1. Introduction
Payments for ecosystem services (PES) have received a lot of attention as an incentive-oriented environmental policy tool, especially in the intersection of poverty and ecological fragility [
1,
2]. PES aims at internalizing market externalities by providing compensation to the providers of ecosystem services (ES) and has gained legitimacy in developing countries due to promoting ecosystem conservation and income increase in a “win-win” manner [
3,
4]. In recent years, the continuous warming of the global climate has not only had a huge impact on the yield of traditional crops, but also had a huge impact on the growth of grassland, which once threatened national food security [
5,
6,
7]. To protect grassland ecology and promote herdsmen’s income, the Chinese government initiated a large-scale ecological compensation program, the Grassland Ecological Compensation Policy (GECP), in 2011. However, for government-financed ecological compensation programs, the buyers are not the direct users but a third party acting on behalf of the environment service users [
8]. Affected by a variety of political, social, and other pressures, the tradeoff between PES’s multiple goals makes people doubt PES’s ability to achieve an income increase [
9,
10]. Therefore, it is important to correctly examine the relationship between PES and income and to clarify the internal mechanisms between them. This not only helps to consolidate and improve the grassland ecological compensation policy, but also has important practical significance for the realization of the dual goals of grassland ecology and herdsmen’s income. At the same time, it provides corresponding research methods and theoretical references for the research on the effects of other ecological compensation policies in the future.
Even though there are a lot of studies on the relationship between PES and income, the results are not all the same. Some studies argue that PES programs contribute to income improvements. For example, increased PES participation can promote income growth in China [
11]. However, there is often an emphasis on the tradeoff between multiple goals in government-financed ecological compensation programs, focusing on overall regional equitability distribution [
8]. As a result, fewer funds may be directed toward areas at greater risk of degradation, which are closely associated with high opportunity costs and high ecological threat activities [
12]. Sims and Alis-Garcia investigated Mexico’s PES scheme and found that PES has produced a significant but slight increase in poverty in areas with high participation rates [
13]. In addition, Yang et al. found that the Grain-to-Bamboo Program (GTBP, which is a local PES program to grow bamboo on cropland) negatively affected income through decreased crop production [
14]. In addition, due to the low quality of institutions in many developing countries, there is a high possibility of “elite capture” (elite interests becoming dominant, while the interests of disadvantaged people or those with a traditional lifestyle are ignored [
15,
16]) in the implementation of PES, so there is a risk of widening the income gap between different families [
17]. For example, through the case of PES in China’s Wolong Nature Reserve, Sheng and Wang found that PES participation in promoting income growth is more beneficial to small and medium farmers than large farmers, and this promotion effect can also exacerbate economic inequality [
11].
The research specifically on the impact of GECP on income has not yet reached a consensus, and three different conclusions were formed on the significant, insignificant, and even negative effects of the policy on the herder’s income increase. Hou et al. used microscopic data from 2017–2019 in five Chinese pastoralist provinces to empirically conclude that although the second round of GECP can positively promote the herder’s income increase, it also exacerbates income inequality within herders [
18]; Hu et al. demonstrated that the implementation of the GECP could not greatly influence the reduction in the number of cattle present on any farm size [
19]; while Zhang et al. found that GECP can improve and guarantee the income level of low-income herdsmen and help narrow the gap between rich and poor through a case study approach [
20]. However, the majority of the herdsmen’s income level is lower than before due to insufficient relevant supporting policies. Despite the lack of consensus in the above studies, there is a growing consensus among these types of studies that GECP may not achieve the desired goals if they cannot effectively address the livelihoods of herdsmen.
Generally speaking, although the existing literature has extensively explored PES and income, there is still significant disagreement and a lack of corresponding mechanism analysis, thus providing new empirical evidence and more detailed analysis on this issue is necessary. Second, existing studies focus on the analysis of PES on income growth and are relatively inadequate on income disparity, especially in examining the differences in the average effects of PES across counties. Obviously, comprehensive consideration of income growth and the income gap can help to understand the economic effect of PES more comprehensively. To this end, in order to test the relationship between PES and income growth and income gap, and to clarify its internal mechanism, this paper uses the difference-in-differences (DID) model to empirically test the impact of GECP on herdsmen’s income using county level panel data for 499 counties in six Chinese pastoralist provinces from 2000 to 2019. Then, the mediating effects model is used to empirically test the specific path of GECP on income. Finally, this paper applies the inclusive growth framework to PES programs as a means of assessing differences in how different regions benefit from GECP [
21].
