**1. Introduction**

From a worldwide perspective, energy, resource and ecological emergencies have become serious challenges. Economist Daly [1] pointed out that man-made capital has become relatively abundant and the constraints to human development have been transformed into scarce natural capital. Zeb et al. [2] argued that the depletion of natural resources and the adverse effects of environmental degradation, including desertification, drought, land degradation, lack of freshwater resources and loss of biodiversity are increasing and worsening the various challenges facing humanity. Forestry has multiple benefits and can provide practical solutions to address these issues. The green development of forestry and the improvement of forestry eco-efficiency have become the focus of attention of the international community [3,4].

As an important basic industry of the national economy, forestry plays a pivotal role in human societal development. For a long time, China's forestry economic growth mode has been characterized by a large number of factor inputs; this is a crude economic growth mode relying on the massive consumption of resources to promote [5] it. Under the current conditions of resource scarcity in China, this type of crude forestry economic growth will

**Citation:** Tan, J.; Su, X.; Wang, R. Exploring the Measurement of Regional Forestry Eco-Efficiency and Influencing Factors in China Based on the Super-Efficient DEA-Tobit Two Stage Model. *Forests* **2023**, *14*, 300. https://doi.org/10.3390/f14020300

Academic Editors: Noriko Sato and Tetsuhiko Yoshimura

Received: 19 January 2023 Revised: 1 February 2023 Accepted: 1 February 2023 Published: 3 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

encounter a "limit"; when growth approaches its "limit" or people are aware of this "limit", economic growth needs to improve the use efficiency of input factors of production to break through this "limit", that is, to increase the share of the total factor productivity contribution to forestry economic growth. According to relevant economic theories, the growth of output can depend on factor inputs as well as technological progress [6,7]. The development of China's forestry industry is so rapid that it is obvious to measure it numerically, but the question remains: what is the real quality of this forestry development? In today's increasingly prominent resource and environmental problems, ensuring rapid economic development while reducing environmental pollution and resource waste is not only a sizable challenge for social development, but also one of the urgent tasks facing the future development of forestry. Therefore, a scientific and objective discussion of the quality of forestry development is conducive to a better understanding of what will be the sustainable development level of forestry in the future [8–10]. Schaltegger and Sturm [11] proposed an eco-efficiency concept, which has been widely recognized by scholars in various fields. Specifically in the field of forestry, eco-efficiency is a measure of the level of sustainable development of forestry, and its objective is to measure whether forestry can minimize environmental pollution and resource consumption while achieving multifaceted value in a comprehensive manner, with the premise of ensuring the quality of forest products [12]. Focusing on FECO improvement is conducive to advocating for modern forestry development through the concept of coordinated and sustainable development of society, economy and ecology [13,14].

The following are this paper's main contributions: (1) Existing studies mainly study productivity and explore its efficiency from the perspective of production, while the issue of forest efficiency from an ecological perspective has rarely been addressed; this paper considers the inputs and undesired outputs and measures regional forest eco-efficiency in China, which is a useful supplement to the existing studies; (2) Existing studies mainly focus on specific regions and lack comparative studies between regions; this paper provides theoretical support by comparing the east, central and west regions; (3) Exploring forest eco-efficiency in the context of sustainable development and proposing corresponding policies can provide a reference for regional green development. Therefore, this paper adopts the super-efficient DEA model to measure the forestry eco-efficiency of 30 Chinese provinces and cities (except Hong Kong, Macao, Taiwan and Tibet) for 14 years from 2008 to 2021, and then introduces the Tobit model to analyze the influencing factors for forestry eco-efficiency in order to better understand the sustainable development level of forestry and provide some theoretical support for the sustainable development of modern forestry in the future.

#### **2. Literature Review**

#### *2.1. Connotation of Eco-Efficiency in Forestry*

Eco-efficiency is the ratio of the value of economic and social development (GDP) to the physical amount of resource and environmental consumption, which creatively connects three indicators: resources, economy and environment. It emphasizes the unity of environmental and economic benefits, establishes a connection between the best economic and environmental goals and provides a link between regions; it provides an important evaluation tool for the sustainable development of regions and industries, and becomes an important reference for policy makers [15,16]. This concept is generally accepted and widely used in the evaluation and research of the forest industry by domestic and foreign scholars, such as Wu and Zhang [17]. They considered that the eco-efficiency of the forest industry refers to the direct impact on the forest's ecological environment caused by the inputs of technological improvement and environmental management, such as air quality improvement and wastewater treatment, in order to ameliorate the ecological impact brought by the forestry industry, i.e., industrial efficiency in the forestry industry. According to Chen et al. [18], FECO is a measure of the sustainable development of forestry, and its objective is to measure whether forestry can minimize environmental pollution

and resource consumption while ensuring the quantity and quality of forest products and achieving its multifaceted value in a comprehensive manner. Hong et al. [19] pointed out that for forestry to be sustainable, coordination between input and output factors should be ensured. Zheng and Yin [20] argued that FECO facilitates a win-win input and output relationship between economic and social benefits.

