5 resultados para Recursive programming

em Repositório digital da Fundação Getúlio Vargas - FGV


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This paper uses dynamic programming to study the time consistency of optimal macroeconomic policy in economies with recurring public deficits. To this end, a general equilibrium recursive model introduced in Chang (1998) is extended to include govemment bonds and production. The original mode! presents a Sidrauski economy with money and transfers only, implying that the need for govemment fmancing through the inflation tax is minimal. The extended model introduces govemment expenditures and a deficit-financing scheme, analyzing the SargentWallace (1981) problem: recurring deficits may lead the govemment to default on part of its public debt through inflation. The methodology allows for the computation of the set of alI sustainable stabilization plans even when the govemment cannot pre-commit to an optimal inflation path. This is done through value function iterations, which can be done on a computeI. The parameters of the extended model are calibrated with Brazilian data, using as case study three Brazilian stabilization attempts: the Cruzado (1986), Collor (1990) and the Real (1994) plans. The calibration of the parameters of the extended model is straightforward, but its numerical solution proves unfeasible due to a dimensionality problem in the algorithm arising from limitations of available computer technology. However, a numerical solution using the original algorithm and some calibrated parameters is obtained. Results indicate that in the absence of govemment bonds or production only the Real Plan is sustainable in the long run. The numerical solution of the extended algorithm is left for future research.

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This paper analyses general equilibrium models with finite heterogeneous agents having exogenous expectations on endogenous uncertainty. It is shown that there exists a recursive equilibrium with the state space consisting of the past aggregate portfolio distribution and the current state of the nature and that it implements the sequential equilibrium. We establish conditions under which the recursive equilibrium is continuous. Moreover, we use the continuous recursive relation of the aggregate variables to prove that if the economy has two types of agents, the one who commits persistent mistakes on the expectation rules of the future endogenous variables is driven out of the market by the others with correct anticipations of the variables, that is, the rational expectations agents.

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Este trabalho consiste em estudar modelos incluindo agentes com informação completa e incompleta sobre o ambiente econômico. Prova-se a existência de equilíbrio em que esses dois agentes coexistem e sob, algumas condições, obtêm-se que esse equilíbrio é recursivo e contínuo, ou seja, pode ser implementado por uma função contínua de transição que relaciona as variáveis de equilíbrio entre dois períodos consecutivos. Mostra-se, sob algumas hipóteses, que em equilíbrios recursivos contínuos, os agentes que cometem erros persistentes nas antecipações dos preços de equilíbrio são eliminados do mercado. Finalmente, exibimos diversos exemplos numéricos, no caso de mercados incompletos e informação completa, em que os agentes com expectativas racionais são eliminados do mercado. Usam-se métodos numéricos alternativos que possibilitam computar um equilíbrio em modelos com agentes heterogêneos.

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This paper shows existence of approximate recursive equilibrium with minimal state space in an environment of incomplete markets. We prove that the approximate recursive equilibrium implements an approximate sequential equilibrium which is always close to a Magill and Quinzii equilibrium without short sales for arbitrarily small errors. This implies that the competitive equilibrium can be implemented by using forecast statistics with minimal state space provided that agents will reduce errors in their estimates in the long run. We have also developed an alternative algorithm to compute the approximate recursive equilibrium with incomplete markets and heterogeneous agents through a procedure of iterating functional equations and without using the rst order conditions of optimality.