Impact of pilot public hospital reform on efficiencies: a DEA analysis of county hospitals in East China, 2009–2015

Table 11 Robustness: impact of pilot reform on pure technical efficiency (different estimation methods)

Variables (Y = Pure technical efficiency)	(1)	(2)	(3)
Variables (Y = Pure technical efficiency)	Baseline Model	Tobit Model with LSDV	Tobit Model with Random Effects
Post*Pilot Reform	−0.030^**	−0.029^***	−0.024^***
	(0.012)	(0.008)	(0.008)
Log GDP per capita	−0.068	−0.063^**	0.054^**
	(0.055)	(0.030)	(0.024)
Log Government Revenue	−0.003	−0.003	0.033^**
	(0.018)	(0.014)	(0.017)
Log Government Expenditure	−0.037	−0.038^*	−0.023
	(0.025)	(0.021)	(0.016)
Services Industry Proportion	0.300^*	0.279^***	0.635^***
	(0.161)	(0.102)	(0.096)
Log Healthcare Institution Bed	−0.022	−0.017	−0.032^*
	(0.021)	(0.013)	(0.018)
Share of Education Enrollment	−0.000	−0.001	0.004^**
	(0.004)	(0.002)	(0.002)
Year Effects	Yes	Yes	NO
Individual Effects	Yes	Yes	NO
Rho			0.578
Log likelihood		2291.96	1193.35
N	2555	2555	2555

Note: The numbers in parentheses are standard errors. Significant levels are denoted as ^*p < 0.1, ^**p < 0.05, ^***p < 0.01. Control variables include GDP per capita, government revenue per capita, government expenditure per capita, the output in the services industry as a share of GDP, the number of beds in healthcare institutions in the population (10, 000), the share of education enrollment in population

ISSN: 2191-1991