As a high-quality and sustainable growth model, green development has different economic, ecological, and social dimensions and is strategically important for the realization of modern city construction and the sustainable development of human society. The low-carbon city pilot policy (LCCP) is an innovative initiative for promoting green urban development and building a harmonious society in China. Based on balanced panel data from 277 prefecture-level cities from 2007 to 2020, this paper measures the level of urban green development in terms of three dimensions: green economic growth, ecological welfare enhancement, and social welfare increase. This paper also adopts a multi-period difference-in-differences (DID) method for investigating the impact of LCCP on green development with the panel dataset. The results of the study show that: (1) LCCP is generally beneficial to urban green development, and the results still hold after a series of robustness check analyses. (2) The results of the mechanism analysis show that the construction of low-carbon cities has improved the level of green technology innovation, thereby promoting the level of regional green development. Environmental regulation has a masking effect between low-carbon city construction and green development in this study. When environmental regulation is controlled for, the coefficient of the effect of LCCP on green development increases, reflecting that environmental regulation also plays an important role between the two. (3) According to the geographical location, whether it is a resource-based city, and the city cluster, we found that the low-carbon city pilot policy has a significant positive role in promoting green development in the central region, non-resource-based cities, and the Jing-Jin-Ji, but not in the eastern region, the western region, the Yangtze River Delta and Pearl River Delta. We also found that in resource-based cities, this effect presents a significant negative relationship. The above findings enrich the literature on low-carbon city pilot policies and green development and provide Empirical evidence for relevant countries and regions to carry out low-carbon city pilots.

Based on survey data from 579 farmer households in major non-timber forest product (NTFP) regions of Zhejiang Province, this study comprehensively employs binary logit/ordered probit and machine learning methods for cross-validation. It systematically examines the effects of multiple factors, including perceived property rights security, technical training, village rules and regulations, ecological awareness, and economic incentives, on forest farmers’ adoption of green production technologies. The cross-validation between econometric and machine learning approaches enhances the reliability of the findings. Results show that perceived property rights security is robustly and positively associated with green production behavior, while village rules and regulations and ecological awareness emerge as the two most critical driving factors. These associations exhibit significant NTFP-type heterogeneity: the impacts of technical training and forestry subsidies vary in direction depending on the crop cultivated, rendering traditional one-size-fits-all policies ineffective. This study highlights the crucial role of informal institutions and environmental awareness in the green transition, offering empirical evidence for designing differentiated training programs, optimizing penalty gradients, and implementing targeted subsidy policies.

This study investigates the drivers of green production practices among forest-cultivated ginseng growers in Jilin Province, China, by integrating the Theory of Planned Behavior (TPB) and the Technology–Organization–Environment (TOE) framework. Based on survey data from 369 households in the major production regions of Tonghua, Baishan, and Yanbian areas, an Ordered Probit model and a Light Gradient Boosting Machine (LGBM) algorithm are employed for cross-validation. The results indicate that growers’ cognitive traits (awareness of green production standards and ecological/quality safety) and willingness (acceptance of price premiums for green products) are the most stable and critical drivers. Policy incentives (e.g., certification subsidies and outreach) not only directly promote green practices but also exhibit synergistic effects through interactions with resource endowments and psychological cognition. Regional heterogeneity is evident: Tonghua shows policy–market co-drive, Baishan is dominated by ecological constraints and safeguard policies, while Yanbian relies more on education and individual resources. Accordingly, this study proposes a differentiated policy system based on diagnosis–intervention–evaluation to support the high-quality development of forest-cultivated ginseng industry and ecological-economic synergies.