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In today’s race toward a more circular economy, optimization of tariff design is important for minimizing the environmental impact and costs of municipal waste management. This study examines the overlap of an incentive-based tariff method and the unit pricing system. We address whether this overlap impacts the effectiveness and efficiency of waste management in Italian municipalities. Based on a panel data sample for 5,512 municipalities from 2016 to 2022, a generalized method of moments estimation was employed for a linear dynamic panel model. The results suggest that there is room for optimizing their overlap under certain circumstances—specifically, when the availability of waste treatment facilities is adequate and the percentage of separate waste collection is high. The interaction between the percentage of separate collection and the incentive tariff method contributed to cost reduction, confirming the need for consistency and compatibility of a tariff scheme with circular economy objectives. The effective adoption of both tools, as well as other actions such as information campaigns and service delivery improvements, can promote waste sorting and investment in management facilities. The results provide insights for policymakers seeking to design more effective and efficient policy measures aimed at maximizing environmental effectiveness, in accordance with the polluter-pays principle, and minimizing costs
In today’s race toward a more circular economy, optimization of tariff design is important for minimizing the environmental impact and costs of municipal waste management. This study examines the overlap of an incentive-based tariff method and the unit pricing system. We address whether this overlap impacts the effectiveness and efficiency of waste management in Italian municipalities. Based on a panel data sample for 5,512 municipalities from 2016 to 2022, a generalized method of moments estimation was employed for a linear dynamic panel model. The results suggest that there is room for optimizing their overlap under certain circumstances—specifically, when the availability of waste treatment facilities is adequate and the percentage of separate waste collection is high. The interaction between the percentage of separate collection and the incentive tariff method contributed to cost reduction, confirming the need for consistency and compatibility of a tariff scheme with circular economy objectives. The effective adoption of both tools, as well as other actions such as information campaigns and service delivery improvements, can promote waste sorting and investment in management facilities. The results provide insights for policymakers seeking to design more effective and efficient policy measures aimed at maximizing environmental effectiveness, in accordance with the polluter-pays principle, and minimizing costs
The rapid progress in science and technology has ushered in a new era of organized and efficient development within the digital economy. China has repeatedly emphasized the need for high-quality development that prioritizes ecological conservation. The central challenge is to balance economic growth with environmental protection, ensuring sustainable development. Understanding the environmental impact of the digital economy is critical for achieving green growth in China. This paper investigates the relationship between the digital economy and ecological protection, using data from 30 provinces and cities in China between 2012 and 2021. Through empirical analysis, including a two-way fixed effect model, mechanism analysis, regional difference analysis, and robustness tests, the study found a significant negative correlation between the digital economy and environmental pollution. This indicates that the development of the digital economy can effectively improve the ecological environment. In the information age, seizing the opportunities presented by the digital economy is crucial. By deepening the digital industry and leveraging digital technologies, China can enhance enterprise production, promote innovation, and create a positive feedback loop between economic development and environmental optimization. However, it is essential to recognize regional disparities in digital economy development and work to narrow these gaps, ensuring balanced and sustainable growth across the country.
Amid the rapidly changing digital environment and the growing flow of information, the digital economy has become a significant driving force behind economic progress. At the same time, governments worldwide are increasingly prioritizing environmental protection and green development, making the challenge of harmonizing economic growth with environmental protection to achieve high-quality development, a critical issue. This study, using data from 285 prefecture-level cities in China, places the digital economy, environmental regulations, and high-quality economic development in the same framework to explore their interconnections. Furthermore, machine learning and the SHAP (Shapley Additive Explanations) model were employed to analyze the complex nonlinear effects and interactions between these factors, clarifying the significance of various parameters. The findings reveal significant regional differences in high-quality economic growth, digital industrialization, industrial digitization, digital governance, data valorization, and environmental regulations across China, with generally low overall levels. Digital governance, industrial digitization, and digital industrialization all contribute to high-quality economic development, with digital industrialization having the most significant impact. However, challenges such as data privacy concerns and inadequate governance can hinder the positive effects of data valorization on high-quality economic progress.
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