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Labor-Market Heterogeneity, Aggregation, and the Policy-(In)variance of DSGE Model Parameters

Author

Listed:
  • Yongsung Chang

    (University of Rochester)

  • Sun-Bin Kim

    (Yonsei University)

  • Frank Schorfheide

    (University of Pennsylvania)

Abstract
Data from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply are simulated under various fiscal policy regimes and an approximating representative-agent model is estimated. Preference and technology parameter estimates of the representative-agent model are not invariant to policy changes and the bias in the representative-agent model’s policy predictions is large compared to predictive intervals that reflect parameter uncertainty. Since it is not always feasible to account for heterogeneity explicitly, it is important to recognize the possibility that the parameters of a highly aggregated model may not be invariant with respect to policy changes.

Suggested Citation

  • Yongsung Chang & Sun-Bin Kim & Frank Schorfheide, 2011. "Labor-Market Heterogeneity, Aggregation, and the Policy-(In)variance of DSGE Model Parameters," RCER Working Papers 566, University of Rochester - Center for Economic Research (RCER).
    • Handle: RePEc:roc:rocher:566
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Labor-Market Heterogeneity, Aggregation, and the Policy-(In)variance of DSGE Model Parameters
      by Christian Zimmermann in NEP-DGE blog on 2011-10-03 18:18:34

    Citations

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    Cited by:

    1. Fabio Canova & Filippo Ferroni & Christian Matthes, 2015. "Approximating Time Varying Structural Models With Time Invariant Structures," Working Paper 15-10, Federal Reserve Bank of Richmond.
    2. Salvador Barrios & Mathias Dolls & Anamaria Maftei & Andreas Peichl & Sara Riscado & Janos Varga & Christian Wittneben, 2019. "Dynamic Scoring Of Tax Reforms In The European Union," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 38(1), pages 239-262, January.
    3. Hurtado, Samuel, 2014. "DSGE models and the Lucas critique," Economic Modelling, Elsevier, vol. 44(S1), pages 12-19.
    4. Jang-Ok Cho & Thomas Cooley & Hyung Seok Kim, 2015. "Business Cycle Uncertainty and Economic Welfare," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(2), pages 185-200, April.
    5. Dolls, Mathias & Wittneben, Christian, 2017. "Dynamic Scoring of Tax Reforms in the EU," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168261, Verein für Socialpolitik / German Economic Association.
    6. Frank Schorfheide, 2012. "EconomicDynamics Interviews Frank Schorfheide on DSGE Model Estimation," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 13(2), April.
    7. repec:zbw:bofrdp:2018_022 is not listed on IDEAS
    8. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Research Discussion Papers 22/2018, Bank of Finland.
    9. Marcin Bielecki & Michał Brzoza‐Brzezina & Marcin Kolasa & Krzysztof Makarski, 2019. "Could the Boom‐Bust in the Eurozone Periphery Have Been Prevented?," Journal of Common Market Studies, Wiley Blackwell, vol. 57(2), pages 336-352, March.
    10. Moore, Rachel & Pecoraro, Brandon, 2020. "Macroeconomic implications of modeling the Internal Revenue Code in a heterogeneous-agent framework," Economic Modelling, Elsevier, vol. 87(C), pages 72-91.
    11. Nils M. Gornemann & Keith Kuester & Makoto Nakajima, 2012. "Monetary policy with heterogeneous agents," Working Papers 12-21, Federal Reserve Bank of Philadelphia.
    12. Saito, Yuta, 2014. "Are Deep Parameters Policy-Invariant?," MPRA Paper 66236, University Library of Munich, Germany.
    13. Dmitry I. Malakhov & Nikolay P. Pilnik & Igor G. Pospelov, 2015. "Stability of Distribution of Relative Sizes of Banks as an Argument for the Use of the Representative Agent Concept," HSE Working papers WP BRP 116/EC/2015, National Research University Higher School of Economics.
    14. Yagihashi, Takeshi, 2018. "How costly is a misspecified credit channel DSGE model in monetary policymaking?," Economic Modelling, Elsevier, vol. 68(C), pages 484-505.
    15. Macnamara Patrick, 2016. "Understanding entry and exit: a business cycle accounting approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 47-91, January.

    More about this item

    Keywords

    Aggregation; DSGE Models; Fiscal Policy; Heterogeneous-Agents Economy; Policy Predictions; Representative-Agent Models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory

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