模型回归以后，怎么反过来求y的估计值啊？

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面板数据，做了固定效应或随机效应回归，然后怎么估计被解释变量y的值啊？？？

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关键词：估计值 随机效应回归 随机效应 面板数据 固定效应 模型

把系数带入方程式计算即可！

面板数据也可以这样做吗？？那用predict 可以得到估计值吗？？两者什么区别？？

LSC893045160 发表于 2013-8-11 22:11
面板数据也可以这样做吗？？那用predict 可以得到估计值吗？？两者什么区别？？

help xtreg postestimation                   predict dialogs:  re/be/fe/mle  pa
                                                     dialog:  xttest0         
                                                   also see:  xtreg           
------------------------------------------------------------------------------

Title

    [XT] xtreg postestimation -- Postestimation tools for xtreg


Description

    The following postestimation commands are of special interest after
    xtreg:

    command        description
    ------------------------------------------------------------------------
    xttest0        Breusch and Pagan LM test for random effects
    ------------------------------------------------------------------------

    The following standard postestimation commands are also available:

    command          description
    ------------------------------------------------------------------------
    (1) estat        AIC, BIC, VCE, and estimation sample summary
        estimates    cataloging estimation results
        hausman      Hausman's specification test
        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
        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
        test         Wald tests of simple and composite linear hypotheses
        testnl       Wald tests of nonlinear hypotheses
    ------------------------------------------------------------------------
    (1) estat ic is not appropriate with xtreg, be, xtreg, pa, or xtreg, re.


Special-interest postestimation commands

    xttest0, for use after xtreg, re, presents the Breusch and Pagan
    Lagrange multiplier test for random effects, a test that Var(v_i)=0.


Syntax for predict

    For all but the population-averaged model

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


    Population-averaged model

        predict [type] newvar [if] [in] [, PA_statistic nooffset]


    statistic      description
    ------------------------------------------------------------------------
    Main
      xb           xb, fitted values; the default
      stdp         calculate standard error of the fitted values
      ue           u_i + e_it, the combined residual
    * xbu          xb + u_i, prediction including effect
    * u            u_i, the fixed- or random-error component
    * e            e_it, the overall error component
    ------------------------------------------------------------------------
    Unstarred statistics are available both in and out of sample; type
      predict ... if e(sample) ... if wanted only for the estimation sample.
      Starred statistics are calculated only for the estimation sample, even
      when if e(sample) is not specified.

    PA_statistic   description
    ------------------------------------------------------------------------
    Main
      mu           probability of depvar; considers the offset()
      rate         probability of depvar
      xb           calculate linear prediction
      stdp         calculate standard error of the linear prediction
      score        first derivative of the log likelihood with respect to xb
    ------------------------------------------------------------------------
    These statistics are available both in and out of sample; type predict
      ... if e(sample) ... if wanted only for the estimation sample.


Menu

    Statistics > Postestimation > Predictions, residuals, etc.


Options for predict

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

    xb calculates the linear prediction, that is, a + bx_it.  This is the
        default for all except the population-averaged model.

    stdp calculates the standard error of the linear prediction.  For the
        fixed-effects model, this excludes the variance due to uncertainty
        about the estimate of u_i.

    mu and rate both calculate the predicted probability of depvar.  mu
        takes into account the offset(), and rate ignores those adjustments.
        mu and rate are equivalent if you did not specify offset().  mu is
        the default for the population-averaged model.

    ue calculates the prediction of u_it + e_it.

    xbu calculates the prediction of a + bx_it + u_i, the prediction
        including the fixed or random component.

    u calculates the prediction of u_i, the estimated fixed or random
        effect.

    e calculates the prediction of e_it.

    score calculates the equation-level score.

    nooffset is relevant only if you specified offset(varname) for xtreg.
        It modifies the calculations made by predict so that they ignore the
        offset variable; the linear prediction is treated as xb rather than
        xb + offset.


Syntax for xttest0

        xttest0


Menu

    Statistics > Longitudinal/panel data > Linear models > Lagrange
        multiplier test for random effects


Examples

    Setup
        . webuse nlswork
        . xtset idcode

    Fit random-effects model
        . xtreg ln_w grade age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp
            tenure c.tenure#c.tenure 2.race not_smsa south, re

    Store random-effects results for later use
        . estimates store random_effects

    Breusch and Pagan Lagrangian multiplier test for random effects
        . xttest0

    Fit fixed-effects model
        . xtreg ln_w grade age c.age#c.age ttl_exp c.ttl_exp#c.ttl_exp
            tenure c.tenure#c.tenure 2.race not_smsa south, fe

    Hausman specification test
        . hausman . random_effects


Also see

    Manual:  [XT] xtreg postestimation

      Help:  [XT] xtreg

好的

同问啊