Compared to the research that has come before, this paper may be innovative in the following aspects: First, this study adds to the limited literature on PES and income growth in the Chinese context [
14], and examines the internal mechanism between PES and income growth through the mediating effects of transfer income, optimizing the allocation of labor, and promoting the scale of shed feeding. Secondly, this study uses the inclusive growth model to empirically test the relationship between PES and the income gap between different counties, which helps to examine the relationship between PES and income from the perspective of economic inequality [
22]. Third, previous research on GECP mainly focused on Inner Mongolia, while other provinces were less involved and mainly focused on microscopic cross-sectional data [
23]. However, this paper takes 499 counties in six provinces in western China as the research object, using long-term panel data from 2000 to 2019, which greatly avoids biased results caused by unobserved omitted variables.
2. Policy Background and Theoretical Basis
2.1. Study Area
The study area mainly includes six provinces: Tibet, Qinghai, Gansu, Ningxia, Inner Mongolia, and Xinjiang. It is primarily found in Northwest China. With less precipitation, the climate is temperate continental and alpine. It is an arid and semi-arid area with high terrain. The six provinces in pastoral areas have a total grassland area of 293 million hectares, respectively, accounting for 3/4 of the country’s grassland area. Among them, the grassland areas of the Tibet Autonomous Region and the Inner Mongolia Autonomous Region reached 82 million hectares and 79 million hectares, accounting for 68.1% and 68.8% of the total land area of each region. The number of cattle, sheep, and large livestock in the six provinces of pastoral areas in 2020 is 38.378 million, 162.57 million, and 43.274 million heads, respectively, accounting for 40.1%, 53%, and 42.2% of the national total.
2.2. Policy Background
In order to prevent grassland degradation and take the livelihoods of herdsmen into account, the Chinese government enacted the “Guidance on Implementation of the Grassland Ecological Protection Subsidy and Incentive Mechanism Policy” in 2011, which marked the initial establishment of the GECP. It is also the program with the largest matching funds and the largest coverage in grassland ecological protection to date. Specifically, in the first round (2011–2015), GECP funds are mainly divided into the grassland prohibition (GP) subsidy, the grass-livestock balance (GLB) subsidy, and the production material subsidy for herding households. Among them, the GP subsidy is mainly for grasslands with poor living environments and serious grassland ecological degradation, located in big rivers, or water conservation areas, whereas the GLB subsidy is for grasslands other than the grassland prohibition area. The GLB subsidy is primarily intended to calculate the reasonable livestock carrying capacity of grasslands based on carrying capacity, and then the government will reward herdsmen for meeting requirements. According to statistics from the National Forestry and Grassland Administration, in the first round of GECP, a total of 253.4 million hectares of grassland were covered, while the subsidy funds for grassland prohibition and grass-livestock balance could reach 1.559 billion dollars per year, accounting for 81.30% of the total amount of subsidy funds.
Following the implementation of the first round of GECP, some studies reported that the low standard of compensation and laxity of regulation may be the primary reasons for ineffective programs [
8]. In 2016, the Ministry of Agriculture and the Ministry of Finance of China jointly promulgated a new round of the GECP (2016–2020) for this purpose. The GP and GLB subsidies were increased from 6 to 7.5 and 1.5 to 2.5 (CNY/mu/year), respectively, in the new round of policies, while production material subsidies were eliminated. Local governments are also required to increase supervision and establish mechanisms for reward and punishment. Monitoring results show that over the 10 years following GECP implementation, total grassland vegetation cover has increased from 51% in 2011 to 56.1% in 2020, and the production of fresh grass can be as high as 1.1 billion tons. In addition, herdsmen in the policy implementation area are able to obtain 98.98
$ per capita per year, and transfer income has increased by 212
$ per household. To continue to consolidate and enhance the achievements in grassland ecological protection, the Chinese government continues to implement the third round of GECP in 2021, increasing investment funds and further expanding the scope of implementation. The compensation area in 2021 is shown in
Figure 1.
