IDEAS home Printed from https://ideas.repec.org/a/mup/actaun/actaun_2018066061383.html
   My bibliography  Save this article

Disparity in Performance of the Czech Construction Sector: Evidence from the Markov-Switching Model

Author

Listed:
  • Václav Adamec

    (Department of Statistics and Operations Research, School of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

Abstract

Activities in the construction sector are assumed to be influenced by inflow of mortgage funding in the private housing sector and public finances targeted at large infrastructure projects, apart from climate variables. In this study, we modeled seasonal time series representing monthly output in the Czech construction sector in CZK mil. during 2000:1 through 2016:12 (T = 204) adjusted for calendar variations and seasonal movements via TRAMO-SEATS and then transformed to natural logarithms of gross returns. A Markov-Switching model with two states, no intercept, average monthly temperature, average monthly precipitation and parameters of first-order autoregression process was specified and estimated by the Expectation-Maximization. In State 1 of regular performance, the log-differenced returns were significantly and positively influenced by precipitation levels, but not by ambient outdoor temperature. In State 2 of non-standard operation of the construction sector, the transformed series was unaffected by precipitation levels, but instead by ambient outdoor temperatures. First-order autocorrelation dependency in both regimes was established. Changes in legal and macroeconomic environment pertinent to tax law amendments affecting VAT or corporate tax, country's accession to EU or large construction project deadlines were shown to induce nonstandard regime in the construction sector (State 2). The model classified 91 % observations in the first state, while only 9 % data belonged to the State 2. Transition probability matrix indicates that change from model State 1 to State 2 is difficult to attain. At the same time, once State 2 was established, it tends to persist or change to State 1 with near equal probability. Ability of the Markov-Switching model to identify both states is reasonably good.

Suggested Citation

  • Václav Adamec, 2018. "Disparity in Performance of the Czech Construction Sector: Evidence from the Markov-Switching Model," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 66(6), pages 1383-1391.
    • Handle: RePEc:mup:actaun:actaun_2018066061383
    DOI: 10.11118/actaun201866061383
    as

    Download full text from publisher

    File URL: http://acta.mendelu.cz/doi/10.11118/actaun201866061383.html
    Download Restriction: free of charge
    File URL: http://acta.mendelu.cz/doi/10.11118/actaun201866061383.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.11118/actaun201866061383?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    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. Christopher K. Allsup & Irene S. Gabashvili, 2024. "Modeling the Dynamics of Growth in Master-Planned Communities," Papers 2408.14214, arXiv.org, revised Aug 2024.

    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. Gaia Garino & Lucio Sarno, 2004. "Speculative Bubbles in U.K. House Prices: Some New Evidence," Southern Economic Journal, John Wiley & Sons, vol. 70(4), pages 777-795, April.
    2. Dmitry Kulikov, 2012. "Testing for Rational Speculative Bubbles on the Estonian Stock Market," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 4(1).
    3. Dimitrios Koutmos, 2020. "Market risk and Bitcoin returns," Annals of Operations Research, Springer, vol. 294(1), pages 453-477, November.
    4. Muhsin Kar & Tayfur Bayat & Selim Kayhan, 2016. "Impacts of Credit Default Swaps on Volatility of the Exchange Rate in Turkey: The Case of Euro," IJFS, MDPI, vol. 4(3), pages 1-18, July.
    5. Alison Tarditi, 1996. "Modelling the Australian Exchange Rate, Long Bond Yield and Inflationary Expectations," RBA Research Discussion Papers rdp9608, Reserve Bank of Australia.
    6. Pat Wilson & John Okunev & Tiffany Hutcheson, 1998. "Regime Switches in Property Market Risk Premiums: Some International Comparisons," Working Paper Series 80, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    7. Andrew Davies, 2006. "Testing for international equity market integration using regime switching cointegration techniques," Review of Financial Economics, John Wiley & Sons, vol. 15(4), pages 305-321.
    8. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    9. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    10. Su, EnDer, 2017. "Stock index hedging using a trend and volatility regime-switching model involving hedging cost," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 233-254.
    11. Scott C. Linn & Zhen Zhu, 1997. "Aggregate Merger Activity: New Evidence on the Wave Hypothesis," Southern Economic Journal, John Wiley & Sons, vol. 64(1), pages 130-146, July.
    12. Arielle Beyaert & Juan rez-Castej, 2000. "Switching regime models in the Spanish inter-bank market," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 93-112.
    13. Cruz-Rodríguez, Alexis, 2004. "Un análisis del ciclo económico de la República Dominicana bajo cambios de régimen [Analysis of business cycle of the Dominican Republic using Markov Switching model]," MPRA Paper 54352, University Library of Munich, Germany.
    14. Iuga, Iulia Cristina & Mudakkar, Syeda Rabab & Dragolea, Larisa Loredana, 2024. "Agricultural commodities market reaction to COVID-19," Research in International Business and Finance, Elsevier, vol. 69(C).
    15. 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.
    16. Hematizadeh, Roksana & Tajaddini, Reza & Hallahan, Terrence, 2022. "Dynamic asset allocation strategy using a state-dependent Markov model: Applications to international equity markets," Journal of International Money and Finance, Elsevier, vol. 128(C).
    17. Just, Małgorzata & Echaust, Krzysztof, 2020. "Stock market returns, volatility, correlation and liquidity during the COVID-19 crisis: Evidence from the Markov switching approach," Finance Research Letters, Elsevier, vol. 37(C).
    18. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, October.
    19. Utku Akseki & Abdurrahman Nazif Çatık & Barış Gök, 2014. "A regime-dependent investigation of the impact of macroeconomic variables on the housing market activity in Turkey," Economics Bulletin, AccessEcon, vol. 34(2), pages 1081-1090.
    20. Tsung-wu Ho, 2001. "Analyzing the Crowding-out Problems of Taiwan," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 26(1), pages 115-131, June.

    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:mup:actaun:actaun_2018066061383. 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: Ivo Andrle (email available below). General contact details of provider: https://mendelu.cz/en/ .

    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.