### Econometrics & Times Series Analysis

**Prerequisites**: Functions of one and several variables, Linear and Matrix Algebra, Statistics, Undergraduate Econometrics.

This course emphasizes the theoretical aspects of statistical analysis, focusing on techniques for estimating econometric models. The goal is to help students develop a solid theoretical background in econometrics, the ability to implement the techniques, and to analyse empirical studies in economics. The analytical context of the course is as follows:

*Simple Linear Regression Model*: Deriving OLS estimator, Properties of OLS, Functional forms, Gauss-Markov Assumptions, Statistical properties of OLS, Hypothesis testing with OLS;

*Multiple Regression Analysis*: Interpretations of OLS estimates, Gauss-Markov Theorem, Specification issues, Testing a single parameter, Testing multiple linear restrictions;

*Multiple Regression Analysis with Dummy Variables*: Binary variables, Multiple categories, Interactions among dummy variables, Linear probability model;

*Heteroskedasticity*: Testing for heteroskedasticity, Correcting for heteroskedasticity;

*Asymptotic theory*: Consistency, OLS asymptotics;

*Time Series Analysis*: Unit Roots, Stationarity, Cointegration, Causailty, AR processes, MA processes, ARMA, ARIMA, Model selection, VAR, GVAR.