nep-cmp New Economics Papers
on Computational Economics
Issue of 2008‒01‒19
five papers chosen by
Stan Miles
Thompson Rivers University

  1. A Rational Expectations Model for Simulation and Policy Evaluation of the Spanish Economy By J.E. Boscá; A. Díaz; R. Doménech; J. Ferri; E. Pérez; L. Puch
  2. A further note on a new class of solutions to dynamic programming problems arising in economic growth By Juergen Antony; Alfred Maussner
  3. Hydrogen in Passenger Transport: A Macroeconomic Analysis By Jokisch, Sabine; Mennel, Tim
  4. Humans versus computer algorithms in repeated mixed strategy games By Spiliopoulos, Leonidas
  5. Aplicação da Amostragem por Importância à Simulação de Opções Asiáticas Fora do Dinheiro By Jaqueline Terra Moura Marins

  1. By: J.E. Boscá (University of Valencia, Spain); A. Díaz (Ministry of Economics and Finance, Spain); R. Doménech (Economic Bureau of the Prime Minister, Spain. University of Valencia, Spain); J. Ferri (University of Valencia, Spain); E. Pérez (Ministry of Economics and Finance, Spain); L. Puch (FEDEA, Universidad Complutense and ICAE, Spain)
    Abstract: This paper describes a Rational Expectations Model of the Spanish economy, REMS, which is in the tradition of small open economy dynamic general equilibrium models, with a strongly microfounded system of equations. The model is built on standard elements, but incorporates some distinctive features to provide an accurate description of the Spanish economy. We contribute to the existing models of the Spanish economy by adding search and matching rigidities to a small open economy framework. Our model also incorporates habits in consumption and rule-of-thumb households. As Spain is a member of EMU, we model the interaction between a small open economy and monetary policy in a monetary union. The model is primarily constructed to serve as a simulation tool at the Spanish Ministry of Economic Affairs and Finance. As such, it provides a great deal of information regarding the transmission of policy shocks to economic outcomes. The paper describes the structure of the model in detail, as well as the estimation and calibration technique and some examples of simulations.
    Keywords: general equilibrium, rigidities, policy simulations
    JEL: E24 E32 E62
    Date: 2007–12
  2. By: Juergen Antony (University of Augsburg, Department of Economics); Alfred Maussner (University of Augsburg, Department of Economics)
    Abstract: This note extends the finding of Benhabib and Rusticchini (1994) who provide a class of SDGE models, whose solution is characterized by a constant savings rate. We show that this class of models may be interpreted as a standard representative agent SDGE model with costly adjustment of capital and provides a solution to the traditional discrete time Ramsey problem.
    Keywords: capital and labor substitution, dynamic programming, growth, numerical solutions of SDGE models
    JEL: C61 C68 E21 O4
    Date: 2008–01
  3. By: Jokisch, Sabine; Mennel, Tim
    Abstract: Hydrogen is often seen as a promising future energy carrier given the major reliance of today’s transport sector on finite fossil fuels. This working paper assesses the macroeconomic effects of introducing hydrogen as fuel in passenger transport within the framework of the computable general equilibrium (CGE) model PACE-T(H2). Our simulation results suggest small improvements in the macroeconomic performance in almost all European countries from the introduction of hydrogen. The magnitude of economic effects however depends on the assumed learning curve of hydrogen cars and on the future development of hydrogen infrastructure costs. The results presented in this paper build on data and projections developed in the EU funded ‘HyWays’ project.
    Date: 2007
  4. By: Spiliopoulos, Leonidas
    Abstract: This paper is concerned with the modeling of strategic change in humans’ behavior when facing different types of opponents. In order to implement this efficiently a mixed experimental setup was used where subjects played a game with a unique mixed strategy Nash equilibrium for 100 rounds against 3 preprogrammed computer algorithms (CAs) designed to exploit different modes of play. In this context, substituting human opponents with computer algorithms designed to exploit commonly occurring human behavior increases the experimental control of the researcher allowing for more powerful statistical tests. The results indicate that subjects significantly change their behavior conditional on the type of CA opponent, exhibiting within-sub jects heterogeneity, but that there exists comparatively little between-subjects heterogeneity since players seemed to follow very similar strategies against each algorithm. Simple heuristics, such as win-stay/lose-shift, were found to model subjects and make out of sample predictions as well as, if not better than, more complicated models such as individually estimated EWA learning models which suffered from overfitting. Subjects modified their strategies in the direction of better response as calculated from CA simulations of various learning models, albeit not perfectly. Examples include the observation that subjects randomized more effectively as the pattern recognition depth of the CAs increased, and the drastic reduction in the use of the win-stay/lose-shift heuristic when facing a CA designed to exploit this behavior.
    Keywords: Behavioral game theory; Learning; Experimental economics; Simulations; Experience weighted attraction learning; Simulations; Repeated games; Mixed Strategy Nash equilibria; Economics and psychology
    JEL: C9 C63 C70 C73 C72 C91
    Date: 2008–01–09
  5. By: Jaqueline Terra Moura Marins
    Abstract: According to previous results, the main variance reduction techniques performed well during the Monte Carlo simulation of Asian calls (Marins, Santos e Saliby, 2003). Control Variate best performed in terms of the precision of the estimates, whereas Descriptive Sampling was the fastest technique. However, a performance deterioration was noted as the exercise probability of the Asian calls was decreased, or equivalently, as these calls became out of the money. In this the out of the money region, the call exercise becomes a rare event and the simulation process remains injured. One possible solution is to implement Importance Sampling, which is a specific technique to deal with rare event simulation problems. This technique has already performed well in the out of the money European call simulation case (Saliby, Marins and Santos, 2005). Therefore, the objective of this article is to use Importance Sampling in the simulation out of the money Asian calls, in order to verify if the precision of the estimates is preserved. It is also implemented a combination of Importance Sampling with the two previously mentioned best techniques, Control Variate and Descriptive Sampling. According to the main findings, Importance Sampling was not only crucial to allow simulation in the out of the money region, but also to provide additional precision gains when combined with the two other techniques.
    Date: 2007–12

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