[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0123.html
   My bibliography  Save this paper

Specification Testing in Panel Data With Instrumental Variables

Author

Listed:
  • Gilbert E. Metcalf
Abstract
This paper shows a convenient way to test whether instrumental variables are correlated with individual effects in a panel data set. It shows that the correlated fixed effects specification tests developed by Hausman and Taylor (1981) extend in an analogous way to panel data sets with endogenous right hand side variables. In the panel data context, different sets of instrumental variables can be used to construct the test. Asymptotically, I show that the test in many cases is more efficient if an incomplete set of instruments is used. However, in small samples one is likely to do better using the complete set of instruments. Monte Carlo results demonstrate the likely gains for different assumptions about the degree of variance in the data across observations relative to variation across time.

Suggested Citation

  • Gilbert E. Metcalf, 1996. "Specification Testing in Panel Data With Instrumental Variables," NBER Technical Working Papers 0123, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0123
    Note: PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0123.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Badi H. Baltagi, 2021. "Simultaneous Equations with Error Components," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 157-186, Springer.
    2. Nelson, Charles R & Startz, Richard, 1990. "The Distribution of the Instrumental Variables Estimator and Its t-Ratio When the Instrument Is a Poor One," The Journal of Business, University of Chicago Press, vol. 63(1), pages 125-140, January.
    3. Holtz-Eakin, Douglas, 1988. "Testing for individual effects in autoregressive models," Journal of Econometrics, Elsevier, vol. 39(3), pages 297-307, November.
    4. Cornwell, Christopher & Schmidt, Peter & Wyhowski, Donald, 1992. "Simultaneous equations and panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 151-181.
    5. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    6. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    7. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    8. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318, Elsevier.
    9. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    10. Holly, Alberto, 1982. "A Remark on Hausman's Specification Test," Econometrica, Econometric Society, vol. 50(3), pages 749-759, May.
    11. K. Newey, Whitney, 1985. "Generalized method of moments specification testing," Journal of Econometrics, Elsevier, vol. 29(3), pages 229-256, September.
    12. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    13. Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989. "Efficient Estimation Using Panel Data," Econometrica, Econometric Society, vol. 57(3), pages 695-700, May.
    14. Amemiya, Takeshi & MaCurdy, Thomas E, 1986. "Instrumental-Variable Estimation of an Error-Components Model," Econometrica, Econometric Society, vol. 54(4), pages 869-880, July.
    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. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    2. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    3. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    4. Edward Barbier, 2007. "Frontiers and sustainable economic development," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(1), pages 271-295, May.
    5. Peter Egger, 2008. "On the role of distance for outward FDI," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 375-389, June.
    6. Beste Hamiye Beyaztas & Soutir Bandyopadhyay & Abhijit Mandal, 2021. "A robust specification test in linear panel data models," Papers 2104.07723, arXiv.org.
    7. Lee, Yoon-Jin, 2014. "Testing a linear dynamic panel data model against nonlinear alternatives," Journal of Econometrics, Elsevier, vol. 178(P1), pages 146-166.
    8. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.

    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. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    2. Donald W.K. Andrews & Biao Lu, 1999. "Consistent Model and Moment Selection Criteria for GMM Estimation with Applications to Dynamic Panel Data Models," Cowles Foundation Discussion Papers 1233, Cowles Foundation for Research in Economics, Yale University.
    3. Andrews, Donald W. K. & Lu, Biao, 2001. "Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models," Journal of Econometrics, Elsevier, vol. 101(1), pages 123-164, March.
    4. Manuel Arellano & Olympia Bover, 1990. "La econometría de datos de panel," Investigaciones Economicas, Fundación SEPI, vol. 14(1), pages 3-45, January.
    5. Mitze, Timo & Alecke, Björn & Untiedt, Gerhard, 2008. "Trade, FDI and Cross-Variable Linkages: A German (Macro-)Regional Perspective," MPRA Paper 12245, University Library of Munich, Germany.
    6. Yves Guillotin & Patrick Sevestre, 1994. "Estimations de fonctions de gains sur données de panel : endogéneité du capital humain et effets de la sélection," Économie et Prévision, Programme National Persée, vol. 116(5), pages 119-135.
    7. Juan González-Alegre, 2015. "Does fiscal decentralization affect the effectiveness of intergovernmental grants? European regional policy and Spanish autonomous regions," Papers in Regional Science, Wiley Blackwell, vol. 94(4), pages 817-847, November.
    8. repec:eco:journ1:2014-03-22 is not listed on IDEAS
    9. William Boulding & Markus Christen, 2003. "Sustainable Pioneering Advantage? Profit Implications of Market Entry Order," Marketing Science, INFORMS, vol. 22(3), pages 371-392.
    10. O'Brien, Raymond & Patacchini, Eleonora, 2003. "Testing the exogeneity assumption in panel data models with "non classical" disturbances," Discussion Paper Series In Economics And Econometrics 0302, Economics Division, School of Social Sciences, University of Southampton.
    11. Garcia, Serge & Reynaud, Arnaud, 2004. "Estimating the benefits of efficient water pricing in France," Resource and Energy Economics, Elsevier, vol. 26(1), pages 1-25, March.
    12. Baltagi, Badi H., 2023. "The two-way Hausman and Taylor estimator," Economics Letters, Elsevier, vol. 228(C).
    13. Peter Egger, 2008. "On the role of distance for outward FDI," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 375-389, June.
    14. Kraft Kornelius & Ugarkovič Marija, 2006. "Gesetzliche Mitbestimmung und Kapitalrendite Co-Determination and Return on Equity / Co-Determination and Return on Equity," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(5), pages 588-604, October.
    15. 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.
    16. Ahn, Seung C. & Low, Stuart, 1996. "A reformulation of the Hausman test for regression models with pooled cross-section-time-series data," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 309-319.
    17. Daniel Klepinger & Shelly Lundberg & Robert Plotnick, 1999. "How Does Adolescent Fertility Affect the Human Capital and Wages of Young Women?," Journal of Human Resources, University of Wisconsin Press, vol. 34(3), pages 421-448.
    18. Jalal El Ouardighi, 2005. "La spécialisation des activités technologiques des régions européennes : une approche empirique de la convergence," Discussion Papers (REL - Recherches Economiques de Louvain) 2005033, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    19. Derek Hum & Wayne Simpson, 2002. "Analysis of the Performance of Immigrant Wages Using Panel Data," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C2-1, International Conferences on Panel Data.
    20. Sakari Lähdemäki & Eero Lehto & Eero Mäkynen, 2018. "The Role of Natural Resources and Geography for Productivity in Developed Countries," Working Papers 320, Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE.
    21. Jean-Louis ARCAND & Béatrice D'HOMBRES & Paul GYSELINCK, 2004. "Instrument Choice and the Returns to Education: New Evidence from Vietnam," Working Papers 200422, CERDI.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:nbr:nberte:0123. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.