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Estimation And Inference In Social Experiments

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  • Christopher Ferrall

Abstract

This paper develops a framework for analyzing the outcome of experiments carried out on forward-looking subjects. Natural experiments, unexpected policy changes, and true experiments are all included in the framework as special cases. These concepts are defined in conjunction with explicit notions of controlled and randomized experiments. The persistent issues of sample-selection bias and heterogeneous impacts that surround interpretations of experiments are endogenous to the model. Special attention is given to interpreting empirical impact of the treatment within the model. The environments in which estimated mean impacts correspond to mean subjective impacts are specified, and they are found to be a small, uninteresting subset of environments contained within the framework.

Suggested Citation

  • Christopher Ferrall, 2002. "Estimation And Inference In Social Experiments," Working Paper 1008, Economics Department, Queen's University.
  • Handle: RePEc:qed:wpaper:1008
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    References listed on IDEAS

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    8. Christopher Ferrall, 2012. "Explaining and Forecasting Results of the Self-sufficiency Project," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(4), pages 1495-1526.
    9. Pencavel, John, 1987. "Labor supply of men: A survey," Handbook of Labor Economics, in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 1, pages 3-102, Elsevier.
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    Cited by:

    1. Christopher Ferrall, 2012. "Explaining and Forecasting Results of the Self-sufficiency Project," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(4), pages 1495-1526.
    2. Jaap Abbring & Gerard Van Den Berg, 2005. "Social experiments and instrumental variables with duration outcomes," IFS Working Papers W05/19, Institute for Fiscal Studies.

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    Keywords

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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