Table 3. Impact of the meso-interventions (input-oriented results).

Unit of analysis	Results	Pre-Interventions	Post-Interventions	Variation (%)
Global System	Probability of being efficient(1) (PRTE⩵1):	0.2040	0.2047	0.34
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7831	0.7857	0.33
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.001161	0.001363	17.40
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.001444	0.001695	17.40
	Probability of having a RTE score greater than 0.75:	0.6240	0.6281	0.66
S4	Probability of being efficient(1)(PRTE⩵1):	0.2324	0.2280	-1.90
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.9357	0.9362	0.06
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.001708	0.001583	-7.30
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.002123	0.001968	-7.30
	Probability of having a RTE score greater than 0.75:	0.9260	0.9311	0.51
S6	Probability of being efficient(1)(PRTE⩵1):	0.2159	0.2159	0.00
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.8069	0.8059	-0.12
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.007061	0.003662	-48.14
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.008778	0.004553	-48.14
	Probability of having a RTE score greater than 0.75:	0.6422	0.6563	1.41
S7	Probability of being efficient(1)(PRTE⩵1):	0.2363	0.2488	5.30
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7391	0.7563	2.34
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.008573	0.005478	-36.10
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.010658	0.006811	-36.10
	Probability of having a RTE score greater than 0.75:	0.5033	0.5199	1.66
S8	Probability of being efficient(1)(PRTE⩵1):	0.2859	0.2858	-0.04
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.8541	0.8473	-0.79
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.001843	0.002502	35.77
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.002291	0.003110	35.77
	Probability of having a RTE score greater than 0.75:	0.7555	0.7344	-2.11
S9	Probability of being efficient(1)(PRTE⩵1):	0.1447	0.1422	-1.75
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.8467	0.8440	-0.31
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.002497	0.004550	82.22
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.003104	0.005657	82.22
	Probability of having a RTE score greater than 0.75:	0.7074	0.7019	-0.55
S10	Probability of being efficient(1)(PRTE⩵1):	0.2017	0.1882	-6.68
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7836	0.7836	0.00
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.005560	0.005940	6.83
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.006913	0.007384	6.83
	Probability of having a RTE score greater than 0.75:	0.5871	0.5844	-0.26
S11	Probability of being efficient(1)(PRTE⩵1):	0.2403	0.2477	3.07
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7756	0.7908	1.96
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.003327	0.004019	20.80
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.004136	0.004996	20.80
	Probability of having a RTE score greater than 0.75:	0.6154	0.6356	2.02
S12	Probability of being efficient(1)(PRTE⩵1):	0.2244	0.2264	0.89
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7681	0.7614	-0.87
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.004239	0.008103	91.15
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.005270	0.010074	91.15
	Probability of having a RTE score greater than 0.75:	0.5642	0.5514	-1.28
S13	Probability of being efficient(1)(PRTE⩵1):	0.3113	0.3244	4.23
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.8040	0.8124	1.04
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.003734	0.001781	-52.30
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.004643	0.002214	-52.30
	Probability of having a RTE score greater than 0.75:	0.6264	0.6435	1.71
S14	Probability of being efficient(1)(PRTE⩵1):	0.2045	0.2041	-0.21
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.7653	0.7766	1.49
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.003330	0.002666	-19.94
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.004140	0.003315	-19.94
	Probability of having a RTE score greater than 0.75:	0.5360	0.5666	3.06
S15	Probability of being efficient(1)(PRTE⩵1):	0.1479	0.1440	-2.63
	Efficiency average $\left(\stackrel{-}{RTE}\right)$:	0.6128	0.6158	0.50
	Efficiency standard deviation(2)$\left(\stackrel{-}{{\sigma }_{RTE}}\right)$:	0.007666	0.006536	-14.74
	Efficiency error(2)$\left(\stackrel{-}{{\epsilon }_{RTE}}\right)$:	0.009530	0.008126	-14.74
	Probability of having a RTE score greater than 0.75:	0.3289	0.3314	0.24

⁽¹⁾ 7500 simulations.

⁽²⁾ On average.

⁽³⁾ On average calculated taking into consideration the RTE average.