1. Introduction
As an essential power source for national economic development, agriculture has received significant attention from the Party and the State. In order to achieve sustainable growth in agricultural output, China has been increasing its investment in agricultural research over the past two decades. Public agricultural research investment exceeded that of the United States for the first time in 2009 [
1]. As of 2017, China’s total agricultural inputs have accumulated 1102.4 billion. The increasing number of inputs in the agricultural sector has also made it easier for farmers to access water, electricity, farm machinery, etc. According to the National Bureau of Statistics 2020 statistics, the power generation capacity of rural hydropower stations was 2,423,689 million kilowatt-hours, the number of small tractors nationwide reached 1.72 million units, and the national crop mechanization rate reached more than 70%. However, the extensive use of agrochemicals in agricultural production has caused severe environmental pollution, posing a threat to agricultural products and rural environmental safety. The Second National Pollution Source Census indicates that one of the environmental pollution sources within China is agricultural pollution sources. Data in the China Ecological and Environmental Status Bulletin 2020 also show that the utilization rate of chemical fertilizers for the three major food crops of rice, wheat and corn in 2020 was 40.2%, the utilization rate of pesticides was 40.6%, and the total utilization rate of livestock and poultry manure was only 75%. Therefore, agricultural development should ensure the balance of the supply and demand of agricultural products under the rigid constraint of resources and fully consider the carrying capacity of resources and environmental protection issues. It has been discovered that agricultural green development is the key to solving China’s agricultural resource and environmental concerns [
2]. Increasing green total factor productivity in agriculture is an efficient method of achieving green agricultural development [
3,
4]. In China, the contribution of agricultural green total factor productivity to agricultural output is as high as 60%, and it plays a vital role in ensuring China’s food security and contributing to high-quality agricultural development [
5].
China has made amazing gains in economic development since the reform and opening up, becoming the world’s second-largest economy and contributing more than 30% to the global economy for several years in a row. The “demographic dividend” is without a doubt one of the most important elements driving China’s fast economic expansion. The “demographic dividend” is rapidly disappearing. According to the definition of the World Health Organization (WHO), if the proportion of older individuals over the age of 60 exceeds 10% of the total population or if the proportion of older persons over the age of 65 reaches 7%, a country or territory has become an aging society. According to the information from the fifth national census in 2000, the proportion of the elderly population over sixty years old in China was 10.93%. Taking this as the standard, China has been an aging society since 2000. In recent years, population aging in China has been intensifying, and this indicator has continued to climb. As of the seventh census in 2021, China’s old population has surpassed 264 million people, accounting for 18.7% of the total population. Population aging will bring about a shrinkage in the total population and labor force, which will lead to potential socioeconomic problems, such as a decrease in the economic growth rate [
6].
The increase in the proportion of the aging population will also have an impact on the demographic structure, and the change in demographic structure will affect a variety of economic conditions. At the same time, economic development cannot be separated from energy consumption [
7], and as a major player in the world electricity market, China’s electricity consumption has been in the forefront of the world [
8]. According to statistics, China overtook the United States to become the world’s top electricity consumer in 2011. According to resource allocation theory, there is a mutual substitution relationship between agricultural labor and agricultural machinery. Agricultural machinery will be underutilized if too much labor is invested in agricultural production. In the process of effective resource allocation from labor-intensive to agricultural capital and energy-intensive production, its energy consumption (electricity consumption) will generally increase significantly [
9]. Along with the shift in the type of resource use and the rise in people’s income levels, the energy consumption intensity gradually changes from the initial rising state to a declining state [
10]. As China’s economy enters into a new normal, the population development and residents’ lifestyles are also changing dramatically, and China’s population structure is aging and gradually developing in depth. In contrast, the increasing aging population will weaken the agricultural labor supply. On the other hand, the increasing aging population will also force the upgrading of agricultural technology, which will gradually replace the traditional crude production methods. Agricultural technical efficiency and agricultural technological progress have jointly promoted agricultural green total factor productivity.
