Econometrics

Module Code: EC3090

Module Title: Econometrics

• ECTS Weighting: 10
• Semester/Term Taught: Michaelmas + Hilary Term
• Contact Hours: 44 hours of lectures, 5 hours of tutorials and 15 hours of computer workshops
• Module Personnel: Lecturer - Professor Gaia Narciso/ Lecturer - Professor Agustín Bénétrix

Learning Outcomes

On successful completion of this module, you will be able to:

• Confidently discuss core underlying statistical principals;
• Derive estimators for linear regression and show their properties;
• Derive appropriate tests for the underlying assumptions of the general linear model and demonstrate how to correct for violations of these assumptions;
• Confidently discuss the problem of identification;
• Construct, estimate and test econometric models with limited variables;
• Estimate and test models using instrumental variables and two stage least squares;
• Identify and estimate two and three equation simultaneous equation models;
• Perform basic time series analysis;
• Perform basic econometric analysis for panel data;
• Use the techniques developed to test simple economic models;
• Use STATA to estimate econometric models;
• Present a research topic and research plan to their peers and write an empirical paper on an applied research topic.

Module Learning Aims

This module provides an introduction to the theory and methods of modern econometrics. It begins by reviewing and extending the statistical material covered in the senior freshman year. Following this students are guided through the fundamental principals of econometrics and working through to more advanced topics as the module progresses. The module provides a balance between core theoretical material and an extensive applied component which aims to develop student's practical skills necessary to conduct independent applied research.

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Module Content

Topics discussed during Michaelmas Term include:

• Statistical Review: Populations, parameters and random sampling; finite-sample properties of estimators, introduction to asymptotic theory; methods of estimation (method of moments, maximum likelihood, least squares, interval estimation); hypothesis testing.
• The Simple Regression Model: Ordinary Least Squares (OLS) estimation; properties of OLS; Goodness of Fit; Functional Form.
• Multiple Regression Analysis: Estimation and interpretation; model specification (determining which variables to include and which functional form to use); the multicollinearity problem.
• Inference: hypothesis testing in the context of multiple regression analysis using t-tests and F-tests.
• Misspecification of Disturbance Terms: Heteroscedasticity and Autocorrelation.

Topics discussed during Hilary Term include:

• Identification: problem of identification; incomplete (missing) data; treatment response.
• Limited variable models: (i) binary (dummy) explanatory (independent) variables; (ii) limited dependent variable models: binary dependent variable models including the linear probability, logit & probit models; tobit (corner solution) model; Poisson (count) model; censored and truncated models; (iii) policy analysis and sample selection corrections.
• Instrumental Variables (IV) & Two Stage Least Squares (2SLS): motivation; IV estimation; 2SLS; testing; 2SLS with heteroscedasticity.
• Simultaneous Equation Models (SEM): nature of SEM; simultaneity bias in OLS; identification and estimation in two and three equation SEM.
• Introduction to Time Series Analysis: stationarity/non-stationarity; unit roots and cointegration; VAR models.
• Introduction to Panel Data Analysis: Pooling cross sections over time; Fixed and Random effects estimation.

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Recommended Reading List

Primary Texts:

• J.M. Wooldridge, Introductory Econometrics: A Modern Approach, 4/e, South-Western, 2009
• D. Gujarati and D. Porter, Basic Econometrics, 5/e, McGraw-Hill, 2009
• Enders Walter, Applied Econometric Time Series, 3/e, Wiley, 2010

Secondary Texts:

• Gujarati, Econometrics by Example, Palgrave MacMillan, 2011

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Module Pre Requisite

EC2040

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Assessment Details

• Michaelmas/Hilary Term: 8 Homework Assignments due over both terms accounting for 20% of the overall grade.
• Each student will present on the topic of their project in week 1 of Hilary Term which is worth 5% of the overall grade.
• A project is due in Week 12 of Hilary Term which is worth 15% of the overall grade.
• The annual exam is worth 60% of the overall grade.

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Module Website

Blackboard
http://agustinbenetrix.org/

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