COORDINATOR: Miguel A. Delgado
This course offers
an introduction to data analysis in Social Sciences with the assistance
of the multiple regression model. The emphasis is on the interpretation
of the model and the application of statistical inference techniques to
solve relevant practical problems. The course discusses in detail how
to make inferences under non-standard situations, relevant in Social
Sciences, due to the nature of the variables in the model (qualitative,
transformed to allow nonlinear relations or non-observable,) or to the
nature of data. The rigorous formal justification of the applied
statistical inference techniques is out of the scope of this course.
The background in Probability, Statistics, Algebra and Calculus offered
in Mathematics I & II and Statistics I & II is more than enough
for this course.
At the end of the course, the student will acquire a good working knowledge on the interpretation of the linear regression model, discriminating between alternative specifications by means of statistical inference, and using GRETL for estimation and hypothesis testing.
knowledge of linear algebra, calculus and statistical theory is
required, which is provided by Mathematics for Economics I & II and
1. The nature of econometrics and economic data (SW. Ch. 1)
2. The simple regression model (SW. Ch. 4,5).
3. Multiple regression analysis: estimation (SW Ch. 6)
4. Multiple regression analysis: inference (SW. Ch. 7)
5. Nonlinear regression using linerar multiple resgression (SW. Ch. 8).
6. Regression with binary dependent variable( SW. Cp. 11).
7. Instrumental variables estimation and two stages least squares (SW. Cp. 12).
The continuous evaluation consists of 2 exams during the course,
whose grade will depend also on the homeworks handed in according to
the instructor criteria. The continuous evaluation will only count if
the grade in the final exam is bigger or equal than 4.5 (45%).
TEXTBOOK AND ONLINE RESOURCES:
Stock, J.H. y Watson, M.M., Introduction to Econometrics, 3rd Edition, Addison Wesley, 2012.
© 2017 UC3M - Departamento de Economía