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Identification of local interaction models with imperfect location data

Author

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  • Timothy G. Conley

    (Graduate School of Business, University of Chicago, 1101 East 58th Street, Chicago, IL 60637, USA)

  • Giorgio Topa

    (Department of Economics, New York University, 269 Mercer Street, New York, NY 10003, USA)

Abstract

This paper considers the problem of estimating a local interaction model defined at the level of individual agents, in the absence of perfect information about agent locations in the relevant socio-economic space. We consider two types of data limitations: one in which individual locations are measured with error, the other in which location information is correct but only up to some spatial region (e.g., census tracts or zip codes). Our results indicate that the model parameters are not identified almost surely in the former situation, whereas identification is preserved in the latter. We also suggest a potential estimation strategy that can yield useful information about the likely range of parameters even when point identification fails. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • Timothy G. Conley & Giorgio Topa, 2003. "Identification of local interaction models with imperfect location data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(5), pages 605-618.
  • Handle: RePEc:jae:japmet:v:18:y:2003:i:5:p:605-618 DOI: 10.1002/jae.736
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    References listed on IDEAS

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    1. Brock, William A. & Durlauf, Steven N., 2001. "Interactions-based models," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 54, pages 3297-3380 Elsevier.
    2. Montgomery, James D, 1991. "Social Networks and Labor-Market Outcomes: Toward an Economic Analysis," American Economic Review, American Economic Association, vol. 81(5), pages 1407-1418, December.
    3. Marianne Bertrand & Erzo F. P. Luttmer & Sendhil Mullainathan, 2000. "Network Effects and Welfare Cultures," The Quarterly Journal of Economics, Oxford University Press, vol. 115(3), pages 1019-1055.
    4. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    5. Goolsbee, Austan & Klenow, Peter J, 2002. "Evidence on Learning and Network Externalities in the Diffusion of Home Computers," Journal of Law and Economics, University of Chicago Press, vol. 45(2), pages 317-343, October.
    6. Philip J. Cross & Charles F. Manski, 2002. "Regressions, Short and Long," Econometrica, Econometric Society, vol. 70(1), pages 357-368, January.
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    Citations

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    Cited by:

    1. Conley, Timothy G. & Topa, Giorgio, 2007. "Estimating dynamic local interactions models," Journal of Econometrics, Elsevier, vol. 140(1), pages 282-303, September.
    2. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    3. Frédéric PUECH, 2005. "How Do Criminals Locate? Crime and Spatial Dependence in Minas Gerais," Working Papers 200524, CERDI.
    4. ÖZGÜR, Onur & BISIN, Alberto, 2011. "Dynamic Linear Economies with Social Interactions," Cahiers de recherche 04-2011, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    5. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, pages 23-53.
    6. Galbiati, Roberto & Zanella, Giulio, 2012. "The tax evasion social multiplier: Evidence from Italy," Journal of Public Economics, Elsevier, vol. 96(5), pages 485-494.
    7. Gabriella Conti & Andrea Galeotti & Gerrit Müller & Stephen Pudney, 2013. "Popularity," Journal of Human Resources, University of Wisconsin Press, vol. 48(4), pages 1072-1094.
      • Conti, Gabriella & Galeotti, Andrea & Mueller, Gerrit & Pudney, Stephen, 2009. "Popularity," ISER Working Paper Series 2009-03, Institute for Social and Economic Research.
      • Gabriella Conti & Andrea Galeotti & Gerrit Mueller & Stephen Pudney, 2012. "Popularity," NBER Working Papers 18475, National Bureau of Economic Research, Inc.
    8. Arnab Bhattacharjee & Sean Holly, 2011. "Structural interactions in spatial panels," Empirical Economics, Springer, pages 69-94.
    9. Lawrence E. Blume & William A. Brock & Steven N. Durlauf & Yannis M. Ioannides, 2010. "Identification of Social Interactions," Discussion Papers Series, Department of Economics, Tufts University 0754, Department of Economics, Tufts University.
    10. Guccio, C. & Lisi, D., 2014. "Social interactions in inappropriate behavior for childbirth services: Theory and evidence from the Italian hospital sector," Health, Econometrics and Data Group (HEDG) Working Papers 14/28, HEDG, c/o Department of Economics, University of York.
    11. Guccio, Calogero & Lisi, Domenico, 2016. "Thus do all. Social interactions in inappropriate behavior for childbirth services in a highly decentralized healthcare system," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 1-17.
    12. repec:kap:jgeosy:v:19:y:2017:i:4:d:10.1007_s10109-017-0249-y is not listed on IDEAS

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