nep-cmp New Economics Papers
on Computational Economics
Issue of 2008‒04‒29
eight papers chosen by
Stan Miles
Thompson Rivers University

  1. Artificial Markets under a Complexity Perspective By Alejandro Reveiz Herault
  2. Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System By George Atsalakis; Dimitrios Nezis; George Matalliotakis; Camelia Ioana Ucenic; Christos Skiadas
  3. InfSOCSol2: an updated MATLAB package for approximating the solution to a continuous-time infinite horizon stochastic optimal control problem By Azzato, Jeffrey; Krawczyk, Jacek
  4. JBendge: An Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models By Viktor Winschel; Markus Krätzig
  5. Smart Forward Shooting By Manoj Atolia; Edward F. Buffie
  6. Competitive search equilibrium in a DSGE model By David M. Arseneau; Sanjay K. Chugh
  7. Adaptive microfoundations for emergent macroeconomics By Edoardo Gaffeo; Domenico Delli Gatti; Saul Desiderio; Mauro Gallegati
  8. Analysis of Poverty and Inequality in Bolivia,1999-2005: A Microsimulation Approach By Claudia Gutierrez

  1. By: Alejandro Reveiz Herault
    Abstract: The focus of this study is to build, from the ‘bottom-up’, a market with artificially intelligent adaptive agents based on the institutional arrangement of the Colombian Foreign Exchange Market (1994-1999) in order to determine simple agents’ design, rules and interactions that are sufficient to create interesting behaviours at the macroscopic level - emerging patterns that replicate the properties of the time series from the case study. Tools from artificial intelligence research, such as genetic algorithms and fuzzy logic, are the basis of the agents’ mental models, which in turn are used for forecasting, quoting and learning purposes in a double auction market. Sets of fuzzy logic rules yield adequate, approximately continuous risk and utility preferences without the need to fix their mathematical form ex-ante. Statistical properties of financial time series are generated by the artificial market, as well as some additional non-linearity linked to the existence of a crawling band. Moreover, the behaviour of the simulated exchange rate is consistent with currency band theory. Agent’s learning favours forecasting rules based on regulatory signals against rules based on fundamental information. Also, intra-day volatility is strongly linked to the rate of arrival and size of real sector trades. Intra-day volatility is also a function of the frequency of learning and search specialisation. It is found that when a moderately low frequency of learning is used, volatility increases.
    Keywords: Adaptive agents, artificial markets, constrained generating procedures, fuzzy logic and genetic algorithms. Classification JEL: G1; G12; G39.
  2. By: George Atsalakis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); Dimitrios Nezis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); George Matalliotakis (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE); Camelia Ioana Ucenic (University of Crete - Technical University Cluj Napoca); Christos Skiadas (Data Analysis and Forecasting Laboratory, Technical University of Crete, GREECE)
    Abstract: Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS. The model predicts the yearly mortality in a one step ahead prediction scheme. The method of trial and error was used in order to decide the type of membership function that describe better the model and provides the minimum error. The output of the models is the next year¢s mortality. The results were presented and compared based on three different kinds of errors: RMSE, MAE, and MAPE. The ANFIS model gives good results for the case of two gbell membership functions and 500 epochs. Finally, the ANFIS model gives better results than the AR and ARMA model.
    Keywords: ANFIS, Forecasting, Mortality, Modeling.
    Date: 2007
  3. By: Azzato, Jeffrey; Krawczyk, Jacek
    Abstract: This paper describes a suite of MATLAB routines devised to provide an approximately optimal solution to an infinite-horizon stochastic optimal control problem. The suite is an updated version of that described in [Kra01b]. Its routines implement a policy improvement algorithm to optimise a Markov decision chain approximating the original control problem, as described in [Kra01c].
    Keywords: Computational techniques; Economic software; Computational methods in stochastic optimal control; Computational economics; Approximating Markov decision chains
    JEL: C63 C87
    Date: 2008–04–22
  4. By: Viktor Winschel; Markus Krätzig
    Abstract: We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The imple- mented solution methods for nding the unknown policy function are the standard linearization around the deterministic steady state, and a function iterator using a multivariate global Chebyshev polynomial approximation with the Smolyak op- erator to overcome the course of dimensionality. The operator is also useful for numerical integration and we use it for the integrals arising in rational expecta- tions and in nonlinear state space lters. The estimation step is done by a parallel Metropolis-Hastings (MH) algorithm, using a linear or nonlinear lter. Implemented are the Kalman, Extended Kalman, Particle, Smolyak Kalman, Smolyak Sum, and Smolyak Kalman Particle lters. The MH sampling step can be interactively moni- tored and controlled by sequence and statistics plots. The number of parallel threads can be adjusted to benet from multiprocessor environments. JBendge is based on the framework JStatCom, which provides a standardized ap- plication interface. All tasks are supported by an elaborate multi-threaded graphical user interface (GUI) with project management and data handling facilities.
