面板数据残差平方和

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请问各位 在面板数据中 估计完方程后，怎么计算面板数据残差平方和 非常感谢指点

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关键词：面板数据 平方和 非常感谢 数据 面板 残差 平方和

zyjbs 发表于 2011-5-24 19:50 请问各位 在面板数据中 估计完方程后，怎么计算面板数据残差平方和

先把你的估计方程的命令写一下。

版主您好 我的估计方程 xtreg y n w k s ,fe

请您多指教 前一阵看您的stata作图 很有启发

zyjbs 发表于 2011-5-24 21:45 xtreg y n w k s,fe

该命令中，residual涉及两部分：u_i与e_it。你想计算哪部分的平方和？

版主您好 想估计e_it 部分的平方和 不知用什么命令 请指教

您好 版主 顺便想问一下 估计u_i用什么命令 请指教 非常感谢

zyjbs 发表于 2011-5-25 10:10 估计u_i用什么命令

predict u, u

zyjbs 发表于 2011-5-25 10:09 想估计e_it 部分的平方和 不知用什么命令

predict e,e
egen s=sum(e^2)

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.