Small and Medium Enterprises (SMEs) have a fundamental role in advanced economies in generating employment and in fostering innovation, but they often struggle with lack of financing resources due to the presence of information asymmetries. Loan Guarantee Instruments are the most adopted schemes to mitigate market imperfections, allowing banks to shift some risk on the guarantor, thus leading to a less restrictive lending behavior. The overall aim of this thesis is to examine whether the Tranched Cover Fund, a guarantee scheme implemented in an Italian region, is appropriate to the financing needs of local SMEs. The primary objective was to determine the effectiveness of the fund by measuring financial and economic additionality. Moreover, the study provides the first effectiveness prediction model allowing to predict the potential success of the scheme on a firm basis using simple and readily available information about companies. Finally, the study investigates the presence of causal relationships between financial additionality and a number of independent factors to understand whether possible adjustments might lead to higher effectiveness. Three major findings emerge from the study: first, the Tranched Cover Fund demonstrates to be an effective instrument to increase credit availability to local SMEs; second, the effectiveness of the Fund is predicted through loan characteristics and companies’ data, such as the amount, the interest rate, employees, EBITDA, Equity and ROI. Finally, it turns out that the odds of experiencing financial additionality are affected by managers’ personal characteristics and firms’ characteristics and financials.
Date of Award | 12 May 2016 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Fabio Amatucci (Supervisor) & Ricardo Reis (Co-Supervisor) |
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- Mestrado em Gestão: Programa Internacional
Do government loan guarantee instruments make sense?: evaluating effectiveness of the tranched cover fund
Viggiano, C. (Student). 12 May 2016
Student thesis: Master's Thesis