IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v251y2025ics0165176525001399.html
   My bibliography  Save this article

Heterogeneous effects of economic cycles across the income distribution: A common factor model approach

Author

Listed:
  • Valizadeh, Pourya
  • Issar, Akash
  • Bryant, Henry

Abstract

We extend the work of Bitler and Hoynes (2015), which uses state-level panel data and a two-way fixed effects (TWFE) model to examine the heterogeneous effects of economic cycles across the household income distribution. Using a more flexible common factor model that allows common shocks to have differential effects across states, we find statistically and economically significant differences from TWFE estimates, particularly at the lower tail of the income distribution. While TWFE estimates suggest a hump-shaped pattern — where effects are smaller at the lower and upper tails — our estimates indicate that cyclical impacts are largest at the lowest income levels and decline monotonically as income rises. These results suggest that conventional TWFE models may understate the vulnerability of lowest-income households to economic downturns.

Suggested Citation

  • Valizadeh, Pourya & Issar, Akash & Bryant, Henry, 2025. "Heterogeneous effects of economic cycles across the income distribution: A common factor model approach," Economics Letters, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:ecolet:v:251:y:2025:i:c:s0165176525001399
    DOI: 10.1016/j.econlet.2025.112302
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176525001399
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2025.112302?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Marianne Bitler & Hilary Hoynes & Elira Kuka, 2017. "Child Poverty, the Great Recession, and the Social Safety Net in the United States," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 36(2), pages 358-389, March.
    2. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    3. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2016. "Exponent of Cross‐Sectional Dependence: Estimation and Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 929-960, September.
    4. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    5. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    6. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    7. Pourya Valizadeh & Bart L. Fischer & Henry L. Bryant, 2024. "SNAP enrollment cycles: New insights from heterogeneous panel models with cross‐sectional dependence," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 354-381, January.
    8. Karabiyik, Hande & Reese, Simon & Westerlund, Joakim, 2017. "On the role of the rank condition in CCE estimation of factor-augmented panel regressions," Journal of Econometrics, Elsevier, vol. 197(1), pages 60-64.
    9. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    10. Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2024. "Revisiting Event-Study Designs: Robust and Efficient Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3253-3285.
    11. Marianne Bitler & Hilary Hoynes, 2016. "The More Things Change, the More They Stay the Same? The Safety Net and Poverty in the Great Recession," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 403-444.
    12. Alexander Chudik & M. Hashem Pesaran, 2013. "Large Panel Data Models with Cross-Sectional Dependence: A Survey," CESifo Working Paper Series 4371, CESifo.
    13. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    14. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    15. Marianne Bitler & Hilary Hoynes, 2015. "Heterogeneity in the Impact of Economic Cycles and the Great Recession: Effects within and across the Income Distribution," American Economic Review, American Economic Association, vol. 105(5), pages 154-160, May.
    16. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    17. Hilary Hoynes & Douglas L. Miller & Jessamyn Schaller, 2012. "Who Suffers during Recessions?," Journal of Economic Perspectives, American Economic Association, vol. 26(3), pages 27-48, Summer.
    Full references (including those not matched with items on IDEAS)

    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. Stauskas, Ovidijus & De Vos, Ignace, 2024. "Handling Distinct Correlated Effects with CCE," MPRA Paper 120194, University Library of Munich, Germany.
    2. J. B. Qian, 2016. "Estimation of Panel Model with Spatial Autoregressive Error and Common Factors," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 367-399, March.
    3. Markus Eberhardt & Andrea Filippo Presbitero, 2013. "This Time They're Different: Heterogeneity;and Nonlinearity in the Relationship;between Debt and Growth," Mo.Fi.R. Working Papers 92, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    4. Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.
    5. Jan Ditzen, 2021. "Estimating long-run effects and the exponent of cross-sectional dependence: An update to xtdcce2," Stata Journal, StataCorp LLC, vol. 21(3), pages 687-707, September.
    6. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2024. "Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 147-195, Springer.
    7. Daniel Goya, 2014. "The Multiple Impacts of the Exchange Rate on Export Diversification," Cambridge Working Papers in Economics 1436, Faculty of Economics, University of Cambridge.
    8. Markus Eberhardt & Francis Teal, 2020. "The Magnitude of the Task Ahead: Macro Implications of Heterogeneous Technology," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(2), pages 334-360, June.
    9. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    10. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2429, Faculty of Economics, University of Cambridge.
    11. Philip Kerner & Torben Klarl & Tobias Wendler, 2021. "Green Technologies, Environmental Policy and Regional Growth," Bremen Papers on Economics & Innovation 2104, University of Bremen, Faculty of Business Studies and Economics.
    12. Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni, 2020. "Forecasting using heterogeneous panels with cross-sectional dependence," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1211-1227.
    13. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2019. "Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels," SERIES 02-2019, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Jun 2019.
    14. Valizadeh, Pourya & Fischer, Bart L. & Bryant, Henry L., 2022. "Investigating the Differential Effects of the Economy on SNAP Participation: A Factor Model Approach," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322367, Agricultural and Applied Economics Association.
    15. Westerlund, Joakim & Sharma, Susan Sunila, 2019. "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, vol. 77(C), pages 3-12.
    16. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    17. Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2021. "Visualization, Identification, and stimation in the Linear Panel Event-Study Design," Working Papers 21-44, Federal Reserve Bank of Philadelphia.
    18. Lynn Bergeland Morgan & Peter C. B. Phillips & Donggyu Sul, 2023. "Policy Evaluation with Nonlinear Trended Outcomes: COVID-19 Vaccination Rates in the US," Cowles Foundation Discussion Papers 2380, Cowles Foundation for Research in Economics, Yale University.
    19. Markus Eberhardt & Francis Teal, 2013. "No Mangoes in the Tundra: Spatial Heterogeneity in Agricultural Productivity Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 914-939, December.
    20. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:eee:ecolet:v:251:y:2025:i:c:s0165176525001399. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.