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This paper aims to provide an examination of the general and heterogeneous allowed treatment effects of high-speed rail (HSR) on tourism in cities in China. Based on the implementation of a generalized difference-in-differences (GDID) model and a dose–response (DR) assessment under a quasi-experimental background, this study found significant evidence of a positive average effect of HSR operation on tourism development for both domestic and international tourism. The event study indicates that the counterfactual method implied in this paper is valid, since the parallel trend assumption is confirmed, and the treatment effect of HSR on city tourism has an upwardly increasing trend over time. The heterogeneity test, which separates large cities from medium-sized and small cities, shows that the effect is quite different for the two city types; the effect is not optimistic for large cities, but it is consistently positive for medium-sized and small cities. As an original contribution, this paper conducts a DR study, allowing heterogeneous treatment effects to be captured when cities have different HSR development statuses. This novel method relaxes the strong assumption that there is only one effect level on average for all cities. The results argue that cities with higher HSR development will enjoy more benefits in terms of arrivals and revenues both from home and abroad; however, there are significant differences for the two city groups, as well as for domestic and international tourism. Thus, the findings can offer important information for policy decision making and serve as a valuable reference for research, especially regarding the conclusion drawn from the heterogeneity effect based on city size and HSR development status.

This paper uses a multi-period PSM-DID model to explore the impact of land transfers on food production from a spatial perspective and analyses the income effects, scale effects, and structural effects of such transfers. The empirical results are as follows. (1) Land transfers have reduced the proportion of food crops planted by farmers, and the planting structure has shifted towards cash crops, which has obvious structural effects. (2) The impact of land transfers on the planting structure is spatially heterogeneous. Land transfers are more common in the south than in the north. Land transfers have reduced wheat planting in the north, while rice planting has been reduced in the south. (3) Land transfers have increased the operating income of farmers and have an income effect, but the income of farmers in the north is higher than that of farmers in the south. (4) Land transfers do not have scale effects. Current land transfers among farmers are mainly conducted on a small scale and do not improve farmers’ efficiency in planting food. The following suggestions are proposed. (1) A market mechanism for land transfers should be established to promote large-scale land transfers. (2) The trend towards non-grain cultivation due to land transfers should be halted to ensure food security. (3) The different impacts of urbanization in the northern and southern regions should be considered, and the division of labour in grain-producing areas should be strengthened. (4) Land transfer models should be developed, and the development of smart agriculture should be explored.

Human activities have placed enormous pressure on the world’s water resources. To improve the efficiency of water supply and wastewater treatment, public–private partnerships (PPPs) are widely used for sewage treatment. However, an academic question remains about whether PPP sewage treatment projects (PPPSTs) help reduce urban sewage disposal when responsibilities shift from the public sector to the private sector. This study used panel data of 267 prefecture-level cities in China from 2009 to 2020 to construct a difference-in-difference (DID) model based on the counterfactual framework to answer this question empirically. The model results significantly support the effect of PPPSTs on sewage disposal reduction. Furthermore, these results passed the parallel trend test and the placebo test, and the results were still achieved when the quadratic term of the core variable was introduced, indicating that the model is reliable. In addition, the moderating effect models were used to expand the analysis. That is, the regressions were derived by multiplying the relevant extended variables and the core independent variables. This analysis indicates that the operation mode of PPPST and the characteristics of national demonstration play an essential role in reducing the amount of urban sewage disposal. However, the effect of fiscal decentralization is not apparent. These conclusions were also confirmed in the model using the investment scale of PPPSTs. Therefore, paying attention to the formation of PPPST contracts and adopting a practical supervision system is of great significance for improving the effect of sewage disposal reduction.

At the end of 2019, the COVID-19 pandemic broke out globally and had a tremendous impact on tourism development in countries around the world. The rapid shift of tourism from “over-tourism” to “under-tourism”, threatening the future of the global economy and society, has generated considerable interest from academia and the policy community, but the impact of COVID-19 on tourism variation remains untested by empirical evidence. Based on the daily Baidu Index of 247 prefecture-level cities in China from 2018 to 2021, this study assessed the treatment effect of COVID-19 on tourism and analyzed its dynamic characteristics using the regression-discontinuity-design (RDD) method combined with tourism network attention (TNA) data. The results show that after the outbreak of the COVID-19 pandemic, the level value of TNA dropped significantly by 2.12 (p < 0.10), and the difference value of TNA (TNA_diff) dropped significantly by 10.77 (p < 0.01), indicating that COVID-19 has a negative causal effect on tourism development, and its impact is more pronounced in major tourist source cities, with a coefficient of −14.91 (p < 0.01) corresponding to −4.57 (p < 0.01) for non-major tourist source cities when the dependent variable TNA_diff. The identification of dynamic effects further confirms that the negative impact of the pandemic on tourism network attention is fluctuating and persistent during the study period, with the two major “golden weeks” and peak season being the most severe. Compared to 2020, the TNA has generally shown an upward trend since 2021, indicating signs of a rebound in the vitality of resident tourism, which is conducive to the healthy development of the tourism market.