IDEAS home Printed from https://ideas.repec.org/p/ran/wpaper/wr-941.html
   My bibliography  Save this paper

Point and Set Identification in Linear Panel Data Models with Measurement Error

Author

Listed:
  • Erik Meijer
  • Laura Spierdijk
  • Tom Wansbeek

Abstract

The rich dependency structure of panel data can be exploited to generate moment conditions that can be used to identify linear regression models in the presence of measurement error. This paper adds to a small body of literature on this topic by showing how heteroskedasticity and nonlinear relationships between the error-ridden regressors and error-free regressors lead to identifying moment conditions in a static panel data setting, how suitably chosen linear combinations of lagged and lead values of the dependent variable can be used as instrumental variables in a dynamic panel data with measurement errors, and how reverse regression can be generalized to the panel data setting, thereby giving bounds on regression coefficients in the absence of point identification.

Suggested Citation

  • Erik Meijer & Laura Spierdijk & Tom Wansbeek, 2012. "Point and Set Identification in Linear Panel Data Models with Measurement Error," Working Papers WR-941, RAND Corporation.
    • Handle: RePEc:ran:wpaper:wr-941
    as

    Download full text from publisher

    File URL: https://www.rand.org/content/dam/rand/pubs/working_papers/2012/RAND_WR941.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francisca Antman & David McKenzie, 2007. "Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity," Journal of Development Studies, Taylor & Francis Journals, vol. 43(6), pages 1057-1083.
    2. Joseph G. Altonji & Aloysius Siow, 1987. "Testing the Response of Consumption to Income Changes with (Noisy) Panel Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 293-328.
    3. Tom Wansbeek & Arie Kapteyn, 1992. "Simple Estimators for Dynamic Panel Data Models with Errors in Variables," Palgrave Macmillan Books, in: Ronald Bewley & Tran Hoa (ed.), Contributions to Consumer Demand and Econometrics, chapter 13, pages 238-251, Palgrave Macmillan.
    4. Wansbeek, Tom & Bekker, Paul, 1996. "On IV, GMM and ML in a dynamic panel data model," Economics Letters, Elsevier, vol. 51(2), pages 145-152, May.
    5. 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.
    6. Mark Harris & Laszlo Matyas, 2000. "Performance of the operational Wansbeek-Bekker estimator for dynamic panel data models," Applied Economics Letters, Taylor & Francis Journals, vol. 7(3), pages 149-153.
    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.
    Full references (including those not matched with items on IDEAS)

    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. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    2. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.
    3. Martin A. Carree, 2002. "Nearly Unbiased Estimation in Dynamic Panel Data Models with Exogenous Variables," Tinbergen Institute Discussion Papers 02-007/2, Tinbergen Institute.
    4. Humberto López & Luis Servén, 2015. "Too Poor to Grow," Central Banking, Analysis, and Economic Policies Book Series, in: Ricardo J. Caballero & Klaus Schmidt-Hebbel (ed.),Economic Policies in Emerging-Market Economies Festschrift in Honor of Vittorio Corbo, edition 1, volume 21, chapter 13, pages 309-350, Central Bank of Chile.
    5. Dercon, Stefan & Van Campenhout, Bjorn, 2012. "Nonlinear dynamics of livestock assets: Evidence from Ethiopia," IFPRI discussion papers 1215, International Food Policy Research Institute (IFPRI).
    6. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
    7. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    8. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    9. Badri Narayanan G., 2005. "Effects of Trade liberalisation, Environmental and Labour Regulations on Employment in India's Organised Textile Sector," Labor Economics Working Papers 22363, East Asian Bureau of Economic Research.
    10. 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.
    11. 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.
    12. Youngho Kang & Byung-Yeon Kim, 2018. "Immigration and economic growth: do origin and destination matter?," Applied Economics, Taylor & Francis Journals, vol. 50(46), pages 4968-4984, October.
    13. Alcaraz, Carlo & Villalvazo, Sergio, 2017. "The effect of natural gas shortages on the Mexican economy," Energy Economics, Elsevier, vol. 66(C), pages 147-153.
    14. Thorsten Lehnert, 2019. "Asset pricing implications of good governance," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-14, April.
    15. Cho, Seo-young & Vadlamannati, Krishna Chaitanya, 2010. "Compliance for big brothers: An empirical analysis on the impact of the anti-trafficking protocol," University of Göttingen Working Papers in Economics 118, University of Goettingen, Department of Economics.
    16. Katsushi S. Imai & Raghav Gaiha & Ganesh Thapa & Samuel Kobina Annim, 2013. "Financial Crisis In Asia: Its Genesis, Severity And Impact On Poverty And Hunger," Journal of International Development, John Wiley & Sons, Ltd., vol. 25(8), pages 1105-1116, November.
    17. Marco Botta & Luca Colombo, 2016. "Macroeconomic and Institutional Determinants of Capital Structure Decisions," DISCE - Working Papers del Dipartimento di Economia e Finanza def038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    18. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    19. Vieira, Flávio & MacDonald, Ronald & Damasceno, Aderbal, 2012. "The role of institutions in cross-section income and panel data growth models: A deeper investigation on the weakness and proliferation of instruments," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 127-140.
    20. Hakkala, Katariina & Heyman, Fredrik & Sjöholm, Fredrik, 2007. "Cross-Border Acquisitions, Multinationals and Wage Elasticities," Working Paper Series 709, Research Institute of Industrial Economics.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

    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:ran:wpaper:wr-941. 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: Benson Wong (email available below). General contact details of provider: https://edirc.repec.org/data/lpranus.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.