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论坛 计量经济学与统计论坛 五区 计量经济学与统计软件 Stata专版
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2013-03-24
第一次在此版发贴不合规矩,让版主给删了
不得不说此版的管理做得相当严谨。

经过摸索,对面板数据的单位根检验提出若干问题
背景:29国 七年28期非平衡季度数据

1.需要采用哪种方法:经过总结 非平衡数据不能使用Hadri,排除。除了判断平衡非平衡,还要判断同根不同根,怎么判断?
2.忽略第一步,尝试使用Fisher-ADF,PP都会出现“sample may not include multiple panels“提示,怎么解决?
3.无论使用哪种方法,都有截距项和趋势项的判断,按网上资料的指引,是通过时序图来判断,请问怎么用stata作面板数据的时序图?

谢谢!


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2013-3-24 02:25:08
面板数据应该用面板数据对于的命令,你用适用于时间序列的命令,处理面板数据,就会报错。
你先查xt命令的help会列出相关的命令,


Title

    [XT] xt -- Introduction to xt commands


Syntax

        xtcmd ...


Description

    The xt series of commands provide tools for analyzing panel data (also known as longitudinal data or in some
    disciplines as cross-sectional time series when there is an explicit time component).  Panel datasets have
    the form x_[it], where x_[it] is a vector of observations for unit i and time t.  The particular commands
    (such as xtdescribe, xtsum, and xtreg) are documented in alphabetical order in the entries that follow this
    entry.  If you do not know the name of the command you need, try browsing the second part of this description
    section, which organizes the xt commands by topic.  Remarks of [XT] xt describes concepts that are common
    across commands.

    The xtset command sets the panel variable and the time variable; see [XT] xtset.  Most xt commands require
    that the panel variable be specified, and some require that the time variable also be specified.  Once you
    xtset your data, you need not do it again.  The xtset information is stored with your data.

    If you have previously tsset your data by using both a panel and a time variable, these settings will be
    recognized by xtset, and you need not xtset your data.

    If your interest is in general time-series analysis, see [U] 26.16 Models with time-series data and the
    Time-Series Reference Manual.

    Data management and exploration tools

        xtset        Declare data to be panel data
        xtdescribe   Describe pattern of xt data
        xtsum        Summarize xt data
        xttab        Tabulate xt data
        xtdata       Faster specification searches with xt data
        xtline       Line plots with xt data


    Linear regression estimators

        xtreg        Fixed-, between- and random-effects, and population-averaged linear models
        xtregar      Fixed- and random-effects linear models with an AR(1) disturbance
        xtmixed      Multilevel mixed-effects linear regression
        xtgls        Panel-data models using GLS
        xtpcse       Linear regression with panel-corrected standard errors
        xthtaylor    Hausman-Taylor estimator for error-components models
        xtfrontier   Stochastic frontier models for panel data
        xtrc         Random-coefficients regression
        xtivreg      Instrumental variables and two-stage least squares for panel-data models


    Unit-root tests

        xtunitroot   Panel-data unit-root tests


    Dynamic panel-data estimators

        xtabond      Arellano-Bond linear dynamic panel-data estimation
        xtdpd        Linear dynamic panel-data estimation
        xtdpdsys     Arellano-Bover/Blundell-Bond linear dynamic panel-data estimation


    Censored-outcome estimators

        xttobit      Random-effects tobit models
        xtintreg     Random-effects interval-data regression models


    Binary-outcome estimators

        xtlogit      Fixed-effects, random-effects, & population-averaged logit models
        xtmelogit    Multilevel mixed-effects logistic regression
        xtprobit     Random-effects and population-averaged probit models
        xtcloglog    Random-effects and population-averaged cloglog models


    Count-data estimators

        xtpoisson    Fixed-effects, random-effects, & population-averaged Poisson models
        xtmepoisson  Multilevel mixed-effects Poisson regression
        xtnbreg      Fixed-effects, random-effects, & population-averaged negative binomial models


    Multilevel (hierarchical) mixed-effects estimators

        xtmelogit    Multilevel mixed-effects logistic regression
        xtmepoisson  Multilevel mixed-effects Poisson regression
        xtmixed      Multilevel mixed-effects linear regression


    Generalized estimating equations estimator

        xtgee        Population-averaged panel-data models using GEE





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2013-3-24 02:59:03
具体语法已明,请问二楼,怎么作时序图,以作对截距项 或者趋势项的粗略判断
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2013-3-24 03:06:58
蓝色 发表于 2013-3-24 02:25
面板数据应该用面板数据对于的命令,你用适用于时间序列的命令,处理面板数据,就会报错。
你先查xt命令的 ...
具体语法已明,请问二楼,怎么作时序图,以作对截距项 或者趋势项的粗略判断
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2013-3-24 03:07:05
蓝色 发表于 2013-3-24 02:25
面板数据应该用面板数据对于的命令,你用适用于时间序列的命令,处理面板数据,就会报错。
你先查xt命令的 ...
具体语法已明,请问二楼,怎么作时序图,以作对截距项 或者趋势项的粗略判断,谢谢
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2013-5-29 19:31:22
我也有同样的问题,ADF检验出现sample may not include multiple panels,而且面板数据已经定义过了,楼主是如何解决的?
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