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

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

  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 Changeb
 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
  1. 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
  2. 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