nep-cmp New Economics Papers
on Computational Economics
Issue of 2014‒10‒17
23 papers chosen by
Stan Miles
Thompson Rivers University

  1. Impact Assessment of Thailand’s Promotion of Strategic Export Industries: A Computable General Equilibrium Model (CGE) Approach By Kriengsak CHAREONWONGSAK
  2. Aging and the Regional Economy: Simulation Results from the Chicago CGE Model By Geoffrey J.D. HEWINGS; Seryoung PARK
  3. The Role of Income Transfer Programs in the Fall of Income Inequality in Brasil : a CGE Micro-Simulation Approach By Samir Cury; Allexandro Mori Coelh; Euclides Pedroso
  4. Forecasting Medium-Term Distributional Effects of the Economic Crisis: A CGE-Microsimulation Approach By Michael FEIL
  5. Impact Analysis of Regional Knowledge Subsidy: a CGE Approach Applied to Sardinia By Patrizio LECCA; Giorgio GARAU
  6. Complex Dynamics and Financial Fragility in an Agent Based Model By GALLEGATI Mauro; GIULIONI Gianfranco; KICHIJI Nozomi
  7. Analysis of International Emissions Trading System Applying Multi-Agent Model By Kenichi Matsumoto
  8. Assessing Economic and Fiscal Reforms in Lebanon. A dynamic CGE Analysis with Debt Constraints By Beatriz GAITAN S.; Bernd LUCKE; Jacopo ZOTTI
  9. Analysis of Economic and Environmental Impacts of CO2 Abatement in Japan Applying a CGE Model with Knowledge Investment By Kenichi MATSUMOTO; Azusa OKAGAWA
  10. Disinflation Simulation with Disaggregated Output Gap Model for Hungary By Viktor VÁRPALOTAI
  11. Fuzzy Cotrolled Simulation for Traffic Flow By Zahra Javaheri; Azadeh M.A
  12. Migration Impact on Moroccan Unemployment: a Static Computable General Equilibrium Analysis By Fida KARAM; Bernard DECALUWÉ
  13. Evaluation of CO2 Emission Trading in Ukraine: the CGE approach By Olga Diukanova
  14. Analysis of the Millennium Development Goals for Egypt - Using an Extended Economy Wide Simulation Model By Motaz KHORSHID; Hans LOFGREN; Ahmed KAMALY; Sohair ABOU EL-EENEIN
  15. Opening Services Markets within Europe: Modelling Foreign Establishments in a CGE Framework By Hugo ROJAS-ROMAGOSA; Arjan LEJOUR; Gerard VERWEIJ
  16. Unions and Economic Inefficiency in Brazil: A CGE Approach By Ignacio Tavares ARAUJO JUNIOR; Nayana RUTH FIGUEREDO
  17. Demographic Changes and the Gains from Globalisation: An Overlapping Generations CGE Analysis By Patrick GEORGES; Marcel MERETTE
  18. Generalized local branching heuristics and the capacitated ring tree problem By HILL, Alessandro; VOß, Stefan
  19. Some Border Management Options: A CGE Investigation By Marcel MÉRETTE; Evangelia PAPADAKI
  20. Economic Implications of Deeper South Asian–Southeast Asian Integration : A CGE Approach By Ganeshan Wignaraja; Peter Morgan; Michael Plummer; Fan Zhai
  21. Trade Policy Analysis of Edible Oil Imports of India under CGE framework By KM Shivakumar; S.Kombairaju; M.Chandrasekaran
  22. Forecasting of International Financial Markets with Neural Networks: a New Approach By Rouhia NOOMENE; Roberto LOPEZ
  23. Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks By Tae-Hwy Lee; Zhou Xi; Ru Zhang