It is noteworthy that in order to accelerate the dual goals of grassland ecological protection and increasing herdsmen’ income, a range of supporting policies based on GECP have been issued by local governments. The program attempts to establish a modern, large-scale livestock production system in order to sustain and expand the project’s implementation effect. It makes sense to speed up the transformation of herdsmen’s production through subsidies to infrastructure and productive assets. They assist the herdsmen in improving the scale reward and production efficiency in order to offset losses. To this end, the government subsidized the construction of sheds and the development of artificial grass in the herding areas and adopted the “government support and self-financing of the herdsmen” method in order to encourage the herdsmen to invest in the production of herding.
2.3. Theoretical Basis
From a neoclassical economic perspective, the GECP will reduce herdsmen’s grazing activities through both incentives and supervision, but with a substantial increase in the cost of production compared to the previous system. If herdsmen produce as an independent economic agent, they will alter the allocation of factors of production in order to maintain their returns when the quantity and price of a particular factor of production change. The fundamental question of whether GECP can achieve income growth thus lies in the trade-off between livestock producer’s grazing losses and policy gains. With this in mind, this paper will conduct an in-depth analysis of the path of GECP benefits in order to explain possible changes in the herdsmen’s incomes. From the above analysis, it can be seen that the source of the herdsmen’s income is divided into two levels: first, the direct effect of the GECP funds; second, the indirect effect of GECP by influencing herdsmen’s production and lifestyle. Next, this paper will analyze the direct and indirect effects of GECP in detail. The framework diagram of GECP’s impact on herder’s income is shown in
Figure 2.
(1) Direct effect. The GECP will grant direct subsidy funds to herdsmen participating in the project to improve their transfer income (TI). Furthermore, subsidy funds may have heterogeneous income-increasing effects for herders with varying levels of poverty. The impact of subsidy funds on the herdsmen’s income will have diminishing marginal returns as household capital increases while controlling for potential confounding factors. That means subsidy funds will have a greater marginal benefit for severely poor herdsmen than for other herdsmen in general. For example, subsidy funds account for a larger share of income for poor households and a smaller share for other households, which implies that remuneration funds have a greater marginal growth effect on poor households. At the macroeconomic level, the number of poor households is higher in economically backward areas, which results in a greater marginal benefit of grassland ecological compensation funds for backward regions than for developed ones, which in turn helps narrow the income gap between the different regions.
(2) Indirect effects. Since the implementation of the policy may alter the production and lifestyle of the herdsmen, this paper mainly analyzes the indirect effect of GECP from the two aspects of labor transfer and livestock scale of barn feeding.
For the labor transfer (LT). The GECP affects income through labor transfer in two main ways: first, the prohibition or grazing restriction reduces the labor input of grazing production and puts the liberated labor into other industries for production [
24,
25], increasing the time spent on non-farm or leisure [
26]. Second, it enhances human capital and provides external employment opportunities [
27,
28]. For example, GECP can provide grassland ecological protection jobs for poor herdsmen, which in turn will have an important impact on their income [
29]. In terms of impact on income gap, herdsmen in backward areas have little room for competence, which means that it is difficult for them to build labor skills that match the needs of the labor market [
30]. Therefore, herdsmen in backward areas have a lower probability of obtaining either off-farm employment opportunities or higher labor returns. Consequently, there is a possibility of widening the income gap between herdsmen in different areas.
For the livestock scale of barn feeding (BF), the GECP has reduced the livestock scale of pasture feeding (PF) in the program area; herdsmen must meet the daily needs of livestock through barn feeding (BF), so the program will inevitably expand the livestock scale of BF. In terms of impact on income gap, the motivation–opportunity–ability theory posits that herdsmen are known to make feeding changes based on their knowledge and abilities. In economically developed regions, herdsmen generally have higher capacity and are more likely to switch from PF to BF with policy support, further promoting BF operations to achieve income growth. For the backward areas, the majority of herdsmen are not able to bear the huge cost of BF, so they have to reduce the number of livestock to maintain their livelihoods, which may reduce income. In turn, GECP may widen the income gap between regions by affecting livestock scale of barn feeding.
