Las implicaciones sobre la calidad del agua, medida ésta a través de los parámetros de carácter físico-químico empleados en la literatura específica, es uno de los principales problemas asociados a los trasvases de aguas superficiales. En este trabajo se realiza una valoración de la...

The aim of this paper is to analyze the impact of the SAR model misspecification. We concentrate on the effect of ignoring random effects (both independent and spatially correlated) in the SAR model. The results from the Monte Carlo simulation suggests the overestimation of the spatial parameter...

In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai, Jain and Ching, Econometrica 77:1865-1899, 2009) (IJC). In the conventional nested fixed point algorithm, most of the...

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernandez-Villaverde and Rubio-Ramirez (2004) and the Kalman filter. The Sequential Monte Carlo filter exploits the nonlinear structure of the...

This paper provides a structural empirical analysis of Dutch auctions of houseplants at the flower auction in Aalsmeer, the Netherlands. The data set is unique for Dutch auctions in the sense that it includes observations of all losing bids in an interval adjacent to the winning bid. The size of...

This paper studies the computational complexity of Bayesian and quasi-Bayesian estimation in large samples carried out using a basic Metropolis random walk. The framework covers cases where the underlying likelihood or extremum criterion function is possibly non-concave, discontinuous, and of...

Many modelling issues and policy debates in macroeconomics depend on whether macroeconomic times series are best characterized as linear or nonlinear. If departures from linearity exist, it is important to know whether these are endogenously generated (as in, e.g., a threshold autoregressive...

This paper estimates the parameters of a stylized dynamic stochastic general equilibrium model using maximum likelihood and Bayesian methods, paying special attention to the issue of weak parameter identification. Given the model and the available data, the posterior estimates of the weakly...

This work deals with multivariate stochastic volatility models, which account for a time-varying variance-covariance structure of the observable variables. We focus on a special class of models recently proposed in the literature and assume that the covariance matrix is a latent variable which...