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Structural Estimation and Experiments: Applications to Contracting Models

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  • Charles Bellemare
  • Steeve Marchand
  • Bruce Shearer

Abstract

Structural estimation requires the specification of behavioral models that can be used to conduct ex ante policy evaluations and welfare analysis. Experiments generate data by exogenously varying key variables to measure outcomes under various treatment conditions. Gains from combining experiments and structural estimation can be considerable. We illustrate these gains through two recent papers (Bellemare and Shearer, 2011, 2013) in the area of contracts and compensation systems. In both papers, the combination of structural modeling and experiments is essential - experiments cannot be conducted to implement all possible treatments of interest, while structural estimation using naturally occurring (payroll) data either is infeasible or requires restrictive modeling assumptions.

Suggested Citation

  • Charles Bellemare & Steeve Marchand & Bruce Shearer, 2016. "Structural Estimation and Experiments: Applications to Contracting Models," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 172(2), pages 342-363, June.
  • Handle: RePEc:mhr:jinste:urn:sici:0932-4569(201606)172:2_342:seaeat_2.0.tx_2-n
    DOI: 10.1628/10.1628/093245616X14540550139746
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    References listed on IDEAS

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    1. Daniel A. Ackerberg & Maristella Botticini, 2002. "Endogenous Matching and the Empirical Determinants of Contract Form," Journal of Political Economy, University of Chicago Press, vol. 110(3), pages 564-591, June.
    2. Esther Duflo & Rema Hanna & Stephen P. Ryan, 2012. "Incentives Work: Getting Teachers to Come to School," American Economic Review, American Economic Association, vol. 102(4), pages 1241-1278, June.
    3. Patrick Bajari & Ali Hortacsu, 2005. "Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data," Journal of Political Economy, University of Chicago Press, vol. 113(4), pages 703-741, August.
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    5. Charles Bellemare & Sabine Kröger & Arthur van Soest, 2008. "Measuring Inequity Aversion in a Heterogeneous Population Using Experimental Decisions and Subjective Probabilities," Econometrica, Econometric Society, vol. 76(4), pages 815-839, July.
    6. Orazio P. Attanasio & Costas Meghir & Ana Santiago, 2012. "Education Choices in Mexico: Using a Structural Model and a Randomized Experiment to Evaluate PROGRESA," Review of Economic Studies, Oxford University Press, vol. 79(1), pages 37-66.
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    10. Meta Brown & Christopher J. Flinn & Andrew Schotter, 2011. "Real-Time Search in the Laboratory and the Market," American Economic Review, American Economic Association, vol. 101(2), pages 948-974, April.
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    Cited by:

    1. Florian Englmaier & Guido Friebel & Gerd Muehlheusser & Andreas Roider, 2016. "Symposium on Evidence-Based Management," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 172(2), pages 305-311, June.

    More about this item

    JEL classification:

    • J33 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Compensation Packages; Payment Methods
    • M52 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Compensation and Compensation Methods and Their Effects
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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