Does China’s Municipal Solid Waste Source Separation Program Work? Evidence from the Spatial-Two-Stage-Least Squares Models

Abstract

This paper evaluates the impact of the second municipal solid waste (MSW) source separation program on municipal solid waste generation (MSWG) in China. Without considering the spatial interactions between cities, the second MSW source separation program has a nonsignificant adverse effect on the per capita municipal solid waste generation (PMSWG). Relaxing the stable-unit-treatment-value assumption (SUTVA), which holds in most of the previous estimation literature on treatment effects, involving the spatial spillover effect among cities, as well as correcting the endogenous local policy has a significantly negative but not robust impact on the PMSWG. The estimation results of the generalized nesting spatial regression models (GNS) imply that the spatial interaction characteristics among Chinese prefecture-level cities may, if neglected, lead to underestimation of the reduction effects of the second MSW source separation policy on the absolute amount of PMSWG. More importantly, our study indicates that although not all the spatial econometric models support the significant reduction effect of source separation on the absolute amount of PMSWG, the source separation program significantly reduces the relative amount of PMSWG, and this result is robust in all spatial models.

Prueba de hipótesis de la curva ambiental de Kuznets para residuos sólidos urbanos en municipios del Estado de México e Hidalgo 2010-2018

“…De acuerdo con Jaligot & Chenal (2018), esta característica puede conducir a errores de medición y diferencias en la cantidad estimada de RSU municipales, por lo que Jaligot & Chenal (2018) establecen y emplean modelos de efectos fijos (en adelante EF) para CKA de RSU municipales; considerando que EF puede capturar el efecto de dicha variación en la estimación de RSU. El empleo de EF para contrastar CKA en residuos municipales es corroborado en estudios de Europa y Asia (Grabarczyk et al, 2018;Jaligot & Chenal, 2018;Renzhi & Baek, 2020;Zhao et al, 2020). Por lo anterior, se optó por estimar y analizar EF.…”

“…Los modelos estadísticos ajustados en este trabajo, es decir EF, regresión por Prais-Winsten y FGLS, están representados en la ecuación 1 (Das, 2019;Jaligot & Chenal, 2018;Renzhi & Baek, 2020;Zhao et al, 2020).…”

“…Los modelos se ajustaron en Stata versión 16.1 (Stata, 2020) a través de los procedimientos "xtreg" para EF, "xtpcse" para regresión por Prais-Winsten para considerar autocorrelación y corrección de errores por heterocedasticidad y "xtgls" para obtener estimaciones por FGLS (Jaligot & Chenal, 2018;Renzhi & Baek, 2020;Zhao et al, 2020).…”

Source separation, transportation, pretreatment, and valorization of municipal solid waste: a critical review

“…Chen et al presented a community investigation demonstrating that source separation could not only reduce the load of landfills, the moisture of waste incineration, and increase the lower heating value of MSW, but also reduce the carbon emission by at least 66.8% (Chen et al, 2020 ). The source separation program would significantly reduce the relative per-capita waste generation through the spatial-two-stage-least squares models analysis (Zhao et al, 2020 ). However, many challenges remain, such as people’s attitudes, treatment facilities, economic benefits.…”

I Am Better Than Others: Waste Management Policies and Self-Enhancement Bias

“…A new national-level policy was issued in 2017, and 46 pilot cities were selected to implement the new mandatory waste separation policy "Implementation plan on the household solid waste classification system." Shanghai became the leading city in 2019 to enforce the mandatory waste separation policy [16][17][18][19]. It concluded that the mandatory policy could reduce household food waste.…”