[此贴子已经被作者于2007-9-21 18:04:17编辑过]

可是如果不选clear,结果就是no; data in memory would be lost
我用xtdata,fe clear后

看了下数据，好像没变化

对比起，这是我的一个疏忽。使用xtdata时要注意两个问题：

1. 多数情况下，都需要附加 clear 选项，否则会出现上面的错误信息；

2. 建议将转换操作相关的命令都放在 preserve restore 配对命令中，以防止对原始数据的修改（对于具有喜欢保存数据恶习`的朋友这一点尤为重要！）

下面我举例说明这个命令的使用：

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• Stata Log File Browser Page.htm

* ====================== The codes =====================

*--> Goals for this notes:
* 1. show that the dataset before and after xtdata transform are different
* 2. show how to use xtdata command by tesing the higher order correlation of panel data

use "D:\stata9\ado\Examples\XTFiles\grunfeld.dta", clear

tsset company year /*declare Panel-variable and Time-variable*/
drop time

* -> The data will be changed after using `xtdata' command
* the original dataset
list in 1/5
* the transformed data
* FE
preserve
xtdata mvalue invest kstock year, fe clear
list in 1/5
restore
* RE
preserve
qui xtreg mvalue invest kstock, re theta
local theta = e(theta)
xtdata mvalue invest kstock year, re clear ratio(`theta')
list in 1/5
restore

*-> An example for using `xtdata' command
* abar: 高阶序列相关，for both re and fe
*-> for Fe model
preserve /*由于xtdata命令会删除原有变量*/
xtreg mvalue invest kstock ,fe
xtdata mvalue invest kstock year, fe clear
reg mvalue invest kstock
abar, lags(2) /*the arab command can only be used after reg, ivreg,ivreg2 command*/
restore

*=====================================================

* ====================== The results =====================

. do "C:\DOCUME~1\new\LOCALS~1\Temp\STD00000000.tmp"

. *--> Goals for this notes:
. * 1. show that the dataset before and after xtdata transform are different
. * 2. show how to use xtdata command by tesing the higher order correlation of panel data
.
. use "D:\stata9\ado\Examples\XTFiles\grunfeld.dta", clear

.
. tsset company year /*declare Panel-variable and Time-variable*/
panel variable: company (strongly balanced)
time variable: year, 1935 to 1954

. drop time

.
. * -> The data will be changed after using `xtdata' command
. * the original dataset
. list in 1/5

+-------------------------------------------+
| company year invest mvalue kstock |
|-------------------------------------------|
1. | 1 1935 317.6 3078.5 2.8 |
2. | 1 1936 391.8 4661.7 52.6 |
3. | 1 1937 410.6 5387.1 156.9 |
4. | 1 1938 257.7 2792.2 209.2 |
5. | 1 1939 330.8 4313.2 203.4 |
+-------------------------------------------+

. * the transformed data
. * FE
. preserve

. xtdata mvalue invest kstock year, fe clear

. list in 1/5

+----------------------------------------------------+
| company year invest mvalue kstock |
|----------------------------------------------------|
1. | 1 1935 -144.4617 -173.6639 -369.6179 |
2. | 1 1936 -70.26176 1409.536 -319.8179 |
3. | 1 1937 -51.46175 2134.936 -215.5179 |
4. | 1 1938 -204.3617 -459.964 -163.2179 |
5. | 1 1939 -131.2618 1061.036 -169.0179 |
+----------------------------------------------------+

. restore

. * RE
. preserve

. qui xtreg mvalue invest kstock, re theta

. local theta = e(theta)

. xtdata mvalue invest kstock year, re clear ratio(`theta')
(theta=0.7565)

. list in 1/5

+-------------------------------------------------------------------+
| company year invest mvalue kstock constant |
|-------------------------------------------------------------------|
1. | 1 463.9634 -142.3741 -200.1035 -487.7485 .2434885 |
2. | 1 464.9634 -68.17412 1383.097 -437.9485 .2434885 |
3. | 1 465.9634 -49.3741 2108.497 -333.6485 .2434885 |
4. | 1 466.9634 -202.2741 -486.4035 -281.3485 .2434885 |
5. | 1 467.9634 -129.1741 1034.597 -287.1485 .2434885 |
+-------------------------------------------------------------------+

. restore

.
. *-> An example for using `xtdata' command
. * abar: 高阶序列相关，for both re and fe
. *-> for Fe model
. preserve /*由于xtdata命令会删除原有变量*/

. xtreg mvalue invest kstock ,fe

Fixed-effects (within) regression Number of obs = 200
Group variable (i): company Number of groups = 10

R-sq: within = 0.4117 Obs per group: min = 20
between = 0.8078 avg = 20.0
overall = 0.7388 max = 20

F(2,188) = 65.78
corr(u_i, Xb) = 0.6955 Prob > F = 0.0000

------------------------------------------------------------------------------
mvalue | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
invest | 2.856166 .3075147 9.29 0.000 2.249543 3.462789
kstock | -.5078673 .1403662 -3.62 0.000 -.7847625 -.2309721
_cons | 804.9802 32.43177 24.82 0.000 741.0033 868.9571
-------------+----------------------------------------------------------------
sigma_u | 905.81517
sigma_e | 268.73329
rho | .91910377 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(9, 188) = 113.76 Prob > F = 0.0000

. xtdata mvalue invest kstock year, fe clear

. reg mvalue invest kstock

Source | SS df MS Number of obs = 200
-------------+------------------------------ F( 2, 197) = 68.93
Model | 9500910.96 2 4750455.48 Prob > F = 0.0000
Residual | 13576904.9 197 68918.2991 R-squared = 0.4117
-------------+------------------------------ Adj R-squared = 0.4057
Total | 23077815.9 199 115968.924 Root MSE = 262.52

------------------------------------------------------------------------------
mvalue | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
invest | 2.856166 .3004081 9.51 0.000 2.263737 3.448594
kstock | -.5078673 .1371224 -3.70 0.000 -.7782835 -.2374511
_cons | 804.9802 31.68228 25.41 0.000 742.5002 867.4602
------------------------------------------------------------------------------

. abar, lags(2) /*the arab command can only be used after reg, ivreg,ivreg2 command*/
Arellano-Bond test for AR(1): z = 3.30 Pr > z = 0.0010
Arellano-Bond test for AR(2): z = -0.33 Pr > z = 0.7397

. restore

*=====================================================

[此贴子已经被作者于2007-9-22 16:26:50编辑过]