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<Root level> Examples |
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.
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Estimates a linear regression using an adaptive kernel estimator |
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Demonstrates use of information criteria |
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Demonstrates AR1 instruction |
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Demonstrates Arellano-Bond estimator for dynamic panel model |
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Simulates a univariate GARCH process with an autoregressive mean model. |
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Demonstrates BOXJENK instruction, various procedures |
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Demonstrates Gibbs sampling applied to an ARMA model |
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Uses @BJDIFF and @GMAUTOFIT to choose a specification for an ARIMA model. |
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Demonstrates methods for working with forecasts in a static univariate model. |
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Computes betas for large number of stocks |
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Estimates a bivariate form of the Hodrick-Prescott filter. |
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Estimates term structure using non-linear methods |
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Estimates term structure with cubic splines |
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Example of bootstrapping with an ARMA model |
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Example of bootstrapping with cointegration |
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Example of bootstrapping feasible GLS (for heteroscedasticity) |
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Demonstrates basic bootstrapping techniques |
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Demonstrates bootstrapping spectral density estimates |
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Demonstrates bootstrapping with a VAR |
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Demonstrates bootstrapping with a VECM |
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Demonstrates estimation of a model with a Box-Cox transformation |
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Demonstrates estimation of a dynamic model using DSGE and DLM. |
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Demonstrates Bayesian VAR selection of prior and estimation for forecasting purposes. |
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Solves Cass-Koopmans growth model |
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Demonstrates (bivariate) causality tests |
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Estimates CKLS models of the short-term interest rate. |
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Demonstrates different ways to do a Chow test with known break points. |
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Demonstrates cointegration tests |
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Demonstrates conditional forecasting |
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Demonstrates various stability tests |
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Demonstrates non-linear systems estimation (NLSYSTEM) |
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Demonstrates use of a copula as an alternative to a multivariate GARCH model |
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Demonstrates Durbin’s Cumulated Periodogram test for serial correlation. |
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Demonstrates estimation of structural VAR’s |
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Demonstrates estimation of distributed lags |
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Example of state-space model with multiple observables |
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Example of Kalman Smoothing |
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Example of Kalman filtering and out-of-sample forecasting using a state-space model |
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Example of unconditional simulation of a state-space model |
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Example of conditional simulation of a state-space model |
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Example of the use of the @DLMIRF procedure for doing impulse responses in a state-space model. |
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Computes the historical decomposition for a DSGE model. |
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Example of solution of a non-linear DSGE model through linearization |
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Demonstrates estimation of an vector error correction model |
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Demonstrates bootstrapping with an E-GARCH model |
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Demonstrates forecasting an E-GARCH model using random simulations |
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Model specification for Erceg-Henderson-Levin model |
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Demonstrates EM algorithm applied to a "mixture" model |
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Simple example from the Introduction to demonstrate input/output |
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Example from the Introduction to demonstrate data transformation and linear regressions. |
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Example from the Introduction to demonstrate filtering and graphics. |
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Example from the Introduction working with cross section data, using SMPL options and scatter (x-y) graphs. |
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Demonstrates exponential smoothing |
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Demonstrates exponential smoothing |
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Demonstrates estimation of a model with fractional differencing |
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Demonstrates frequency domain deseasonalization |
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Example of rolling estimates for GARCH model with backtesting for Value At Risk calculations. |
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Demonstrates bootstrapping with a GARCH model |
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Example of GARCH model with Dynamic Equicorrelation (DECO). |
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Example of use of fluctuation test for a univariate GARCH model to check for stability. |
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Demonstrates Gibbs sampling with GARCH model |
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Demonstrates importance sampling with GARCH model |
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Demonstrates multivariate GARCH |
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Demonstrates bootstrapping on a multivariate GARCH model |
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Demonstrates Gibbs sampling applied to a DCC GARCH model |
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Demonstrates 2-step DCC estimates |
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Example of estimation of a multivariate GARCH model using MAXIMIZE |
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Example of simulation of a multivariate (DVECH) GARCH process |
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Demonstrates univariate GARCH with nonparametric density |
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Demonstrates univariate GARCH |
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Demonstrates univarate GARCH with the GARCH instruction and DENSITY option. |
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Examples of estimates of univariate GARCH models using MAXIMIZE. |
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Example of univariate GARCH-M with dummy shift in the "M" effect and variance. |
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Example of computing the Volatility Impulse Response (VIRF) for a GARCH model which doesn't have a "VECH" form. |
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Demonstrates contour graph |
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Demonstrates Gibbs sampling with a linear regression |
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Demonstrates Gibbs sampling on dynamic probit model |
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Demonstrates Gibbs sampling applied to a Bayesian VAR |
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Demonstrates Gibbs sampling applied to a Bayesian VAR using the @BVARBuildPriorMN procedure to create the precision matrices. |
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Demonstrates generalized instrumental variables |
