The productivity of return migrants: the case of China’s “Sea Turtles”

Table 6 Estimation results from IV estimation in the AFT model

	25% longer imcomplete durations				Tobit
	OLS	IV_LP	IV_Probit	IV_WR ^a	OLS	IV_LP	IV_Probit
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
	(Std.)	(Std.)	(Std.)	(Std.)	(Std.)	(Std.)	(Std.)
Foreign	0.12			0.42^*	0.05
	(0.07)			(0.19)	(0.07)
Fitted_LP		0.31^*				0.38^*
		(0.15)				(0.16)
Fitted_Probit			0.36^*				0.35^*
			(0.16)				(0.16)
Experience	-0.01^*	-0.01^*	-0.01^*	-0.02^**	-0.02^***	-0.02^***	-0.02^***
	(0.00)	(0.00)	(0.00)	(0.01)	(0.00)	(0.00)	(0.00)
Offshore	0.25^**	0.09	0.10	0.08	0.28^**	0.00	0.04
	(0.09)	(0.11)	(0.11)	(0.12)	(0.09)	(0.11)	(0.11)
JointVenture	0.18^*	0.04	0.06	0.04	0.23^*	0.00	0.04
	(0.08)	(0.10)	(0.10)	(0.10)	(0.09)	(0.10)	(0.10)
Syndicate	0.04	0.03	0.01	0.00	0.15^***	0.12^**	0.11^*
	(0.04)	(0.04)	(0.04)	(0.04)	(0.05)	(0.04)	(0.04)
TotalFund	0.01	0.01	0.01	0.01	0.02^***	0.02^***	0.02^***
	(0.00)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
ExitRatio	-0.04	-0.04	-0.04	-0.05	-0.00	0.00	0.00
	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)
Tenure1	-0.02^***	-0.02^***	-0.02^***	-0.02^***	-0.03^***	-0.03^***	-0.03^***
	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Roundsize	-0.01	0.00	-0.00	-0.00	0.00	0.00	-0.00
	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Tenure2	-0.11^***	-0.11^***	-0.10^***	-0.10^***	-0.18^***	-0.18^***	-0.17^***
	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Development	-0.27^***	-0.25^**	-0.22^**	-0.21^**	-0.08	-0.08	-0.08
	(0.08)	(0.08)	(0.08)	(0.08)	(0.08)	(0.08)	(0.08)
Expansion	-0.20^*	-0.24^*	-0.24^*	-0.22^*	0.18	0.15	0.12
	(0.10)	(0.10)	(0.10)	(0.10)	(0.11)	(0.10)	(0.10)
Late Stage	-0.15	-0.17	-0.19	-0.17	0.44^*	0.51^**	0.45^*
	(0.17)	(0.17)	(0.17)	(0.17)	(0.20)	(0.19)	(0.19)
N	728	621	602	602	728	621	602

^* p < 0.05, ^** p < 0.01, ^*** p < 0.001.
Industry, region and year fixed effects are included in all regressions.
The coefficients (standard errors) for linear probability and probit regressions in the first stage are 0.011. (0.004) and 0.028 (0.014), respectively.
^aIV_WR is a procedure Wooldridge proposed (see Wooldridge 2002, pp.623), which is to do a probit in the first stage, and then to estimate the empirical model using the fitted value as an IV. This approach yields more efficient estimates under certain conditions.