Table 1 PCSE and Sys-GMM estimates of...

Table 1

PCSE and Sys-GMM estimates of simple model

	LogTi (Theil index: proxy of export concentration)
	PCSE			Sys-GMM
	(1)	(2)	(3)	(4)	(5)	(6)
LogAVA	0.033**			0.047**
LogAVA	(0.016)			(0.021)
LogAgr_Emp		0.121***			0.077**
LogAgr_Emp		(0.024)			(0.036)
LogAgr_prod			−0.058***			−0.081**
LogAgr_prod			(0.01)			(0.038)
LlogTi				0.664***	0.542***	0.613***
LlogTi				(0.109)	(0.097)	(0.117)
_cons	1.356***	0.978***	1.839***	0.348*	0.359**	1.112***
_cons	(0.048)	(0.098)	(0.071)	(0.195)	(0.164)	(0.305)
Observations	824	840	756	784	797	722
R-squared	0.919	0.943	0.945
Countries				44	43	43
Instruments				10	10	8
AR(1)				0.00	0.00	0.00
AR(2)				0.475	0.406	0.571
Sargan				0.702	0.957	0.922
Hansen				0.765	0.925	0.830

	LogTi (Theil index: proxy of export concentration)
	PCSE			Sys-GMM
	(1)	(2)	(3)	(4)	(5)	(6)
LogAVA	0.033**			0.047**
LogAVA	(0.016)			(0.021)
LogAgr_Emp		0.121***			0.077**
LogAgr_Emp		(0.024)			(0.036)
LogAgr_prod			−0.058***			−0.081**
LogAgr_prod			(0.01)			(0.038)
LlogTi				0.664***	0.542***	0.613***
LlogTi				(0.109)	(0.097)	(0.117)
_cons	1.356***	0.978***	1.839***	0.348*	0.359**	1.112***
_cons	(0.048)	(0.098)	(0.071)	(0.195)	(0.164)	(0.305)
Observations	824	840	756	784	797	722
R-squared	0.919	0.943	0.945
Countries				44	43	43
Instruments				10	10	8
AR(1)				0.00	0.00	0.00
AR(2)				0.475	0.406	0.571
Sargan				0.702	0.957	0.922
Hansen				0.765	0.925	0.830

Note(s): Robust standard errors are in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1

Source(s): Authors’ own work

Sharing Unavailable