xtptm y x1 x2 x3, rx(x3) thrvar(x3) iters(2000) grid(200) regime(1)
================ Fundamental information: ===================
Number of Regime independent variables: 3
Number of Regime dependent variables: 1
Number of individuals in panel: 31
Number of periods in panel: 6
================ Ordinary Fixed effect regression: =========
Sum of Squared Residuls: 14.4362
Stardard error of regression: 0.3092
Regression Result(ordinary standard error):
----------------------------------------------------
| Coef Std t Prob
----+-----------------------------------------------
1 | 0.0004 0.0019 0.1997 0.8420
2 | -0.0167 0.0056 -2.9871 0.0033
3 | 0.1652 0.0299 5.5198 0.0000
4 | 0.0000 0.0000 . .
----------------------------------------------------
Regression Result(Robust standard error):
-----------------------------------------------------
| Coef Std_Robust t Prob
----+------------------------------------------------
1 | 0.0004 0.0019 0.2073 0.8360
2 | -0.0167 0.0047 -3.5292 0.0006
3 | 0.1652 0.0339 4.8679 0.0000
4 | 0.0000 0.0000 . .
-----------------------------------------------------
================ Single threshold regession: ===================
Minimized Sum of Squared Residuals: 12.6956
Standard error of residuals: 0.2909
Threshold estimator: 0.8662
95% conf. intv. of threshold: 0.8265 0.9855
LR Critical value to test gamma=gamma0: 7.3523
Threshold regression(Ordinary Std. Error):
----------------------------------------------------
| Coef Std t prob
----+-----------------------------------------------
1 | -0.0003 0.0018 -0.1613 0.8720
2 | -0.0169 0.0053 -3.2032 0.0017
3 | -0.2883 0.1039 -2.7754 0.0062
4 | 0.0000 0.0000 . .
5 | 0.4294 0.0947 4.5349 0.0000
----------------------------------------------------
Threshold regression(Robust Std. Error):
-----------------------------------------------------
| Coef Std_Robust t prob
----+------------------------------------------------
1 | -0.0003 0.0017 -0.1751 0.8613
2 | -0.0169 0.0044 -3.7957 0.0002
3 | -0.2883 0.1120 -2.5733 0.0110
4 | 0.0000 0.0000 . .
5 | 0.4294 0.1067 4.0249 0.0001
-----------------------------------------------------
Note: Critcal (Inverse CDF of LR stat): -2*ln(1-sqrt(1-alpha))
Ho: No threshold; Ha: Single threshold
Number of bootstrap:2000
F-stat & Prob: 20.5650 0.0000
F-critical value of 90% 95% 99%:
1
+---------------+
1 | 2.651986327 |
2 | 3.825480484 |
3 | 7.342568767 |
+---------------+
Thresholds in single model:
.8662311887
============== Descrpitive statistic in each regime: ===========
Descriptive statistics of y-X-THR at regime : 1
----------------------------------------------------------------
| Mean Std Min Max Count
----+-----------------------------------------------------------
1 | 0.1092 0.2893 0.0000 1.8654 66
2 | 29.4194 15.3181 1.7116 93.5920 66
3 | 11.4890 9.4872 2.5822 53.2790 66
4 | 0.5691 0.2300 0.0600 0.8600 66
5 | 0.5691 0.2300 0.0600 0.8600 66
6 | 0.5691 0.2300 0.0600 0.8600 66
----------------------------------------------------------------
Descriptive statistics of y-X-THR at regime : 2
----------------------------------------------------------------
| Mean Std Min Max Count
----+-----------------------------------------------------------
1 | 0.3047 0.5466 0.0000 2.9999 120
2 | 28.2207 15.5481 0.0000 67.9303 120
3 | 7.5719 4.2729 1.4761 19.9777 120
4 | 2.3397 2.4756 0.8700 12.8000 120
5 | 2.3397 2.4756 0.8700 12.8000 120
6 | 2.3397 2.4756 0.8700 12.8000 120
----------------------------------------------------------------
LR and Thresholds series are stored in Stata matrix: LR#
You can observe the scatter plot by: _matplot LR#, columns(1 2)
.