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Labor-Market Heterogeneity, Aggregation, and the Lucas Critique

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  • Yongsung Chang
  • Sun-Bin Kim
  • Frank Schorfheide

Abstract

This paper assesses biases in policy predictions due to the lack of invariance of "structural'' parameters in representative-agent models. We simulate data under various fiscal policy regimes from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply. Imperfect aggregation manifests itself through preference shocks in the estimated representative-agent model. Preference and technology parameter estimates are not invariant with respect to policy changes. As a result, the bias in the representative-agent model's policy predictions is large compared to the length of predictive intervals that reflect parameter uncertainty.

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  • Yongsung Chang & Sun-Bin Kim & Frank Schorfheide, 2010. "Labor-Market Heterogeneity, Aggregation, and the Lucas Critique," NBER Working Papers 16401, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16401
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    1. Labor-Market Heterogeneity, Aggregation, and the Lucas Critique
      by Christian Zimmermann in NEP-DGE blog on 2010-10-08 08:16:08

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    1. Francesco Sergi, 2018. "DSGE Models and the Lucas Critique. A Historical Appraisal," Working Papers 20181806, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    2. Pesaran, M. Hashem & Smith, Ron P., 2011. "Beyond the DSGE Straitjacket," IZA Discussion Papers 5661, Institute of Labor Economics (IZA).
    3. Fernando J. Pérez Forero, 2017. "Measuring the Stance of Monetary Policy in a Time-Varying," Working Papers 102, Peruvian Economic Association.
    4. Christian Bayer & Volker Tjaden, 2016. "Large Open Economies and Fixed Costs of Capital Adjustment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 21, pages 125-146, July.
    5. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    6. Francisco J. Buera & Benjamin Moll, 2012. "Aggregate Implications of a Credit Crunch," NBER Working Papers 17775, National Bureau of Economic Research, Inc.

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    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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