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Development of a Multi-Household Version of the Monash Model

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  • Rimmer, Maureen

Abstract

This paper is ongoing work by the Centre of Policy Studies and the Impact Project that integrates the ideas of micro simulation with Computable General Equilibrium (CGE) modelling. In micro simulation the behaviour of individuals or households is modelled directly, typically using unit record data, whereas CGE models place an emphasis on market interactions and can take account of the indirect effect on households of changes in market conditions. For many policy issues (such as taxation reform), a combination of the two approaches is desirable so that both the direct and the indirect effects of such reform can be addressed. What is needed is for unit record data to be used in combination with a CGE model; that is, for the modelling of households to be combined with the modelling of markets. This can be achieved by embedding a detailed household sector in an CGE model. The solution of the model then provides distributional results for the representative households directly. In this paper a detailed household sector comprising 100 types of households — differentiated by income and demographic grouping — is developed and embedded in the MONASH Model. Simulations are conducted that measure the economy wide effects of redistributing income across these households.

Suggested Citation

  • Rimmer, Maureen, 1995. "Development of a Multi-Household Version of the Monash Model," Impact Project Archive 295048, Impact Research Centre, University of Melbourne.
    • Handle: RePEc:ags:ircipa:295048
    DOI: 10.22004/ag.econ.295048
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    References listed on IDEAS

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    1. Alan A. Powell, 1993. "A Decade Of Applied General Equilibrium Modelling At The University Of Melbourne," Economic Papers, The Economic Society of Australia, vol. 12(1), pages 87-103, March.
    2. Rimmer, Maureen T. & Powell, Alan A., "undated". "ENGEL FLEXIBILITY IN HOUSEHOLD BUDGET STUDIES: Non-parametric Evidence versus Standard Functional Forms," Center of Policy Studies (COPS) Impact Project Papers 266350, Monash University Center of Policy Studies.
    3. Lewbel, Arthur, 1991. "The Rank of Demand Systems: Theory and Nonparametric Estimation," Econometrica, Econometric Society, vol. 59(3), pages 711-730, May.
    4. Rimmer, Maureen T. & Powell, Alan A., "undated". "An Implicitly Directly Additive Demand System: Estimates for Australia," Center of Policy Studies (COPS) Impact Project Papers 266346, Monash University Center of Policy Studies.
    5. Rimmer, Maureen T. & Powell, Alan A., "undated". "Demand Patterns Across the Development Spectrum: Estimates of the AIDADS System," Center of Policy Studies (COPS) Impact Project Papers 266348, Monash University Center of Policy Studies.
    6. BARTEN, Anton P., 1968. "Estimating demand equations," LIDAM Reprints CORE 21, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    8. B. R. Parmenter & G. A. Meagher, 1985. "Policy Analysis Using a Computable General Equilibrium Model: A Review of Experience at the IMPACT Project," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 18(1), pages 3-15, March.
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