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Heterogeneity and Aggregate Fluctuations

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We develop a state-space model with a state-transition equation that takes the form of a functional vector autoregression and stacks macroeconomic aggregates and a cross-sectional density. The measurement equation captures the error in estimating log densities from repeated cross-sectional samples. The log densities and the transition kernels in the law of motion of the states are approximated by sieves, which leads to a nite-dimensional representation in terms of macroeconomic aggregates and sieve coefficients. We use this model to study the joint dynamics of technology shocks, per capita GDP, employment rates, and the earnings distribution. We nd that the estimated spillovers between aggregate and distributional dynamics are generally small, a positive technology shock tends to decrease inequality, and a shock that raises the inequality of earnings leads to a small but not significant increase in GDP.

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  • Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021. "Heterogeneity and Aggregate Fluctuations," Cowles Foundation Discussion Papers 2289, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2289
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    Cited by:

    1. Yoosoon Chang & Fabio Gomez-Rodriguez & Christian Matthes, 2023. "The Influence of Fiscal and Monetary Policies on the Shape of the Yield Curve," CAEPR Working Papers 2023-008 Classification-E, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Hilde C. Bjørnland & Yoosoon Chang & Jamie L. Cross, 2023. "Oil and the Stock Market Revisited: A mixed functional VAR approach," Working Papers No 03/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. Matthew D. Cocci & Mikkel Plagborg-M{o}ller, 2021. "Standard Errors for Calibrated Parameters," Papers 2109.08109, arXiv.org, revised Oct 2023.
    4. Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series wps115, Bank of Russia.
    5. Bilbiie, F. & Primiceri, G. E. & Tambalotti, A., 2022. "Inequality and Business Cycles," Cambridge Working Papers in Economics 2275, Faculty of Economics, University of Cambridge.
    6. Matthew D. Cocci & Mikkel Plagborg-Møller, 2021. "Standard Errors for Calibrated Parameters," Working Papers 2021-20, Princeton University. Economics Department..
    7. Stephanie Ettmeier, 2022. "No Taxation without Reallocation: The Distributional Effects of Tax Changes," Discussion Papers of DIW Berlin 2022, DIW Berlin, German Institute for Economic Research.
    8. Laura Liu & Mikkel Plagborg-M{o}ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," Papers 2101.04771, arXiv.org, revised Jun 2022.
    9. Laura Liu & Mikkel Plagborg‐Møller, 2023. "Full‐information estimation of heterogeneous agent models using macro and micro data," Quantitative Economics, Econometric Society, vol. 14(1), pages 1-35, January.

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    More about this item

    Keywords

    Bayesian Model Selection; Econometric Model Evaluation; Earnings Distribution; Functional Vector Autoregressions; Heterogeneous Agent Models; State-space Model; Technology Shocks;
    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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