[求助] 面板固定效应后残差如何获得？

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<p> RT</p><p>predict res，r 不行了</p><p>谢谢！</p>

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关键词：固定效应 predict Pred dic edi 如何

predict u, u

predict e, e

predict ue, ue 

谢谢~~

sungmoo 发表于 2009-5-4 00:28
predict u, upredict e, epredict ue, ue 

我也是刚做了面板的固定效应模型，现在需要获得残差，就直接用这个命令就可以了吗？得到的结果u、e、ue分别是什么意思啊？如果我要检验残差的稳定性，应该对哪一个做单位根检验呢？

sungmoo 发表于 2009-5-4 00:28
predict u, upredict e, epredict ue, ue 

我好像有点明白了，是不是ue拿来做单位根检验的？

看stata的help 的 xtreg postestimation的解释啊。
这些东西你是不能猜想的。
为什么自己找一下help就这么困难呢？
里面讲的都很清楚的


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.
   

蓝色 发表于 2011-8-13 17:57
看stata的help 的 xtreg postestimation的解释啊。
这些东西你是不能猜想的。
为什么自己找一下help就这么 ...

恩，这个我已经学习了，就是不确定该用哪一个残差做单位根检验，是用复合扰动项ue吗？

我用的是frontier函数，结果指令说option score not allowed
怎么求复合误差项啊？或者说是无效率项/技术效率变化量