These provide the code and (most of) the output from the standard example programs—those either described in the manual, or provided outside of the Paper Replications and Textbook examples. The list below is in alphabetical order. The web site has these (and the Paper Replications) organized by subject and/or by any of the authors.
Estimates a linear regression using an adaptive kernel estimator 

Demonstrates use of information criteria 

Demonstrates AR1 instruction 

Demonstrates ArellanoBond estimator for dynamic panel model 

Simulates a univariate GARCH process with an autoregressive mean model. 

Demonstrates BOXJENK instruction, various procedures 

Demonstrates Gibbs Sampling applied to an ARMA model 

Uses @BJDIFF and @GMAUTOFIT to choose a specification for an ARIMA model. 

Demonstrates methods for working with forecasts in a static univariate model. 

Computes betas for large number of stocks 

Estimates a bivariate form of the HodrickPrescott filter. 

Estimates term structure using nonlinear methods 

Estimates term structure with cubic splines 

Example of bootstrapping with an ARMA model 

Example of bootstrapping with cointegration 

Example of bootstrapping feasible GLS (for heteroscedasticity) 

Demonstrates basic bootstrapping techniques 

Demonstrates bootstrapping spectral density estimates 

Demonstrates bootstrapping with a VAR 

Demonstrates bootstrapping with a VECM 

Demonstrates estimation of a dynamic model using DSGE and DLM. 

Demonstrates Bayesian VAR selection of prior and estimation for forecasting purposes. 

Solves CassKoopmans growth model 

Demonstrates (bivariate) causality tests 

Estimates CKLS models of the shortterm interest rate. 

Demonstrates different ways to do a Chow test with known break points. 

Demonstrates cointegration tests 

Demonstrates conditional forecasting 

Demonstrates various stability tests 

Demonstrates nonlinear systems estimation (NLSYSTEM) 

Demonstrates use of a copula as an alternative to a multivariate GARCH model 

Demonstrates Durbin’s Cumulated Periodogram test for serial correlation. 

Demonstrates estimation of structural VAR’s 

Demonstrates estimation of distributed lags 

Example of statespace model with multiple observables 

Example of Kalman Smoothing 

Example of Kalman filtering and outofsample forecasting using a statespace model 

Example of unconditional simulation of a statespace model 

Example of conditional simulation of a statespace model 

Example of the use of the @DLMIRF procedure for doing impulse responses in a statespace model. 

Computes the historical decomposition for a DSGE model. 

Example of solution of a nonlinear DSGE model through linearization 

Demonstrates estimation of an vector error correction model 

Demonstrates bootstrapping with an EGARCH model 

Demonstrates forecasting an EGARCH model using random simulations 

Model specification for ErcegHendersonLevin model 

Demonstrates EM algorithm applied to a "mixture" model 

Simple example from the Introduction to demonstrate input/output 

Example from the Introduction to demonstrate data transformation and linear regressions. 

Example from the Introduction to demonstrate filtering and graphics. 

Example from the Introduction working with cross section data, using SMPL options and scatter (xy) graphs. 

Demonstrates exponential smoothing 

Demonstrates exponential smoothing 

Demonstrates estimation of a model with fractional differencing 

Demonstrates frequency domain deseasonalization 

Example of rolling estimates for GARCH model with backtesting for Value At Risk calculations. 

Demonstrates bootstrapping with a GARCH model 

Example of GARCH model with Dynamic Equicorrelation (DECO). 

Example of use of fluctuation test for a univariate GARCH model to check for stability. 

Demonstrates Gibbs sampling with GARCH model 

Demonstrates importance sampling with GARCH model 

Demonstrates multivariate GARCH 

Demonstrates bootstrapping on a multivariate GARCH model 

Demonstrates Gibbs sampling applied to a DCC GARCH model 

Demonstrates 2step DCC estimates 

Example of estimation of a multivariate GARCH model using MAXIMIZE 

Example of simulation of a multivariate (DVECH) GARCH process 

Demonstrates univariate GARCH with nonparametric density 

Demonstrates univariate GARCH 

Examples of estimates of univariate GARCH models using MAXIMIZE. 

Example of univariate GARCHM with dummy shift in the "M" effect and variance. 

Example of computing the Volatility Impulse Response (VIRF) for a GARCH model which doesn't have a "VECH" form. 

