Stata 15 help for spxtregress_postestimation

[SP] spxtregress postestimation -- Postestimation tools for spxtregress

Postestimation commands

The following postestimation command is of special interest after spxtregress:

Command Description ------------------------------------------------------------------------- estat impact direct, indirect, and total impacts -------------------------------------------------------------------------

The following postestimation commands are also available:

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 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] newvar [if] [in] [, statistic]

statistic Description ------------------------------------------------------------------------- Main rform reduced-form mean; the default direct direct mean indirect indirect mean xb linear prediction ------------------------------------------------------------------------- These statistics are only available in a subset of the estimation sample.

Menu for predict

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as the reduced-form mean, the direct mean, the indirect mean, or the linear prediction.

Options for predict

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

rform, the default, calculates the reduced-form mean. It is the predicted mean of the dependent variable conditional on the independent variables and any spatial lags of the independent variables. See Methods and formulas.

direct calculates the direct mean. It is a unit's predicted contribution to its own reduced-form mean. The direct and indirect means sum to the reduced-form mean.

indirect calculates the indirect mean. It is the predicted sum of the other units' contributions to a unit's reduced-form mean.

xb calculates the predicted linear combination of the independent variables.

Syntax for margins

margins [marginlist] [, options]

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

statistic Description ------------------------------------------------------------------------- rform reduced-form mean; the default direct direct mean indirect indirect mean xb linear prediction -------------------------------------------------------------------------

For the full syntax, see [R] margins.

Menu for margins

Statistics > Postestimation

Description for margins

margins estimates margins of response for reduced-form mean, direct mean, indirect mean, and linear predictions.

Syntax for estat impact

estat impact [varlist] [if] [in] [, nolog]

varlist is a list of independent variables, including factor variables, taken from the fitted model. By default, all independent variables from the fitted model are used.

Description for estat impact

estat impact estimates the mean of the direct, indirect, and total impacts of independent variables on the reduced-form mean of the dependent variable.

Options for estat impact

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

nolog suppresses the calculation progress log that shows the percentage completed. By default, the log is displayed.


Setup . copy . . copy . . use homicide_1960_1990 . xtset _ID year . spset

Create a contiguity weighting matrix with the default spectral normalization . spmatrix create contiguity W if year == 1990

Fit a spatial autoregressive random-effects model . spxtregress hrate ln_population ln_pdensity gini i.year, re dvarlag(W)

Obtain direct, indirect, and total effects of the covariates . estat impact

Obtain the averages of the effects of gini . estat impact gini

Create an inverse-distance weighting matrix with the default spectral normalization . spmatrix create idistance M if year == 1990

Refit the model above but specify the interaction of gini and year . spxtregress hrate ln_population ln_pdensity c.gini##i.year, re dvarlag(M) errorlag(M)

Test the significance of the gini and year interaction . contrasts c.gini#year

Obtain the effect of gini by year based on year 1960 . estat impact gini if year == 1960

Stored results

estat impact stores the following in r():

Scalars r(N) number of observations

Macros r(xvars) names of independent variables

Matrices r(b_direct) vector of estimated direct impacts r(Jacobian_direct) Jacobian matrix for direct impacts r(V_direct) estimated variance-covariance matrix of direct impacts r(b_indirect) vector of estimated indirect impacts r(Jacobian_indirect) Jacobian matrix for indirect impacts r(V_indirect) estimated variance-covariance matrix of indirect impacts r(b_total) vector of estimated total impacts r(Jacobian_total) Jacobian matrix for total impacts r(V_total) estimated variance-covariance matrix of total impacts

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