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Demonstrates bootstrapping applied to Granger causality test |
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Demonstrates creation of a box plot |
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Demonstrates graphing forecasts |
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Demonstrates graphing a general function |
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Demonstrates high-low-close graphs |
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Demonstrates overlay graphs |
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Hamilton switching model example |
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Demonstrates Hannan efficient estimation |
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Demonstrates GMM (IV) in linear model |
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Calculation of decomposition of long-run variance using the techniques from Hasbrouck(1995) |
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Demonstrates Hausman test (2SLS vs 3SLS) |
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Demonstrates various forms of weighted least squares |
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Demonstrates heteroscedastity tests |
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Demonstrates historical decomposition |
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Demonstrates use of Hodrick-Prescott filter |
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Demonstrates computing and graphing impulse response functions |
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Demonstrates looping over graph instructions |
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Demonstrates instrumental variables estimation |
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Demonstrates intervention model |
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Estimates Klein’s Model I |
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Example of the LIST aggregator |
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Demonstrates use of lowess non-parametric fit |
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Example of the use of MAXIMIZE to estimate a stochastic frontier model |
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Example of Monte Carlo option pricing |
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Example of a mixture model (not-Markovian) demonstrating the different estimation strategies. |
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Demonstrates Monte Carlo analysis of a test statistic |
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Demonstrates Monte Carlo Impulse Response to exogenous variable |
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Demonstrates Monte Carlo Impulse Response for a structural near-VAR |
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Demonstrates Monte Carlo Impulse Responses for a Near-VAR |
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Demonstrates Monte Carlo Impulse Responses for overidentified SVARs |
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Demonstrates Monte Carlo Impulse Responses for a standard VAR |
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Demonstrates Monte Carlo integration for a Vector Error Correction Model (with fixed cointegrating vector) |
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Estimates a Markov-Switching variance model |
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Demonstrates use of neural networks |
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Demonstrates non-linear least squares |
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Demonstrates various techniques for maximum likelihood |
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Demonstrates non-parametric regression |
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Estimation of an observable index model. |
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Demonstrates user-defined menus (USERMENU) |
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Analysis of linear regression with single structural break |
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Demonstrates basic panel data techniques |
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Demonstrates Granger causality test with heterogeneous panel |
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Demonstrates estimation of polynomial distributed lags |
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Demonstrates calculation of optimal portfolios |
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Demonstrates logit and probit models |
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Demonstrates quadratic programming |
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Demonstrates sample randomization techniques |
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Demonstrates estimation of a RegARIMA model (linear regression with ARIMA error process) |
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Panel data probit model with random effects |
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Demonstrates robust estimation techniques in a linear model |
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Shows a test for STAR with outlier adjustments. |
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Example of a Granger causality test using rolling windows |
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Demonstrates different tests for serial correlation |
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Demonstrates Shiller smoothness prior for a distributed lag |
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Example of Gibbs sampling analysis for a Shiller smoothness prior for a distributed lag |
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Example of a VECM with a structural model with short-and-long run restrictions |
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Example of "shutdown" methodology for Vector Autoregression |
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Solves a DSGE, including impulse responses |
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Demonstrates add-factoring in a simultaneous equations model |
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Demonstrates estimation techniques in a simultaneous equations model |
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Demonstrates forecasts for a simultaneous equations model |
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Demonstrates calculation of multipliers in a simultaneous equations model |
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Demonstrates forecast statistics in a simultaneous equations model |
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Demonstrates forecasting using spectral techniques |
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Calculates and graphs a spectral density |
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Demonstrates multiple graphs per page |
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Demonstrates estimation of a SUR model |
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Demonstrates estimation of a stochastic volatility model |
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Demonstrates GLS matrix weighted estimator for a panel data set |
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Estimates a Markov Switching ARCH model |
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Selects and estimates a STAR Model |
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Demonstrates tobit and other limited dependent variable techniques |
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Demonstrates time-varying coefficient estimation in a VAR using @TVARSET. |
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Demonstrates time-varying coefficient estimation in a VAR |
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Demonstrates probit/logit models |
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Demonstrates several testing procedures for unit roots |
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Demonstrates several testing procedures for unit roots allowing for breaks |
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Demonstrates block causality tests in a VAR |
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Simulates a multivariate GARCH model with a VAR mean process. |
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Demonstrates lag length selection techniques in a VAR |
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Estimates a multivariate GARCH model with a VARMA mean process. |
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Demonstrates causality test in the context of a VECM. |
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Demonstrates estimation of a GARCH model with a VECM mean model. |
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Demonstrates calculation of volatility estimates from price data |
Copyright © 2024 Thomas A. Doan