nep-cmp New Economics Papers
on Computational Economics
Issue of 2006‒03‒25
five papers chosen by
Stan Miles
York University

  1. A Practical Guide to Inference in Simulation Models By T. Brenner; C. Werker
  2. Artificial Neural Networks in Financial Modelling By Crescenzio Gallo; Giancarlo De Stasio; Cristina Di Letizia
  3. A Data Set Generation Algorithm in Combinatorial Auctions By Crescenzio Gallo; Giancarlo De Stasio; Cristina Di Letizia
  4. Continuous State Dynamic Programming via Nonexpansive Approximation By John Stachurski
  5. Macroeconomic impacts of the reform of public services in Uruguay - A CGE analysis By María Inés Terra; Alvaro Forteza; Gabriel Katz; Andrés Pereyra

  1. By: T. Brenner; C. Werker
    Abstract: This paper introduces a categorization of simulation models. It provides an explicit overview of the steps that lead to a simulation model. We highlight the advantages and disadvantages of various simulation approaches by examining how they advocate different ways of constructing simulation models. To this end, it discusses a number of relevant methodological issues, such as how realistic simulation models are obtained and which kinds of inference can be used in a simulation approach. Finally, the paper presents a practical guide on how simulation should and can be conducted.
    Keywords: Methodology, Simulation Models, Practical Guide
    JEL: B41 B52 C63
    Date: 2006–03
  2. By: Crescenzio Gallo; Giancarlo De Stasio; Cristina Di Letizia
    Abstract: The study of Artificial Neural Networks derives from first trials to translate in mathematical models the principles of biological “processing”. An Artificial Neural Network deals with generating, in the fastest times, an implicit and predictive model of the evolution of a system. In particular, it derives from experience its ability to be able to recognize some behaviours or situations and to “suggest” how to take them into account. This work illustrates an approach to the use of Artificial Neural Networks for Financial Modelling; we aim to explore the structural differences (and implications) between one- and multi- agent and population models. In one-population models, ANNs are involved as forecasting devices with wealth-maximizing agents (in which agents make decisions so as to achieve an utility maximization following non-linear models to do forecasting), while in multipopulation models agents do not follow predetermined rules, but tend to create their own behavioural rules as market data are collected. In particular, it is important to analyze diversities between one-agent and one-population models; in fact, in building one-population model it is possible to illustrate the market equilibrium endogenously, which is not possible in one-agent model where all the environmental characteristics are taken as given and beyond the control of the single agent.
    Keywords: artificial neural network, financial modelling, population model, market equilibrium.
    JEL: C53 C69 C90 D58
    Date: 2006–01
  3. By: Crescenzio Gallo; Giancarlo De Stasio; Cristina Di Letizia
    Abstract: The generation of realistic data sets in a Combinatorial Auction may be a challenging problem. Well-formed data sets are very useful in the evaluation of algorithms trying to solve the winner determination problem. In this paper a general data set generation scheme is presented, both from an algorithmic and economic point of view. As a case study, a possible auction setting is discussed where the goods on sale are connections between points in space.
    Keywords: bid, combinatorial auction, data set generation.
    JEL: C51 C61 C87 C99
    Date: 2006–01
  4. By: John Stachurski
    Abstract: This paper studies fitted value iteration for continuous state dynamic programming using nonexpansive function approximators. A number of nonexpansive approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.
    Keywords: Dynamic Programming; Approximation
    JEL: C63 C61
    Date: 2006
  5. By: María Inés Terra (Departmento de Economía, Facultad de Ciencias Sociales, Universidad de la República); Alvaro Forteza (Departmento de Economía, Facultad de Ciencias Sociales, Universidad de la República); Gabriel Katz (Departmento de Economía, Facultad de Ciencias Sociales, Universidad de la República); Andrés Pereyra (Departmento de Economía, Facultad de Ciencias Sociales, Universidad de la República)
    Abstract: This paper investigates the macroeconomic impacts of the reform of public services in Uruguay. A computable general equilibrium (CGE) model is used to simulate different policy scenarios, analyzing the reforms of the regulatory framework of public services, changes in their investment policies, modifications in the competitive environment and reforms in their tax structure. The results show that the macroeconomic effects of the proposed reforms are relatively small.
    Keywords: Social Accounting Matrix, Computable General Equilibrium Models, public services, public sector reform.
    JEL: E17 H11 H32 L42
    Date: 2005–12

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