help spivreg postestimation                                also see:  spivreg  
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Title

    spivreg postestimation -- Postestimation tools for spivreg


Description

    The following postestimation commands are available after spivreg:

    command          description
    -------------------------------------------------------------------------
INCLUDE help post_estat
INCLUDE help post_estimates
INCLUDE help post_lincom
INCLUDE help post_lrtest
INCLUDE help post_nlcom
        predict      predicted values
INCLUDE help post_predictnl
INCLUDE help post_test
INCLUDE help post_testnl
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Syntax for predict

        predict [type] newvar [if] [in] [, statistic]

    statistic        Description
    -------------------------------------------------------------------------
    Main
      naive          predictions based on the observed values of y; the
                       default
      xb             linear prediction
    -------------------------------------------------------------------------


Options for predict

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

    naive predicted values based on the observed values of y, Y*g +
        lambda*W*y + X*b.

    xb calculates the linear prediction X*b.


Remarks

    The methods implemented in predict after spivreg are documented in
    Drukker, Prucha, and Raciborski (2011) which can be downloaded from 
    http://econweb.umd.edu/~prucha/Papers/WP_spivreg_2011.pdf.

    The predictor computed by the option naive will generally be biased; see
    Kelejian and Prucha (2007) for an explanation.

    See Remarks in spreg postestimation for a more detailed discussion of
    biased and unbiased spatial predictors.


Examples

    Setup
        . use pollute
        . spmat use cobj using pollute.spmat
        . spivreg pollution area (factories = penalties), id(id) dlmat(cobj)
            elmat(cobj)

    Obtain predicted values based on the observed values of y
        . predict yhat


References

    Drukker, D. M., I. R. Prucha, and R. Raciborski. 2011.  A command for
        estimating spatial-autoregressive models with spatial autoregressive
        disturbances and additional endogenous variables.  Working paper, The
        University of Maryland, Department of Economics, 
        http://econweb.umd.edu/~prucha/Papers/WP_spivreg_2011.pdf.

    Kelejian H. H., and I. R. Prucha. 2007. The relative efficiencies of
        various predictors in spatial econometric models containing spatial
        lags.  Regional Science and Urban Economics 37, 363-374.


Also see

    Online:  spivreg, spreg (if installed)