Accurate employee turnover prediction models are critical in the early detection of unanticipated turnover, and thus giving managers sufficient time to deal with turnover related management issues. The logit and probit models have been successfully applied to solve nonlinear classifying and...

Gaining highly skilled human capital is one of the key motivations for mergers and acquisitions (M&A), particularly in knowledge-intensive sectors such as the technology industry. However, the inherent cultural differences and organizational misalignments during the integration process can lead...

Parsimony is a desirable feature of economic models but almost all human behaviors are characterized by vast individual variation that appears to defy parsimony. How much parsimony do we need to give up to capture the fundamental aspects of a population's distributional preferences and to...

Parsimony is a desirable feature of economic models but almost all human behaviors are characterized by vast individual variation that appears to defy parsimony. How much parsimony do we need to give up to capture the fundamental aspects of a population's distributional preferences and to...

In this paper we study international linkages when forecasting unemployment rates in a sample of 24 OECD economies. We propose a Global Unemployment Factor (GUF) and test its predictive ability considering in-sample and out-of-sample exercises. Our main results indicate that the predictive...

Population size and structure in conjunction with the participation behavior are the determinants of labor supply. Thereby, among the demographic components, migration is the one shaping both the size and the structure of a population the strongest in the short to medium term while...

We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, in order to evaluate the efficiency and speed of information aggregation, as well as test recent theoretical results on manipulative behavior by traders. We...

We use machine learning to uncover regularities in the initial play of matrix games. We first train a prediction algorithm on data from past experiments. Examining the games where our algorithm predicts correctly, but existing economic models don't, leads us to add a parameter to the best...

This paper studies a robustness of solutions in finite depth of reasoning models. The level-k and cognitive hierarchy models conventionally assume that each player has a commonly known anchor behavior to obtain a sharp prediction. We provide a general framework to examine whether the obtained...