COMMUNICATIONS:
[In progress]
Course Starting Date: 30/09/2020 - Online Lectures will be compelled via Zoom. Please be connected for the starting time of each lecture.
Course Hours: 72
Office Hours: During the Course, Tuesday: 10.00-14.00, conditional to an appointment (emilio.zanettichini@uniroma1.it) due to the COVID restrictions. No office hours is allowed during the exam week(s).
EXAM DATES: See Infostud.
Propedeutic Exams: see https://web.uniroma1.it/fac_economia/propedeuticita
EXAM RULES: The evaluation consists in a written take-home hand-out about the argument explained in the lectures.
The evaluation is based on the effectiveness of the knowledge of the econometric methodology (and its "mechanincs") aquired by the candidate, quality of the exposition of the results and their effectiveness.
The Teacher will check the degree of knowledge acquired by the student via oral examination. No ad-personam call is allowed.
COURSE DESCRIPTION: The course is compelled via frontal lectures where Theacher will explain the arguments at the blackboard. Some slides could be eventually projected.
TEXTBOOK and SYLLABUS (subject to change during the Course completion):
TEXTBOOK: Stock, J. and M. Watson (SW). The criteria for this choice are: 1) clarity in exposition: all the main mathematical formulas in the main text are developed step-by-step; 2) flexibility of the arguments treated: the Course Syllabus is a selection of the 16 Chapters constituting the Textbook; 3) Impactfulness of the topic treated: the empirical examples used in the manual as well the presence of chapters dedicated to the treatment of large data makes this manual a pillars for any applied scientist.
ALTERNATIVE TEXTBOOK:
R. Carter Hil , William E. Griffith , Guay C. Lim, PRINCIPLES OF ECONOMETRICS, 5th ed, Wiley, 2018.
DETAILED LIST OF CHAPTER(s) COVERED BY COURSE:
PART I: INTRODUCTION AND REVIEW
1. Economic Questions and Data
2. Review of Probability
3. Review of Statistics
PART II: FUNDAMENTALS OF REGRESSION ANALYSIS
4. Linear Regression with One Regressor
5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
6. Linear Regression with Multiple Regressors
7. Hypothesis Tests and Confidence Intervals in Multiple Regression
8. Nonlinear Regression Functions
9. Assessing Studies Based on Multiple Regression
PART III: FURTHER TOPICS IN REGRESSION ANALYSIS
10. Regression with Panel Data
11. Regression with a Binary Dependent Variable
12. Instrumental Variables Regression
13. Experiments and Quasi-Experiments
14. Prediction with Many Regressors and Big Data
PART IV: APPLICATIONS IN HEALTH ECONOMICS
This part of the Course will be compelled by Prof. Di Novi (University of Pavia).
APPENDICES: Any appendix at the end of each chapters in the previous list is fundamental.
ADDITIONAL READINGS
Colonescu, C. "Principles of Econometrics with R", 2016 - available online at: https://bookdown.org/ccolonescu/RPoE4/
This book gives the basis of the usage of R software for the practice of many parts of the arguments in the Syllabus.