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

Table 9 Impact of Pilot Reform on Hospital Efficiency (with Bias-corrected efficiency)

Variables	(1)	(2)	(3)	(4)
Variables	Hospital Efficiency	Pure Technical Efficiency	Scale Efficiency	Bias-Corrected Efficiency
Post*Pilot Reform	−0.019	−0.030^**	0.023^**	−0.019^*
	(0.012)	(0.012)	(0.010)	(0.010)
Log GDP per capita	−0.050	−0.068	0.019	−0.052
	(0.054)	(0.055)	(0.034)	(0.044)
Log Government Revenue	0.008	−0.003	0.007	0.007
	(0.019)	(0.018)	(0.021)	(0.023)
Log Government Expenditure	−0.050^*	−0.037	−0.015	−0.016
	(0.028)	(0.025)	(0.037)	(0.025)
Services Industry Proportion	0.232	0.300^*	−0.061	0.299^**
	(0.156)	(0.161)	(0.140)	(0.143)
Log Healthcare Institution Bed	−0.034	−0.022	−0.040^***	−0.027^*
	(0.021)	(0.021)	(0.015)	(0.016)
Share of Education Enrollment	0.002	−0.000	0.004	−0.003
	(0.004)	(0.004)	(0.003)	(0.003)
Year Effects	Yes	Yes	Yes	Yes
Individual Effects	Yes	Yes	Yes	Yes
N	2555	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. Bias-corrected Efficiency is the DEA estimates after 1000 times Simarwilson’s bootstrapped-DEA approach. 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