IDEAS home Printed from https://ideas.repec.org/p/usi/wpaper/774.html
   My bibliography  Save this paper

Errors-in-Variables Models with Many Proxies

Author

Listed:
  • Federico Crudu

Abstract

This paper introduces a novel method to estimate linear models when explanatory variables are observed with error and many proxies are available. The empirical Euclidean likelihood principle is used to combine the information that comes from the various mismeasured variables. We show that the proposed estimator is consistent and asymptotically normal. In a Monte Carlo study we show that our method is able to efficiently use the information in the available proxies, both in terms of precision of the estimator and in terms of statistical power. An application to the effect of police on crime suggests that measurement errors in the police variable induce substantial attenuation bias. Our approach, on the other hand, yields large estimates in absolute value with high precision, in accordance with the results put forward by the recent literature.

Suggested Citation

  • Federico Crudu, 2017. "Errors-in-Variables Models with Many Proxies," Department of Economics University of Siena 774, Department of Economics, University of Siena.
  • Handle: RePEc:usi:wpaper:774
    as

    Download full text from publisher

    File URL: http://repec.deps.unisi.it/quaderni/774.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2004. "The Role of Social Capital in Financial Development," American Economic Review, American Economic Association, vol. 94(3), pages 526-556, June.
    2. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    3. Mikael Lindahl & Alan B. Krueger, 2001. "Education for Growth: Why and for Whom?," Journal of Economic Literature, American Economic Association, vol. 39(4), pages 1101-1136, December.
    4. Jonas Andersson & Jarle Møen, 2016. "A Simple Improvement of the IV-estimator for the Classical Errors-in-Variables Problem," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 113-125, February.
    5. Darren Lubotsky & Martin Wittenberg, 2001. "Interpretation of Regressions with Multiple Proxies," Working Papers 836, Princeton University, Department of Economics, Industrial Relations Section..
    6. repec:bla:ecinqu:v:51:y:2013:i:3:p:1651-1681 is not listed on IDEAS
    7. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    8. Whitney K. Newey & Frank Windmeijer, 2009. "Generalized Method of Moments With Many Weak Moment Conditions," Econometrica, Econometric Society, vol. 77(3), pages 687-719, May.
    9. George J. Borjas, 2021. "Ethnicity, Neighborhoods, and Human-Capital Externalities," World Scientific Book Chapters, in: Foundational Essays in Immigration Economics, chapter 7, pages 135-160, World Scientific Publishing Co. Pte. Ltd..
    10. Darren Lubotsky & Martin Wittenberg, 2006. "Interpretation of Regressions with Multiple Proxies," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 549-562, August.
    11. Tsao, Min & Wu, Fan, 2015. "Two-sample extended empirical likelihood for estimating equations," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 1-15.
    12. Ashenfelter, Orley & Krueger, Alan B, 1994. "Estimates of the Economic Returns to Schooling from a New Sample of Twins," American Economic Review, American Economic Association, vol. 84(5), pages 1157-1173, December.
    13. Dan A. Black & Jeffrey A. Smith, 2006. "Estimating the Returns to College Quality with Multiple Proxies for Quality," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 701-728, July.
    14. Barron, John M & Berger, Mark C & Black, Dan A, 1997. "How Well Do We Measure Training?," Journal of Labor Economics, University of Chicago Press, vol. 15(3), pages 507-528, July.
    15. Bernal, Pedro & Mittag, Nikolas & Qureshi, Javaeria A., 2016. "Estimating effects of school quality using multiple proxies," Labour Economics, Elsevier, vol. 39(C), pages 1-10.
    16. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.
    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. Jonas Andersson & Jarle Møen, 2016. "A Simple Improvement of the IV-estimator for the Classical Errors-in-Variables Problem," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 113-125, February.
    2. Aaron Chalfin & Justin McCrary, 2013. "The Effect of Police on Crime: New Evidence from U.S. Cities, 1960-2010," NBER Working Papers 18815, National Bureau of Economic Research, Inc.
    3. Barry P. Bosworth & Susan M. Collins, 2003. "The Empirics of Growth: An Update," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(2), pages 113-206.
    4. Angel de la Fuente & Antonio Ciccone, 2003. "Human capital in a global and knowledge-based economy," UFAE and IAE Working Papers 562.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    5. Nybom, Martin & Vosters, Kelly, 2015. "Intergenerational Persistence in Latent Socioeconomic Status: Evidence from Sweden," Working Paper Series 3/2015, Stockholm University, Swedish Institute for Social Research.
    6. Bernal, Pedro & Mittag, Nikolas & Qureshi, Javaeria A., 2016. "Estimating effects of school quality using multiple proxies," Labour Economics, Elsevier, vol. 39(C), pages 1-10.
    7. Colagrossi, Marco & d’Hombres, Béatrice & Schnepf, Sylke V, 2020. "Like (grand)parent, like child? Multigenerational mobility across the EU," European Economic Review, Elsevier, vol. 130(C).
    8. repec:bla:ecorec:v:91:y:2015:i::p:1-24 is not listed on IDEAS
    9. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    10. Doppelhofer, Gernot & Hansen, Ole-Petter Moe & Weeks, Melvyn, 2016. "Determinants of long-term economic Growth redux: A Measurement Error Model Averaging (MEMA) approach," Discussion Paper Series in Economics 19/2016, Norwegian School of Economics, Department of Economics.
    11. Evan Starr, 2019. "Consider This: Training, Wages, and the Enforceability of Covenants Not to Compete," ILR Review, Cornell University, ILR School, vol. 72(4), pages 783-817, August.
    12. repec:bla:ecinqu:v:51:y:2013:i:3:p:1651-1681 is not listed on IDEAS
    13. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
    14. Doppelhofer, G. & Moe Hansen, O-P. & Weeks, M., 2017. "Determinants of long-term economic growth redux: A Measurement Error Model Averaging (MEMA) approach," Cambridge Working Papers in Economics 1702, Faculty of Economics, University of Cambridge.
    15. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    16. Ingo Borchert & Batshur Gootiiz & Aaditya Mattoo, 2014. "Policy Barriers to International Trade in Services: Evidence from a New Database," The World Bank Economic Review, World Bank, vol. 28(1), pages 162-188.
    17. Neidhöfer, Guido & Serrano, Joaquín & Gasparini, Leonardo, 2018. "Educational inequality and intergenerational mobility in Latin America: A new database," Journal of Development Economics, Elsevier, vol. 134(C), pages 329-349.
    18. repec:cep:stiecm:/2014/572 is not listed on IDEAS
    19. Hausman, Jerry & Lewis, Randall & Menzel, Konrad & Newey, Whitney, 2011. "Properties of the CUE estimator and a modification with moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 45-57.
    20. Holmlund, Helena, 2007. "A Researcher's Guide to the Swedish Compulsory School Reform," Working Paper Series 9/2007, Stockholm University, Swedish Institute for Social Research.
    21. Di Miceli, Andrea, 2019. "Horizontal vs. vertical transmission of fertility preferences," Journal of Comparative Economics, Elsevier, vol. 47(3), pages 562-578.
    22. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    23. SHAH, Syed Muhammad Noaman Ahmed & KEBEWAR, mazen, 2013. "US Corporate Bond Yield Spread: A default risk debate," MPRA Paper 44887, University Library of Munich, Germany.

    More about this item

    Keywords

    data combination; empirical Euclidean likelihood; errors-in-variables; instrumental variables.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

    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:usi:wpaper:774. 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: Fabrizio Becatti (email available below). General contact details of provider: https://edirc.repec.org/data/desieit.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.