nep-cmp New Economics Papers
on Computational Economics
Issue of 2005‒10‒22
seven papers chosen by
Stan Miles
York University

  1. Agent-Based Computational Modeling And Macroeconomics By Tesfatsion, Leigh S.
  2. Optimal Government Policies in Models with Heterogeneous Agents By Radim Bohacek; Michal Kejak
  3. Solving General Equilibrium Models with Incomplete Markets and Many Assets By Martin D. D. Evans (Georgetown University) and Viktoria Hnatkovska (Georgetown University)
  4. Tax Systems under Fiscal Adjustment: A Dynamic CGE Analysis of the Brazilian Tax Reform By Victor Duarte Lledo
  5. Nonparametric Risk Management with Generalized Hyperbolic Distributions By Ying Chen; Wolfgang Härdle; Seok-Oh Jeong
  6. Using and producing ideas in computable endogenous growth By K. Vela Velupillai
  7. Generalized Stochastic Gradient Learning By George W. Evans; Seppo Honkapohja; Noah Williams

  1. By: Tesfatsion, Leigh S.
    Abstract: Agent-based Computational Economics (ACE) is the computational study of economic processes modeled as dynamic systems of interacting agents. This essay discusses the potential use of ACE modeling tools for the study of macroeconomic systems. Points are illustrated using an ACE model of a two-sector decentralized market economy.
    Keywords: Agent-based computational economics; Complex adaptive systems; Macroeconomics; Microfoundations;
    JEL: B4 C6 C7 D4 D5 D6 D8 L1
    Date: 2005–07–26
  2. By: Radim Bohacek; Michal Kejak
    Abstract: In this paper we develop a new methodology for finding optimal government policies in economies with heterogeneous agents. The methodology is solely based on three classes of equilibrium conditions from the government’s and individual agent’s optimization problems: 1) the first order conditions; 2) the stationarity condition on the distribution function; and, 3) the aggregate market clearing conditions. These conditions form a system of functional equations which we solve numerically. The solution takes into account simultaneously the effect of government policy on individual allocations and (from the government’s point of view) optimal distribution of agents in the steady state. This general methodology is applicable to a wide range of optimal government policies in models with heterogeneous agents. We illustrate it on a steady state Ramsey problem with heterogeneous agents, finding the optimal tax schedule. JEL Keywords: Optimal macroeconomic policy, optimal taxation, computational techniques, heterogeneous agents, distribution of wealth and income
    JEL: C61 C68 D30 D58
    Date: 2005–09
  3. By: Martin D. D. Evans (Georgetown University) and Viktoria Hnatkovska (Georgetown University) (Department of Economics, Georgetown University)
    Abstract: This paper presents a new numerical method for solving general equilibrium models with many assets. The method can be applied to models where there are heterogeneous agents, time-varying investment opportunity sets, and incomplete markets. It also can be used to study models where the equilibrium dynamics are non-stationary. We illustrate how the method is used by solving a one— and two-sector versions of a two—country general equilibrium model with production. We check the accuracy of our method by comparing the numerical solution to the one-sector model against its known analytic properties. We then apply the method to the two-sector model where no analytic solution is available. Classification-JEL Codes: C68; D52; G11.
    Keywords: Portfolio Choice; Perturbation Methods; Incomplete Markets; Asset Prices.
  4. By: Victor Duarte Lledo
    Abstract: This paper uses a dynamic computable general equilibrium model (CGE) to analyze the macroeconomic and redistributive effects of replacing turnover and financial transaction taxes in Brazil by a consumption tax. In order to approximate Brazil's compliance with its fiscal adjustment targets, the proposed reform is subject to a non increasing path for the level of public debt. Despite an increase in the average consumption tax rate in the first years after the reform, a majority of individuals experienced an increase in their lifetime welfare. This result rejects the hypothesis that the on-going fiscal adjustment effort carried on by the Brazilian government was an obstacle to the implementation of a more efficient tax system.
    Keywords: Tax reforms , Brazil , Fiscal reforms , Economic models ,
    Date: 2005–08–01
  5. By: Ying Chen; Wolfgang Härdle; Seok-Oh Jeong
    Abstract: In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more appropriately. The nonparametric adaptive methodology has the desirable property of estimating homogeneous volatility in a short time interval. For DEM/USD exchange rate data and a German bank portfolio data the proposed GHADA model provides more accurate value at risk calculation than the traditional model based on the normal distribution. All calculations and simulations are done with XploRe.
    Keywords: adaptive volatility estimation, generalized hyperbolic distribution, value at risk, risk management
    JEL: C
    Date: 2004–10
  6. By: K. Vela Velupillai
    Abstract: It is shown that Paul Romer’s suggestion to model algorithmically the use and production of ideas in an endogenous growth model is formally feasible. Such a modelling exercise imparts a natural evolutionary flavour to growth models. However, it is also shown that the policy implications are formally indeterminate in a precise and effective sense.
    Keywords: endogenous growth,algorithmic ideas,computable growth
    JEL: C63 D24 E10 O41
    Date: 2005
  7. By: George W. Evans; Seppo Honkapohja; Noah Williams
    Abstract: We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is a transformation of variables for which E-stability governs SG stability. GSG algorithms with constant gain have a deeper justification in terms of parameter drift, robustness and risk sensitivity.
    JEL: C62 C65 D83 E10 E17
    Date: 2005–10

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