现在毕业论文我就差这最后一个估计结果与分析的部分。实在看不懂xtptm那个程序的一些结果汇报,还请老师指点。
我用的命令与得到的结果如下:
1. 我最不明白的是那些序号代表什么变量,我能看到得到的门槛值是0.1070,
2. 我还想知道变量 GrGY 在门槛左右的估计系数是哪两个呢?
3. 还有一个问题是,在这个结果我中我还应该关注哪些重要的统计量?
4. 参数grid的意义不太明白,通常设置多少合适?
5. _matplot LR, columns(1 2) 画的是残差平方各的门槛变化图吗?是不是文章一般都要给出这个图?
我的测试数据在附件中
谢谢连老师。没有你的毕业论文恐怕够呛啊。
. xtptm Yr IY1 Nr, rx(GrGY) thrvar(GY) trim(0.05) iters(1000) grid(100)
================ Fundamental information: ===================
Number of Regime independent variables: 2
Number of Regime dependent variables: 1
Number of individuals in panel: 23
Number of periods in panel: 32
================ Ordinary Fixed effect regression: =========
Sum of Squared Residuls: 1.0014
Stardard error of regression: 0.0376
Regression Result(ordinary standard error):
----------------------------------------------------
| Coef Std t Prob
----+-----------------------------------------------
1 | 0.1191 0.0123 9.6929 0.0000
2 | 0.0280 0.0463 0.6047 0.5455
3 | 0.0215 0.0270 0.7975 0.4254
----------------------------------------------------
Regression Result(Robust standard error):
-----------------------------------------------------
| Coef Std_Robust t Prob
----+------------------------------------------------
1 | 0.1191 0.0126 9.4749 0.0000
2 | 0.0280 0.0416 0.6744 0.5003
3 | 0.0215 0.0273 0.7873 0.4314
-----------------------------------------------------
================ Single threshold regession: ===================
Minimized Sum of Squared Residuals: 0.9824
Standard error of residuals: 0.0372
Threshold estimator: 0.1070
95% conf. intv. of threshold: 0.1054 0.1103
LR Critical value to test gamma=gamma0: 7.3523
Threshold regression(Ordinary Std. Error):
----------------------------------------------------
| Coef Std t prob
----+-----------------------------------------------
1 | 0.1267 0.0123 10.2617 0.0000
2 | 0.0199 0.0460 0.4329 0.6652
3 | 0.2059 0.0564 3.6478 0.0003
4 | 0.0621 0.0289 2.1475 0.0321
----------------------------------------------------
Threshold regression(Robust Std. Error):
-----------------------------------------------------
| Coef Std_Robust t prob
----+------------------------------------------------
1 | 0.1267 0.0123 10.2948 0.0000
2 | 0.0199 0.0416 0.4780 0.6328
3 | 0.2059 0.0605 3.4049 0.0007
4 | 0.0621 0.0307 2.0245 0.0433
-----------------------------------------------------
Note: Critcal (Inverse CDF of LR stat): -2*ln(1-sqrt(1-alpha))
Ho: No threshold; Ha: Single threshold
Number of bootstrap:1000
F-stat & Prob: 13.7630 0.0000
F-critical value of 90% 95% 99%:
1
+---------------+
1 | 2.741849207 |
2 | 3.691648533 |
3 | 6.261118273 |
+---------------+
Thresholds in single model:
.1070386543
============== Descrpitive statistic in each regime: ===========
Descriptive statistics of y-X-THR at regime : 1
----------------------------------------------------------------
| Mean Std Min Max Count
----+-----------------------------------------------------------
1 | 1.1073 0.0467 1.0080 1.2559 241
2 | 0.2949 0.0981 0.0915 0.6499 241
3 | 1.0245 0.0241 0.9391 1.2003 241
4 | 0.0930 0.0226 0.0281 0.1659 241
5 | 0.0824 0.0167 0.0390 0.1064 241
----------------------------------------------------------------
Descriptive statistics of y-X-THR at regime : 2
----------------------------------------------------------------
| Mean Std Min Max Count
----+-----------------------------------------------------------
1 | 1.1078 0.0387 0.9091 1.2380 495
2 | 0.3811 0.1436 0.0579 0.9270 495
3 | 1.0195 0.0338 0.7836 1.2795 495
4 | 0.1800 0.0606 0.0896 0.5878 495
5 | 0.1585 0.0496 0.1071 0.4378 495
----------------------------------------------------------------
LR and Thresholds series are stored in Stata matrix: LR#
You can observe the scatter plot by: _matplot LR#, columns(1 2)


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