We estimate by means of indirect inference a structural economic model where firms’ exit and investment decisions are the solution to a discrete-continuous dynamic programming problem. In the model the exit probability depends on the current capital stock and a measure of short-run...

In social and economic networks linked agents often share additional links in common. There are two competing explanations for this phenomenon. First, agents may have a structural taste for transitive links - the returns to linking may be higher if two agents share links in common. Second,...

In social and economic networks linked agents often share additional links in common. There are two competing explanations for this phenomenon. First, agents may have a structural taste for transitive links - the returns to linking may be higher if two agents share links in common. Second,...

I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution...

Objective: Even in highly regulated and advanced health care markets, treatment costs and outcome quality substantially vary across facilities. Interhospital variation - particularly when it is not attributable to different patient compositions - might indicate inefficiencies in the health care...

A novel spatial autoregressive model for panel data is introduced, which incorporates multilayer networks and accounts for time-varying relationships. Moreover, the proposed approach allows the structural variance to evolve smoothly over time and enables the analysis of shock propagation in...

In order to simplify the representation of a technological relationship between inputs and outputs, a production unit's technology must typically satisfy some restrictive conditions, some of them being well known in the literature. This paper presents new results for aggregating labour inputs...

This paper introduces a new model for spatial time series in which cross-sectional dependence varies nonlinearly over space by means of smooth transitions. We refer to our model as the Smooth Transition Spatial Autoregressive (ST-SAR). We establish consistency and asymptotic Gaussianity for the...

The authors address the issue of estimation and inference in dependent non-stationary panels of small cross-section dimensions. The main conclusion is that the best results are obtained applying bootstrap inference to single-equation estimators, such as fully modified ordinary least squares and...