a spatial econometric framework, (i) we estimate the e®ect of pecuniary...

This paper derives the LIML estimator for a spatial autoregressive model with endogenous regressors in the presence of many instruments. The LIML estimator is consistent when the number of instruments increases at a slower rate relative to the sample size. Due to spatial correlation, the LIML...

We propose a novel mechanism to facilitate understanding of systemic risk in financial markets. The literature on systemic risk has focused on two mechanisms, common shocks and domino-like sequential default. Our approach is a formal model that provides an intellectual combination of the two by...