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Near Identification of Policy Trade-Offs Using Preference Proxies to Elicit Hidden Information in the Linear Case

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  • Jean-Paul Azam

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

This paper shows that neither OLS nor 2SLS can generically identify policy trade offs in the linear case, except under extreme assumptions. Practitioners must be content with near identification and the paper discusses how to choose between these two methods. It shows that a two-stage approach using preference proxies to elicit hidden information can potentially narrow the identification gap and that a simple specification test can be used to assess whether these proxies really contribute to improving identification.

Suggested Citation

  • Jean-Paul Azam, 2021. "Near Identification of Policy Trade-Offs Using Preference Proxies to Elicit Hidden Information in the Linear Case," Post-Print hal-03273618, HAL.
    • Handle: RePEc:hal:journl:hal-03273618
    DOI: 10.22158/elp.v4n1p48
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    References listed on IDEAS

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