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Table 2 Stochastic frontier and metafrontier estimation results (t-statistics in parentheses). This tables documents the estimation results from the regression model in (1) - (4) using data from 2005 to 2014. The second columns shows the regression results for a pooled model for all countries. The last column gives the metafrontier parameter results as in (6). The t-statistics for the metafrontier parameters are based on simulated standard errors (simulation with 500 replications)

From: Health care service provision in Europe and regional diversity: a stochastic metafrontier approach

  Pooled Austria France Germany Italy Scandinavia Spain Metafrontier
Output elasticities (x it )         
Intercept 0.013 -0.042 0.034 0.01 0.053 -0.04 0.065 0.152
  (1.42) (-3.63) (4.18) (1.62) (5.68) (-5.91) (4.05) (11.31)
ln(doctors) 0.092 0.261 0.465 0.219 -0.07 0.539 0.161 0.125
  (4.11) (3.90) (12.33) (5.59) (-2.44) (11.31) (4.54) (3.46)
ln(beds) -0.109 -0.275 -0.551 -0.258 -0.149 -0.213 -0.148 -0.209
  (-13.67) (-4.91) (-16.46) (-5.75) (-3.46) (-8.62) (-2.88) (-6.99)
ln(popdens) -0.006 -0.071 -0.049 -0.058 -0.034 -0.079 -0.016 -0.035
  (-1.47) (-8.25) (-6.53) (-7.19) (-3.17) (-8.41) (-2.21) (-4.19)
Effects on inefficiency (z it )         
Intercept -1.49 -0.134 3.421 -1.193 1.455 -8.408 1.119  
  (-1.87) (-0.07) (3.73) (-1.36) (1.69) (-1.72) (1.47)  
ln(gdp p.c.) -1.83 -5.878 -2.449 -3.344 -1.38 -1.765 -1.056  
  (-4.2) (-4.43) (-2.97) (-4.78) (-3.48) (-0.67) (-1.21)  
education -0.031 -0.019 -0.089 -0.128 -0.39 -0.139 -0.12  
  (-2.2) (-0.34) (-3.29) (-6.04) (-5.20) (-2.10) (-3.69)  
age65 -4.26 -25.972 -22.513 2.791 5.303 23.964 0.303  
  (-1.03) (-2.60) (-4.00) (0.63) (1.03) (1.18) (0.06)  
ln(popdens) 0.564 -0.937 0.343 -0.451 0.092 -1.954 0.212  
  (4.03) (-1.65) (1.73) (-1.70) (0.54) (-4.00) (2.16)  
σ v 0.994 0.932 0.953 0.943 0.966 0.924 0.984  
\(\gamma =\sigma _{u}^{2}/\sigma ^{2}\) 0.318 0.92 0.882 0.72 0.846 0.731 0.842  
log-likelihood 968.757 138.016 350.592 525.984 228.379 153.657 179.541  
no of observations 1149 90 218 368 177 116 180