A comprehensive evaluation of eco-productivity of the municipal solid waste service in Chile
Manuel Mocholi-Arce1, Ramon Sala-Garrido1, Maria Molinos-Senante2(), Alexandros Maziotis3
. Departamento de Matemáticas para la Economía y la Empresa, Universidad de Valencia, Valencia 46010, Spain . Institute of Sustainable Processes, Universidad de Valladolid, Valladolid 47011, Spain . Department of Business, New York College, Athina 10558, Greece
Moving toward a circular economy requires improvement of the economic and environmental performance of municipalities in their provision of municipal solid waste (MSW) services. Understanding performance changes over years is fundamental to support decision-making. This study employs the Luenberger-Hicks-Moorsteen productivity indicator to evaluate eco-productivity change and its drivers in the MSW sector in Chile over the years 2015–2019. The further use of decision tree and linear regression analysis allows exploration of the interaction between operating characteristics and eco-productivity estimations. The results of the eco-productivity assessment show that, although the Chilean MSW sector was still facing a transitional period, from 2015 to 2019, eco-productivity increased 1.28% per year. Gains in eco-productivity were due to technical progress and small gains in efficiency, whereas scale effect had an adverse impact. Other factors such as waste spending per inhabitant and the amount of waste collected and recycled per inhabitant had a significant impact on the eco-productivity of Chilean municipalities.
Manuel Mocholi-Arce,Ramon Sala-Garrido,Maria Molinos-Senante, et al. A comprehensive evaluation of eco-productivity of the municipal solid waste service in Chile[J]. Front. Environ. Sci. Eng.,
2025, 19(1): 11.
Tab.1 Descriptive statistics of the variables to evaluate eco-productivity change a)
Fig.1 Evolution of the LHMPI and contribution of inputs and outputs for Chilean municipalities in the management of MSW.
Fig.2 Evolution of the LHMPI and its drivers for Chilean municipalities in the management of MSW.
Variable
Fixed effects
Random effects
Coef.
St. Err.
Z-stat
p-value
Coef.
St. Err.
Z-stat
p-value
Constant
1.893
1.423
1.330
0.185
1.245
0.117
10.603
0.000
Recyclabe waste per capita
0.047
0.014
3.310
0.001
0.030
0.008
3.659
0.000
Unsorted waste per capita
−0.059
0.027
−2.178
0.03
−0.021
0.013
−1.645
0.099
Waste spending per capita
−0.059
0.066
−0.901
0.368
−0.023
0.014
−1.639
0.101
Populaton density
−0.002
0.382
−0.006
0.995
0.011
0.010
1.124
0.261
R2
0.47
0.47
X2 stat
4.95
0.4
20.36
0.000
Hausman test
Ho: preferred model RE
X2 stat
7.49
p-value
0.112
Tab.2 Annual growth rate of eco-productivity change and its components by Chilean region
Fig.3 Regression tree (predicted variable is LHMPI).
Variable
Coef.
Rob. Std. Err.
Z-stat
p-value
Constant
1.245
0.066
18.746
0.000
Recyclable waste per capita
0.030
0.008
4.058
0.000
Unsorted waste per capita
−0.021
0.012
−1.745
0.081
Waste spending per cap
−0.023
0.010
−2.193
0.028
Populaton density
0.011
0.006
1.819
0.069
R2
0.47
X2 (5)
27.09
0.000
Tab.3 Estimates of random effects model to identify operational variables affecting eco-productivity change with robust standard errors
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