Demonstrates contour graph 

Demonstrates Gibbs sampling with a linear regression 

Demonstrates Gibbs sampling on dynamic probit model 

Demonstrates Gibbs Sampling applied to a Bayesian VAR 

Demonstrates generalized instrumental variables 

Demonstrates bootstrapping applied to Granger causality test 

Demonstrates creation of a box plot 

Demonstrates graphing forecasts 

Demonstrates graphing a general function 

Demonstrates highlowclose graphs 

Demonstrates overlay graphs 

Hamilton switching model example 

Demonstrates Hannan efficient estimation 

Demonstrates GMM (IV) in linear model 

Calculation of decomposition of longrun variance using the techniques from Hasbrouck(1995) 

Demonstrates Hausman test (2SLS vs 3SLS) 

Demonstrates various forms of weighted least squares 

Demonstrates heteroscedastity tests 

Demonstrates historical decomposition 

Demonstrates use of HodrickPrescott filter 

Demonstrates computing and graphing impulse response functions 

Demonstrates looping over graph instructions 

Demonstrates instrumental variables estimation 

Demonstrates intervention model 

Estimates Klein’s Model I 

Example of the LIST aggregator 

Demonstrates use of lowess nonparametric fit 

Example of the use of MAXIMIZE to estimate a stochastic frontier model 

Example of Monte Carlo option pricing 

Example of a mixture model (notMarkovian) demonstrating the different estimation strategies. 

Demonstrates Monte Carlo analysis of a test statistic 

Demonstrates Monte Carlo Impulse Response to exogenous variable 

Demonstrates Monte Carlo Impulse Response for a structural nearVAR 

Demonstrates Monte Carlo Impulse Responses for a NearVAR 

Demonstrates Monte Carlo Impulse Responses for overidentified SVARs 

Demonstrates Monte Carlo Impulse Responses for a standard VAR 

Demonstrates Monte Carlo integration for a Vector Error Correction Model (with fixed cointegrating vector) 

Estimates a MarkovSwitching variance model 

Demonstrates use of neural networks 

Demonstrates nonlinear least squares 

Demonstrates various techniques for maximum likelihood 

Demonstrates nonparametric regression 

Estimation of an observable index model. 

Demonstrates userdefined menus (USERMENU) 

Analysis of linear regression with single structural break 

Demonstrates basic panel data techniques 

Demonstrates Granger causality test with heterogeneous panel 

Demonstrates estimation of polynomial distributed lags 

Demonstrates calculation of optimal portfolios 

Demonstrates logit and probit models 

Demonstrates quadratic programming 

Demonstrates sample randomization techniques 

Demonstrates estimation of a RegARIMA model (linear regression with ARIMA error process) 

Panel data probit model with random effects 

Demonstrates robust estimation techniques in a linear model 

Shows a test for STAR with outlier adjustments. 

Example of a Granger causality test using rolling windows 

Demonstrates Shiller smoothness prior for a distributed lag 

Example of Gibbs sampling analysis for a Shiller smoothness prior for a distributed lag 

Example of a VECM with a structural model with shortandlong run restrictions 

Solves a DSGE, including impulse responses 

Demonstrates addfactoring in a simultaneous equations model 

Demonstrates estimation techniques in a simultaneous equations model 

Demonstrates forecasts for a simultaneous equations model 

Demonstrates calculation of multipliers in a simultaneous equations model 

Demonstrates forecast statistics in a simultaneous equations model 

Demonstrates forecasting using spectral techniques 

Calculates and graphs a spectral density 

Demonstrates multiple graphs per page 

Demonstrates estimation of a SUR model 

Demonstrates estimation of a stochastic volatility model 

Demonstrates GLS matrix weighted estimator for a panel data set 

Estimates a Markov Switching ARCH model 

Selects and estimates a STAR Model 

Demonstrates tobit and other limited dependent variable techniques 

Demonstrates timevarying coefficient estimation in a VAR 

Demonstrates probit/logit models 

Demonstrates several testing procedures for unit roots 

Demonstrates several testing procedures for unit roots allowing for breaks 

Demonstrates block causality tests in a VAR 

Simulates a multivariate GARCH model with a VAR mean process. 

Demonstrates lag length selection techniques in a VAR 

Estimates a multivariate GARCH model with a VARMA mean process. 

Demonstrates causality test in the context of a VECM. 

Demonstrates estimation of a GARCH model with a VECM mean model. 