Guia docente 2022_23
Facultad de Ciencias Económicas y Empresariales
Grado en Economía
  Econometrics I
Topic Sub-topic
TOPIC 1: Empirical questions and the problem of causal inference - Types of empirical questions and examples.
- The problem of causal inference.
- Methods for estimating causal effects.
TOPIC 2: Linear regression model (I)

- Selection on observables.
- Linear regression model: specification.
- Ordinary Least Squares estimation.
- Interpretation of estimates: when do we identify a causal effect?
TOPIC 3: Linear regression model (II)

- Goodness of fit.
- The random component of the Ordinary Least Squares estimator.
- Assumptions of the regression model.
- Precision of the estimates.
- Properties of the Ordinary Least Squares estimator.
TOPIC 4: Linear regression model (III) - Obtaining additional information from the parameter estimates: changes of scale of the variables; elasticities; Beta coefficients.
- Non-linearities between the dependent variable and the explanatory variables of the model.
TOPIC 5: Inference in the linear regression model - Assumption of normality.
- Hypothesis testing on a single parameter.
- Confidence intervals.
- Contrasts of multiple restrictions on the parameters.
TOPIC 6: Dummy variables - A single independent dummy variable.
- Dummy variables for multiple categories
- Interactions involving dummy variables.
TOPIC 7: Specification and data problems in regression analysis - Consequences of misspecification of the functional form.
- Omission of relevant variables.
- Inclusion of irrelevant variables.
- Multicollinearity
TOPIC 8: Heteroscedasticity - Detection
- Consequences
- Solutions
TOPIC 9: Correlation of error terms across observations - Detection
- Consequences
- Solution
TOPIC 10: Endogeneity - Causes of endogeneity: omitted variable bias, measurement error in explanatory variables, bidirectional causality.
- Instrumental variables estimation.
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