Stata 15 help for mgarch_ccc_postestimation

[TS] mgarch ccc postestimation -- Postestimation tools for mgarch ccc

Postestimation commands

The following standard postestimation commands are available after mgarch ccc:

Command Description ------------------------------------------------------------------------- contrast contrasts and ANOVA-style joint tests of estimates estat ic Akaike's and Schwarz's Bayesian information criteria (AIC and BIC) estat summarize summary statistics for the estimation sample estat vce variance-covariance matrix of the estimators (VCE) estimates cataloging estimation results forecast dynamic forecasts and simulations lincom point estimates, standard errors, testing, and inference for linear combinations of coefficients lrtest likelihood-ratio test margins marginal means, predictive margins, marginal effects, and average marginal effects marginsplot graph the results from margins (profile plots, interaction plots, etc.) nlcom point estimates, standard errors, testing, and inference for nonlinear combinations of coefficients predict predictions, residuals, influence statistics, and other diagnostic measures predictnl point estimates, standard errors, testing, and inference for generalized predictions pwcompare pairwise comparisons of estimates test Wald tests of simple and composite linear hypotheses testnl Wald tests of nonlinear hypotheses -------------------------------------------------------------------------

Syntax for predict

predict [type] {stub*|newvarlist} [if] [in] [, statistic options]

statistic Description ------------------------------------------------------------------------- Main xb linear prediction; the default residuals residuals variance conditional variances and covariances correlation conditional correlations ------------------------------------------------------------------------- These statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only for the estimation sample.

options Description ------------------------------------------------------------------------- Options equation(eqnames) names of equations for which predictions are made dynamic(time_constant) begin dynamic forecast at specified time -------------------------------------------------------------------------

Menu for predict

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as linear predictions and conditional variances, covariances, and correlations. All predictions are available as static one-step-ahead predictions or as dynamic multistep predictions, and you can control when dynamic predictions begin.

Options for predict

+------+ ----+ Main +-------------------------------------------------------------

xb, the default, calculates the linear predictions of the dependent variables.

residuals calculates the residuals.

variance predicts the conditional variances and conditional covariances.

correlation predicts the conditional correlations.

+---------+ ----+ Options +----------------------------------------------------------

equation(eqnames) specifies the equation for which the predictions are calculated. Use this option to predict a statistic for a particular equation. Equation names, such as equation(income), are used to identify equations.

One equation name may be specified when predicting the dependent variable, the residuals, or the conditional variance. For example, specifying equation(income) causes predict to predict income, and specifying variance equation(income) causes predict to predict the conditional variance of income.

Two equations may be specified when predicting a conditional variance or covariance. For example, specifying equation(income, consumption) variance causes predict to predict the conditional covariance of income and consumption.

dynamic(time_constant) specifies when predict starts producing dynamic forecasts. The specified time_constant must be in the scale of the time variable specified in tsset, and the time_constant must be inside a sample for which observations on the dependent variables are available. For example, dynamic(tq(2008q4)) causes dynamic predictions to begin in the fourth quarter of 2008, assuming that your time variable is quarterly; see [D] datetime. If the model contains exogenous variables, they must be present for the whole predicted sample. dynamic() may not be specified with residuals.

Syntax for margins

margins [marginlist] [, options]

margins [marginlist] , predict(statistic ...) [predict(statistic ...) ...] [options]

statistic Description ------------------------------------------------------------------------- default linear predictions for each equation xb linear prediction for a specified equation variance conditional variances and covariances correlation conditional correlations residuals not allowed with margins ------------------------------------------------------------------------- xb defaults to the first equation.

Statistics not allowed with margins are functions of stochastic quantities other than e(b).

For the full syntax, see [R] margins.

Menu for margins

Statistics > Postestimation

Description for margins

margins estimates margins of response for linear predictions and conditional variances, covariances, and correlations. All predictions are available as static one-step-ahead predictions or as dynamic multistep predictions, and you can control when dynamic predictions begin.

Examples

Setup . webuse stocks . mgarch ccc (toyota nissan = , noconstant) (honda = , noconstant), arch(1) garch(1)

Forecast conditional variances 50 time periods into the future, using dynamic predictions beginning in time period 2016, and then graph the forecasts . tsappend, add(50) . predict H*, variance dynamic(2016) . tsline H_toyota_toyota H_nissan_nissan H_honda_honda if t>1600, legend(rows(3)) xline(2015)


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index