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PESCADF: Stata module to perform Pesaran's CADF panel unit root test in presence of cross section dependence

Author

Listed:
  • Piotr Lewandowski

    (Warsaw School of Economics, Institute for Structural Research)

Programming Language

Stata

Abstract

pescadf runs the t-test for unit roots in heterogenous panels with cross-section dependence, proposed by Pesaran (2003). Parallel to Im, Pesaran and Shin (IPS, 2003) test, it is based on the mean of individual DF (or ADF) t-statistics of each unit in the panel. Null hypothesis assumes that all series are non-stationary. To eliminate the cross dependence, the standard DF (or ADF) regressions are augmented with the cross section averages of lagged levels and first-differences of the individual series (CADF statistics). Considered is also a truncated version of the CADF statistics, which has finite first and second order moments. The exact critical values of the t-bar statistic are given by Pesaran (2003). The critical values and summary statistics of the individual t are also given in the paper, so the Z[t-bar] statistic parallel to IPS (2003) Z[t-bar] (4.10) is distributed standard normal under the null hypothesis of nonstationarity.

Suggested Citation

  • Piotr Lewandowski, 2006. "PESCADF: Stata module to perform Pesaran's CADF panel unit root test in presence of cross section dependence," Statistical Software Components S456732, Boston College Department of Economics, revised 08 Oct 2007.
    • Handle: RePEc:boc:bocode:s456732
    Note: This module should be installed from within Stata by typing "ssc install pescadf". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pescadf.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pescadf.hlp
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    Citations

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    Cited by:

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    3. Canarella, Giorgio & Miller, Stephen M. & Nourayi, Mahmoud M., 2013. "Firm profitability: Mean-reverting or random-walk behavior?," Journal of Economics and Business, Elsevier, vol. 66(C), pages 76-97.
    4. Chletsos Michael & Roupakias Stelios, 2020. "The effect of military spending on income inequality: evidence from NATO countries," Empirical Economics, Springer, vol. 58(3), pages 1305-1337, March.
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    8. Silvia CODERONI & Roberto ESPOSTI, 2011. "Is there a Long-Term Relationship between Agricultural GHG Emissions and Productivity Growth? The Case of Italian Agriculture," Working Papers 369, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Silvia Domeneghetti & Andrea Vaona, 2015. "Regional aspects of aggregate profitability dynamics in Italy," Working Papers 04/2015, University of Verona, Department of Economics.
    10. Polemis, Michael & Tselekounis, Markos, 2019. "Does deregulation drive innovation intensity? Lessons learned from the OECD telecommunications sector," MPRA Paper 92770, University Library of Munich, Germany.
    11. Fotis, Panagiotis & Polemis, Michael, 2018. "The impact of market deregulation on milk price: A dynamic panel data approach," MPRA Paper 86542, University Library of Munich, Germany.
    12. Mika, Alina & Zumer, Tina, 2017. "Indebtedness in the EU: a drag or a catalyst for growth?," Working Paper Series 2118, European Central Bank.
    13. Silvia Coderoni & Roberto Esposti, 2014. "Is There a Long-Term Relationship Between Agricultural GHG Emissions and Productivity Growth? A Dynamic Panel Data Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(2), pages 273-302, June.
    14. Erich Gundlach & Martin Paldam, 2016. "Socioeconomic transitions as common dynamic processes," Economics Working Papers 2016-06, Department of Economics and Business Economics, Aarhus University.
    15. Coderoni, Silvia & Esposti, Roberto, 2011. "Long-Term Agricultural GHG Emissions and Economic Growth: The Agricultural Environmental Kuznets Curve across Italian Regions," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114426, European Association of Agricultural Economists.
    16. Kyle McNabb, 2016. "Tax structures and economic growth: New evidence from the Government Revenue Dataset," WIDER Working Paper Series 148, World Institute for Development Economic Research (UNU-WIDER).

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