This thesis is a collection of three essays in causal evaluation. The first chapter investigates the effects of formal ties between firms and banks on the amount of credit received. I focus on the micro-effects of ties (bank-firm level) and how they reverberate at the macro level. Results are consistent with the literature considering links as a source of favoritism. However, efficient firms are more likely to be connected to banks, thus benefiting more often than less efficient firms from connections. The comparison of Portugal’s GDP in 2017 with that produced under a hypothetical scenario where every tie was severed shows that severing links results in virtually no changes in GDP. I interpret the result as evidence that the different likelihood of being connected experienced by efficient and not efficient firms counterbalances the misallocating potential of connections.The second chapter introduces a novel Stata implementation of Egger and von Ehrlich’s (2013) econometric framework for the estimation of treatment effect when the treatment is continuous and multidimensional. After the illustration of the package, I present a simple simulation to show the capability of the method to overcome bias.The third chapter consists of an evaluation of European regional policy. It analyzes how different mixes of investments in infrastructure and productive investments affect regions’ growth rate. The main results are that allocations in infrastructure foster growth only when coupled with expenditures in productive investments. Moreover, the highest growth is obtained when investments have high intensity in both dimensions. By generating two hypothetical scenarios, I investigate how the allocation of funds can be improved. The results show that regions could allocate more efficiently. However, the actual transfer intensity is not enough to choose the mix that would globally maximize growth. The findings are consistent with Becker et al. (2012) since enforcing common support restricts the analysis to regions with low transfer intensity.
| Identifer | oai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/318965 |
| Date | 05 October 2021 |
| Creators | Cristofoletti, Enrico |
| Contributors | Cristofoletti, Enrico, Gabriele, Roberto, Gaffeo, Edoardo |
| Publisher | Università degli studi di Trento, place:TRENTO |
| Source Sets | Università di Trento |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | firstpage:1, lastpage:136, numberofpages:136 |
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