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Application of the binary Propensity Score Matching methodology to evaluation of EU Rural Development programmes – a micro-level approach




The main objective of this study is to show how various micro-economic direct/indirect effects (e.g. deadweight loss, leverage effects, etc.) and selected general equilibrium effects (e.g. substitution and displacement effects) of EU RD programmes can be calculated using recently developed advanced econometric semi-parametric evaluation methodologies. Answers to EU Common Evaluation Questions (CEQ) regarding the effects of an RD programme on programme beneficiaries at farm level (including deadweight loss and leverage effects) are provided by comparing changes in specific result indicators collected at a farm level (e.g. profits, employment, gross-value added, labour productivity, etc.) in the group of programme beneficiaries with an appropriately selected control group (counterfactual analysis - based on matching). Direct programme effects are calculated on the basis of Average Treatment on Treated (ATT) indicators (for programme beneficiaries), Average Treatment Effects on Non-Treated (ATNT) indicators (for programme non-beneficiaries) and Average Treatment Effects (for both groups) using a combination of propensity score matching (PSM) and difference in differences (DID) methods. A modified propensity score and difference in differences methodology (modified PSM-DID) is applied to derive various general equilibrium effects (e.g. substitution or displacement effects). The empirical analysis is focused on evaluation of effects of the SAPARD programme in Slovakia (years 2002-2005) and the Agrarinvestitionsförderungsprogramm (AFP) in Schleswig Holstein, Germany (2000-2006) using micro-economic data (balanced panels) of bookkeeping farms (including programme participants and non-participants) in respective countries.

Suggested Citation

  • Jerzy Michalek, 2012. "Application of the binary Propensity Score Matching methodology to evaluation of EU Rural Development programmes – a micro-level approach," JRC Working Papers JRC71977, Joint Research Centre (Seville site).
  • Handle: RePEc:ipt:iptwpa:jrc71977

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    References listed on IDEAS

    1. Karel Haegeman & Elisabetta Marinelli & Susana Elena Perez & Gerard Carat & Alexander Degelsegger & Gorazd Weiss & Philine Warnke, 2012. "Era Fabric Map - First Edition," JRC Working Papers JRC71972, Joint Research Centre (Seville site), revised Aug 2012.
    2. Wiesenthal, Tobias & Leduc, Guillaume & Haegeman, Karel & Schwarz, Hans-Günther, 2012. "Bottom-up estimation of industrial and public R&D investment by technology in support of policy-making: The case of selected low-carbon energy technologies," Research Policy, Elsevier, pages 116-131.
    3. Tobias Wiesenthal & Guillaume Leduc & Hans-Gunther Schwarz & Karel Haegeman, 2009. "RandD Investment in the Priority Technologies of the European Strategic Energy Technology Plan," JRC Working Papers JRC52225, Joint Research Centre (Seville site).
    4. Totti Könnölä & Karel Haegeman, 2012. "Embedding foresight in transnational research programming," Science and Public Policy, Oxford University Press, vol. 39(2), pages 191-207, March.
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    More about this item


    impact assessment; counterfactual analysis; evaluation; propensity score matching;

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy

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