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Riccardo D'Alberto is a Senior Fixed-Term Researcher (RTD-B) at the Department of Economics of the University of Verona.
He obtained a Ph.D. in Statistical Sciences at the Department of Statistical Sciences "P. Fortunati" of the Alma Mater Studiorum – University of Bologna, defending a thesis entitled "Statistical Matching Imputation among Different Farm Data Sources," supervised by Professor Meri Raggi and Professor Davide Viaggi.
His main research interests include the integration of different data sources (primary, secondary, official statistics, web data, etc.) with a focus on parametric and non-parametric techniques of Statistical Matching and Record Linkage; counterfactual analysis with Propensity Score methods and Diff-in-Diff estimators, with particular attention to the impact assessment of public and agro-environmental policies; the estimation of willingness to pay and willingness to accept in relation to environmental public goods, and the transfer of estimates from Contingent Valuation and Choice Experiment of these values using non-parametric matching techniques.
Riccardo has been a project member in the following European projects funded by the Horizon 2020 program: PROVIDE (Grant Agreement No. 633838), LIFT (Grant Agreement No. 770747), and CONSOLE (Grant Agreement No. 817949). The PROVIDE and CONSOLE projects were coordinated by the research group of Professor Viaggi (Alma Mater Studiorum – University of Bologna). Riccardo also participated in the European project funded by the FP7 IMPRESA program (Grant Agreement No. 609448), and in the following European projects funded by the Horizon 2020 program: SUFISA (Grant Agreement No. 635577), RUBIZMO (Grant Agreement No. 773621). Finally, he was a paid consultant for the following European Commission Tender projects: AGRI/2020/OP/0004 (Contract No. Ares(2020)3784847), AGRI-2016-EVAL-04 (Contract No. 30-CE-0887790/00-21).
Modules running in the period selected: 2.
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|Course||Name||Total credits||Online||Teacher credits||Modules offered by this teacher|
|Master’s degree in Marketing and Corporate Communication||Business Statistics (2023/2024)||9||6|
|Master’s degree in Banking and Finance||Financial statistics (2023/2024)||9||9|
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