Unit BUSINESS AND ECONOMIC STATISTICS
- Course
- Finance and quantitative methods for economics
- Study-unit Code
- A000206
- Location
- PERUGIA
- Curriculum
- Finanza ed assicurazione
- Teacher
- David Aristei
- Teachers
-
- David Aristei
- Hours
- 42 ore - David Aristei
- CFU
- 6
- Course Regulation
- Coorte 2021
- Offered
- 2022/23
- Learning activities
- Caratterizzante
- Area
- Matematico, statistico, informatico
- Academic discipline
- SECS-S/03
- Type of study-unit
- Opzionale (Optional)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- English
- Contents
- The course is organized in four main parts:
1) Models with binary dependent variables
2) Multi-response models
3) Limited dependent variable models
4) Linear regression models for longitudinal data - Reference texts
- Main textbook:
Verbeek, M., A guide to Modern Econometrics, Fourth Edition, Wiley, 2012.
Additional suggested textbooks:
- Greene, W., Econometric Analysis, 7th Ed., Prentice Hall, 2012.
- Wooldridge, J.M., Econometric Analysis of Cross Section and Panel Data, 2nd Ed. Mit Press, 2010.
- Cameron, A.C. e Trivedi, P.K., Microeconometrics: Methods and Applications, Cambridge Press, 2005.
Class slides and materials used during the laboratory sessions will be distributed through the UniStudium e-larning platoform - Educational objectives
- This course will introduce students to the most relevant methods of advanced econometric analysis and to their use in estimating economic relationships with cross-sectional and panel data.
Specific attention will be also devoted to on empirical applications. Every week there will be a computer laboratory session in which students will apply concepts learned during the theoretical lectures, using the econometric software STATA. - Prerequisites
- This course requires knowledge of inferential statistics and multiple regression analysis, which should be gained during the first year of the second cycle degree course.
- Teaching methods
- Face-to-face lessons completed with practical laboratory activities
- Other information
- Learning verification modality
- Oral examination
- Extended program
- 1) Models with binary dependent variables
The linear probability model.
Logit and probit models.
Specification issues: binary choice model with heteroscedasticity
Binary choice models with endogenous regressors
2) Multi-response models
Ordered Response Models: ordered logit and ordered probit models.
Multinomial models: the multinomial logit model.
3) Limited dependent variable models
Censored and truncated dependent variables.
Truncanted regression model
The Standard Tobit model
Extensions of the standard Tobit model: the Tobit II model
Sample selection bias
4) Linear regression models for longitudinal data
The static linear model.
The fixed- effect model.
The random-effects model.
Specification tests.