nep-cmp New Economics Papers
on Computational Economics
Issue of 2006‒04‒22
six papers chosen by
Stan Miles
York University

  1. New Neural Network Methods for Forecasting Regional Employment: An Analysis of German Labour Markets By Roberto Patuelli; Aura Reggiani; Peter Nijkamp; Uwe Blien
  2. New computational results for the nurse scheduling problem: A scatter search algorithm By Maenhout, B.; Vanhoucke, M.;
  3. La simulation de Monte Carlo: forces et faiblesses (avec applications Visual Basic et Matlab et présentation d’une nouvelle méthode QMC) By Francois-Éric Racicot; Raymond Théoret
  4. The Effects of Increasing Openness and Integration to the MERCOSUR on the Uruguayan Labour Market: a CGE Modelling Analysis By Maria Ines Terra; Marisa Bucheli; Silvia Laens; Carmen Estrades
  5. Introducing Imperfect Competition in CGE Models:Technical Aspects and Implications By Roberto Roson
  6. Functional Forms and Parametrization of CGE Models By Nabil Annabi; John Cockburn; Bernard Decaluwé

  1. By: Roberto Patuelli (Department of Spatial Economics, Vrije Universiteit Amsterdam); Aura Reggiani (Department of Economics, University of Bologna, Italy); Peter Nijkamp (Department of Spatial Economics, Vrije Universiteit Amsterdam); Uwe Blien (Institut für Arbeitsmarkt und Berufsforschung (IAB), Nuremberg)
    Abstract: In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in several fields, because of their effectiveness in handling complex data sets when the functional relationship between dependent and independent variables is not explicitly specified. The present paper compares two NN methodologies. First, it uses NNs to forecast regional employment in both the former West and East Germany. Each model implemented computes single estimates of employment growth rates for each German district, with a 2-year forecasting range. Next, additional forecasts are computed, by combining the NN methodology with Shift-Share Analysis (SSA). Since SSA aims to identify variations observed among the labour districts, its results are used as further explanatory variables in the NN models. The data set used in our experiments consists of a panel of 439 German districts. Because of differences in the size and time horizons of the data, the forecasts for West and East Germany are computed separately. The out-of-sample forecasting ability of the models is evaluated by means of several appropriate statistical indicators.
    Keywords: networks; forecasts; regional employment; shift-share analysis; shift-share regression
    JEL: C23 E27 R12
    Date: 2006–02–17
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20060020&r=cmp
  2. By: Maenhout, B.; Vanhoucke, M.;
    Abstract: In this paper, we present a scatter search algorithm for the well-known nurse scheduling problem (NSP). This problem aims at the construction of roster schedules for nurses taking both hard and soft constraints into account. The objective is to minimize the total preference cost of the nurses and the total penalty cost from violations of the soft constraints. The problem is known to be NP-hard. The contribution of this paper is threefold. First, we are, to the best of our knowledge, the first to present a scatter search algorithm for the NSP. Second, we investigate two different types of solution combination methods in the scatter search framework, based on four different cost elements. Last, we present detailed computational experiments on a benchmark dataset presented recently, and solve these problem instances under different assumptions. We show that our procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints.
    Keywords: meta-heuristics; scatter search; nurse scheduling
    Date: 2006–04–07
    URL: http://d.repec.org/n?u=RePEc:vlg:vlgwps:2006-06&r=cmp
  3. By: Francois-Éric Racicot (Département des sciences administratives, Université du Québec (Outaouais) et LRSP); Raymond Théoret (Département de stratégie des affaires, Université du Québec (Montréal))
    Abstract: Monte Carlo simulation has an advantage upon the binomial tree as it can take into account the multidimensions of a problem. However it convergence speed is slower. In this article, we show how this method may be improved by various means: antithetic variables, control variates and low discrepancy sequences: Faure, Sobol and Halton sequences. We show how to compute the standard deviation of a Monte Carlo simulation when the payoffs of a claim, like a contingent claim, are nonlinear. In this case, we must compute this standard deviation by doing a great number of repeated simulations such that we arrive at a normal distribution of the results. The mean of the means of these simulations is then a good estimator of the wanted price. We also show how to combine Halton numbers with antithetic variables to improve the convergence of a QMC. That is our new version of QMC which is then well named because the result varies from one simulation to the other in our version of the QMC while the result is fixed (not random) in a classical QMC, like in the binomial tree.
