Toccafondi, Niccolò (2025) Experimental Methods For Policy Analysis. Advisor: Bilancini, Prof. Ennio. Coadvisor: Di Guida, Prof. Sibilla . pp. 169. [IMT PhD Thesis]
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Text (Doctoral thesis)
Toccafondi_phdthesis.pdf - Published Version Restricted to IMT staff and National library only until 19 June 2026. Download (1MB) | Request a copy |
Abstract
Traditional policy analysis typically address policy relevant questions using observational data and quasi experimental methodologies. There are cases, however, when observational data are either not available to researchers, not ft for causal interpretation, or non-existent. In these cases experimental methods provide a valid alternative to support the policy-making process in the design, implementation and evaluation phases. This dissertation contributes to the growing feld of experimental policy analysis by examining three policy-relevant questions where observational data are private and not available to researchers (Chapter 2), are affected by a censoring bias and are not ft for causal interpretation (Chapter 3) and are non-existent (Chapter 4). In Chapter 2, I find that virtual currencies increase participants’ willingness to pay for transactions involving risk and ambiguity, even if the exchange rate remains constant. Moreover, when the nominal value of a virtual currency is higher than its real value, participants reduce their willingness to pay and become more sensitive to risk and ambiguity. In Chapter 3, I examine the effects of providing real-time information on ER congestion. I find an increase of the total number of ER visits. This evidence suggests that when information is available the uncertainty of ER visits decreases, leading risk-averse individuals to choose the ER more frequently. In Chapter 4, I provide evidence supporting the importance of complementing theory-driven lectures with hands-on, gamifed activities for computer science and cybersecurity education.
Item Type: | IMT PhD Thesis |
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Subjects: | H Social Sciences > HB Economic Theory |
PhD Course: | Economics, Networks and Business Analytics |
Identification Number: | https://doi.org/10.13118/imtlucca/e-theses/452 |
Date Deposited: | 15 Jul 2025 10:07 |
URI: | http://e-theses.imtlucca.it/id/eprint/452 |
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