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Experiments, Surveys and the Use of Representative Samples as Reference Data

Author

Listed:
  • Thomas Siedler
  • Bettina Sonnenberg

Abstract

During the last two decades, laboratory experiments have come into increasing prominence and constitute a popular method of research to examine behavioral outcomes and social preferences. However, it has been debated whether results from these experiments can be extrapolated to the real world and whether, for example, sample selection into the experiment might constitute a major shortcoming of this methodology. This note discusses potential benefits of combining experimental methods and representative datasets as a means to overcome some of the limitations of lab experiments. We also outline how large representative surveys can serve as reference data for researchers collecting

Suggested Citation

  • Thomas Siedler & Bettina Sonnenberg, 2010. "Experiments, Surveys and the Use of Representative Samples as Reference Data," Working Paper Series of the German Council for Social and Economic Data 146, German Council for Social and Economic Data (RatSWD).
  • Handle: RePEc:rsw:rswwps:rswwps146
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    File URL: http://www.ratswd.de/download/RatSWD_WP_2010/RatSWD_WP_146.pdf
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    References listed on IDEAS

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    1. Antoni Bosch-Domènech & José G. Montalvo & Rosemarie Nagel & Albert Satorra, 2002. "One, Two, (Three), Infinity, ...: Newspaper and Lab Beauty-Contest Experiments," American Economic Review, American Economic Association, vol. 92(5), pages 1687-1701, December.
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    Cited by:

    1. David Richter & Jürgen Schupp, 2012. "SOEP Innovation Sample (SOEP-IS): Description, Structure and Documentation," SOEPpapers on Multidisciplinary Panel Data Research 463, DIW Berlin, The German Socio-Economic Panel (SOEP).

    More about this item

    Keywords

    experiments; survey; representativity;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D0 - Microeconomics - - General
    • D6 - Microeconomics - - Welfare Economics
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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