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Econometric Mediation Analyses: Identifying the Sources of Treatment Effects from Experimentally Estimated Production Technologies with Unmeasured and Mismeasured Inputs

Author

Listed:
  • James J. Heckman

    (University of Chicago)

  • Rodrigo Pinto

    (University of Chicago)

Abstract

This paper presents an econometric mediation analysis. It considers identification of production functions and the sources of output effects (treatment effects) from experimental interventions when some inputs are mismeasured and others are entirely omitted.

Suggested Citation

  • James J. Heckman & Rodrigo Pinto, 2013. "Econometric Mediation Analyses: Identifying the Sources of Treatment Effects from Experimentally Estimated Production Technologies with Unmeasured and Mismeasured Inputs," Working Papers 2013-006, Human Capital and Economic Opportunity Working Group.
  • Handle: RePEc:hka:wpaper:2013-006
    Note: ECI
    as

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    File URL: http://humcap.uchicago.edu/RePEc/hka/wpaper/Heckman_Pinto_2013_Econ_Mediation_Analysis_2013-04-14a_sjs.pdf
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    References listed on IDEAS

    as
    1. James Heckman & Seong Hyeok Moon & Rodrigo Pinto & Peter Savelyev & Adam Yavitz, 2010. "Analyzing social experiments as implemented: evidence from the HighScope Perry Preschool Program," CeMMAP working papers CWP22/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    3. John Horn, 1965. "A rationale and test for the number of factors in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 30(2), pages 179-185, June.
    4. Flavio Cunha & James J. Heckman, 2008. "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    5. Louis Guttman, 1954. "Some necessary conditions for common-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(2), pages 149-161, June.
    6. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
    7. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, May.
    8. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    9. James Heckman & Seong Hyeok Moon & Rodrigo Pinto & Peter Savelyev & Adam Yavitz, 2010. "Analyzing social experiments as implemented: A reexamination of the evidence from the HighScope Perry Preschool Program," Quantitative Economics, Econometric Society, vol. 1(1), pages 1-46, July.
    10. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Production Function; Mediation Analysis; Measurement Error; Missing Inputs;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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