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Computation of Equilibria in OLG Models with Many Heterogeneous Households

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  • Sebastian Rausch
  • Thomas Rutherford

Abstract

Over the past twenty years infinite horizon general equilibrium models with overlapping enerations (OLG) have become an important tool for policy analysis, and have been fruitfully applied in fields such as macroeconomics or public finance (see, e.g., Auerbach and Kotlikoff (1987), and Kotlikoff (2000) for an overview). OLG models naturally involve a large number of variables and equations that describe the equilibrium behavior of economic agents. As a consequence, the development of large-scale OLG models is often limited by the computational capacity of available numerical solution methods. In particular, models that exhibit a rich household side including a variety of household-specific effects, a large number of heterogeneous households, and realistic agent lifetimes typically require “customized solution methods” which may be both costly to implement and difficult to validate.
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  • Sebastian Rausch & Thomas Rutherford, 2010. "Computation of Equilibria in OLG Models with Many Heterogeneous Households," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 171-189, August.
  • Handle: RePEc:kap:compec:v:36:y:2010:i:2:p:171-189
    DOI: 10.1007/s10614-010-9229-8
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    Cited by:

    1. Peichl, Andreas, 2008. "The benefits of linking CGE and Microsimulation Models - Evidence from a Flat Tax analysis," FiFo Discussion Papers - Finanzwissenschaftliche Diskussionsbeiträge 08-6, University of Cologne, FiFo Institute for Public Economics.
    2. Sebastian Rausch & Thomas Rutherford, 2010. "Computation of Equilibria in OLG Models with Many Heterogeneous Households," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 171-189, August.
    3. Lanz, Bruno & Rausch, Sebastian, 2012. "Cap-and-Trade Climate Policies with Price-Regulated Firms: How Costly Are Free Allowances?," Conference papers 332267, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Florian Landis & Sebastian Rausch & Mirjam Kosch & Christoph Böhringer, 2019. "Efficient and Equitable Policy Design: Taxing Energy Use or Promoting Energy Savings?," The Energy Journal, , vol. 40(1), pages 73-104, January.
    5. Magnani, Riccardo & Mercenier, Jean, 2009. "On linking microsimulation and computable general equilibrium models using exact aggregation of heterogeneous discrete-choice making agents," Economic Modelling, Elsevier, vol. 26(3), pages 560-570, May.
    6. Balistreri, Edward J. & Hillberry, Russell H. & Rutherford, Thomas F., 2010. "Trade and welfare: Does industrial organization matter?," Economics Letters, Elsevier, vol. 109(2), pages 85-87, November.
    7. Rausch, Sebastian & Metcalf, Gilbert E. & Reilly, John M., 2011. "Distributional impacts of carbon pricing: A general equilibrium approach with micro-data for households," Energy Economics, Elsevier, vol. 33(S1), pages 20-33.
    8. Sameera Awawda & Mohammad Abu-Zaineh, 2019. "An Operationalizing Theoretical Framework for the Analysis of Universal Health Coverage Reforms: First Test on an Archetype Developing Economy," Working Papers halshs-02009858, HAL.
    9. Orlando Gomes, 2022. "Human capital and growth in an OLG-life cycle model," SN Business & Economics, Springer, vol. 2(1), pages 1-26, January.
    10. Kathy Hibbard & Anthony Janetos, 2013. "The regional nature of global challenges: a need and strategy for integrated regional modeling," Climatic Change, Springer, vol. 118(3), pages 565-577, June.
    11. Melnikov, N.B. & O'Neill, B.C. & Dalton, M.G., 2012. "Accounting for household heterogeneity in general equilibrium economic growth models," Energy Economics, Elsevier, vol. 34(5), pages 1475-1483.
    12. Melnikov, Nikolai B. & O’Neill, Brian C. & Dalton, Michael G. & van Ruijven, Bas J., 2017. "Downscaling heterogeneous household outcomes in dynamic CGE models for energy-economic analysis," Energy Economics, Elsevier, vol. 65(C), pages 87-97.
    13. Jansson, Torbjorn & Bakker, Martha M. & Boitier, B. & Fougeyrollas, A. & Helming, John F.M. & van Meijl, Hans & Verkerk, P.J., 2008. "Linking models for land use analysis: experiences from the SENSOR project," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44169, European Association of Agricultural Economists.
    14. Schmitz, Christoph & Biewald, Anne & Lotze-Campen, Hermann & Popp, Alexander, 2011. "Increased Agricultural Trade and its Impacts on Food System, Land-use and Greenhouse Gas Emissions," Conference papers 332165, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    15. Hoffmann, Christin, 2019. "Estimating the benefits of adaptation to extreme climate events, focusing on nonmarket damages," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    16. Gauthier de Maere d'Aertrycke & Olivier Durand-Lasserve & Marco Schudel, 2014. "Integration of Power Generation Capacity Expansion in an Applied General Equilibrium Model," Working Papers 2014.71, Fondazione Eni Enrico Mattei.
    17. Boeters, Stefan & Savard, Luc, 2013. "The Labor Market in Computable General Equilibrium Models," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 1645-1718, Elsevier.

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    More about this item

    Keywords

    Computable general equilibrium; Overlapping generations; Microsimulation; Sequential recalibration; C68; C81; D61; D91;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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