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Modelling Agricultural Public R&D Cofinancing Within A Principal-Agent Framework. The case of an Italian region

Author

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  • Valentina Cristiana MATERIA

    (Universita' Politecnica delle Marche, Dipartimento di Economia)

  • Roberto ESPOSTI

    (Universita' Politecnica delle Marche, Dipartimento di Economia)

Abstract

This paper analyses how a public institution chooses the optimal contract (cofinancing rate) in funding agricultural R&D research projects. A theoretical model is developed within a principal-agent framework taking into account the asymmetric information both players have to handle. The researcher (the agent) initially does not know the cofinancing granted by the funding institution (the principal). This latter, in turn, only observes some objective features of the researchers and of the selected research projects and, ex post, the research outcome, but not the agent's actual effort on the project. The principal uses the available information to offer the cofinancing rate (the contract) that, under specific contractual clauses, induces the agent's effort that maximizes principal's utility. The model eventually assumes the form of a Stackelberg-type game. An empirically testable relation is also derived from the theoretical model and is then applied to the agricultural R&D programme funded by the Italian region Emilia-Romagna over years 2001-2006.

Suggested Citation

  • Valentina Cristiana MATERIA & Roberto ESPOSTI, 2010. "Modelling Agricultural Public R&D Cofinancing Within A Principal-Agent Framework. The case of an Italian region," Working Papers 347, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    • Handle: RePEc:anc:wpaper:347
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    References listed on IDEAS

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    8. Esposti, Roberto & Materia, Valentina, 2015. "The determinants of the public R&D cofinancing rate An empirical assessment on agricultural research," 2015 Conference, August 9-14, 2015, Milan, Italy 211624, International Association of Agricultural Economists.
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    More about this item

    Keywords

    Censored-Normal Regression; Principal-Agent Problem; Public R&D Funding; Stackelberg-type game;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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