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Assessing the Impact of Financial Aids to Firms: Causal Inference in the presence of Interference

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  • Arpino, Bruno
  • Mattei, Alessandra

Abstract

We consider policy evaluations when SUTVA is violated because of the presence of interference among units. We propose to explicitly model interactions as a function of units characteristics. Our approach is applied to the evaluation of a policy implemented in Tuscany (a region in Italy) on small handicraft firms. Results show that the benefits from the policy are reduced when treated firms are subject to high levels of interference. Moreover, the average causal effect is slightly underestimated when interference is ignored. These findings point to the importance of considering possible interference among units when evaluating and planning policy interventions.

Suggested Citation

  • Arpino, Bruno & Mattei, Alessandra, 2013. "Assessing the Impact of Financial Aids to Firms: Causal Inference in the presence of Interference," MPRA Paper 51795, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:51795
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    Cited by:

    1. Chiara Bocci & Marco Mariani, 2015. "L?approccio delle funzioni dose-risposta per la valutazione di trattamenti continui nei sussidi alla r&s," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2015(3 Suppl.), pages 81-102.
    2. Daniele Di Gennaro & Guido Pellegrini, 2016. "Policy Evaluation In Presence Of Interferences: A Spatial Multilevel Did Approach," Working Papers 0416, CREI Università degli Studi Roma Tre, revised 2016.
    3. Di Gennaro, Daniele & Pellegrini, Guido, 2016. "Evaluating direct and indirect treatment effects in Italian R&D expenditures," MPRA Paper 76467, University Library of Munich, Germany, revised 28 Jan 2017.
    4. Augusto Cerqua & Guido Pellegrini, 2014. "Beyond the SUTVA: how policy evaluations change when we allow for interactions among firms," Working Papers 2/14, Sapienza University of Rome, DISS.

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    More about this item

    Keywords

    Causal inference; Interference; Policy evaluation; Potential outcomes; SUTVA;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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