en
Ateneo
en
Ateneo

PhD – 40th cycle – Thematic fields – Econometrics

Econometrics

Doctoral School in Economics

Department of Economics and Social Sciences, Marche Polytechnic University

Course description: 

The Econometrics course will be organized in 3 blocks. The first block (21 hours) will present the econometric theory of maximum likelihood and generalized method of moments estimation, linear regression models, and instrumental variable estimation. In the second block (21 hours), students will study linear panel data and limited dependent variable models. The third block (21 hours) will present models for time series data. Further 25 hours of computer tutorials will be aimed at developing analytical skills using Gretl (http://gretl.sourceforge.net) .

Learning outcomes:

  • Development of analytical skills so that students can evaluate critically the econometric outputs in the economic literature and correctly interpret them.
  • Development of analytical and technical skills so that students can design proper econometric model to answer their research questions.
  • Development of computer programming skills so that students can estimate sophisticated and state-of-art econometric models.

Prerequisites: 

Students should have knowledge, at least at undergraduate level, of the following topics:

  • Scope of Econometrics, the structure of economic data.
  • Causality and the notion of ceteris paribus in econometrics.
  • Definition of the simple linear regression model and its interpretation.
  • Ordinary Least Squares (OLS) estimates and OLS properties.
  • Interpretation of OLS estimates.
  • Multiple regression analysis: many independent variables in the linear regression model.
  • OLS estimates and their interpretation with multiple regressors.
  • Inference in multiple regression analysis.
  • The Gauss-Markov theorem.
  • Testing hypothesis about a single parameter.
  • Testing hypothesis about multiple linear restrictions.
  • OLS asymptotic.
  • Goodness-of-fit measures.
  • Linear models (in the parameters) with quadratics and/or logarithms of the regressors.
  • Linear models with interaction terms.
  • Linear models with qualitative independent variables.
  • Heteroskedasticity: testing and robust inference.
  • Misspecification: functional form misspecification, omitted variables, measurement error.

These topics are in chapters 1 to 9 and 15 of “Introductory Econometrics: A Modern Approach” (Wooldridge, 7th edition, 2015). Alternatively, they can be found in chapters 1-9 and 12 of “Introduction to Econometrics” (Stock and Watson, 3rd edition, 2015). These textbooks are for undergraduate economics students who have taken a course of introductory probability and statistics.

Syllabus:

Block 1:

  • Asymptotic theory
  • Maximum likelihood: Estimation
  • Maximum likelihood: Testing
  • Generalized method of moments
  • Linear regression model
  • Robust inference
  • Instrumental variable estimation

Block 2:

  • Linear panel data models: fixed and random effects models
  • Introduction to dynamic panel data models
  • Binary response models.
  • Heteroskedasticity and endogenous regressors in nonlinear models.
  • Ordered, multinomial, and count data models
  • Tobit model
  • Sample selection issues.

Block 3:

  • Dynamic models
  • Time series and stochastic processes.
  • ARMA models.
  • Nonstationary processes and unit roots tests.
  • VAR models.

Exam:

An open-book written exam will be held in January. The test will consist of three exercises, one per block In case of resit, the resit will be an open-book written exams on all the blocks.

Lecturers:

  • Lecturer of 1st block: Claudia Pigini
  • Lecturer of 2nd block: Matteo Picchio and Claudia Pigini
  • Lecturer of 3rd block: Giulio Palomba
  • Instructors of computer tutorials: Alessandro Pionati, Marco Tedeschi, and Francesco Valentini

Reading list:

  • Hansen B.E. Probability and statistics for economists 2022 Princeton University Press –
  • Hansen B.E. Econometrics 2022 Princeton University Press
  • Wooldridge J.M.  Econometric Analysis of Cross Sections and Panel Data 2010 MIT Press.
  • Cochrane J.H., Time Series for Macroeconomics and Finance 2005 http://econ.lse.ac.uk/staff/wdenhaan/teach/cochrane.pdf .
  • Lütkepohl H. and Krätzig Applied Time Series Econometrics 2004 CUP.

A detailed list of selected chapters from these textbooks will be provided during the course.

Software for computer tutorials: