IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v94y2012i4p935-947.html
   My bibliography  Save this article

The Propagation of Regional Recessions

Author

Listed:
  • James D. Hamilton

    (University of California, San Diego)

  • Michael T. Owyang

    (Federal Reserve Bank of St. Louis)

Abstract

This paper develops a framework for inferring common Markov-switching components in panel data sets with large cross-section and time series dimensions. We study similarities and differences across U.S. states in the timing of business cycles. We hypothesize that there exists a small number of cluster designations, with individual states in a given cluster sharing certain business cycle characteristics. We find that although oil-producing and agricultural states can sometimes experience a separate recession from the rest of the United States, for the most part, differences across states appear to be a matter of timing, with some states entering recession or recovering before others. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
  • Handle: RePEc:tpr:restat:v:94:y:2012:i:4:p:935-947
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00197
    File Function: link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Michael A. Kouparitsas, 1999. "Is the United States an optimal currency area?," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Oct.
    2. Del Negro, Marco, 2002. "Asymmetric shocks among U.S. states," Journal of International Economics, Elsevier, vol. 56(2), pages 273-297, March.
    3. Gerald Carlino & Keith Sill, 2001. "Regional Income Fluctuations: Common Trends And Common Cycles," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 446-456, August.
    4. Mark D. Partridge & Dan S. Rickman, 2005. "Regional cyclical asymmetries in an optimal currency area: an analysis using US state data," Oxford Economic Papers, Oxford University Press, vol. 57(3), pages 373-397, July.
    5. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    6. James D. Hamilton, 2005. "What's real about the business cycle?," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 435-452.
    7. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
    8. Bram van Dijk & Philip Hans Franses & Richard Paap & Dick van Dijk, 2011. "Modelling regional house prices," Applied Economics, Taylor & Francis Journals, vol. 43(17), pages 2097-2110.
    9. Owyang, Michael T. & Piger, Jeremy M. & Wall, Howard J. & Wheeler, Christopher H., 2008. "The economic performance of cities: A Markov-switching approach," Journal of Urban Economics, Elsevier, vol. 64(3), pages 538-550, November.
    10. Carlino, Gerald A. & DeFina, Robert H., 2004. "How strong is co-movement in employment over the business cycle? Evidence from state/sector data," Journal of Urban Economics, Elsevier, vol. 55(2), pages 298-315, March.
    11. Forni, Mario & Reichlin, Lucrezia, 2001. "Federal policies and local economies: Europe and the US," European Economic Review, Elsevier, vol. 45(1), pages 109-134, January.
    12. Fruhwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2008. "Model-Based Clustering of Multiple Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 78-89, January.
    13. Andrew Harvey (ed.), 1994. "Time Series," Books, Edward Elgar Publishing, volume 0, number 599.
    14. Geweke, John & Keane, Michael, 2007. "Smoothly mixing regressions," Journal of Econometrics, Elsevier, vol. 138(1), pages 252-290, May.
    15. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    16. Gerald Carlino & Robert Defina, 1998. "The Differential Regional Effects Of Monetary Policy," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 572-587, November.
    17. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
    18. Krueger, Alan B & Burton, John F, Jr, 1990. "The Employers' Costs of Workers' Compensation Insurance: Magnitudes, Determinants, and Public Policy," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 228-240, May.
    19. Theodore M. Crone, 2005. "An Alternative Definition of Economic Regions in the United States Based on Similarities in State Business Cycles," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 617-626, November.
    20. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    21. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    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. Owyang, Michael T. & Rapach, David E. & Wall, Howard J., 2009. "States and the business cycle," Journal of Urban Economics, Elsevier, vol. 65(2), pages 181-194, March.
    2. Sergei S. Shibaev, 2016. "Recession Propagation In Small Regional Economies: Spatial Spillovers And Endogenous Clustering," Working Paper 1369, Economics Department, Queen's University.
    3. Wall, Howard J., 2013. "The employment cycles of neighboring cities," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 177-185.
    4. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2013. "Discordant city employment cycles," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 367-384.
    5. Wall, Howard, 2023. "The Great, Greater, and Greatest Recessions of US States," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 53(1), January.
    6. Ghent, Andra C. & Owyang, Michael T., 2010. "Is housing the business cycle? Evidence from US cities," Journal of Urban Economics, Elsevier, vol. 67(3), pages 336-351, May.
    7. Hernández-Murillo, Rubén & Owyang, Michael T. & Rubio, Margarita, 2017. "Clustered housing cycles," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 185-197.
    8. Guisinger, Amy Y. & Owyang, Michael T. & Soques, Daniel, 2024. "Industrial Connectedness and Business Cycle Comovements," Econometrics and Statistics, Elsevier, vol. 29(C), pages 132-149.
    9. Sungyup Chung, 2016. "Assessing the regional business cycle asymmetry in a multi-level structure framework: a study of the top 20 US MSAs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 229-252, January.
    10. Roberto Casarin & Komla Mawulom Agudze & Monica Billio & Eric Girardin, 2014. "Growth-cycle phases in China�s provinces: A panel Markov-switching approach," Working Papers 2014:19, Department of Economics, University of Venice "Ca' Foscari".
    11. Sungyup Chung, 2016. "Assessing the regional business cycle asymmetry in a multi-level structure framework: a study of the top 20 US MSAs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 229-252, January.
    12. Maria Gadea & Ana Gómez-Loscos & Antonio Montañés, 2012. "Cycles inside cycles: Spanish regional aggregation," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(4), pages 423-456, December.
    13. Ana Gómez-Loscos & M. Dolores Gadea & Eduardo Bandres, 2020. "Business cycle patterns in European regions," Empirical Economics, Springer, vol. 59(6), pages 2639-2661, December.
    14. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2018. "Countercyclical Policy and the Speed of Recovery after Recessions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(4), pages 675-704, June.
    15. Dalibor Stevanovic & Stéphane Surprenant & Rachidi Kotchoni, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.
    16. Stefano Magrini & Margherita Gerolimetto & Hasan Engin Duran, 2011. "Understanding the lead/lag structure among regional business cycles," Working Papers 2011_06, Department of Economics, University of Venice "Ca' Foscari".
    17. Keisuke Kondo, 2022. "Spatial dependence in regional business cycles: evidence from Mexican states," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    18. Magrini Stefano & Gerolimetto Margherita & Duran Hasan Engin, 2013. "Business cycle dynamics across the US states," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 795-822, April.
    19. Beckworth, David, 2010. "One nation under the fed? The asymmetric effects of US monetary policy and its implications for the United States as an optimal currency area," Journal of Macroeconomics, Elsevier, vol. 32(3), pages 732-746, September.
    20. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.

    More about this item

    Keywords

    university tuition; graduation rates;

    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

    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:tpr:restat:v:94:y:2012:i:4:p:935-947. 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: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    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.