Measuring Efficiency at Local Government Level: Research Findings and Methodology
Discover the DEA and SFA methodologies used to measure efficiency at the local government level, along with detailed research findings and second-stage analysis. Explore DEA efficiency scores, SFA efficiency scores, size classifications, and kernel estimation of explanatory variables on efficiency scores.
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Measuring efficiency at local government level Marjan Nikolov
VARIABLES FIRST STAGE: DEA-VRS ESTIMATION Ministry of Finance, 2010 excel database received from the Treasury Department INPUT VARIABLES Current expenditures OUTPUT VARIABLES Population - ages 0-4 Population - ages 5-19 Population - ages 20 to 64 Population ages over 65 Length of asphalt-equivalent roads (kilometers) State Statistical Office (SSO), 2010 estimates of population 2009 for length of roads
Research methodology - DEA Non-parametric DEA AE= OR / OQ TE = OQ / OP x2 y S P Q R Q1 S x 1 y O
Research methodology - SFA Parametric SFA 5 = + + + ln( C ) ln( OUT ) ( V U ) i i i i 0 1 5 = = + + U iz w i i i 0 i 1
Findings DEA efficiency scores SFA efficiency scores Size class 0.573 All sizes POP < 5,000 0.596 0.585 0.502 0.585 0.831 5,000 POP < 10,000 0.720 0.810 10,000 POP < 15,000 0.614 0.720 15,000 POP < 20,000 0.551 0.400 20,000 POP < 60,000 0.345 0.218 POP 60,000
Research findings SECOND STAGE SECOND STAGE- -KERNEL Kernel Fit (Normal, h = 0.0978) KERNEL Kernel Fit (Normal, h = 529.30) Kernel Fit (Normal, h = 26.248) DEA scores 1.0 DEA scores 1.0 1.0 DEA scores 0.8 0.8 0.8 0.6 0.6 0.6 DEA DEA DEA 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0.2 0.4 0.6 0.8 0 1000 2000 3000 4000 0 50 100 150 200 ETF OWNTAX DENSITY Figure. Kernel estimation of the explanatory variables on DEA-VRS efficiency scores
