IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/31604.html
   My bibliography  Save this paper

Hidden panel cointegration

Author

Listed:
  • Abdulnasser, Hatemi-J

Abstract

This article extends the seminal work of Granger and Yoo (2002) on hidden cointegration to panel data analysis. It shows how cumulative negative and positive changes can be constructed for each panel variable. It also shows how tests similar to the augmented Dickey-Fuller tests can be implemented to find out whether the cointegration is hidden in the panel or not. An application is provided to investigate the impact of permanent positive and negative shocks in the government expenditure on the national output in a panel of three countries.

Suggested Citation

  • Abdulnasser, Hatemi-J, 2011. "Hidden panel cointegration," MPRA Paper 31604, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:31604
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/31604/1/MPRA_paper_31604.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    2. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    3. Granger, Clive W.J. & YOON, GAWON, 2002. "Hidden Cointegration," University of California at San Diego, Economics Working Paper Series qt9qn5f61j, Department of Economics, UC San Diego.
    4. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    5. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    6. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    7. Abdulnasser Hatemi-J, 2012. "Asymmetric causality tests with an application," Empirical Economics, Springer, vol. 43(1), pages 447-456, August.
    8. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Department of Economics Working Papers 2000-02, Department of Economics, Williams College.
    9. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    10. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    11. Quah, Danny, 1994. "Exploiting cross-section variation for unit root inference in dynamic data," Economics Letters, Elsevier, vol. 44(1-2), pages 9-19.
    12. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    14. repec:bla:obuest:v:61:y:1999:i:0:p:653-70 is not listed on IDEAS
    15. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    16. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    17. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    18. Hatemi-J, Abdulnasser, 2011. "Asymmetric generalized impulse responses and variance decompositions with an application," MPRA Paper 31700, University Library of Munich, Germany.
    19. Peter Pedroni, 2004. "Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis," Department of Economics Working Papers 2004-15, Department of Economics, Williams College.
    20. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    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. Fatma Zeren & Burcu Kilinc Savrul, 2013. "Revisited Export-Led Growth Hypothesis For Selected European Countries: A Panel Hidden Cointegration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 18(1), pages 134-151, May.
    2. Hatemi-J, Abdulnasser, 2011. "Asymmetric generalized impulse responses and variance decompositions with an application," MPRA Paper 31700, University Library of Munich, Germany.
    3. Hatemi-J, Abdulnasser & Mustafa, Alan, 2016. "A MS-Excel Module to Transform an Integrated Variable into Cumulative Partial Sums for Negative and Positive Components with and without Deterministic Trend Parts," MPRA Paper 73813, University Library of Munich, Germany.

    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. Karikallio, Hanna, 2015. "Cross-commodity Price Transmission and Integration of the EU Livestock Market of Pork and Beef: Panel Time-series Approach," 2015 Conference, August 9-14, 2015, Milan, Italy 211832, International Association of Agricultural Economists.
    2. Andries, Natalia & Billon, Steve, 2016. "Retail bank interest rate pass-through in the euro area: An empirical survey," Economic Systems, Elsevier, vol. 40(1), pages 170-194.
    3. Helmut Herwartz & Jordi Sardà & Bernd Theilen, 2016. "Money demand and the shadow economy: empirical evidence from OECD countries," Empirical Economics, Springer, vol. 50(4), pages 1627-1645, June.
    4. Md Shahiduzzaman & Allan Layton & Khorshed Alam, 2015. "On the contribution of information and communication technology to productivity growth in Australia," Economic Change and Restructuring, Springer, vol. 48(3), pages 281-304, November.
    5. Sangjoon Jun, 2006. "The Nexus between IT Investment and Banking Performance in Korea," Global Economic Review, Taylor & Francis Journals, vol. 35(1), pages 67-96.
    6. In Choi, 2012. "Panel Cointegration," Working Papers 1208, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    7. Skare, Marinko & Ozturk, Ilhan & Porada-Rochoń, Małgorzata & Stjepanovic, Sasa, 2024. "Energy as the new frontier: Dynamic panel data analysis revealing energy's transformative role in economic growth and technological progress," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    8. Costantini, Valeria & Martini, Chiara, 2010. "The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data," Energy Economics, Elsevier, vol. 32(3), pages 591-603, May.
    9. Chaido Dritsaki & Melina Dritsaki, 2014. "Causal Relationship between Energy Consumption, Economic Growth and CO2 Emissions: A Dynamic Panel Data Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 125-136.
    10. Vassilis Monastiriotis & Cigdem Borke Tunali, 2020. "The Sustainability of External Imbalances in the European Periphery," Open Economies Review, Springer, vol. 31(2), pages 273-294, April.
    11. Pourazarm, Elham & Cooray, Arusha, 2013. "Estimating and forecasting residential electricity demand in Iran," Economic Modelling, Elsevier, vol. 35(C), pages 546-558.
    12. Ewing, Bradley T. & Payne, James E. & Caporin, Massimilano, 2022. "The Asymmetric Impact of Oil Prices and Production on Drilling Rig Trajectory: A correction," Resources Policy, Elsevier, vol. 79(C).
    13. Ogali, Oscar I.O. & Okoro, Emeka E. & Olafuyi, Saburi G., 2023. "Assessing consensus on nexus between natural gas consumption and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    14. Lee Chien-Chiang, 2011. "Does Insurance Matter for Growth: Empirical Evidence from OECD Countries," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-28, June.
    15. Mouawiya Al-Awad & Nasri Harb, 2005. "Financial development and economic growth in the Middle East," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1041-1051.
    16. Liddle, Brantley, 2012. "The importance of energy quality in energy intensive manufacturing: Evidence from panel cointegration and panel FMOLS," Energy Economics, Elsevier, vol. 34(6), pages 1819-1825.
    17. Anita CEH CASNI & Maruska VIZEK, 2014. "Interactions between Real Estate and Equity Markets: an Investigation of Linkages in Developed and Emerging Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 100-119, March.
    18. Narayan, Seema & Rehman, Mobeen Ur, 2021. "Can home-biased investors diversify interregionally in the long run?," Economic Modelling, Elsevier, vol. 97(C), pages 167-181.
    19. Liu, Xuyi & Zhang, Shun & Bae, Junghan, 2017. "The nexus of renewable energy-agriculture-environment in BRICS," Applied Energy, Elsevier, vol. 204(C), pages 489-496.
    20. Chou, Win Lin, 2007. "Explaining China's regional health expenditures using LM-type unit root tests," Journal of Health Economics, Elsevier, vol. 26(4), pages 682-698, July.

    More about this item

    Keywords

    Asymmetry; Panel Data; Cointegration; Testing; Government Spending; Output;
    All these keywords.

    JEL classification:

    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:31604. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.