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Creator: Roberds, William Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 261 Abstract:
A method is presented for solving a certain class of hierarchical rational expectations models, principally models that arise from Stackelberg dynamic games. The method allows for numerical solution using spectral factorization algorithms, and estimation of these models using standard maximum likelihood techniques.
Palavra-chave: Rational expectations theory, Stackelberg dynamic game, and Oligopoly model Sujeito: C13 - Estimation: General and C73 - Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
Creator: Fernandez-Villaverde, Jesus and Rubio-Ramírez, Juan Francisco Series: Joint committee on business and financial analysis Abstract:
This paper presents a method to perform likelihood-based inference in nonlinear dynamic equilibrium economies. This type of models has become a standard tool in quantitative economics. However, existing literature has been forced so far to use moment procedures or linearization techniques to estimate these models. This situation is unsatisfactory: moment procedures suffer from strong small samples biases and linearization depends crucially on the shape of the true policy functions, possibly leading to erroneous answers. We propose the use of Sequential Monte Carlo methods to evaluate the likelihood function implied by the model. Then we can perform likelihood-based inference, either searching for a maximum (Quasi-Maximum Likelihood Estimation) or simulating the posterior using a Markov Chain Monte Carlo algorithm (Bayesian Estimation). We can also compare different models even if they are nonnested and misspecified. To perform classical model selection, we follow Vuong (1989) and use the Kullback-Leibler distance to build Likelihood Ratio Tests. To perform Bayesian model comparison, we build Bayes factors. As an application, we estimate the stochastic neoclassical growth model.
Palavra-chave: Sequential Monte Carlo methods, Nonlinear filtering, Dynamic equilibrium economies, and Likelihood-based inference Sujeito: C11 - Bayesian Analysis: General, C10 - Econometric and Statistical Methods and Methodology: General, C13 - Estimation: General, and C15 - Statistical Simulation Methods: General
Creator: Hansen, Lars Peter and Jagannathan, Ravi Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 167 Abstract:
In this paper we develop alternative ways to compare asset pricing models when it is understood that their implied stochastic discount factors do not price all portfolios correctly. Unlike comparisons based on chi-squared statistics associated with null hypotheses that models are correct, our measures of model performance do not reward variability of discount factor proxies. One of our measures is designed to exploit fully the implications of arbitrage-free pricing of derivative claims. We demonstrate empirically the usefulness of methods in assessing some alternative stochastic factor models that have been proposed in asset pricing literature.
Sujeito: C13 - Estimation: General, G10 - General Financial Markets: General (includes Measurement and Data), G12 - Asset Pricing; Trading Volume; Bond Interest Rates, E30 - Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data), C10 - Econometric and Statistical Methods and Methodology: General, and C12 - Hypothesis Testing: General