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BAEcon Economics and Finance / Course details
Year of entry: 2021
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Course unit details:
|Unit level||Level 3|
|Teaching period(s)||Semester 2|
|Available as a free choice unit?||Yes|
This course unit makes use of the basic econometric tools learned in Econ20110 Econometrics and applies them to modern microeconometric issues. Microeconometrics is the application of regression techniques to estimating causal effects using cross-section or panel data sampled from microeconomic agents. The course will be of interest to those studying microeconomics or related areas (e.g. labour economics, public economics, and development economics) and will be useful to students who wish to pursue more advanced applied economics courses later in their career.
|Unit title||Unit code||Requirement type||Description|
The aim of this course to further develop students’ knowledge of modern microeconometric techniques, and so develop the tools required to analyse datasets covering relating to microeconomic units (individuals, households or firms) observed at a single point in time or over time multiple time periods. It focuses on causes of bias/inconsistency, and therefore non-causality, namely endogeneity. These causes are omitted variables, measurement error, simultaneity and self-selection.
After completing this unit, students will:
(i) be able to demonstrate a clear understanding of how the regression model is used when analysing cross-section data;
(ii) know how to use, and interpret the output from the econometric package Stata;
(iii) understand what is meant by a causal effect;
(iv) appreciate the various difficulties in estimating causal effects, and understand the way in which econometric methods, in combination with economic models, can address these difficulties when using cross-sectional and panel data.
Course content includes:
Types of data (panel versus pooled cross-sections); revision of the multiple regression model (focusing on dummy regressors); endogeneity (omitted variables bias and raw and conditional differentials; measurement error; and simultaneity); heteroscedasticity and robust inference; the first difference estimator; policy analysis and the difference-in-difference estimator; the simple instrumental variables estimator; regression discontinuity.
Teaching and learning methods
Lectures and tutorial classes.
- Analytical skills
- Synthesis and analysis of data and critical reflection and evaluation.
- Computer literacy and the application of theoretical knowledge.
20% Mid-term test
- Tutorial feedback.
- Office hours.
- Modl answers
The main reading is:
• Wooldridge Introductory Econometrics, seventh edition (chapters 1-7, 13, 15).
• Angrist and Pischke Mastering ‘Metrics
An alternative to Wooldridge is
• Stock, J.H. and Watson, M.M. Introduction to Econometrics, Pearson, third edition (chapters 10-11-12).
PDF files of the slides should be available for download from the course BB site before each lecture.
|Independent study hours|
|Martyn Andrews||Unit coordinator|
For every 10 course unit credits we expect students to work for around 100 hours. This time generally includes any contact times (online or face to face, recorded and live), but also independent study, work for coursework, and group work. This amount is only a guidance and individual study time will vary.