## *2.2. Measurement of FECO*

Academics have analyzed FECO from different perspectives, and the differences are mainly reflected in the research methods and regional selection. In the process of measuring FECO, the stochastic frontier approach (SFA), the ratio method and the DEA evaluation model are mainly used in China. For example, Can et al. [21] used the SFA method to measure the ecological efficiency of plain forestry and analyzed the degree of ecological contribution of farmland forest networks and small forests to total agricultural output value, plantation output value and livestock output value. Weerawat et al. [22] used the ratio method to analyze several rubber plantation areas in Thailand and made recommendations. Most studies using the DEA evaluation, such as Li et al. [23], measured the forestry inputoutput efficiency using the DEA model, but the output indicators they selected did not reflect the social benefits of forestry; in addition, the only reflected the situation in 2006. Tian and Xu [24] measured the forestry input-output efficiency from 1993 to 2010 in China. At the local level, Lai and Zhang [25] used the super-efficient DEA model to measure the forestry input-output efficiency of 21 cities in Guangdong province and ranked and classified them; Zang et al. [26] measured the technical efficiency of forestry production and its influencing factors from the perspective of forestry production in Chongqing. Zhang and Kang [27] selected the super-efficient DEA-Tobit model to measure forestry production efficiency in 30 Chinese provinces from 2000 to 2014, and pointed out that its efficiency is lower, with significant spatial divergence. Luo et al. [28] also used the DEA model to measure the forestry efficiency of each province and further analyzed the spatial differences using the Gini coefficient and Moran index and concluded that forestry efficiency increased year by year but was still low in general. Tian et al. [29] used the C2R-DEA model (DEA model without considering returns to scale) and the SE-DEA model to measure forestry production efficiency in China. In 2012, Tian et al. [29] analyzed and measured the inputoutput efficiency of forestry using the super-efficient DEA model.

#### *2.3. Influencing Factors of FECO*

In recent years, many scholars have used DEA measurements to evaluate regional FECO and constructed an index system to study the key factors affecting FECO in the region. For example, Zheng et al. [30] examined the impact of industrial agglomeration on FECO through an econometric model and found that the level of industrial agglomeration and eco-efficiency in provinces with high levels of forestry industry development in China showed different degrees of increase during the study period. Chen and Geng [31] pointed out that the economy of scale efficiency of the forestry industry would be affected by property rights factors, local government intervention behavior, market concentration, market entry barriers and externalities. Jiang et al. [32] argued that the industrialization of forestry is an objective requirement, an inevitable result of the market economy and an effective way to improve efficiency in modern forestry. Hou [33] believed that the economic productivity or environmental productivity of forestry can be improved through the division of labor and specialization. Li and Tang [34] considered that the rationalization of the industrial structure is an effective means to improve the efficiency of forestry. Tian and Xu [24] measured the input-output efficiency of forestry in China from 1993 to 2010 and analyzed its influencing factors in depth. Zang et al. [26] measured the technical efficiency of forestry production and its influencing factors from the perspective of forestry production of Chongqing foresters. Zhang and Xiong [35] concluded that forestry ecological construction and protection, forest ecological compensation and forestry prevention and control inputs have negative and significant effects on the comprehensive FECO.

The studies that have been conducted lack an analysis of forestry eco-efficiency, and in the field of forestry in China, a unified definition of forestry eco-efficiency has not been clearly established. This is mainly because, although the development of forestry has the dual attributes of economic value and ecological value, there are problems such as long investment recovery cycles and economic externalities, which, together with the emergence of natural and man-made disasters, do not guarantee that forestry development can meet people's expectations. In the process of pursuing the economic value of forestry, people gradually ignore the ecological benefits. Therefore, this paper measures the forestry ecoefficiency of 30 provinces in China from the provincial panel data of 30 provinces from 2008–2021 (due to limited data sources, Hong Kong, Macao, Taiwan and Tibetan areas are not considered for the time being), and further explores the regional differences and spatial and temporal characteristics of forestry eco-efficiency. On this basis, the factors affecting forestry eco-efficiency are explored to better protect the diversity of forestry ecosystems. While the forestry ecological economy is developing continuously, we should also pay attention to the protection of forestry ecology, so as to realize people's expectations for a better ecological environment in the near future.