3. Data and Methodology
3.1. Econometrics Model
(1) Baseline model. The double difference in difference (DID) means that the time change of the dependent variable in the experimental group is subtracted from the time change of the dependent variable in the control group to obtain the effect of the experiment on the experimental group. “Experiment” in this paper refers to the 2011 Guidance on the Implementation of Grassland Ecological Protection Subsidy and Incentive Mechanism Policy, which the Chinese government issued and put into action. Taking 499 counties in 6 provinces in Western China as observation samples, the experimental group consisted of 332 counties that participated in GECP, and the control group consisted of 145 counties that did not participate in GECP. Therefore, in this paper, the double difference refers specifically to the changes in the per capita income of herdsmen who participated in GECP between 2000 and 2019 minus the changes in the per capita income of herdsmen in counties that did not participate in GECP to observe the impact of GECP on herdsmen’s income. The time variable (time) is the dummy variable before and after the program implementation in 2011. The estimating equation to test the income growth of GECP is as follows:
The where and represent the county and year, and denotes the relevant indicators of income in the county , including the level of rural per capita income. The coefficient of the interaction term between policy variables and time variables is the concern of this paper, which is expressed as the average treatment effect of GECP on income. is the individual fixed effect, is the time fixed effect, and is the random error term. is a set of control variables, including the degree of traditional financial development (FIN), the level of education (EDU), urbanization (URB), the level of agricultural modernization (AGR), and the degree of government participation in the economy (GOV).
(2) Dynamic effect model. This model was used to test the hypothesis of the parallel trend of DID, and to further examine the dynamic changes in the income growth of GECP. Referring to the Event Study Approach proposed by Jacobson et al., this paper constructs the following model [
31]:
denotes a series of estimates from 2000–2019, and the other variables are the same as in the baseline regression.
(3) Mediating effect model. Consistent with Hayes et al. [
32], the two-stage process mediation model below is proposed in order to examine whether the transfer income, labor transfer, and the livestock scale of barn feeding play an intermediary role in the process of GECP increasing the income:
is denoted as the mediating variable, and the other variables are the same as in the baseline regression.
(4) Income gap model. To examine the impact of GECP on the income gap, this paper borrows from the inclusive growth analysis framework proposed by Zhang and Wan [
21] and incorporates the interaction term (
) between policy and the lagged term
in model (1), and the estimated equation is shown below:
Thus, Equations (3) and (4) is the effect of GECP (policy) on the income (
).
It can be seen that the effect of GECP on income (
) is divided into two parts: the first part,
, shows the effect of GECP on
while all other conditions do not change; the second part,
, is expressed as the effect of the previous period’s income (
) on the current period’s income (
) through GECP. Specifically, if
> 0, counties with larger income in the previous period benefit more from GECP; on the contrary, if
< 0, counties with smaller income in the previous period benefit more from GECP; furthermore, if
= 0, it means that GECP does not affect the income gap. It should be noted that in estimating Equation (6), there may be endogeneity problems using the least squares method because the explanatory variables include the lagged terms of the dependent variable, so the systematic moment estimation (GMM) method of Blundell and Bond [
33] is used in this paper.
3.2. Variable Selection
Mediating variables. In this paper, transfer income, labor transfer, and livestock scale of barn feeding were selected as mediating variables. Among them, transfer income was expressed using per capita transfer income. Labor force allocation was expressed using the annual variation of primary industry employees at the county level. The number of large-scale farms was selected as a proxy variable for barn feeding, and the greater the number of large-scale farms, the larger the livestock scale of barn feeding. In this paper, farms with an annual sheep slaughtering capacity of 100 or more heads are defined as large-scale farms according to the division of the Ministry of Agriculture and Rural Affairs of China.
Control variables. Drawing on the studies of Qi et al. [
34] and Tang et al. [
35], the control variables selected in this paper include (1) the degree of traditional financial development, as measured by the ratio of the loan balance of regional financial institutions to regional GDP. (2) The level of education, as measured by the proportion of illiteracy population in rural areas above 15 years old. (3) Urbanization, expressed as the proportion of total population at the end of the year relative to household population. (4) The level of agricultural modernization, expressed as the proportion of the value added of the primary sector to GDP. (5) The degree of government participation in the economy, expressed as the ratio of county-level fiscal expenditure to county-level GDP.
