[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/2289.html
   My bibliography  Save this paper

Heterogeneity and Aggregate Fluctuations

Author

Listed:
Abstract
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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d22/d2289.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fuentes-Albero, Cristina & Melosi, Leonardo, 2013. "Methods for computing marginal data densities from the Gibbs output," Journal of Econometrics, Elsevier, vol. 175(2), pages 132-141.
    2. Krueger, D. & Mitman, K. & Perri, F., 2016. "Macroeconomics and Household Heterogeneity," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 843-921, Elsevier.
    3. Yongsung Chang & Sun-Bin Kim, 2006. "From Individual To Aggregate Labor Supply: A Quantitative Analysis Based On A Heterogeneous Agent Macroeconomy ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(1), pages 1-27, February.
    4. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    5. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    6. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    7. SeHyoun Ahn & Greg Kaplan & Benjamin Moll & Thomas Winberry & Christian Wolf, 2018. "When Inequality Matters for Macro and Macro Matters for Inequality," NBER Macroeconomics Annual, University of Chicago Press, vol. 32(1), pages 1-75.
    8. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    9. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    10. John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
    11. Pablo Ottonello & Thomas Winberry, 2020. "Financial Heterogeneity and the Investment Channel of Monetary Policy," Econometrica, Econometric Society, vol. 88(6), pages 2473-2502, November.
    12. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    13. Coibion, Olivier & Gorodnichenko, Yuriy & Kueng, Lorenz & Silvia, John, 2017. "Innocent Bystanders? Monetary policy and inequality," Journal of Monetary Economics, Elsevier, vol. 88(C), pages 70-89.
    14. Yongsung Chang & Sun‐Bin Kim & Kyooho Kwon & Richard Rogerson, 2019. "2018 Klein Lecture: Individual And Aggregate Labor Supply In Heterogeneous Agent Economies With Intensive And Extensive Margins," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(1), pages 3-24, February.
    15. Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
    16. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    17. Greg Kaplan & Giovanni L. Violante, 2018. "Microeconomic Heterogeneity and Macroeconomic Shocks," Journal of Economic Perspectives, American Economic Association, vol. 32(3), pages 167-194, Summer.
    18. Eichenbaum, Martin & Parker, Jonathan A. (ed.), . "NBER Macroeconomics Annual 2017," National Bureau of Economic Research Books, University of Chicago Press, number 9780226577838, July.
    19. Reiter, Michael, 2009. "Solving heterogeneous-agent models by projection and perturbation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 649-665, March.
    20. Chang, Yoosoon & Kim, Chang Sik & Park, Joon Y., 2016. "Nonstationarity in time series of state densities," Journal of Econometrics, Elsevier, vol. 192(1), pages 152-167.
    21. Huggett, Mark, 1997. "The one-sector growth model with idiosyncratic shocks: Steady states and dynamics," Journal of Monetary Economics, Elsevier, vol. 39(3), pages 385-403, August.
    22. Yongsung Chang & Sun-Bin Kim & Kyooho Kwon & Richard Rogerson, 2018. "Individual and Aggregate Labor Supply in Heterogeneous Agent Economies with Intensive and Extensive Margins," NBER Working Papers 24985, National Bureau of Economic Research, Inc.
    23. Eichenbaum, Martin & Parker, Jonathan A. (ed.), 2018. "NBER Macroeconomics Annual 2017," National Bureau of Economic Research Books, University of Chicago Press, number 9780226577661, September.
    24. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil prices uncertainty, endogenous regime switching, and inflation anchoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 820-839, September.
    2. Bilbiie, F. & Primiceri, G. E. & Tambalotti, A., 2022. "Inequality and Business Cycles," Janeway Institute Working Papers 2234, Faculty of Economics, University of Cambridge.
    3. 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.
    4. Hilde C. Bjørnland & Yoosoon Chang & Jamie L. Cross, 2023. "Oil and the Stock Market Revisited: A Mixed Functional VAR Approach," CAMA Working Papers 2023-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Matthew D. Cocci & Mikkel Plagborg-M{o}ller, 2021. "Standard Errors for Calibrated Parameters," Papers 2109.08109, arXiv.org, revised Jun 2024.
    6. 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.
    7. Matthew D. Cocci & Mikkel Plagborg-Møller, 2021. "Standard Errors for Calibrated Parameters," Working Papers 2021-20, Princeton University. Economics Department..
    8. 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.
    9. 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.
    10. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," Working Papers No 01/2024, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    11. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.
    3. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    4. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    5. Felipe Alves & Christian Bustamante & Xing Guo & Katya Kartashova & Soyoung Lee & Thomas Michael Pugh & Kurt See & Yaz Terajima & Alexander Ueberfeldt, 2022. "Heterogeneity and Monetary Policy: A Thematic Review," Discussion Papers 2022-2, Bank of Canada.
    6. Broer, Tobias, 2020. "Consumption insurance over the business cycle," CEPR Discussion Papers 14579, C.E.P.R. Discussion Papers.
    7. Kase, Hanno & Melosi, Leonardo & Rottner, Matthias, 2024. "Estimating Nonlinear Heterogeneous Agent Models with Neural Networks," The Warwick Economics Research Paper Series (TWERPS) 1499, University of Warwick, Department of Economics.
    8. Ruediger Bachmann & Jinhui Bai & Minjoon Lee & Fudong Zhang, 2020. "The Welfare and Distributional Effects of Fiscal Volatility: a Quantitative Evaluation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 127-153, October.
    9. Ruediger Bachmann & Jinhui Bai & Minjoon Lee & Fudong Zhang, 2020. "The Welfare and Distributional Effects of Fiscal Volatility: a Quantitative Evaluation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 127-153, October.
    10. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    11. Emoto, Masakazu & Sunakawa, Takeki, 2021. "Applying the explicit aggregation algorithm to heterogeneous agent models in continuous time," Economics Letters, Elsevier, vol. 206(C).
    12. Grimaud, Alex, 2021. "Precautionary saving and un-anchored expectations," ECON WPS - Working Papers in Economic Theory and Policy 08/2021, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    13. Pierre Mabille, 2019. "Aggregate Precautionary Savings Motives," 2019 Meeting Papers 344, Society for Economic Dynamics.
    14. Adrien Auclert & Ludwig Straub & Matthew Rognlie, 2019. "Micro Jumps, Macro Humps: monetary policy and business cycles in an estimated HANK model," 2019 Meeting Papers 1449, Society for Economic Dynamics.
    15. Takeki Sunakawa, 2020. "Applying the Explicit Aggregation Algorithm to Heterogeneous Macro Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 845-874, March.
    16. Hasumi, Ryo & Iiboshi, Hirokuni, 2019. "A Bayesian Estimation of HANK models with Continuous Time Approach:Comparison between US and Japan," MPRA Paper 92292, University Library of Munich, Germany.
    17. Fernández-Villaverde, Jesús & Levintal, Oren, 2024. "The Distributional Effects of Asset Returns," CEPR Discussion Papers 18855, C.E.P.R. Discussion Papers.
    18. Heejeong Kim, 2022. "Inequality, Disaster risk, and the Great Recession," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 187-216, July.
    19. Papp, Tamás K. & Reiter, Michael, 2020. "Estimating linearized heterogeneous agent models using panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    20. Del Negro, Marco & Schorfheide, Frank, 2008. "Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1191-1208, October.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cwl:cwldpp:2289. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Brittany Ladd (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.