The standard literature on working time has modelled the decisions of firms in a deterministic framework in which firms can choose between employment and overtime (given mandated standard hours). Contrary to this approach, we consider the impact of uncertainty and real options on the decision of...

Building on the empirical evidence resulting from a newly developed database of foreign direct investment (FDI) operations in the countries of Central and Eastern Europe (CEECs), panel data techniques are used to show that, at the sector level, a consistent modelling of FDI flows needs to take...

Following the real option literature, whether or not uncertainty shocks drive business cycles depends on the degree of adjustment frictions. The more plants freeze and remain inactive in response to increased uncertainty, the stronger the adverse effects on the economic activity. Using quarterly...

Using quarterly worker flow data of U.S. establishments, we find that an unexpected increase in uncertainty reduces hirings and quits, while it raises layoffs. This finding suggests that the real option effect of uncertainty is less important for employment decisions. Hence plants do not freeze...

The objective of this paper is to combine a real options framework with portfolio optimization techniques and to apply this new framework to investments in the electricity sector. In particular, a real options model is used to assess the adoption decision of particular technologies under...

This paper investigates the relative impact of microeconomic agglomeration mechanisms on plant's total factor productivity (TFP) using German establishment and employment level data. Contrasting different strategies to estimate TFP from plant level production functions reveals that not...

We compute aggregate productivity of three categories of regions, classified by level of urbanization in the Netherlands, from firm-specific total factor productivity (TFP) measures. TFP measures are estimated by a semi-parametric algorithm, within 2-digit industries, covering agriculture,...

In this paper we propose a Bayesian estimation approach for a spatial autoregressive logit specification. Our approach relieson recent advances in Bayesian computing, making use of Pólya-Gamma sampling for Bayesian Markov-chain Monte Carlo algorithms.The proposed specification assumes that the...