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An Economic Analysis of Exclusion Restrictions for Instrumental Variable Estimation

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  • Van den Berg, Gerard
Abstract
Instrumental variable estimation requires untestable exclusion restrictions. With policy effects on individual outcomes, there is typically a time interval between the moment the agent realizes that he may be exposed to the policy and the actual exposure or the announcement of the actual treatment status. In such cases there is an incentive for the agent to acquire information on the value of the IV. This leads to violation of the exclusion restriction. We analyze this in a dynamic economic model framework. This provides a foundation of exclusion restrictions in terms of economic behavior. The results are used to describe policy evaluation settings in which instrumental variables are likely or unlikely to make sense. For the latter cases we analyze the asymptotic bias. The exclusion restriction is more likely to be violated if the outcome of interest strongly depends on interactions between the agent's effort before the outcome is realized and the actual treatment status. The bias has the same sign as this interaction effect. Violation does not causally depend on the weakness of the candidate instrument or the size of the average treatment effect. With experiments, violation is more likely if the treatment and control groups are to be of similar size. We also address side-effects. We develop a novel economic interpretation of placebo effects and provide some empirical evidence for the relevance of the analysis.

Suggested Citation

  • Van den Berg, Gerard, 2007. "An Economic Analysis of Exclusion Restrictions for Instrumental Variable Estimation," CEPR Discussion Papers 6157, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:6157
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    Cited by:

    1. Gerard J. van den Berg & Annette H. Bergemann & Marco Caliendo, 2009. "The Effect of Active Labor Market Programs on Not-Yet Treated Unemployed Individuals," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 606-616, 04-05.
    2. Gerard J. van den Berg & Christine Dauth & Pia Homrighausen & Gesine Stephan, 2023. "Informing employees in small and medium‐sized firms about training: Results of a randomized field experiment," Economic Inquiry, Western Economic Association International, vol. 61(1), pages 162-178, January.
    3. Davies, Neil & Dickson, Matt & Smith, George Davey & Windmeijer, Frank & van den Berg, Gerard J., 2019. "The Causal Effects of Education on Adult Health, Mortality and Income: Evidence from Mendelian Randomization and the Raising of the School Leaving Age," IZA Discussion Papers 12192, Institute of Labor Economics (IZA).
    4. Abbring, Jaap H & van den Berg, Gerard J, 2005. "Social experiments and intrumental variables with duration outcomes," Working Paper Series 2005:11, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    5. Muhammad Bashir & Steven Schilizzi, 2015. "Food security policy assessment in the Punjab, Pakistan: effectiveness, distortions and their perceptions," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(5), pages 1071-1089, October.
    6. Belzil, Christian & Hansen, Jörgen, 2008. "Calibration and IV Estimation of a Wage Outcome Equation in a Dynamic Environment," IZA Discussion Papers 3528, Institute of Labor Economics (IZA).
    7. Stephan, Gesine & van den Berg, Gerard & Homrighausen, Pia, 2016. "Randomizing information on a targeted wage support program for older workers: A field experiment," VfS Annual Conference 2016 (Augsburg): Demographic Change 145487, Verein für Socialpolitik / German Economic Association.
    8. Zou, Baoling & Chen, Yudan & Mishra, Ashok K. & Hirsch, Stefan, 2024. "Agricultural mechanization and the performance of the local Chinese economy," Food Policy, Elsevier, vol. 125(C).

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    More about this item

    Keywords

    Information; Placebo effect; Policy evaluation; Randomization; Selection effects; Treatment;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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