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Stationarity of time series and the problem of spurious regression

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  • Baumöhl, Eduard
  • Lyócsa, Štefan

Abstract

The goal of this paper was to introduce some general issues of non-stationarity for practitioners, students and beginning researchers. Using elementary techniques we examined the effect of non-stationary data on the results of regression analysis. We further shoved the effect of larger sample sizes on the spuriousness of regressions and we also examined the well known “rule of thumb” of how to identify spurious regressions. We also demonstrated the problem of spurious regression on a practical example, using closing prices of stock market indices from CEE markets.

Suggested Citation

  • Baumöhl, Eduard & Lyócsa, Štefan, 2009. "Stationarity of time series and the problem of spurious regression," MPRA Paper 27926, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:27926
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    File URL: https://mpra.ub.uni-muenchen.de/27926/1/MPRA_paper_27926.pdf
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    References listed on IDEAS

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    6. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    7. 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.
    8. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
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    Citations

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    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    2. Collin Chikwira, 2023. "The Foreign Exchange Auction System’s Effect on SME Stability and Performance," International Journal of Economics and Financial Issues, Econjournals, vol. 13(5), pages 96-108, September.
    3. Jammazi, Rania & Aloui, Chaker, 2012. "Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling," Energy Economics, Elsevier, vol. 34(3), pages 828-841.
    4. Madanlo, Lalaine & Murcia, John Vianne & Tamayo, Adrian, 2016. "Simultaneity of Crime Incidence in Mindanao," MPRA Paper 72648, University Library of Munich, Germany, revised 20 Jul 2016.
    5. Elena Cigu & Daniela Tatiana Agheorghiesei & Anca Florentina Gavriluță (Vatamanu) & Elena Toader, 2018. "Transport Infrastructure Development, Public Performance and Long-Run Economic Growth: A Case Study for the Eu-28 Countries," Sustainability, MDPI, vol. 11(1), pages 1-22, December.
    6. Noveski Martin, 2018. "Macroeconomic effects of the budget deficit in the Republic of Macedonia," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 4(2), pages 5-14, November.
    7. Oliver Ike Inyiama & Caroline N. Ozouli, 2014. "Interactions between Exchange Rate and Financial Performance Indicators in Nigeria Beer Industry: Evidence from Nigeria Breweries Plc," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 3, November.

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    More about this item

    Keywords

    stationarity; time series data; various unit root tests; spurious regression; the R-squared and the Durbin – Watson statistics “rule of thumb”; CEE stock markets;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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