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Deriving CGE Baselines from Macro-economic Projections

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  • Mueller, Marc
  • Ferrari, Emanuele

Abstract

Quantitative policy analysts are usually confronted with the problem to derive a base-line scenario that reflects the most likely state of an economy in a future year. The methods used in practice to derive such a base-line scenarios are heterogeneous and range from the usage of the last observable year to complete and consistent estimation procedures. In the case of general equilibrium (CGE) analyses, the Scenar2020 project (European Commission 2006a) is one example how projections of macro-economic indicators (exogenous drivers) are used to construct the base-line as a model scenario: Starting from a calibrated version, exogenous variables are modified until macro-economic projections are met. However, numerous projections refer to economic indicators which are endogenous variables within the CGE framework, such as gross domestic product (GDP), market prices, or produced quantities. To investigate methods that allow integrating projections for endogenous CGE variables is the main topic of this study. Our starting point is the work by Arndt et al (2002), where entropy-based (Golan et al 1996) techniques are employed for the estimation of behavioural parameters by fitting a CGE model to time series on endogenous variables. Following this concept, we investigate a method to fit a CGE´s parameters and endogenous variables to market- and macro-economic projections from major research institutes.

Suggested Citation

  • Mueller, Marc & Ferrari, Emanuele, 2011. "Deriving CGE Baselines from Macro-economic Projections," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114638, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae11:114638
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    References listed on IDEAS

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    1. Peter B. Dixon & Maureen T. Rimmer, 2009. "Forecasting with a CGE model: does it work?," Centre of Policy Studies/IMPACT Centre Working Papers g-197, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Decreux, Yvan & Valin, Hugo, 2007. "MIRAGE, Updated Version of the Model for Trade Policy Analysis: Focus on Agriculture and Dynamics," Working Papers 7284, TRADEAG - Agricultural Trade Agreements.
    3. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.
    4. Arndt, Channing & Robinson, Sherman & Tarp, Finn, 2002. "Parameter estimation for a computable general equilibrium model: a maximum entropy approach," Economic Modelling, Elsevier, vol. 19(3), pages 375-398, May.
    5. Golan, Amos & Judge, George & Robinson, Sherman, 1994. "Recovering Information from Incomplete or Partial Multisectoral Economic Data," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 541-549, August.
    6. Heckelei, Thomas & Mittelhammer, Ronald C. & Jansson, Torbjorn, 2008. "A Bayesian Alternative To Generalized Cross Entropy Solutions For Underdetermined Econometric Models," Discussion Papers 56973, University of Bonn, Institute for Food and Resource Economics.
    7. Sandra Poncet, 2006. "The Long Term Growth Prospects of the World Economy: Horizon 2050," Working Papers 2006-16, CEPII research center.
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    Keywords

    general equilibrium model; baseline construction; parameter estimation; macro-economic projections; Research Methods/ Statistical Methods;

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