| Chapter 4 - Statistical Inference |
| educ.sha |
Test Procedures
|
| Chapter 5 - Computation and Optimization |
| maxfunc.sha |
Example 5.10 - Maximizing a
function of a single variable.
|
| Chapter 6 - The Classical Multiple Linear Regression Model |
| gasoline.sha |
Examples 6.3 & 6.15 - Demand for Gasoline
|
| invest.sha |
Examples 6.8, 6.12, 6.14, 6.17, 6.18 - Investment Equation
|
| consump.sha |
Example 6.11 - Consumption Function
|
| longley.sha |
Example 6.19 - Multicollinearity
|
| Chapter 7 - Inference and Prediction |
| invest.sha |
Examples 7.1, 7.2, 7.3, 7.4, 7.17, 7.18 -
Hypothesis Testing and Prediction |
| metal.sha |
Examples 7.5, 7.6, 7.7 - More Hypothesis Testing
|
| gasmodel.sha |
Chow test for structural change,
Hansen test of model stability, CUSUM and CUSUMSQ tests based on
recursive residuals. |
| USdata.sha |
Examples 7.14, 7.15 - Testing Nonlinear
Restrictions and Choosing between Nonnested Models
|
| Chapter 8 - Functional Form, Nonlinearity |
| consump.sha |
Example 8.1 - Dummy Variables in Regression
|
| ex82.sha |
Example 8.2 - Analysis of Variance
|
| Chapter 9 - Large Sample Results |
| gasoline.sha |
Example 9.2 - Estimating an Elasticity
|
| frontier.sha |
Example 9.8 - Estimation of the
Stochastic Frontier Model. |
| lad.sha |
Example 9.10 - Least Absolute Error
estimation.
Calculation of bootstrap standard errors is also shown.
|
| Chapter 10 - Nonlinear Regression Models |
| money.sha |
Examples 10.9, 10.11 - Testing for Linearity vs.
Log-linearity, Box-Cox Regression |
| Chapter 12 - Heteroskedasticity |
| hetreg.sha |
Examples 12.1, 12.4, 12.7, 12.9 - Heteroskedasticity
|
| Chapter 13 - Autocorrelated Disturbances |
| macro.sha |
Examples 13.1, 13.3, 13.4 - Autocorrelation
Consistent Covariance Estimation and the Durbin-Watson test statistic
|
| Chapter 14 - Models for Panel Data |
| fixed.sha |
Examples 14.1, 14.2 - Fixed Effects estimation by transforming
data to group mean deviation form. |
| lsdv.sha |
Example 14.2 - Fixed Effects with Dummy Variables
|
| ranpanel.sha |
Examples 14.4, 14.5 - Random Effects Models and
Hausman's Test for fixed or random effects.
|
| fixed2.sha |
Example 14.6 - Heteroskedasticity Consistent Estimation of
Standard Errors for Fixed Effects Models. |
| Chapter 15 - Systems of Regression Equations |
| pool.sha |
Pooling with Cross-Section
Heteroskedasticity and Cross-Section Correlation.
|
| poolauto.sha |
Example 15.5 - Pooling with AR(1)
errors |
| sure.sha |
The Seemingly Unrelated
Regression Model. |
| sureauto.sha |
Example 15.15 - Autocorrelation in the SUR Model
|
| cost4.sha |
Example 15.18 - A Translog Cost Function
|
| Chapter 19 - Models with Discrete Dependent Variables |
| grade.sha |
Examples 19.1, 19.2, 19.4 - Logit and Probit
Estimation |
| probhet.sha |
Example 19.7 - Probit model with
heteroskedasticity. |
| ship.sha |
Example 19.22 - Poisson Regression
|
| Chapter 20 - Limited Dependent Variable and Duration Models |
| fair.sha |
Example 20.12 - Tobit Estimation;
Marginal Effects for Tobit; Test for Normality; Specification test |
| tobit2.sha |
Doubly Censored (Two-Limit) Tobit
|
| fair2.sha |
Regression Models for Count Data - Poisson
Regression and Negative Binomial Regression
|
