"G. d'Annunzio"
statistics
The main objective of the course is to obtain a basic understanding of the statistical models. The aim is to motivate the students to examine causal relationships between economic phenomena by using a linear regression model. The course focuses on least squares estimation of the model and related statistical inferences. The assumptions of least squares estimation will be critically investigated. We examine the violations of these assumptions and the possible ways to alleviate the assumptions. The emphasis of the course is in the empirical application of the least squares method and its extensions. The economic interpretation of the estimated parameters of regression model and their statistical significance is given a special focus. After the course, students should have the skills to conduct basic empirical econometric analysis.
1) Random variables and sampling theory 2) Simple Regression Analysis 3) Multiple Regression Analysis 4) Nonlinear Models and Transformations of Variables 5) Dummy Variables 6) Specification of Regression Variables 7) Heteroskedasticity 8) Stochastic Regressors and Measurement Errors 9) Simultaneous Equations Estimation 10) Modelli logit 11) Introduction to Panel Data Models
Dougherty C., Introduction to Econometrics (3rd Edition), 2016. Johnston J, Econometrica, Franco Angeli, 3ª Edizione, 2001. Stock, J.H. M.W. Watson: Intoduzione all'Econometria, ed. it a cura di F. Peracchi, Pearson, Milano, 2005
Lessons are held in Italian with theoretical explications of the program topics accompanied by practical examples of business interest (also in the form of group exercises or testimonials of experts). For some contents is provided teaching of computer-based calculation (using a spreadsheet and briefly introducing STATA software).
The exam is written and verifies the learning of theories and problem-solving abilities on topics under program. The test is divided into two parts/exercises (one oriented to the theoretical conceptualization while the other to statistical data processing (exercises with commentary on the results). Note: The student has the right to support three trials from the semester in which the teaching is delivered (in this case from May to February included). Non programmable calculators are allowed.
The teacher receives the students Thursday 14-16
