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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