    Keywords: Financial engineering, derivatives, Monte Carlo simulation, low discrepancy sequences.
    JEL: G12 G13 G33
    Date: 2006–04–10
    URL: http://d.repec.org/n?u=RePEc:pqs:wpaper:052006&r=cmp
  4. By: Maria Ines Terra; Marisa Bucheli; Silvia Laens; Carmen Estrades
    Abstract: Uruguay is a small economy. Its integration into MERCOSUR has increased its exposure to regional macroeconomic instability. The aim of this paper is to assess the impact of regional integration on the country's labour market and poverty. We estimated wage differentials between labour categories, finding a 60 percent wage gap between formal and informal workers. A CGE model with an efficiency wage specification for unskilled labour was built, with results showing that regional shocks deeply affect the Uruguayan economy. The consideration of an efficiency wage model is particularly important when shocks lead to a reallocation of resources towards sectors intensive in unskilled labour. A subsidy on formal, unskilled labour could contribute to decrease informality and therefore increase GDP, but this type of policy needs to be carefully implemented because it may have negative effects on investment. Finally, the effects on poverty and income distribution obtained through microsimulations are consistent with the results of the CGE experiments.
    Keywords: Uruguay, labour market, general equilibrium model, regional itegration, efficiency wage, microsimulation, poverty
    JEL: D58 I32 F15 F16 J41
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:lvl:mpiacr:2006-06&r=cmp
  5. By: Roberto Roson (Department of Economics, University Of Venice Cà Foscari)
    Abstract: This paper considers the technical aspects and the consequences, in terms of simulation results and policy assessment, of introducing imperfect competition in a CGE model. The modifications to the standard CGE framework needed to model imperfect competition in some industries are briefly discussed. Next, the paper examines whether, how much and why, those changes may affect the qualitative output a typical simulation experiment. It is argued that technical choices made in designing the model structure may have a significant impact on the model behavior. This is especially evident when the model output of an imperfect competition closure is compared with the one of a standard closure, assuming perfect competition. As an illustration, a simulation of agricultural trade liberalization is analyzed. Results from the same simulation exercise, but produced by alternative model formulations (one standard competitive and three imperfect competition variants) are presented and discussed. It is found that having imperfect competition in a CGE model does matter in terms of simulation results. Furthermore, alternative formulations of imperfect competition typically bring about quite different findings and implications.
    Keywords: Computable General Equilibrium Models, Imperfect Competition, Oligopolistic Models, Economies of Scale, Empirical Industrial Organization, Agriculture, Trade Liberalization, Trade Policy.
    JEL: D58 F12 L16
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:ven:wpaper:02_06&r=cmp
  6. By: Nabil Annabi; John Cockburn; Bernard Decaluwé
    Abstract: This study focused on the choice of functional forms and their parametrization (estimation of free parameters and calibration of other parameters) in the context of CGE models. Various types of elasticities are defined, followed by a presentation of the functional forms most commonly used in these models and various econometric methods for estimating their free parameters. Following this presentation of the theoretical framework, we review parameter estimates used in the literature. This brief literature review was carried out to be used as a guideline for the choice of parameters for CGE models of developing countries.
    Keywords: Trade liberalization, Poverty, Elasticities, Functional forms, Calibration, Computable General Equilibrium (CGE)Model
    JEL: C51 C81 C82 D58 E27
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:lvl:mpiacr:2006-04&r=cmp

This nep-cmp issue is ©2006 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.