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To match, not to match, how to match: Estimating the farm-level impact of the CAP-first pillar reform (or: How to Apply Treatment-Effect Econometrics when the Real World is;a Mess)

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  • Roberto ESPOSTI

    () (Universit… Politecnica delle Marche, Dipartimento di Scienze Economiche e Sociali)

Abstract

This paper aims at evaluating the impact of the 2003/2005 CAP reform on farm production choices. The outcome of "market orientation" is measured by considering both the short-term production choices and the long-term investment decisions. The Treatment Effect (TE) is estimated through alternative approaches due to the difficulties encountered in finding appropriate counterfactuals. Different versions of the Propensity Score Matching (PSM) estimators, the Difference-In-Difference (DID) estimate, and alternative multiple/continuous TEs estimates, based on the Generalized Propensity Score (GPS), are performed, their statistical robustness assessed and results compared. Results show that the 2003/2005 reform of the first pillar of the CAP actually had an impact more in (re)orienting short-term farm production choices then investment decisions and this effect is significantly more evident for farms with a limited contribution of the CAP on their own Gross Production Value.

Suggested Citation

  • Roberto ESPOSTI, 2014. "To match, not to match, how to match: Estimating the farm-level impact of the CAP-first pillar reform (or: How to Apply Treatment-Effect Econometrics when the Real World is;a Mess)," Working Papers 403, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  • Handle: RePEc:anc:wpaper:403
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    References listed on IDEAS

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    1. Andrea Pufahl & Christoph R. Weiss, 2009. "Evaluating the effects of farm programmes: results from propensity score matching," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(1), pages 79-101, March.
    2. Villa, Juan M., 2012. "Simplifying the estimation of difference in differences treatment effects with Stata," MPRA Paper 43943, University Library of Munich, Germany.
    3. Markus Fr–lich, 2004. "Programme Evaluation with Multiple Treatments," Journal of Economic Surveys, Wiley Blackwell, vol. 18(2), pages 181-224, April.
    4. Salvioni, Cristina & Sciulli, Dario, 2011. "Impact of Rural Development Policy and Less Favored Areas Scheme: A Difference in Difference Matching Approach," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115988, European Association of Agricultural Economists.
    5. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    6. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    7. Chabé-Ferret, Sylvain & Subervie, Julie, 2013. "How much green for the buck? Estimating additional and windfall effects of French agro-environmental schemes by DID-matching," Journal of Environmental Economics and Management, Elsevier, vol. 65(1), pages 12-27.
    8. Michela Bia & Carlos A. Flores & Alfonso Flores-Lagunes & Alessandra Mattei, 2014. "A Stata package for the application of semiparametric estimators of dose–response functions," Stata Journal, StataCorp LP, vol. 14(3), pages 580-604, September.
    9. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    10. Roberto Esposti & Giulia Listorti, 2013. "Agricultural price transmission across space and commodities during price bubbles," Agricultural Economics, International Association of Agricultural Economists, vol. 44(1), pages 125-139, January.
    11. Matias D. Cattaneo & David M. Drukker & Ashley D. Holland, 2013. "Estimation of multivalued treatment effects under conditional independence," Stata Journal, StataCorp LP, vol. 13(3), pages 407-450, September.
    12. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).
    13. Magrini, Emiliano & Montalbano, Pierluigi & Nenci, Silvia & Salvatici, Luca, 2014. "Agricultural trade distortions during recent international price spikes: what implications for food security?," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182726, European Association of Agricultural Economists.
    14. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    15. Jerzy Michalek, 2012. "Counterfactual impact evaluation of EU rural development programmes - Propensity Score Matching methodology applied to selected EU Member States. Volume 2: A regional approach," JRC Working Papers JRC72060, Joint Research Centre (Seville site).
    16. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    17. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    18. Jochen Kluve & Hilmar Schneider & Arne Uhlendorff & Zhong Zhao, 2012. "Evaluating continuous training programmes by using the generalized propensity score," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(2), pages 587-617, April.
    19. Listorti, Giulia & Esposti, Roberto, 2012. "Horizontal Price Transmission in Agricultural Markets: Fundamental Concepts and Open Empirical Issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), issue 1, April.
    20. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    21. Roberto Esposti, 2007. "Regional Growth and Policies in the European Union: Does the Common Agricultural Policy Have a Counter-Treatment Effect?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 116-134.
    22. Renwick, Alan W. & Revoredo-Giha, Cesar, 2008. "Measuring Cross-Subsidisation Of The Single Payment Scheme In England," 109th Seminar, November 20-21, 2008, Viterbo, Italy 44783, European Association of Agricultural Economists.
    23. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    24. Bia, Michela & Mattei, Alessandra, 2007. "Application of the Generalized Propensity Score. Evaluation of public contributions to Piedmont enterprises," POLIS Working Papers 80, Institute of Public Policy and Public Choice - POLIS.
    25. Paul Winters & Alessandro Maffioli & Lina Salazar, 2011. "Introduction to the Special Feature: Evaluating the Impact of Agricultural Projects in Developing Countries," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(2), pages 393-402, June.
    26. Michela Bia & Alessandra Mattei, 2012. "Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(4), pages 485-516, November.
    27. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LP, vol. 8(3), pages 354-373, September.
    28. Austin Nichols, 2007. "Causal inference with observational data," Stata Journal, StataCorp LP, vol. 7(4), pages 507-541, December.
    29. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    30. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    31. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
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    1. Esposti, Roberto, 2014. "The Impact of the 2005 CAP First Pillar Reform as a Multivalued Treatment Effect: Alternative Estimation Approaches," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183067, European Association of Agricultural Economists.

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    Keywords

    common agricultural policy; farm production choices; matching; treatment effects;

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