  1. By: Kriengsak CHAREONWONGSAK
  2. By: Geoffrey J.D. HEWINGS; Seryoung PARK
  3. By: Samir Cury; Allexandro Mori Coelh; Euclides Pedroso
  4. By: Michael FEIL
  5. By: Patrizio LECCA; Giorgio GARAU
  6. By: GALLEGATI Mauro; GIULIONI Gianfranco; KICHIJI Nozomi
  7. By: Kenichi Matsumoto
  8. By: Beatriz GAITAN S.; Bernd LUCKE; Jacopo ZOTTI
  9. By: Kenichi MATSUMOTO; Azusa OKAGAWA
  10. By: Viktor VÁRPALOTAI
  11. By: Zahra Javaheri; Azadeh M.A
  12. By: Fida KARAM; Bernard DECALUWÉ
  13. By: Olga Diukanova
  16. By: Ignacio Tavares ARAUJO JUNIOR; Nayana RUTH FIGUEREDO
  17. By: Patrick GEORGES; Marcel MERETTE
  18. By: HILL, Alessandro; VOß, Stefan
    Abstract: In this paper we present a heuristic framework that is based on mathematical programming to solve network design problems. Our techniques combine local branching with locally exact refinements. In an iterative strategy an existing solution is refined by solving restricted mixed integer programs (MIPs) to optimality. These are obtained from the master problem MIP by (1) fixing a subset of binary variables and (2) limiting the number of variable ips among the unfixed variables. We introduce generalized local branching cuts which enforce (1) and (2). Using these concepts we develop an efficient algorithm for the capacitated ring tree problem (CRTP), a recent network design model for reliable capacitated networks that combines cycle and tree structures. Our implementation operates on top of an efficient branch & cut algorithm for the CRTP. The sets of refinement variables are deduced from single and multi-ball CRTP-tailored network node clusters. We provide computational results using a set of literature instances. We show that the approach is capable of improving existing best results for the CRTP when integrated into a multi-start local search heuristic, but is also efficient when used independently.
    Keywords: Capacitated ring tree problem, Local branching, Mathematical programming, Local search, Network design, Matheuristic
    Date: 2014–09
  19. By: Marcel MÉRETTE; Evangelia PAPADAKI
  20. By: Ganeshan Wignaraja (Asian Development Bank Institute (ADBI)); Peter Morgan; Michael Plummer; Fan Zhai
    Abstract: South and Southeast Asian economic integration via increased trade flows has been increasing significantly over the past 2 decades, but the level of trade continues to be relatively low. This underperformance has been due to both policy-related variables—relatively high tariff and non-tariff barriers—and high trade costs due to inefficient “hard†and “soft†infrastructure (costly transport links and problems related to trade facilitation). The goal of this study is to estimate the potential gains from South Asian–Southeast Asian economic integration using an advanced computable general equilibrium (CGE) model. The paper estimates the potential gains to be large, particularly for South Asia, assuming that the policy- and infrastructure-related variables that increase trade costs are reduced via economic cooperation and investment in connectivity. As Myanmar is a key inter-regional bridge and has recently launched ambitious, outward-oriented policy reforms, the prospects for making progress in these areas are strong. If the two regions succeed in dropping inter-regional tariffs, reducing non-tariff barriers by 50%, and decreasing South Asian–Southeast Asian trade costs by 15%—which this paper suggests is ambitious but attainable—welfare in South Asia and Southeast Asia would rise by 8.9% and 6.4% of gross domestic product, respectively, by 2030 relative to the baseline. These gains would be driven by rising exports and competitiveness, particularly for South Asia, whose exports would rise by two thirds (64% relative to the baseline). Hence, the paper concludes that improvements in connectivity would justify a high level of investment. Moreover, it supports a two-track approach to integration in South Asia, i.e., deepening intra-regional cooperation together with building links to Southeast Asia.
    Keywords: South Asian–Southeast Asian Integration, CGE approach, intra-regional cooperation, South Asia, Southeast Asia
    JEL: C68 F12 F13 F15 F17
    Date: 2014–08
  21. By: KM Shivakumar; S.Kombairaju; M.Chandrasekaran
  22. By: Rouhia NOOMENE; Roberto LOPEZ
  23. By: Tae-Hwy Lee (Department of Economics, University of California Riverside); Zhou Xi (University of California, Riverside); Ru Zhang (University of California, Riverside)
    Abstract: The artificial neural network (ANN) test of Lee et al. (Journal of Econometrics 56, 269–290, 1993) uses the ability of the ANN activation functions in the hidden layer to detect neglected functionalmisspecification. As the estimation of the ANN model is often quite difficult, LWG suggested activate the ANN hidden units based on randomly drawn activation parameters. To be robust to the random activations, a large number of activations is desirable. This leads to a situation for which regularization of the dimensionality is needed by techniques such as principal component analysis (PCA), Lasso, Pretest, partial least squares (PLS), among others. However, some regularization methods can lead to selection bias in testing if the dimensionality reduction is conducted by supervising the relationship between the ANN hidden layer activations of inputs and the output variable. This paper demonstrates that while these supervised regularization methods such as Lasso, Pretest, PLS, may be useful for forecasting, they may not be used for testing because the supervised regularizationwould create the post-sample inference or post-selection inference (PoSI) problem. Our Monte Carlo simulation shows that the PoSI problem is especially severe with PLS and Pretest while it seems relatively mild or even negligible with Lasso. This paper also demonstrates that the use of unsupervised regularization does not lead to the PoSI problem. Lee et al. (Journal of Econometrics 56, 269–290, 1993) suggested a regularization by principal components, which is a unsupervised regularization.While the supervised regularizations may be useful in forecasting, regularization should not be supervised in inference.
    Keywords: Randomized ANN activations • Dimension reduction • Supervised regularization • Unsupervised regularization • PCA • Lasso • PLS • Pretest • PoSI problem
    JEL: C12 C45
    Date: 2013–09

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