Do elections matter for private-sector healthcare management in Brazil? An analysis of municipal health policy

Table 3 Covariates in linear regression models predicting 2012 Levels of Privatization by Party in Power in Brazilian Municipalities^a

	Dental	X-rays	Ultrasounds	Hospital Beds	Outsourcing	Health Expenditures
Incumbency	0.17	−0.07	0.43	−1.90^*	−0.46	0.75
	(0.37)	(0.66)	(0.82)	(0.74)	(0.30)	(0.83)
HDI	0.50^***	0.44^***	0.27^*	0.11	0.21^***	0.31^*
	(0.06)	(0.11)	(0.13)	(0.12)	(0.05)	(0.10)
Upper middle class income	0.05^***	0.04^**	0.07^**	0.05^·	−0.01	0.08^**
	(0.01)	(0.02)	(0.03)	(0.03)	(0.01)	(0.03)
Controls for Baseline and Aggregate Change^b
Total Equipment per capita end of term	2.40^***	4.29^***	3.45^***	0.35^***
	(0.08)	(0.28)	(0.50)	(0.05)
Total Equipment per capita baseline	−2.91^***	−4.32^***	−3.38^***	−0.30^***
	(0.09)	(0.29)	(0.43)	(0.04)
% Private Equipment baseline	0.83^***	0.79^***	0.77^***	0.75^***
Interquartile Range	0.19	0.68	0.72	0.37
	(0.01)	(0.01)	(0.01)	(0.01)
Outsourcing/Health Expenditures					0.63^***
					(0.01)
Health Expenditures per capita						0.77^***
						(0.01)
R² Full Model	0.76	0.76	0.73	0.67	0.44	0.69
R² Political Variables Only	0.01	0.01	0.02	0.01	0.01	0.01
Num. obs.	4650	3075	2429	2987	4347	4476

^a*** p < 0.001, ^** p < 0.01, ^* p < 0.05, ^· p < 0.1. Entries are regression coefficients (standard errors). Note: Incumbency estimates multiplied by 100
^bEstimates for total equipment per capita at end of term and baseline should be considered together. When combined, their sum equals the effect size for the change in the total stock of equipment over the mayoral term

ISSN: 1472-6963