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Heterogeneity in Macroeconomics and the Minimal Econometric Interpretation for Model Comparison

Author

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  • Marco Cozzi

    (Queen's University)

Abstract

This paper formally compares the fit of various versions of the incomplete markets model with aggregate uncertainty, relying on a simple Bayesian empirical framework. The models differ in the degree of households' heterogeneity, with a focus on the role of preferences. For every specification, empirically motivated priors for the parameters are postulated to obtain the models' predictive distributions, which are interpreted as being the distributions of population moments. These are in turn contrasted with the posterior distributions of the same moments obtained from an atheoretical (Bayesian) econometric model. It is shown that aggregate data on consumption and income contain valuable information to determine which models are more likely to have generated the data. In particular, despite its generality, a model with both risk aversion and discount factor heterogeneity displays a very low marginal likelihood, and should not be employed for the design of macroeconomic policies and welfare analysis. It is also found that the other models display similar posterior odds, with the Bayes factors ranging between 1 and 3. Finally, it is shown that practitioners in the field should carefully calibrate the values of the unemployment rate in booms and expansions, as they heavily affect the autocorrelation of aggregate consumption and the correlation between consumption and income. This finding suggests that the magnitude of welfare effects computations is likely to be influenced considerably by these two parameters.

Suggested Citation

  • Marco Cozzi, 2014. "Heterogeneity in Macroeconomics and the Minimal Econometric Interpretation for Model Comparison," Working Papers 1333, Queen's University, Department of Economics.
  • Handle: RePEc:qed:wpaper:1333
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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1333.pdf
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    References listed on IDEAS

    as
    1. Ríos-Rull, José-Víctor & Schorfheide, Frank & Fuentes-Albero, Cristina & Kryshko, Maxym & Santaeulàlia-Llopis, Raül, 2012. "Methods versus substance: Measuring the effects of technology shocks," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 826-846.
    2. Marco Cozzi, 2015. "The Krusell–Smith Algorithm: Are Self-Fulfilling Equilibria Likely?," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 653-670, December.
    3. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    4. Chiu, Jonathan & Molico, Miguel, 2010. "Liquidity, redistribution, and the welfare cost of inflation," Journal of Monetary Economics, Elsevier, vol. 57(4), pages 428-438, May.
    5. Den Haan, Wouter J. & Judd, Kenneth L. & Juillard, Michel, 2010. "Computational suite of models with heterogeneous agents: Incomplete markets and aggregate uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 1-3, January.
    6. Marco Cozzi, 2012. "Risk Aversion Heterogeneity, Risky Jobs and Wealth Inequality," Working Papers 1286, Queen's University, Department of Economics.
    7. DeJong, David N. & Ripoll, Marla, 2007. "Do self-control preferences help explain the puzzling behavior of asset prices?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1035-1050, May.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Incomplete Markets; Heterogeneous Agents; Unemployment Risk; Business Cycles; Calibration; Bayesian Methods; Minimal Econometric Intepretation; Model Comparison;

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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