Course Topics
1) The Experimental Ideal: Causal Effects and the Selection Problem 2) Randomized Control Trials, ethical and practical challenges, communication and policy consulting 3) Natural experiments (discovering, analyzing, evaluating) 4) Panel, Difference-in-Differences, Instrumental Variables 5) Regression Discontinuity Designs 6) Synthetic Control

Teaching format
Lectures, labs, projects.

Educational objectives
Knowledge and understanding: The student acquires specific knowledge of the economic and business domains of his/her interest and necessary to address decision-making and management issues in public and private organisations with an interdisciplinary perspective. In the Data Analytics for Economics pathway, knowledge will be oriented towards economic theory, economic analysis and econometrics through the development of micro- and macroeconomics, decision theory under conditions of uncertainty, time series analysis and forecasting techniques, methods for causal inference from both administrative and experimental data. Knowledge will also be oriented towards data analysis. In the Business Analytics track, the knowledge acquired will concern the tools necessary for analysing and interpreting business and organisational data, as well as business economic measurements, business models and their evolution, tools and techniques to support decision-making, performance measurement systems consistent with digitisation and sustainability processes, the governance of marketing processes, with particular regard to digital and interactive marketing and the impact of digitisation on marketing activities. Aapplying knowledge and understanding: Ability to analyse business issues that characterise data-driven decision support through the application of statistical and computational models. Ability to use and apply models for market analysis and economic policy formulation. Making judgements: Master's graduates will have the ability to apply the acquired knowledge to interpret data in order to make directional and operational decisions in an economic-business context. Master graduates will have the ability to apply the acquired knowledge to support processes related to production, management and risk promotion activities and investment choices through the organisation, analysis and interpretation of complex databases. Communication skills: Master's graduates will be able to communicate effectively in oral and written form the specialised contents of the individual disciplines, using different registers, depending on the recipients and the communicative and didactic purposes, and to evaluate the formative effects of their communication. Learning skills: "MSc graduates should be familiar with the tools of scientific research. They will also be able to make autonomous use of information technologies to carry out bibliographic research and investigations both for their own training and for further education. In addition, through the curricular teaching and the activities related to the preparation of the final thesis, they will be able to acquire the ability - to identify thematic links and to establish relationships between methods of analysis and application contexts; - to frame a new problem in a systematic manner and to implement appropriate analysis solutions; - to formulate general statistical-econometric models from the phenomena studied.

Assessment
For Attending and Non-Attending Students: Project Development: Students will choose a topic relevant to the course and develop either: (a) an evaluation plan for a public policy of their choice, which includes a comprehensive methodology section detailing the proposed data collection and analysis methods using R, or (b) a replication of an existing public policy evaluation, including a critical reflection on the original study's methodology, findings, and implications. For Attending Students: 1. Presentation: Students must present their project plans or replication studies to the class. The presentation should succinctly summarize the project's purpose, methodology, expected outcomes (for evaluation plans), or main findings and critique (for replications). This will account for 30% of the final grade and will be evaluated on clarity, engagement with the audience, and the depth of understanding demonstrated. 2. Project Report: A 1,500-word report must be submitted, documenting the project in detail. For evaluation plans, this should include background, methodology, expected results, and potential impact. For replications, it should discuss the methodology, analysis in R, findings, and a critical reflection. The report counts for 70% of the final grade and will be assessed for thoroughness, insightfulness, and the ability to convey complex information effectively. For Non-attending Students: 2. Extended Project Assignment: Non-attending students will submit a longer project report of 2,500 words that covers the same criteria as above but should also include a more detailed literature review to contextualize their project within the current research landscape. This report will count for 100% of the final grade. Initial Contact: Non-attending students must contact the lecturer within the first four weeks of the course to discuss their project topic and receive guidance. Project work and classroom presentations are valid for 1 academic year and cannot be carried over beyond that time-frame.

Evaluation criteria
Presentation: 1. Clarity of Presentation (20%): The student must present content in a manner that is both clear and comprehensible. Complex concepts should be articulated in a way that is accessible to all audience members. 2. Quality of Argumentation (20%): Arguments should be presented in a logical and persuasive manner, with adequate support from empirical data or scholarly literature. 3. Mastery of Technical Terminology (20%): Usage of technical terminology should be precise and contextually appropriate. 4. Interactive Communication Skills (20%): The student’s ability to engage with the audience through responsive Q&A, as well as the effective use of visual aids, will be evaluated. 5. Structure and Organization (20%): The presentation should have a coherent structure with a clear narrative thread throughout. Project Report: 1. Correct Application of Methods (25%): The report should demonstrate that Impact Evaluation methods have been accurately applied and thoroughly described. 2. Depth of Analysis (25%): The report must reflect a comprehensive analysis and profound understanding of the chosen subject matter. 3. Critical Thinking (25%): The report should critically examine the methods employed and the results achieved, showcasing analytical depth. 4. Accuracy and Completeness (25%): The report must be meticulous in considering and presenting all relevant aspects of the project with precision.