This paper studies the mechanism by which club memberships, activities, and rules are chosen in a decentralized economy. For this purpose, we develop a model of competing auctions for club goods. This is a dynamic game where each seller first chooses an auction format; next, each buyer chooses a...

We consider “must-sell” auctions with asymmetric buyers. First, we study auctions with two asymmetric buyers, where the distribution of valuations of the strong buyer is “stretched” relative to that of the weak buyer. Then, it is known that ineffcient first-price auctions are more...

On many online auction sites it is now possible for a seller to augment his auction with a maximum or buy-out price. The use of this instrument has been justified in "one-shot" auctions by appeal to impatience or risk aversion. Here we offer additional justification by observing that trading on...

This paper evaluates the accuracy of a set of techniques that approximate the solution of continuous-time DSGE models. Using the neoclassical growth model I compare linear-quadratic, perturbation and projection methods. All techniques are applied to the HJB equation and the optimality conditions...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast and...

Motivated by the construction of the Itô stochastic integral, we consider a step function method to discretize and simulate volatility modulated Lévy semistationary processes. Moreover, we assess the accuracy of the method with a particular focus on integrating kernels with a singularity at...

We address the issue of modelling and forecasting macroeconomic variables using medium and large datasets, by adopting VARMA models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares (IOLS) estimator. We establish the...

We present and evaluate a numerical optimization method (together with an algorithm for choosing the starting values) pertinent to the constrained optimization problem arising in the estimation of the GARCH models with inequality constraints, in particular the Simplified Component GARCH Model...