Course Topics
Part 1: Introduction to Applied Research: Data collection, data processing, descriptive analysis, survey design Part 2: Casual Analysis Experimental methods, difference-in-differences, regression discontinuity, instrumental variables, fixed effects models, recent advanced in causal analysis Part 3: Likelihood Methods Likelihood function for i.i.d. data. Estimation by max Likelihood (MLE).Numerical methods for maximizing the likelihood. The EM algorithm.The Cramér Rao lower bound and the Fisher information matrix. Properties of the MLEs. Likelihood ratio tests Part 4: Time Series Analysis Review of different estimation methods (OLS, NLS, ML, GMM, Bayesian). Time-Series Analysis models and methods for predicting future variables: specification, inference and forecasting. (Monte Carlo) Simulation Methods.

Teaching format
The course will combine in-class explanation of the background material, problem-solving and case discussions. Students will be expected to participate actively in class work, which will give them the opportunity to apply theoretical concepts to realistic situations. In order to benefit from this approach, it is important that all students come to class fully prepared.

Educational objectives
PhD programme: The courses aim to train researchers with strong quantitative and theoretical skills, capable of analyzing economic and financial phenomena. Candidates’ dissertations are expected to adhere to the highest standards of scientific rigor and to demonstrate innovative features that make them suitable for publication in leading international peer-reviewed journals. The programme therefore seeks to contribute to the international scientific debate in economics and finance. To this end, candidates will be encouraged to employ state-of-the-art methodologies and to adopt a multidisciplinary approach. The advanced training provided by the programme, together with the research methods required to complete the dissertation, prepares candidates both for an academic career and for high-level professional positions involving policy analysis and policymaking.

Additional educational objectives and learning outcomes
The ability to apply theoretical and empirical models. The ability to interpret the results of econometric and statistical analyses and draw appropriate conclusions. The ability to plan and manage academic research efficiently and independently.

Assessment
Short written assignments and Solution of case studies: Written assignments and case studies will be assigned during the course to be completed and sometimes presented in class.

Evaluation criteria
Standard criteria for evaluating assignments, completeness, correctness.

Required readings

References will be provided by the professors during the course

Further information
10 hours Prof. Francesco Ravazzolo, 12 hours Prof. Steven Stillman, 8 hours Prof. Emanuele Taufer