**5. Discussions**

This paper mainly uses the method of spatial econometrics, based on the data of 41 cities in the YRD region from 2007 to 2019, to analyze the influence and spatial effects of the abundance of forest resources in the YRD region on the level of economic development. The robustness check of the results is carried out by changing the spatial weight matrix, adjusting the sample period, and changing the explained variables. The results of the model estimates are proven to be robust. The main results about our hypotheses are as follows.

Hypothesis 1 was verified. The influence of the abundance of forest resources on the economic development level in the YRD has a U-shaped non-linear characteristic [60]. At the city level in the YRD, forest resources will play different roles in different stages of economic development. The curse of forest resources will gradually evolve into welfare with economic development. In the initial stage of economic development, the abundance of forest resources has a certain inhibitory effect on the level of economic development. When the economy develops to a certain level, abundant forest resources can promote the level of economic development [15].

Hypothesis 2 was verified. Spatial spillover effects of forest resources exist [61]. Spatial factors play an important role in economic growth and convergence. The spatial autocorrelation relationship of economic development level exists. Ignoring spatial factors may lead to biased estimation results. The spatial effects of forest resource abundance on local and surrounding areas are non-linear. However, when we implement the policy of increasing forests and reducing carbon emissions, it must be within a reasonable range. Excessive forest resources may have social costs [56]. It may eventually crowd out the production and living resources of the region and affect economic development.

Hypothesis 3 was verified. The abundance of forest resources can also promote the development of green total factor productivity. This aligns with the great vision of carbon peaking and carbon neutrality. In the long run, the abundance of forest resources will help improve the quantity and quality of economic development, which is consistent with the strategic goals of China's "14th Five-Year Plan" [62].

Hypothesis 4 was not verified. The impact of economic development on the abundance of forest resources does not show any evidence of an EKC curve in the YRD region. Furthermore, the level of economic development inhibits the forest growth. This is mainly due to the expensive land cost in the YRD region and the government's land-use planning. Generally, competing land-use values can lead to changes in land use, which in turn affect increases or decreases in forest cover [63]. In addition, economic and population growth will increase the demand for forest products and may reduce forest resources [44].

#### **6. Conclusions**

Based on the theoretical basis of the resource curse and economic growth, this article attempts to verify the impact of urban forest resource abundance on economic development in the YRD region from the perspective of renewable resources. The research results of this paper provide a reference for the coordinated development of resources and the economy.

The influence of forest resource abundance on economic development in YRD region presents a U-shaped non-linear relationship, and the phenomenon of the resource curse will evolve into resource welfare with the development of society. In addition, the abundance of forest resources can directly promote the improvement of green total factor productivity. However, economic development may inhibit the forest growth, mainly because of the high cost of land in the YRD region. Therefore, there is only a one-way causal relationship between forest resources and economic performance, while economic performance has no feedback effect on forest resources [64].

The impact of forest resource abundance on economic development is affected by many factors, including the initial level of the economy, carbon sequestration potential, energy consumption, urbanization level, science and technology, education level, and other factors. All act together on economic growth.

Although forest resources play a very important role in the critical period of economic transformation and development, we cannot achieve green growth and carbon reduction at the expense of economic development. Economic development and urbanization can go hand in hand with forest development but requires sound management models and additional measures [65].

The YRD region should further adjust and optimize their industrial structure. Each region should implement the industrial dislocation development strategy according to its advantages, give full play to the agglomeration effect and scale effect, and realize the integrated development of modern service and advanced manufacturing industries. Much more attention should be paid to the agglomeration of high-quality talents, capital, and resources. Urbanization is still regarded as a driving force for the upgrading and transformation of the economic structure. Urbanization should gradually realize coordinated development with the economy and gradually transform the extensive development mode into the intensive economic growth mode. In addition, technological innovation is very important to realize the economic development of the YRD region. Especially in the era of the digital economy, increasing investment in scientific research can effectively improve

the level of economic development [66]. Meanwhile, the government should moderately intervene in economic development.

However, the article does have certain flaws. For example, the measure of forest resource abundance is relatively simple on how to manage forest resources efficiently. This is mainly due to the lack of statistical data and methods of forest resources and technology. In future research, forest resources should be refined and classified to analyze better the impact of forest resource abundance on the economy and specific paths and then provide useful suggestions for policymakers.

**Author Contributions:** Conceptualization, Q.Z.; methodology, Q.Z.; formal analysis, Q.Z.; investigation, D.T.; data curation, Q.Z.; writing—original draft preparation, Q.Z.; writing—review and editing, V.B. and D.T.; visualization, Q.Z.; supervision, D.T.; All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the National Social Science Foundation of China (Grant No. 21BJY085) and the Soft Science Project of Jiangsu Provincial Department of Science and Technology (Grant No. BR2021003).

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to other unpublished articles.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

