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Data Science for Institutional and Organizational Economics

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  • Prüfer, Jens

    (Tilburg University, School of Economics and Management)

  • Prüfer, Patricia

    (Tilburg University, School of Economics and Management)

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Suggested Citation

  • Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Other publications TiSEM 4392ac65-4fb6-4e9a-a92d-5, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:4392ac65-4fb6-4e9a-a92d-5da46339c7a9
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    References listed on IDEAS

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    1. Claude Ménard & Mary M. Shirley (ed.), 2018. "A Research Agenda for New Institutional Economics," Books, Edward Elgar Publishing, number 17960.
    2. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates," American Economic Review, American Economic Association, vol. 104(9), pages 2593-2632, September.
    3. Raj Chetty & John N. Friedman & Emmanuel Saez, 2013. "Using Differences in Knowledge across Neighborhoods to Uncover the Impacts of the EITC on Earnings," American Economic Review, American Economic Association, vol. 103(7), pages 2683-2721, December.
    4. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    5. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    6. Jens Prüfer & Christoph Schottmüller, 2021. "Competing with Big Data," Journal of Industrial Economics, Wiley Blackwell, vol. 69(4), pages 967-1008, December.
    7. Rios-Morales, Ruth & Gamberger, Dragan & Smuc, Tom & Azuaje, Francisco, 2009. "Innovative methods in assessing political risk for business internationalization," Research in International Business and Finance, Elsevier, vol. 23(2), pages 144-156, June.
    8. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
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