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Unintended consequences of environmental policies: the case of set-aside and agricultural intensification

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  • Thomas, Alban
  • Chakir, Raja

Abstract

Set-aside policies providing agronomic and ecological benefits have been mainstream practices in European agriculture. Because they may lead to intensification on cultivated land, they can however have mixed environmental effects. To evaluate the indirect impact of a set-aside policy on crop intensification, we consider two elasticity indicators with respect to set-aside subsidy: chemical input demand and intensity of input use. We estimate a structural, multi-output model on a panel of French farmers from 2006 to 2010, accounting for multivariate selection (corner solutions) on crops and land use, with a semi nonparametric Quasi-Maximum Likelihood estimator robust to deviations from normality and homoskedasticity. Results show that a set-aside subsidy can provide farmers with incentives to intensify their production, leading to potential adverse environmental effects that can however be offset by a complementary tax policy instrument.

Suggested Citation

  • Thomas, Alban & Chakir, Raja, 2020. "Unintended consequences of environmental policies: the case of set-aside and agricultural intensification," TSE Working Papers 20-1066, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:123955
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    More about this item

    Keywords

    Set-aside; land use; fertilizer and pesticide input demand; corner solutions; semi nonparametric estimation.;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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