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Survey response and survey characteristics: Micro-level evidence from the ECHP

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  • Nicoletti, Cheti
  • Peracchi, Franco

Abstract

This paper presents some micro-level evidence on the role of the socio-demographic characteristics of the population and the characteristics of the data collection process as predictors of survey response. Our evidence is based on the public use files of the European Community Household Panel (ECHP), a longitudinal household survey covering the countries of the European Union, whose attractive feature is the high level of comparability across countries and over time. We use individual-level information to predict response in the next wave given response in the current wave, focusing on how the probabilities of contact failure and refusal to cooperate vary with the socio-demographic composition of the national populations and the characteristics of the data collection process. We model the response process as the outcome of two sequential events; (i) the contact between the interviewer and an eligible interviewee, and (ii) the cooperation of the interviewee. Our model allows for dependence between the ease of contact and the propensity to cooperate, taking into account the censoring problem caused by the fact that we observe whether a person is a respondent only if she has been contacted.

Suggested Citation

  • Nicoletti, Cheti & Peracchi, Franco, 2004. "Survey response and survey characteristics: Micro-level evidence from the ECHP," Economics & Statistics Discussion Papers esdp04015, University of Molise, Dept. EGSeI.
  • Handle: RePEc:mol:ecsdps:esdp04015
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    References listed on IDEAS

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    1. O'Connell, Philip J. & Russell, Helen & FitzGerald, John, 2006. "Human Resources," Book Chapters, in: Morgenroth, Edgar (ed.),Ex-Ante Evaluation of the Investment Priorities for the National Development Plan 2007-2013, Economic and Social Research Institute (ESRI).
    2. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    3. Pamela Campanelli & Colm O'Muircheartaigh, 2002. "The Importance of Experimental Control in Testing the Impact of Interviewer Continuity on Panel Survey Nonresponse," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(2), pages 129-144, May.
    4. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    5. JM Abowd & Bruno Crépon & Francis Kramarz, 1997. "Moment Estimation with Attrition," Working Papers 97-35, Center for Research in Economics and Statistics.
    6. Morimune, Kimio, 1979. "Comparisons of Normal and Logistic Models in the Bivariate Dichotomous Analysis," Econometrica, Econometric Society, vol. 47(4), pages 957-975, July.
    7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    8. Franco Peracchi, 2002. "The European Community Household Panel: A review," Empirical Economics, Springer, vol. 27(1), pages 63-90.
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    Cited by:

    1. Del Boca, Daniela & Sauer, Robert M., 2009. "Life cycle employment and fertility across institutional environments," European Economic Review, Elsevier, vol. 53(3), pages 274-292, April.
    2. Nicole Watson & Roger Wilkins, 2012. "The Impact of Computer-Assisted Interviewing on Interview Length," Melbourne Institute Working Paper Series wp2012n10, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    3. Andrew E. Clark, 2006. "A Note on Unhappiness and Unemployment Duration," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 52(4), pages 291-308.
    4. Nicole Watson & Roger Wilkins, 2012. "Experimental Change from Paper-Based Interviewing to Computer-Assisted Interviewing in the HILDA Survey," Melbourne Institute Working Paper Series wp2012n06, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

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    More about this item

    Keywords

    Panel data; survey response; bivariate probit model.;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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