Whether a firm is able to attract foreign capital and whether it may participate at the export market depends on whether the fixed costs associated with doing so are at least covered by the incremental operating profits. This paper provides evidence that success for some firms in attracting...

This paper develops a statistical model for measuring spatial interactions when estimating macroeconomic regimes and regime shifts. The model is applied to study the contagion and propagation of recessions in small regional economies in the United States from 1990 to 2015. The empirical analysis...

Whether a firm is able to attract foreign capital and whether it may participate at the export market depends on whether the fixed costs associated with doing so are at least covered by the incremental operating profits. This paper provides evidence that success for some firms in attracting...

This paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides...

This paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides...

We use a spatial econometric extension of the traditional regression-based gravity model introduced in LeSage and Pace (2005) to model commodity flows between 35 regions in Austria. Our focus is on a formal methodology for incorporating information regarding the highway network into the spatial...

A recent literature has developed that combines two prominent empirical approaches to ex ante policy evaluation: randomized controlled trials (RCT) and structural estimation. The RCT provides a “gold-standard" estimate of a particular treatment, but only of that treatment. Structural...

Sparse factor analysis comprises aspects of exploratory and confirmatory factor analysis, seeking to establish a parsimonious structure in the loadings matrix of the model. This task is related to the issue of determining the number of factors required for model representation, the question of...

Due to their indeterminacies, static and dynamic factor models require identifying assumptions to guarantee uniqueness of the parameter estimates. The indeterminacy of the parameter estimates with respect to orthogonal transformations is known as the rotation problem. The typical strategy in...

Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...