William Greene, Econometric Analysis, Fourth Edition, Prentice-Hall, 2000
Tested with SHAZAM Version 10.
| 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 |