Econometrics (2235.YR.013014.1)

General information

Type:	OPT	Curs:	3	Period:	S semester
ECTS Credits:	7 ECTS

Teaching Staff:

Group	Teacher	Department	Language
Year 3	Vladimir Manaev	Economía, Finanzas y Contabilidad	ENG

Statistics

Mathematics

Basic descriptive statistics (univariate, bivariate, multivariate)

Laws of probability

Random variables

Initiation to hypothesis testing

Solid understanding of basic econometrics and statistical modelling is a necessary skill to undertake any relevant analysis of the economic activity at any level. We will learn to develop models empirically to effectively analyse data in the real world, a very common practice in almost any economics profession.

The objective of the course is to understand how to use linear regression analysis properly, as a major tool ubiquitous in economic analysis. The course has three specific goals. First, introduce the basic econometric methodology in the context of the classical linear regression, particularly OLS estimation and inference. Secondly, help future practitioners become more sophisticated consumers of empirical work done by others, evaluate whether analyses are done in a proper manner, and develop their own scientific critical thinking. And third, to start to develop the student's capacity in statistical programming, which is a skill in increasing demand in social science professions.

1. Basics in Probability and Random variables Review of concepts already seen that are necessary to develop later topics

2. Hypothesis testing Mostly review of inference for single parameter models, such as the mean for continuous and binary variables, as well as count data.

3. Simple linear model Construction and derivation of the linear regression model with one variable.

4. Multiple linear model Extension of linear regression to any larger number of variables.

5. Inference in the linear model We evaluate the quality and validity of the fitted model, and study the uncertainty around the point estimates of our regression.

6. Violations of regression assumptions Study of why the assumptions of the linear model are relevant, what occurs in the event they do not hold, and how that can be addressed.

7. Qualitative data and model transformations Introduction of binary, categorical and non-linear transformations to the linear model.

8. Instrumental variables Introduction to "causal" inference: proper estimation of a linear model with relevant missing variables.

9. Logistic regression Introduction to generalised linear models: binary outcomes.

10. Further topics in econometrics - Differences in differences - Introduction to Bayesian modelling

Combination of
- Lecture notes (slides plus blackboard)
- Applied theoretical and practical exercises (short problem sets)
- Statistical programming (introduction to Stata)
- Short tests in selected topics to consolidate key knowledge
- Applied creative project

Introduction to Econometrics, Fourth Edition, Pearson, James H. Stock, Mark W. Watson

Introductory Econometrics. A Modern Approach, Fifth Edition, Cengage, Jeffrey M. Wooldridge

Group	Teacher	Department
Year 3	Vladimir Manaev	Economía, Finanzas y Contabilidad