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Selected Examples for:

Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, South-Western College Publishing, 2000, 2006, 2009


Data Sets used in these examples.

SHAZAM Command Files

Chapter 2   The Simple Regression Model
ceosal1.sha Examples 2.3, 2.6, 2.8, 2.11; Section 2.4 - CEO Salary
vote1.sha Examples 2.5, 2.9 - Election Results
Chapter 3   Multiple Regression Analysis: Estimation
gpa1.sha Examples 3.1, 3.4 - Determinants of College GPA
wage1.sha Example 3.2 - Hourly Wage Equation
401k.sha Example 3.3 - Participation in 401(k) Plans
crime1.sha Example 3.5 - Explaining Arrest Records
sleep75.sha Problem 3.3 - Tradeoff between sleeping and working
Chapter 4   Multiple Regression Analysis: Inference
wage1.sha Example 4.1 - Hourly Wage Equation
meap93.sha Examples 4.2, 4.10 - Schools and Teachers
gpa1.sha Example 4.3 - Determinants of College GPA
hprice2.sha Example 4.5 - Housing Prices and Air Pollution
401k.sha Example 4.6 - Participation in 401(k) Plans
jobtrain.sha Example 4.7 - Effect of Job Training Grants
mlb1.sha Section 4.5 - Major League Baseball Player's Salaries
bwght.sha Example 4.9 - Determinants of Birth Weight
attend.sha Question 4.5 - Calculating test statistics.
hprice1.sha Section 4.5 - Testing General Linear Restrictions
rental.sha Problem 4.4 - Determinants of housing rent
Chapter 5   Multiple Regression Analysis: OLS Asymptotics
bwght.sha Example 5.2 - Determinants of Birth Weight
crime1.sha Example 5.3 - Explaining Arrest Records
Chapter 6   Multiple Regression Analysis: Further Issues
bwght.sha Section 6.1 - Determinants of Birth Weight
hprice2.sha Examples 6.1, 6.2; Section 6.2 - Housing Prices and Air Pollution
wage1.sha Section 6.2 - Models with Quadratics
attend.sha Example 6.3 - Effects of Attendance on Exam Score
ceosal1.sha Example 6.4 - CEO Salary
gpa2.sha Examples 6.5, 6.6 - Prediction
ceosal2.sha Examples 6.7, 6.8 - Predicting CEO salaries
Chapter 7  Multiple Regression Analysis with Qualitative Information
wage1.sha Examples 7.1, 7.5, 7.6, 7.10 - Hourly Wage Equation
gpa1.sha Example 7.2 - Determinants of College GPA
jobtrain.sha Example 7.3; Section 7.6 - Effect of Job Training Grants
hprice1.sha Example 7.4 - Housing Price Regression
lawsch.sha Example 7.8 - Effects of Law School Rankings
mlb1.sha Example 7.11 - Major League Baseball Player's Salaries
gpa3.sha Section 7.4 - The Chow test
mroz.sha Section 7.5 - The Linear Probability Model
crime1.sha Example 7.12 - A Linear Probability Model of Arrests
sleep75.sha Problem 7.1 - Tradeoff between sleeping and working
Chapter 8  Heteroskedasticity
wage1.sha Example 8.1 - Heteroskedasticity Robust Standard Errors
gpa3s.sha Example 8.2 - Heteroskedasticity Robust F Statistic
crime1.sha Example 8.3 - Heteroskedasticity Robust LM Statistic
hprice1.sha Examples 8.4, 8.5 - Tests for Heteroskedasticity
saving.sha Example 8.6 - Weighted Least Squares
smoke.sha Example 8.7 - Feasible GLS
Chapter 9   More on Specification and Data Problems
crime1.sha Example 9.1 - Economic Model of Crime
hprice1.sha Example 9.2 - RESET specification error test
wage2.sha Example 9.3 - Returns to Education
rdchem.sha Examples 9.8, 9.9 - Outlying Observations
infmrt.sha Example 9.10 - State Infant Mortality Rates
Chapter 10   Basic Regression Analysis with Time Series Data
phillips.sha Example 10.1 - Static Phillips Curve
intdef.sha Example 10.2 - Effects of Inflation and Deficits
prminwge.sha Examples 10.3, 10.9 - Employment and Minimum Wage
fertil3.sha Examples 10.4, 10.8 - Fertility Equation
barium.sha Examples 10.5, 10.11 - Antidumping Filings
fair.sha Example 10.6 - Election Outcomes
hseinv.sha Example 10.7 - Housing Investment
Chapter 11  Further Issues in Using OLS with Time Series Data
nyse.sha Example 11.4 - Efficient Markets Hypothesis
phillips.sha Example 11.5 - Expectations Augmented Phillips Curve
fertil3.sha Example 11.6 - Fertility Equation
earns.sha Example 11.7 - Wages and Productivity
wageprc.sha Problem 11.5 - Distributed Lag Model
Chapter 12   Serial Correlation and Heteroskedasticity in Time Series
phillips.sha Section 12.2 - Testing for serial correlation
prminwge.sha Example 12.2 - More Testing for serial correlation
barium.sha Examples 12.3, 12.4 - Breusch-Godfrey test for AR(q) serial correlation and Cochrane-Orcutt Estimation
nyse.sha Examples 12.8, 12.9 - Heteroskedasticity and ARCH in Stock Returns
Chapter 13  Pooling Cross Sections Across Time
fertil1.sha Example 13.1 - Women's Fertility over Time
reteduc.sha Example 13.2 - Returns to Education
kielmc.sha Example 13.3 - Housing Prices
injury.sha Example 13.4 - Effect of Worker Compensation
crime2.sha Section 13.3 - Two-Period Panel Data Analysis, The First-Differenced Estimator
slp75_81.sha Example 13.5 - Sleeping versus Working
crime3.sha Example 13.6 - Distributed Lag with Panel Data
traffic1.sha Example 13.7 - Effect of Drunk Driving Laws
Chapter 14   Advanced Panel Data Methods
jtrain.sha Examples 14.1, 14.3 - Fixed effects estimation including an example with unbalanced panels.
wagepan.sha Example 14.4 - A wage equation using panel data.
Chapter 15  Instrumental Variables Estimation and Two Stage Least Squares
mroz15.sha Examples 15.1, 15.5, 15.7, 15.8; Section 15.6 - Instrumental Variables Estimation, Testing for Endogeneity, Testing for Overidentifying Restrictions, Testing for Heteroskedasticity and Heteroskedasticity-Robust Standard Errors
wage2.sha Examples 15.2, 15.6 - Returns to Education
card.sha Example 15.4 - More Instrumental Variables Estimation
fertil1.sha Example 15.9 - Women's Fertility over Time
jobtrain.sha Example 15.10 - Applying 2SLS to Panel Data
Chapter 16  Simultaneous Equations Models
mroz15.sha Examples 16.3, 16.5 - Labor Supply of Married Working Women
openness.sha Examples 16.4, 16.6 - Inflation and Openness
Chapter 17  Limited Dependent Variable Models
mroz.sha Examples 17.1, 17.2 - Logit and Probit Estimation; Tobit Estimation
crime1.sha Example 17.3 - Poisson Regression
recid.sha Example 17.4 - Censored Regression Model for Duration Analysis
mroz2.sha Example 17.5 - Heckit estimation
Chapter 18  Advanced Time Series Topics
intqrt.sha Example 18.7 - Error Correction Model