UPF GPEM
Department of Economics Fall Semester 2003
ELEMENTS OF ECONOMETRICS
Professor José G. Montalvo, Jaume I 20.218
Office hours: Mondays, 15:00-16:00 or by appointment.
Pone: 93 542 2509
Email: [email protected]
Course Description
Elements of econometrics is a graduate course in applied econometrics with a focus on the basic techniques developed using economic examples and real data sets. The objective of the course is to familiarize students with the basic reasoning in econometrics. The classes cover the usual topics of an econometrics course (multiple regression, asymptotic theory, generalized least squares estimation, instrumental variables and panel data) but with emphasis in applications, interpretation and practical issues. It also includes a discussion of recent techniques (program evaluation and pseudo experiments) as well as an introduction to basic time series techniques. The course also deals with the basic formal econometric results. Students seeking a treatment of econometric theory with a higher level of mathematical content should take Econometrics I.
Grading
Grades will be based on the problem sets (20% with the lowest grade on the problem sets dropped) a midterm exam (30%) and a final exam (50%).
Readings and Reference Material
References to more specific material will be given during lectures.
Stock and Watson (2003), Introduction to Econometrics, Addison-Wesley. Useful to review basic problems and some recent topics.
Greene, W. H. (2002), Econometric Analysis, Maxwell MacMillan International Editions. Useful to review the formal proofs developed during lectures.
Johnston, J. and J. Dinardo (1997), Econometric Methods, McGraw-Hill. Useful for technical results.
PROVISIONAL CLASS SCHEDULE Class Date Topic
1 29-09 Introduction. Methodological issues 2 30-09 Bivariate regression I
3 06-10 Bivariate regression II 4 07-10 Multiple regression I 5 13-10 Multiple regression II 6 14-10 Multiple regression III 7 20-10 Asymptotic theory I 8 21-10 Asymptotic theory II
9 27-10 Maximum likelihood: theory 10 28-10 Maximum likelihood: applications
11 03-11 Midterm exam
12 04-11 Instrumental variables estimation I 13 10-11 Instrumental variables estimation II 14 11-11 Program evaluation I
15 17-11 Program evaluation II
16 18-11 Panel data
17 24-11 Time series I
18 25-11 Time series II 19 01-12 Time series III
20 02-12 Summary of the basic results
