 Checking date: 02/12/2021

Course: 2022/2023

Econometrics II
(12273)
Study: Master in Economics (295)
EPC

Coordinating teacher: ESCRIBANO SAEZ, ALVARO

Department assigned to the subject: Department of Economics

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:

Requirements (Subjects that are assumed to be known)
Notions and methods acquired in Statistics and Econometrics I.
Objectives
Skills and learning outcomes
Description of contents: programme
This course gives an overview of the basic concepts in time series econometrics, with a particular emphasis on the tools needed to undertake empirical analysis. The final objective is to be able to analyze the evolution of the economic variables (inflation, Gross Domestic Product, Money, interest rate¿), to understand the dynamic relationship between those variables, and to predict them. In macroeconomics context, this is very useful for policy makers; since it helps them take their decision based on better knowledge of how many macroeconomic variables affect each other at different horizons. We will focus on the following topics: (1) Characteristics of economic time series data: Stochastic processes and time series, stationarity and ergodicity, simple autocorrelation function (ACF) and Partial autocorrelation function (PACF). [Brockwell P.J. and Davis Chapter I + Lecture notes]. (2) Univariate stationary models: Wold decomposition, ARMA processes, Causal models, invertible models, estimation and inference on the mean and the ACF, estimation and inference on the parameter estimates of ARMA models, white noise tests, model selection (information criteria), methodologies for the design of ARMA models, real data examples (interest rates, growth rate of GDP, temperature, etc.) [B&D chapters II, III & V + Lecture notes]. (3) Forecasting: Forecasts computing, forecast evaluation ¿ [B&D chapters II, III & V + Lecture notes]. (4) Regression with autocorrelation: Consequences of the presence of autocorrelated errors, robust inference through HAC standard errors, endogeneity problems (lagged dependent variable), instrumental Variables solution (Two Step Least Squares). [Wooldridge Chapter 12 & 15]. (5) GARCH models: Motivation, ARCH, GARCH, Estimation, Predictions, extensions of GARCH models. [Hamilton Chapter 21+ Lecture notes]. (6) Multivariate Autoregressive Models (VAR): VAR models, structural form, reduced form, identifiability conditions, Granger-Causality analysis, Impulse response function (IRF). [Enders (2004) + Lecture notes]. (7) Non-stationary processes: Non-stationary processes about a trend (vs. integrated processes, unit root Dickey-Fuller test, forecasting with non-stationary models, structural changes, permanent and transitory shocks. [Stock and Watson Chapter 14, Wooldridge Chapter 18 + Lecture notes]. (8) Cointegration: Spurious regressions, Cointegration, Error-Correction models¿ [Stock and Watson Chapter 14, Wooldridge Chapter 18 + Lecture notes].
Learning activities and methodology
The teaching method will be the following: (1) Magistral classes, where the concepts will be developed in detail and the properties of macroeconomics models of time series will be covered. To facilitate understanding and learning of this material by the student, the students will have access to the class material (slides etc.) via the internet. They will also receive an ample list of complementary materials that will permit them to understand and go deeper into issues covered in class, and into some related issues of interest that may not have been covered in class. (2) Discussion of the exercises done by the student, covering the estimation and specification of classic models in the literature, previously covered in class, such as the various exercises of estimation and forecasting with time series in various economies and different time periods. (3) Comments on current economic issues to which the student can use the knowledge acquired in the course to deepen their understanding. (4) Practical classes in reduced groups where the students will learn to make arguments and reason in public, to use the necessary econometric programs (above all E-Views) to do estimation and testing of macroeconomic models of time-series. This will be done by the use of both algebraic and empirical exercises in class, with an emphasis on the applied nature of this course. (5) Complete an empirical project by the end of the course that demonstrates that the student understands how to apply with rigor and economic reasoning the econometric techniques studied. The project should be well written and have the basic structure of a short scientific article: Introduction, literature review, model and estimation, description of the data used and their quality, empirical results, evaluation of the model and hypothesis tests, conclusions & future extensions. Every student should give a formal oral presentation (in Power Point) of their empirical project in front of all students of the class and the professor. In order to emphasize application of theory to real data, students have to do several empirical projects which involve the use of the online database (accessible via the website of the library of the University of Carlos III de Madrid) and the statistical package EViews. During the classes, students will have the opportunity to learn how to use the online database and the statistical package EViews. Several theoretical problem sets (exercises) will be solved during the course. Students will also have homeworks (exercises) to solve. The homeworks and empirical projects will be evaluated.
Assessment System
• % end-of-term-examination 0
• % of continuous assessment (assigments, laboratory, practicals...) 10
Calendar of Continuous assessment
Basic Bibliography
• Brockwell P.J. and Davis R.A.. Introduction to Time Series and Forecasting. 2nd ed., Springer.. 2002
• Enders W.. Applied Econometric Time Series. 4 ed., Wiley. 2015
• Hamilton, J. Time Series Analysis. Princeton University Press. 1994
• Mills T.C.. The Econometric Modelling of Financial Time Series. 2nd ed., Cambridge University Press. 1999
• Stock, J. and Watson, M.. Introduction to Econometrics. Addison-Wesley. 2003
• Wooldridge, J.M. Introductory Econometrics: A Modern Approach. 2nd ed., Thomson South-Western. 2003