IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1907.12880.html
   My bibliography  Save this paper

A Comparison of First-Difference and Forward Orthogonal Deviations GMM

Author

Listed:
  • Robert F. Phillips

Abstract

This paper provides a necessary and sufficient instruments condition assuring two-step generalized method of moments (GMM) based on the forward orthogonal deviations transformation is numerically equivalent to two-step GMM based on the first-difference transformation. The condition also tells us when system GMM, based on differencing, can be computed using forward orthogonal deviations. Additionally, it tells us when forward orthogonal deviations and differencing do not lead to the same GMM estimator. When estimators based on these two transformations differ, Monte Carlo simulations indicate that estimators based on forward orthogonal deviations have better finite sample properties than estimators based on differencing.

Suggested Citation

  • Robert F. Phillips, 2019. "A Comparison of First-Difference and Forward Orthogonal Deviations GMM," Papers 1907.12880, arXiv.org.
    • Handle: RePEc:arx:papers:1907.12880
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1907.12880
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Robert F. Phillips, 2020. "Quantifying the Advantages of Forward Orthogonal Deviations for Long Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 653-672, February.
    3. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    4. Robert F. Phillips, 2018. "Quantifying the Computational Advantage of Forward Orthogonal Deviations," Papers 1808.05995, arXiv.org.
    5. Phillips, Robert F., 2019. "A numerical equivalence result for generalized method of moments," Economics Letters, Elsevier, vol. 179(C), pages 13-15.
    6. Kazuhiko Hayakawa, 2009. "First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models?: A Simulation Study," Economics Bulletin, AccessEcon, vol. 29(3), pages 2008-2017.
    7. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    8. Cheng Hsiao & Qiankun Zhou, 2017. "First difference or forward demeaning: Implications for the method of moments estimators," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 883-897, October.
    9. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    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. Eduardo de Sá Fortes Leitão Rodrigues, 2021. "Citizens' Confidence in Government and Inefficient Public Spending. Is there a Trust Trap?," Working Papers REM 2021/0199, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. António Afonso & Eduardo Sá Fortes Leitão Rodrigues, 2022. "Corruption and economic growth: does the size of the government matter?," Economic Change and Restructuring, Springer, vol. 55(2), pages 543-576, May.
    3. António Afonso & Eduardo Rodrigues, 2024. "Is public investment in construction and in R&D, growth enhancing? A PVAR approach," Applied Economics, Taylor & Francis Journals, vol. 56(24), pages 2875-2899, May.
    4. Badi H. Baltagi & Ying Deng & Jing Li & Zhenlin Yang, 2023. "Cities in a pandemic: Evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 379-408, March.
    5. António Afonso & Eduardo de Sá Fortes Leitao Rodrigues, 2022. "Is Public Investment in Construction and in R&D, Growth Enhancing? A PVAR Approach," CESifo Working Paper Series 10048, CESifo.
    6. Ayoub Zeraibi & Daniel Balsalobre-Lorente & Khurram Shehzad, 2021. "Testing the Environmental Kuznets Curve Hypotheses in Chinese Provinces: A Nexus between Regional Government Expenditures and Environmental Quality," IJERPH, MDPI, vol. 18(18), pages 1-16, September.

    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. Robert F. Phillips, 2022. "Forward Orthogonal Deviations GMM and the Absence of Large Sample Bias," Papers 2212.14075, arXiv.org.
    2. Robert F. Phillips, 2020. "Quantifying the Advantages of Forward Orthogonal Deviations for Long Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 653-672, February.
    3. Daniel Ştefan Armeanu & Georgeta Vintilă & Ştefan Cristian Gherghina, 2017. "Empirical Study towards the Drivers of Sustainable Economic Growth in EU-28 Countries," Sustainability, MDPI, vol. 10(1), pages 1-22, December.
    4. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja & Tristan Zajonc, 2011. "Do Value-Added Estimates Add Value? Accounting for Learning Dynamics," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 29-54, July.
    5. Samargandi, Nahla & Fidrmuc, Jan & Ghosh, Sugata, 2015. "Is the Relationship Between Financial Development and Economic Growth Monotonic? Evidence from a Sample of Middle-Income Countries," World Development, Elsevier, vol. 68(C), pages 66-81.
    6. Lips, Johannes, 2018. "Debt and the Oil Industry - Analysis on the Firm and Production Level," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181504, Verein für Socialpolitik / German Economic Association.
    7. Alvarez, Javier & Arellano, Manuel, 2022. "Robust likelihood estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 21-61.
    8. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    9. Sarma, Sisira & Zaric, Gregory S. & Campbell, M. Karen & Gilliland, Jason, 2014. "The effect of physical activity on adult obesity: Evidence from the Canadian NPHS panel," Economics & Human Biology, Elsevier, vol. 14(C), pages 1-21.
    10. José María ARRANZ & Carlos GARCÍA SERRANO & Virginia HERNANZ, 2013. "Active labour market policies in Spain: A macroeconomic evaluation," International Labour Review, International Labour Organization, vol. 152(2), pages 327-348, June.
    11. Manthos D. Delis & K. Christos Staikouras & Panagiotis T. Varlagas, 2008. "On the Measurement of Market Power in the Banking Industry," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 1023-1047, September.
    12. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    13. Muinelo-Gallo, Leonel, 2022. "Business cycles and redistribution: The role of government quality," Economic Systems, Elsevier, vol. 46(4).
    14. Huang, Bwo-Nung & Hwang, M.J. & Yang, C.W., 2008. "Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach," Ecological Economics, Elsevier, vol. 67(1), pages 41-54, August.
    15. Tomaso Duso & Lars-Hendrik Röller & Jo Seldeslachts, 2014. "Collusion Through Joint R&D: An Empirical Assessment," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 349-370, May.
    16. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    17. Emilia Del Bono & Marco Francesconi & Yvonne Kelly & Amanda Sacker, 2016. "Early Maternal Time Investment and Early Child Outcomes," Economic Journal, Royal Economic Society, vol. 126(596), pages 96-135, October.
    18. Montes, Gabriel Caldas & da Cunha Lima, Luiza Leitão, 2018. "Effects of fiscal transparency on inflation and inflation expectations: Empirical evidence from developed and developing countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 26-37.
    19. Gabriel Caldas Montes & Paulo Henrique Luna, 2021. "Fiscal transparency, legal system and perception of the control on corruption: empirical evidence from panel data," Empirical Economics, Springer, vol. 60(4), pages 2005-2037, April.
    20. Ferdi Celikay, 2020. "Dimensions of tax burden: a review on OECD countries," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, vol. 25(49), pages 27-43, March.

    More about this item

    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:arx:papers:1907.12880. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.