Resultados da Busca
Creator: McGrattan, Ellen R. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 514 Palavra-chave: Finite element method, Computational time, Accuracy, Stochastic growth model, Applied economics, and Computational method Sujeito: C52 - Model Evaluation, Validation, and Selection and C63 - Computational Techniques; Simulation Modeling
Creator: McGrattan, Ellen R. Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 164 Abstract:
Since it is the dominant paradigm of the business cycle and growth literatures, the stochastic growth model has been used to test the performance of alternative numerical methods. This paper applies the finite element method to this example. I show that the method is easy to apply and, for examples such as the stochastic growth method, gives accurate solutions within a second or two on a desktop computer. I also show how inequality constraints can be handled by redefining the optimization problem with penalty functions.
Palavra-chave: Growth model and Finite element method Sujeito: C68 - Computable General Equilibrium Models and C63 - Computational Techniques; Simulation Modeling
Creator: Geweke, John Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 526 Palavra-chave: Econometrics, Monte Carlo, and Simulation Sujeito: C15 - Statistical Simulation Methods: General and C63 - Computational Techniques; Simulation Modeling
Creator: Den Haan, Wouter J., 1962- Series: Macroeconomics with heterogenous agents, incomplete markets, liquidity constraints, and transaction costs Abstract:
This paper is part of a project to model the interaction between heterogeneous agents in intertemporal stochastic models and to develop numerical algorithms to solve these kind of models. It is well-known that solving dynamic heterogeneous agent models is a challenging problem, since in these models the distribution of wealth and other characteristics evolve endogenously over time. Existing dynamic models in the literature contain therefore just two agents or other simplifying assumptions to limit the heterogeneity.
Sujeito: D52 - General equilibrium and disequilibrium - Incomplete markets and C63 - Mathematical methods and programming - Computational techniques ; Simulation modeling
Creator: Geweke, John, Keane, Michael P., and Runkle, David Edward Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 170 Abstract:
This research compares several approaches to inference in the multinomial probit model, based on Monte-Carlo results for a seven choice model. The experiment compares the simulated maximum likelihood estimator using the GHK recursive probability simulator, the method of simulated moments estimator using the GHK recursive simulator and kernel-smoothed frequency simulators, and posterior means using a Gibbs sampling-data augmentation algorithm. Each estimator is applied in nine different models, which have from 1 to 40 free parameters. The performance of all estimators is found to be satisfactory. However, the results indicate that the method of simulated moments estimator with the kernel-smoothed frequency simulator does not perform quite as well as the other three methods. Among those three, the Gibbs sampling-data augmentation algorithm appears to have a slight overall edge, with the relative performance of MSM and SML based on the GHK simulator difficult to determine.
Creator: Geweke, John Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 532 Abstract:
This paper integrates and extends some recent computational advances in Bayesian inference with the objective of more fully realizing the Bayesian promise of coherent inference and model comparison in economics. It combines Markov chain Monte Carlo and independence Monte Carlo with importance sampling to provide an efficient and generic method for updating posterior distributions. It exploits the multiplicative decomposition of marginalized likelihood into predictive factors, to compute posterior odds ratios efficiently and with minimal further investment in software. It argues for the use of predictive odds ratios in model comparison in economics. Finally, it suggests procedures for public reporting that will enable remote clients to conveniently modify priors, form posterior expectations of their own functions of interest, and update the posterior distribution with new observations. A series of examples explores the practicality and efficiency of these methods.
This paper was prepared for the inaugural Colin Clark Lecture, Australasian Meetings of the Econometric Society, July 1994.
Palavra-chave: Computation, Model comparison, Bayesian inference, and Econometric modeling Sujeito: C53 - Forecasting Models; Simulation Methods and C11 - Bayesian Analysis: General
Creator: Baxter, Marianne, 1956- Series: Nonlinear rational expectations modeling group Abstract:
This paper develops a new method for approximating dynamic competitive equilibria in economies in which competitive equilibrium is not necessarily Pareto optimal. The method involves finding approximate equilibrium policy functions by iterating on the stochastic Euler equations which characterize the economy's equilibrium. Two applications are presented: the stochastic growth model of Brock and Mirman (1971) modified to allow distortionary taxation, and a model of inflation and capital accumulation based on Stockman (1981). The computational speed and accuracy of this approach suggests that it may be a feasible method for studying suboptimal economies with large state spaces.
Sujeito: C61 - Mathematical methods and programming - Optimization techniques ; Programming models ; Dynamic analysis, E51 - Monetary policy, central banking, and the supply of money and credit - Money supply ; Credit ; Money multipliers, and C63 - Mathematical methods and programming - Computational techniques ; Simulation modeling