Argomenti dell'insegnamento
The course consists of the following contents: - Introduction to the theory and practice of linear univariate and multivariate regressions and their interpretations - Testing hypotheses using the t-test, Wald and F-tests and calculating confidence intervals - Further topics: Models with quadratic terms, dummy variables and predictions - Linear regressions with endogeneity and heteroscedasticity - Difference-in-difference estimators - Introduction to time series and panel data Literature - Outlook on machine learning and spatial regression models

Insegnamenti propedeutici
No prerequisites, but basics in statistics are expected

Modalità di insegnamento
Lectures and exercises will take place in presence, lectures and exercises will be available online via Teams

Obiettivi formativi
ILO (Intended Learning Outcomes) ILO 1 Knowledge and understanding ILO 1.1 Estimate and interpret econometric models for the empirical analysis of the above problems; ILO 1.2 the ability to model social and economic phenomena; ILO 1.3 the ability to economically interpret the results of the various mathematical-statistical models used in economics; ILO 1.4 basic knowledge of data management and computer programming for the statistical and econometric analysis of socio-economic data; ILO 1.5 Knowledge of the specialised vocabulary of the topics in this field of study. ILO 2 Ability to apply knowledge and understanding ILO 2.1 the ability to communicate fluently and spontaneously with native speakers on economic topics; ILO 2.2 the ability to independently analyse data and explain empirical relationships between real-world phenomena; ILO 2.3 the ability to create and test simple statistical and econometric models; ILO 2.4 the ability to apply quantitative methods to solve economic problems; ILO 2.5 the ability to read, write and communicate in relation to the technical language of quantitative methods in the three official languages of instruction ILO 3 Making judgements ILO 3.1 Acquire the necessary judgement and methodological tools to critically analyse data, sources, assumptions and implications of scientific practice and the political, ethical and legal contexts in which economic phenomena are situated and with which they interact. ILO 4 Communication skills ILO 4.1 Proficiency in written and spoken Italian, German and English, including the translation of these languages. Intercultural competence. Conceptual conciseness, ability to capture facts in writing, especially for scientific and science-based texts ILO 5 Learning skills ILO 5.1 Fostering critical thinking and analytical skills to recognise complex problems in their long-term dynamics and in the diversity of their - also ethical - implications

Modalità d'esame
A. Modality "participating" and "non-participating" students Assessment 1: Group work (voluntary; 20%): Both participating and non-participating students can take part in a data research project that accounts for 20% of the final grade. Students will work on a practical empirical project using real data and R statistical software. The task includes data management, writing R script files and interpreting the results using statistical and econometric methods. Project work is valid for one academic year and cannot be credited beyond that (ILOs: 1.1, 1.3, 1.4, 1.5, 2.2, 2.3, 2.4, 2.5, 3.1, 4.1 (German), 5.1). Assessment 2: Final written examination (30 % if participating in group work, otherwise 100 %): Students must solve theoretical, practical and computational questions related to a specific problem, demonstrating knowledge and understanding of the theories and methods covered (ILOs: 1.1, 1.3, 1.5, 2.2, 2.3, 2.4, 2.5, 3.1, 4.1 (German), 5.1). The examination modalities are the same for participating and non-participating students.

Criteri di valutazione
All students must achieve a passing grade based on the combined score from the written exam and the take-home research project. The following aspects are relevant to the examination: Correctness of answers, ability to interpret R outputs and a critical appraisal of regression results taking into account econometric and economic theories. The following aspects are relevant for the take-home research project: Correctness of answers, ability to successfully conduct an econometric project in R, interpretation of R outputs and a critical appraisal of results.