3.3. Data Description
To comprehensively examine the impact of GECP on herdsmen’s income, this paper constructs 20 years panel data on county socio-economics for 499 counties in six Chinese pastoralist provinces. Specifically, firstly, considering that GECP was fully implemented in 2011, in order to obtain more diverse data to improve the accuracy and unbiasedness of the estimation results, this paper sets the sample time span as 2000–2019. On the one hand, it can satisfy the need for a parallel trend test with a double difference; on the other hand, it can estimate the long-term dynamic effect of GECP on income. Second, due to more missing data in areas such as Qinghai Province and the Tibet Autonomous Region, the final study involved 499 counties after exclusion, including 346 in the policy group and 153 in the control group. The data are obtained from the China County (City) Social and Economic Statistical Yearbook, the China Regional Economic Statistical Yearbook, and the district and county statistical bulletins. It should be noted that all nominal variables in the data are deflated to 2000 using provincial rural CPI. Meanwhile, for some counties with missing individual indicators, this paper selects the municipal indicators where the missing counties are located for interpolation. The descriptive statistics of each variable are shown in
Table 1.
5. Conclusions
Considering the profound impact of continuous climate change on the grassland ecosystem [
5], we believe that it is necessary to test the implementation effect of GECP from a larger time and space dimension, so as to provide suggestions for improving the policy. The grassland ecological compensation policy is one of the most important ways that China protects the environment. It aims to drive the transformation and upgrading of grassland livestock production and operations, improve herdsmen’s income, and promote the protection and improvement of grassland ecology with the help of performance assessment incentive funds and related supporting policies. Therefore, a more comprehensive assessment of GECP is important not only for understanding the performance of grassland ecological compensation in China, but also for enriching the general understanding of the effects of ecological compensation policies.
The GECP covers the major pastoral areas of China, and the large scope of policy implementation provides a valuable opportunity to identify the effects of large-scale ecological compensation policies. Based on county-level panel data from 2000 to 2019 for 499 counties in six provinces in China’s pastoral areas, this paper assesses the impact of GECP on income growth and the inter-regional income gap, the latter providing a new perspective for ecological compensation policy evaluation. The study found that in terms of income growth, GECP can significantly increase herdsmen’s income, and the intensity of the effect on income growth gradually becomes stronger in the first 5 years of the policy and then flattens out; the mechanism analysis shows that the policy mainly achieves herdsmen’s income growth through the direct effect of compensation funds and the indirect effect of transferring labor and improving the livestock scale of barn feeding. In terms of the income gap, counties with relatively higher per capita income levels of herdsmen benefited more from the policy, indicating that the policy widened the development gap within regions.
The study in this paper responds to the research that has already been done on the different effects of ecological compensation policies on income. It also gives strong evidence that ecological compensation policies have a positive effect on income. On the one hand, this paper argues that GECP significantly increases the average income of herdsmen in the policy implementation area. The mechanism analysis shows that the policy can promote the transformation and upgrading of herdsmen’s production and lives through the paths of influencing compensation funds, labor distribution, and the scale of bred feeding, and thus increase income. On the other hand, this paper finds that the effectiveness of these paths is heterogeneous across different economic development regions, which may widen the income gap between regions. Herdsmen in lagging regions may not be able to afford the high cost of production transformation, and the policy implementation may be further exploited by the non-compliant use of funds and “elite capture”. As a result, the policy should pay attention to and increase support for herder production transformation in backward areas, effectively reduce the costs and risks of herder transformation, and ultimately achieve inclusive income growth for herdsmen. Of course, there are some shortcomings in this study. For example, although this study has grasped the overall effect of GECP on herdsmen’s income from the county level, the responses to the policy may vary in different regions. The heterogeneity of income has not been analyzed empirically, and the formation mechanism of heterogeneity has not been discussed in depth. This will also be one of the directions that follow-up research needs to focus on.