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Statistical analysis of choice experiments and surveys

Author

Listed:
  • McFadden, Daniel L.
  • Bemmaor, Albert C.
  • Caro, Francis G.
  • Dominitz, Jeff
  • Jun, Byung-hill
  • Lewbel, Arthur
  • Matzkin, Rosa L.
  • Molinari, Francesca
  • Schwarz, Norbert
  • Willis, Robert J.
  • Winter, Joachim

Abstract

Measures of households’ past behavior, their expectations with respect to future events and contingencies, and their intentions with respect to future behavior are frequently collected using household surveys. These questions are conceptually difficult. Answering them requires elaborate cognitive and social processes, and often respondents report only their \"best\" guesses and/or estimates, using more or less sophisticated heuristics. A large body of literature in psychology and survey research shows that as a result, responses to such questions may be severely biased. In this paper, (1) we describe some of the problems that are typically encountered, (2) provide some empirical illustrations of these biases, and (3) develop a framework for conceptualizing survey response behavior and for integrating structural models of response behavior into the statistical analysis of the underlying economic behavior.

Suggested Citation

  • McFadden, Daniel L. & Bemmaor, Albert C. & Caro, Francis G. & Dominitz, Jeff & Jun, Byung-hill & Lewbel, Arthur & Matzkin, Rosa L. & Molinari, Francesca & Schwarz, Norbert & Willis, Robert J. & Winter, 2005. "Statistical analysis of choice experiments and surveys," Munich Reprints in Economics 19251, University of Munich, Department of Economics.
  • Handle: RePEc:lmu:muenar:19251
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    References listed on IDEAS

    as
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    Cited by:

    1. Borghans, Lex & Romans, Margo & Sauermann, Jan, 2010. "What makes a good conference? Analysing the preferences of labour economists," Labour Economics, Elsevier, vol. 17(5), pages 868-874, October.
    2. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    3. Omar Galárraga & Sandra Sosa-Rubí & César Infante & Paul Gertler & Stefano Bertozzi, 2014. "Willingness-to-accept reductions in HIV risks: conditional economic incentives in Mexico," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(1), pages 41-55, January.
    4. Fabián Slonimczyk & Marco Francesconi & Anna Yurko, 2017. "Moving On Up for High School Graduates in Russia: The Consequences of the Unified State Exam Reform," CESifo Working Paper Series 6447, CESifo Group Munich.
    5. Delavande, Adeline & Giné, Xavier & McKenzie, David, 2011. "Measuring subjective expectations in developing countries: A critical review and new evidence," Journal of Development Economics, Elsevier, vol. 94(2), pages 151-163, March.
    6. Petri Böckerman & Pekka Ilmakunnas, 2009. "Unemployment and self-assessed health: evidence from panel data," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 161-179.
    7. repec:eee:transa:v:107:y:2018:i:c:p:166-186 is not listed on IDEAS
    8. Donatella Baiardi & Riccardo Puglisi & Simona Scabrosetti, 2012. "Individual Attitudes on Food Quality and Safety: Empirical Evidence on EU Countries," DEM Working Papers Series 014, University of Pavia, Department of Economics and Management.
    9. de Nicola, Francesca & Giné, Xavier, 2014. "How accurate are recall data? Evidence from coastal India," Journal of Development Economics, Elsevier, vol. 106(C), pages 52-65.
    10. A. Ludwig & A. Zimper, 2013. "A parsimonious model of subjective life expectancy," Theory and Decision, Springer, vol. 75(4), pages 519-541, October.
    11. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    12. Jacobsen, Ben & Lee, John B. & Marquering, Wessel & Zhang, Cherry Y., 2014. "Gender differences in optimism and asset allocation," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 630-651.
    13. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 23-50 National Bureau of Economic Research, Inc.
    14. repec:pal:jorsoc:v:60:y:2009:i:1:d:10.1057_palgrave.jors.2602524 is not listed on IDEAS
    15. Stefano Balbi & Carlo Giupponi & Roland Olschewski & Vahid Mojtahed, 2013. "The economics of hydro-meteorological disasters: approaching the estimation of the total costs," Working Papers 2013-12, BC3.
    16. Borghans, Lex & Romans, Margo & Sauermann, Jan, 2010. "What makes a good conference? Analysing the preferences of labour economists," Labour Economics, Elsevier, vol. 17(5), pages 868-874, October.
    17. Dmitri Vinogradov & Yousef Makhlouf, 2017. "Signaling Probabilities in Ambiguity: on the impact of vague news," Working Papers 2017_12, Business School - Economics, University of Glasgow.
    18. Thøgersen, John, 2017. "Housing-related lifestyle and energy saving: A multi-level approach," Energy Policy, Elsevier, vol. 102(C), pages 73-87.
    19. Belyaev, Yuri & Kriström, Bengt, 2012. "Two-step approach to Self-Selected Interval Data in Elicitation Surveys," CERE Working Papers 2012:10, CERE - the Center for Environmental and Resource Economics.
    20. repec:spr:metrik:v:80:y:2017:i:4:d:10.1007_s00184-017-0610-7 is not listed on IDEAS
    21. Richard, Pierre J. & Coltman, Tim & Keating, Byron W., 2009. "Designing IS service strategy: an information acceleration approach," MPRA Paper 40488, University Library of Munich, Germany.

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