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stata與面板數(shù)據(jù)回歸(文件)

 

【正文】 7 8 3 0 . 4 0 0 . 0 0 0 6 . 9 5 8 3 0 1 7 . 9 1 7 4 6 t e c h n o . 1 7 9 0 3 2 1 . 0 3 5 4 1 4 3 5 . 0 6 0 . 0 0 0 . 1 0 9 6 2 1 2 . 2 4 8 4 4 2 9 a d m i n . 0 7 9 3 5 7 . 0 4 3 6 5 2 5 1 . 8 2 0 . 0 6 9 . 0 0 6 2 0 0 4 . 1 6 4 9 1 4 5 h e a l t h . 5 6 8 6 4 2 8 . 0 6 8 6 4 7 4 8 . 2 8 0 . 0 0 0 . 4 3 4 0 9 6 4 . 7 0 3 1 8 9 1 s c i . 0 5 2 0 2 8 2 . 0 5 5 2 6 5 9 0 . 9 4 0 . 3 4 6 . 1 6 0 3 4 7 4 . 0 5 6 2 9 1 c u l t u r e . 0 3 9 5 1 9 4 . 0 3 7 3 4 9 3 1 . 0 6 0 . 2 9 0 . 0 3 3 6 8 3 9 . 1 1 2 7 2 2 7 i n v e s t . 0 0 3 0 8 6 8 . 0 2 7 0 0 2 9 0 . 1 1 0 . 9 0 9 . 0 4 9 8 3 8 . 0 5 6 0 1 1 6 g d p C o e f . S t d . E r r . z P | z | [ 9 5 % C o n f . I n t e r v a l ] c o r r ( u _ i , X ) = 0 ( a s s u m e d ) P r o b c h i 2 = 0 . 0 0 0 0R a n d o m e f f e c t s u _ i ~ G a u s s i a n W a l d c h i 2 ( 6 ) = 2 3 4 2 . 8 0 o v e r a l l = 0 . 8 6 4 1 m a x = 9 b e t w e e n = 0 . 8 9 4 3 a v g = 9 . 0R s q : w i t h i n = 0 . 9 1 1 5 O b s p e r g r o u p : m i n = 9G r o u p v a r i a b l e : s h e n g N u m b e r o f g r o u p s = 3 1R a n d o m e f f e c t s G L S r e g r e s s i o n N u m b e r o f o b s = 2 7 9隨機(jī)效應(yīng)模型 Stata對(duì)面板數(shù)據(jù)模型的估計(jì) ? 首先對(duì)面板數(shù)據(jù)進(jìn)行聲明: ? 前面是截面單元,后面是時(shí)間標(biāo)識(shí): ? tsset pany year ? tsset industry year ? 產(chǎn)生新的變量: gen newvar=human*lnrd ? 產(chǎn)生滯后變量 Gen fiscal(2)= ? 產(chǎn)生差分變量 Gen fiscal(D)= ? 描述性統(tǒng)計(jì): ? xtdes :對(duì) Panel Data截面?zhèn)€數(shù)、時(shí)間跨度的整體描述 ? Xtsum:分組內(nèi)、組間和樣本整體計(jì)算各個(gè)變量的基本統(tǒng)計(jì)量 ? xttab 采用列表的方式顯示某個(gè)變量的分布 ? Stata中用于估計(jì)面板模型的主要命令: xtreg ? xtreg depvar [varlist] [if exp] , model_type [level() ] ? Model type 模型 ? be Betweeneffects estimator ? fe Fixedeffects estimator ? re GLS Randomeffects estimator ? pa GEE populationaveraged estimator ? mle Maximumlikelihood Randomeffects ? estimator ? 主要估計(jì)方法: ? xtreg: Fixed, between and randomeffects, and populationaveraged linear models ? xtregar: Fixed and randomeffects linear models with an AR(1) disturbance ? xtpcse : OLS or PraisWinsten models with panelcorrected standard
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