1.1 The purpose of econometric analysis
1.2 The logic of econometric analysis
1.3 The methods of econometric analysis
1.4 The tools of econometric analysis
Chapter summary

Chapter 2 Designing an econometric project

2.1 Developing a question to be analyzed
2.2 Developing an econometric model to frame the question
2.3 Finding data to estimate the parameters of the model
2.4 Presenting the findings of the analysis
Chapter summary

Part 2: Probability and Statistics
Chapter 3 Random variables

3.1 Definition of a random variable
3.2 The probability density function
3.3 The cumulative distribution function
3.4 Properties of random variables
3.5 The normal density function
3.6 Joint distribution of two random variables
Chapter summary
Computer exercise
Problems

Chapter 4 Estimation

4.1 Estimating the mean and variance of a random variable
4.2 Properties of the mean estimator
4.3 Distribution of the mean estimator
4.4 Confidence intervals
Chapter summary
Computer exercise

Chapter 5 Hypothesis testing

5.1 Economic and econometric hypotheses
5.2 The null hypothesis
5.3 Testing the null hypothesis
5.4 Choosing whether to reject the null hypothesis
5.5 The size and the power of tests
5.6 Tests involving variance estimates
Chapter summary
Computer exercise

Part 3: Linear Regression
Chapter 6 Least Squares Regression

6.1 The problem of measuring slopes
6.2 Models, data, and error terms
6.3 The least square estimator
6.4 The difference between correlation and cause
6.5 Using the estimated regression line to forecast Y
6.6 Measuring the fit of the estimated regression line
Chapter summary
Computer exercise
Problems

Chapter 7 Properties of the least squares estimator

7.1 Desirable properties of estimators
7.2 The classical regression model
7.3 Estimating the variance of ?
7.4 Distribution of the least squares estimators
Chapter summary
Computer exercise

Chapter 8 Multivariate regression

8.1 Estimating a production function
8.2 Equations with more than one right hand side variable
8.3 Interpreting a multivariate Estimation
8.4 Tests involving more than one parameter – the F test
8.5 Tests involving more than one parameter – the Wald and LM tests
Chapter review
Computer exercise

Part 4: Topics in Linear Regression
Chapter 9 Selecting a Functional Form

9.1 Natural monopoly and the shape of the cost function
9.2 Rising and falling costs – quadratic terms
9.3 More complicated changes in costs – interaction terms
9.4 A brief history of electricity cost estimation
9.5 Some additional useful functional forms
Chapter summary
Computer exercise

Chapter 10 Determining the econometric specification

10.1 Finding the best regression equation
10.2 To include or not to include a variable
10.3 Imperfect multicollinearity
10.4 Economic intuition and specifications
Chapter summary
Computer exercise

Chapter 11 Instability of the regression equation

11.1 Economic instability
11.2 Dummy variables
11.3 Allowing slopes to vary
11.4 Testing for shifting curves – the Chow test
11.5 Using dummy variables with panel data
11.6 The reasons why curves shift
Chapter summary
Computer exercise

Part 5: Violations of the Regression Model
Chapter 12 Autocorrelation

12.1 Correlated economic shocks
12.2 The consequences of autocorrelation for least squares
12.3 Testing for autocorrelation: the Durbin-Watson test
12.4 Correcting for autocorrelation
12.5 More complex types of autocorrelation
12.6 Shocks that persist indefinitely
Chapter summary
Computer exercise
Problems

Chapter 13 Heteroskedasticity

13.1 The good, the bad, and the ugly
13.2 The consequences of heteroskedasticity
13.3 When the form of the heteroskedasticity is known
13.4 When the form of the heteroskedasticity is not known
Chapter summary
Computer exercise
Problems

Chapter 14 Estimating multiple equations

14.1 Multiple relationships between economic variables
14.2 Estimating two equations at once
14.3 Single equation vs. joint estimation
14.4 Restrictions between parameters in different equations
Chapter summary
Computer exercise
Problems

Part 6: Advanced Topics
Chapter 15 Endogenous variables

15.1 Solving for the values of endogenous variables
15.2 The consequences of endogenous variables
15.3 Identifying the slope of a single equation
15.4 Estimating both equations simultaneously
15.5 Testing for endogeneity
Chapter summary
Computer exercise
Problems

Chapter 16 Forecasting

16.1 Predicting the future path of the economy
16.2 Using regression equations to forecast the economy
16.3 Forecasting when errors are autocorrelated
16.4 Forecasting the accuracy of forecasts
Chapter summary
Computer exercise
Problems

Chapter 17 Time series analysis

17.1 Dynamic economic models
17.2 Causes and consequences
17.3 A general dynamic model
17.4 Forecasting with dynamic models
17.5 Estimating VARs when the data has unit roots
Chapter summary
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Problems

Chapter 18 Nonlinear models

18.1 The long term effects of research and development
18.2 Estimating equations that are nonlinear in the parameters
18.3 Testing nonlinear restrictions
18.4 Transforming nonlinear equations – the Koyck model
Chapter summary
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Problems

Chapter 19 Dummy dependent variables

19.1 Deciding whether to work or not to work
19.2 A simple model of discrete choice
19.3 The maximum likelihood principle
19.4 Estimating the discrete choice model
Chapter summary
Computer exercise
Problems

Chapter 20 General discrete choice models

20.1 Choosing among more than two options
20.2 Finite choices; variants of the logit model
20.3 Constrained choice: the Tobit model
Chapter summary
Computer exercise
Problems