This paper proposes an approach to proving nonparametric identification for distributions of bidders' values in asymmetric second-price auctions. I consider the case when bidders have independent private values and the only available data pertain to the winner's identity and the transaction...

We use information from two prospective British birth cohort studies to explore the antecedents of adult malaise, an indicator of incipient depression. These studies include a wealth of information on childhood circumstances, behaviour, test scores and family background, measured several times...

Probably not. First, allowing the probabilities attached to the states of the economy to differ from their sample frequencies, the Consumption-CAPM is still rejected by the data and requires a very high level of Relative Risk Aversion(RRA) in order to rationalize the stock market risk premium....

According to Principal-Agent theory, states (the principal) delegate the implementation of a legalized agreement to an international organization (the agent). The conventional wisdom about states’ capacity to control international organizations is that differences among the member states...

In the mid-1980s, many European countries introduced fixed-term contracts. Since then their labor markets have become more dynamic. This paper studies the implications of such reforms for the duration distribution of unemployment, with particular emphasis on the changes in the duration...

The intra-distributional mobility of German income dynamics is analysed using GSOEP. Transition probabilities are found to be time-varying. The tested models comprise various mixed Markov chains in discrete time and a non-stationary mover-stayer model is proposed. In order to explain the...

We study the mechanics of transmission of fiscal shocks to labour markets. We characterize a set of robust implications following government consumption, investment and employment shocks in a RBC and a New- Keynesian model and use part of them to identify shocks in the data. In line with the...

This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the...

We address the problem of parameter estimation for diffusion driven stochastic volatility models through Markov chain Monte Carlo (MCMC). To avoid degeneracy issues we introduce an innovative reparametrisation defined through transformations that operate on the time scale of the diffusion. A...

We contribute to the growing empirical literature on monetary and fiscal interactions by applying a sign restriction identification scheme to a structural TVP-VAR in order to disentangle and evaluate the policy shocks and policy transmissions. This in turn allows us to study the Great Recession...