    Keywords: Dynamic Stochastic General Equilibrium (DSGE) Models, Bayesian Time Series Econometrics, Java, Software Development
    JEL: C11 C13 C15 C32 C52 C63 C68 C87
    Date: 2008–04
  5. By: Manoj Atolia (Department of Economics, Florida State University); Edward F. Buffie (Department of Economics, Indiana University)
    Abstract: In this paper we develop a set of innovative forward-shooting algorithms that solve for the global nonlinear saddle path in models with 1-3 jump variables. Exploiting the fact that the algorithms are mechanical and model-free, we have placed canned, fully-automated programs in the public domain. The programs do not require any substantive human input. The user’s only responsibility is to type in the equations of the model correctly.
    Keywords: forward shooting, automated programs, global saddle path
    JEL: F41 C61 C63
    Date: 2007–11
  6. By: David M. Arseneau; Sanjay K. Chugh
    Abstract: We show how to implement a competitive search equilibrium in a fully-specified DSGE environment. Competitive search, an equilibrium concept well-understood in labor market theory, offers an alternative to the commonly-used Nash bargaining in search-based macro models. Our simulation-based results show that business cycle fluctuations under competitive search equilibrium are virtually identical to those under Nash bargaining for a broad range of calibrations of Nash bargaining power. We also prove that business cycle fluctuations under competitive search equilibrium are exactly identical to those under Nash bargaining restricted to the popularly-used Hosios condition for search efficiency. This latter result extends the efficiency properties of competitive search equilibrium to a DSGE environment. Our results thus provide a foundation for researchers interested in studying business cycle fluctuations using search-based environments to claim that the sometimes-awkward assumption of bargaining per se does not obscure interpretation of results.
    Date: 2008
  7. By: Edoardo Gaffeo; Domenico Delli Gatti; Saul Desiderio; Mauro Gallegati
    Abstract: In this paper we present the basics of a research program aimed at providing microfoundations to macroeconomic theory on the basis of computational agentbased adaptive descriptions of individual behavior. To exemplify our proposal, a simple prototype model of decentralized multi-market transactions is offered. We show that a very simple agent-based computational laboratory can challenge more structured dynamic stochastic general equilibrium models in mimicking comovements over the business cycle.
    Keywords: Microfoundations of macroeconomics, Agent-based economics, Adaptive behavior
    JEL: C63 E10 O11
    Date: 2008
  8. By: Claudia Gutierrez (Institute for Advanced Development Studies)
    Abstract: This paper studies the changes in inequality and poverty in the period 1999-2005 in Bolivia through the analysis of the changes in the labour market. A decomposition method based on micro-simulation techniques was applied. The decomposition works with an income generation model at the household level, which is a set of equations for the individual earnings and for the labour supply and occupational choices for each member of the household. We decomposed the observed change in inequality into four components: i) a shift in the income distribution related to a change in employment rates and the shares of wage and non-wage labour among the employed population (participation effect); ii) a shift related to changes in the remuneration of observed characteristics of the employed population (price effect); iii) a shift related to a change in the distribution of error terms of estimated earn-ings functions (error term effect); and iv) a residual change in inequality not cap-tured by the first three simulated changes in the income distribution. According to our results the increase in inequality of 3 points of the Gini coefficient, was ex-plained by approximately 1 point for the participation, price and error term effects and 2 points for the residual change. The increase in the unemployment rate, the shift in the participation of the non wage earners, the rise in wages and the more unequal distribution of unobserved productive talents deteriorated the income dis-tribution in this period in Bolivia. Regarding the poverty incidence, the observed variation was a reduction by 3 points explained mainly by the residual change. The low magnitude of the simulated effects as determinants of the decline in poverty in those years can be explained by the rising participation of the non labour incomes in the total household income.
    Keywords: Poverty, Inequality, Microsimulation, Bolivia
    JEL: O54 R20 P46
    Date: 2008–01

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