IDEAS home Printed from https://ideas.repec.org/a/spr/anresc/v56y2016i1d10.1007_s00168-015-0732-7.html
   My bibliography  Save this article

Assessing the regional business cycle asymmetry in a multi-level structure framework: a study of the top 20 US MSAs

Author

Listed:
  • Sungyup Chung

    () (Bank of Korea
    University of Illinois)

Abstract

Abstract Dating the regional business cycle phases using a multi-level Markov-switching model revealed that the regional cycle phase transition probability depends on the national cycle phase, although the propagation speed of the national phase into a regional cycle varies across the regions. The estimation of the national factor loadings on regional economies showed that the response of a regional economy to a national impact is mostly greater during a national contraction phase.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:anresc:v:56:y:2016:i:1:d:10.1007_s00168-015-0732-7
    DOI: 10.1007/s00168-015-0732-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00168-015-0732-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

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

    References listed on IDEAS

    as
    1. RenÈ Garcia, 2002. "Are the Effects of Monetary Policy Asymmetric?," Economic Inquiry, Western Economic Association International, vol. 40(1), pages 102-119, January.
    2. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
    3. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
    4. Uribe, Martin & Yue, Vivian Z., 2006. "Country spreads and emerging countries: Who drives whom?," Journal of International Economics, Elsevier, vol. 69(1), pages 6-36, June.
    5. Sylvia Kaufmann, 2000. "Measuring business cycles with a dynamic Markov switching factor model: an assessment using Bayesian simulation methods," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 39-65.
    6. Mark D. Partridge & Dan S. Rickman, 2005. "High-Poverty Nonmetropolitan Counties in America: Can Economic Development Help?," International Regional Science Review, , vol. 28(4), pages 415-440, October.
    7. 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.
    8. 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.
    9. 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.
    10. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    11. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    12. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, December.
    13. Gjerde, Oystein & Saettem, Frode, 1999. "Causal relations among stock returns and macroeconomic variables in a small, open economy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(1), pages 61-74, January.
    14. 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.
    15. 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.
    16. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, Oxford University Press, vol. 120(1), pages 387-422.
    17. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    18. 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.
    19. Karras, Georgios, 1996. "Are the Output Effects of Monetary Policy Asymmetric? Evidence from a Sample of European Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(2), pages 267-278, May.
    20. Ira. O. Scott, 1955. "The Regional Impact of Monetary Policy," The Quarterly Journal of Economics, Oxford University Press, vol. 69(2), pages 269-284.
    21. Tor Jacobson & Per Jansson & Anders Vredin & Anders Warne, 2001. "Monetary policy analysis and inflation targeting in a small open economy: a VAR approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 487-520.
    22. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    23. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    24. 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.
    25. Buckle, Robert A. & Kim, Kunhong & Kirkham, Heather & McLellan, Nathan & Sharma, Jarad, 2007. "A structural VAR business cycle model for a volatile small open economy," Economic Modelling, Elsevier, vol. 24(6), pages 990-1017, November.
    26. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    27. Motonari Hayashida & Geoffrey J. D. Hewings, 2009. "Regional Business Cycles in Japan," International Regional Science Review, , vol. 32(2), pages 119-147, April.
    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. Gomez-Loscos, Ana & Gadea, M. Dolores & Bandres, Eduardo, 2018. "Business cycle patterns in European regions," MPRA Paper 83964, University Library of Munich, Germany.

    More about this item

    Keywords

    C11; C13; O18; R11;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    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:spr:anresc:v:56:y:2016:i:1:d:10.1007_s00168-015-0732-7. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.