Syllabus
Ural State University
Dr. Natalia Shestakova
Applied Econometrics for Microeconomics
Description
The goal of this course is to equip students with advanced understanding of the standard econometric methods, as well as with estimation skills and experience with empirical analysis. The
main focus is on the problem of endogeneity. Circumstances under which endogeneity arises,
tests that allow detecting endogeneity, consequences of endogeneity and various solutions to
the problem are broadly discussed throughout the course. Advanced methods available for the
panel data are introduced to students. In addition, the course improves their understanding of
identification strategies for various empirical problems. Exercise sessions that supplement lecture material acquaint students with STATA. The course is intended for 2nd year MA students.
It is built on the knowledge acquired in previous econometrics courses.
Requirements
Empirical Project: 40 points [20 points class presentation + 20 points written essay]
Home Assignment: 20 points
Final Exam: 40 points
Grading
85 - 100 points = pass (excellent)
70 - 85 points = pass (good)
60 - 70 points = pass (satisfactory)
< 60 points = fail
Schedule
Dec 19: Lecture 1 (4:10-5:40pm, 219), Exercise 1-2 (5:50-7:20, 7:30-9pm, lab)
Dec 21: Exercise 3 (5:50-7:20pm, lab), Lecture 2 (7:30-9pm, 232)
Dec 24: Lecture 3-5 (2:30-4, 4:10-5:40, 5:50-7:20pm, 232)
Dec 26: Lecture 6 (4:10-5:40pm, 219), Exercise 4-5 (5:50-7:20, 7:30-9pm, lab)
Dec 27: Lecture 7-9 (4:10-5:40, 5:50-7:20, 7:30-9pm, 413)
Dec 28: Exercise 6 (5:50-7:20pm, lab), Lecture 10 (7:30-9pm, 232)
Jan 9: Exercise 7-8 (5:50-7:20, 7:30-9pm, lab)
Textbooks
Introductory Econometrics: A Modern Approach, J. M. Wooldridge, 2006. [IW]
Econometric Analysis of Cross Section and Panel Data, J. M. Wooldridge, 2002. [W]
Microeconometrics: Methods and Applications, C. A. Cameron and P. K. Trivedi, 2005.
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Syllabus
Ural State University
Dr. Natalia Shestakova
Course Outline
Lectures
Introduction (Lecture 1, [IW] Ch.1, 2.1-2.3, 3)
• OLS Estimation and Its Properties
• Deviations from the Basic Linear Regression Model
Data Analysis Without Regressions (Lecture 2)
• Individual Variables
• Differences Between Groups
• Relationships Among Variables
Endogeneity Problem (Lectures 3-5)
• Potential Reasons for Endogeneity ([IW] Ch.3, 9, 15-16, [W] Ch.9):
– Functional form misspecification, Omitted variables, Measurement errors in variables, Simultaneity (SEM)
• Solutions to Endogeneity Problem ([IW] Ch.9, 15-16, [W] Ch.5):
– Proxy as a solution to omitted variable bias, Instrumental Variables estimation,
2SLS, Identifying and estimating a structural equation in SEM
• Testing for Endogeneity
• Basic idea behind Hausman test ([W] Ch.6.2)
Introduction to Panel Data Methods (Lecture 6)
• Advantages of having panel data ([IW] Ch.13)
• Additional problems arising with panel data ([IW] Ch.17.5):
– Selectivity bias, Heterogeneity bias
Panel Data Methods (Lectures 7-8)
• Modeling individual heterogeneity ([IW] Ch.13-14, [W] Ch.10)
• Hausman test with panel data ([W] Ch.10.7)
• Dealing with sample selection ([W] Ch. 17)
Limited Dependent Variables (Lecture 9 [IW] Ch.17)
• Linear Probability Model
• Probit, Logit and Tobit Models
Collecting and Using Experimental Data in Economics (Lecture 10)
• Natural Experiments in Economics
• Field and Lab Experiments
• Hypothesis Testing with Experimental Data
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Syllabus
Ural State University
Dr. Natalia Shestakova
Computer Exercises
Working in Stata (Exercise 1-2)
• Interface of the main windows and do-files
• Summarizing data: statistics and graphs
• Statistical tests
Regression Analysis of Artificially Created Datasets (Exercise 3)
• Generating variables with specific distribution
• Estimating linear model with OLS
• Loops and distribution of estimated coefficients
• Dealing with possible violations of Gauss-Markov assumptions
IV and 2SLS estimation in Stata (Exercise 4-5)
• Manual estimation vs. STATA routines
• Illustrating the problem of weak instruments
• Hausman test
Panel Data Methods (Exercise 6)
• Organizing panel data
• Pooled OLS, FD, FE and RE estimation
Group Presentations of Empirical Projects (Exercise 7)
Writing an Academic Article (Exercise 8)
• Why to write an academic article
• Presenting an academic article
• Introduction to LATEX
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