China is currently in the midst of a period of rapid economic growth. It is vital to boost agricultural green total factor productivity in order to speed the building of the development path of agricultural modernization. China has clearly recommended to “increase total factor productivity”, concentrating on the agricultural sector to enhance agricultural green total factor productivity, focus on rural ecological conservation and promote agricultural modernization in the report of the 19th National Congress of China. Based on this, our paper selects the provincial panel facts of China from 2000 to 2019 to examine the long-term relationship between population aging, renewable energy consumption and agricultural green factor productivity. The marginal contributions of this paper may be reflected in the following aspects. First, based on provincial data, this paper investigates the effects of population aging and renewable energy consumption on agricultural green total factor productivity in each province of China. The aging population is one of the most prominent issues facing China in the new era, while agriculture is the foundation of the nation. Exploring their relationship is of great practical significance for promoting agricultural production and realizing rural revitalization. Second, this paper addresses the causality test between population aging, renewable energy consumption and agricultural green total factor productivity, which deepens the understanding of the long-term effects of population aging and agricultural electricity use on agricultural green total factor productivity. Finally, this paper can enrich the theoretical study of population aging and renewable energy consumption and provide a reference basis for the government to formulate policies to improve agricultural green total factor productivity.
The rest of the paper is organized as follows. The second part presents the literature review, the third part describes the methodology used, the fourth part contains the analysis and discussion of the empirical results, and the fifth part contains the conclusion and policy recommendations. References are given at the end of the paper.
2. Literature Review
Total factor productivity (TFP) refers to the additional production efficiency achieved under the condition of a given level of inputs of various factors of production. Not only can it be used to explore the sources of economic growth, but it is also often used as a measure of scientific and technological progress [
11]. Unlike traditional total factor productivity, green total factor productivity (AGTFP) in agriculture is a more accurate indicator of production efficiency that includes resource and environmental pollution constraints [
12,
13,
14]. Existing research suggests that green total factor productivity growth in agriculture largely depends on advances in agricultural technology [
15,
16]. Technological progress has become a significant driver of agricultural output. Human capital is undoubtedly direct among the various factors influencing technological progress [
17]. According to the life cycle theory of human capital stock, the human capital stock of the agricultural labor force shows an “inverted U-shaped” change [
18,
19]. The highly educated labor force is likely to be attracted to areas with higher levels of economic development. Studies have shown that human capital not only enhances the ability of a country or region to develop its technological innovation but also indirectly drives the innovation capacity of other regions that have adopted the technology [
20]; Nelson and Phelps [
21] proposed that the stock of human capital has a positive impact on the dissemination of innovative technologies. Romer [
22] believes that the stock of human capital plays a decisive role in technological growth. In other words, the larger the stock of human capital, the faster the absorptive capacity and diffusion speed of technological innovation. Ang et al. [
17] showed that the degree of influence of human capital on technological innovation and diffusion is different if a country has a low level of human capital. Then, after the introduction of high-tech products, immature human capital is more suitable for imitating the application of new technologies due to the lack of a technology-receptive population, while experienced human capital is more suitable for the innovation of technology.
As the aging of the population accelerates, many issues are becoming more prominent. At present, there is no unified educational conclusion about the impact of population aging on human capital. Overall, the influence of the populace getting old on human capital can be divided into three primary perspectives. The first view is that population aging has a depressive effect on human capital. Choi and Shin [
23] explored the impact of population aging on human capital through an OLG model, suggesting that population aging reduces the labor supply, thus significantly weakening the growth potential of the capital stock and becoming a potential threat to economic growth. Bairoliya and Miller [
24] conducted a study on demographic changes in China. They found that population aging leads to favorable fertility policies by the government, while an increase in fertility leads to a slight decrease in per capita income and human capital investment. A 1% increase in the share of the populace over the age of 65 is associated with a 0.3% decrease in per capita education expenditure, which has a dampening effect on average educational attainment. Khor et al. [
25] studied the stock of human capital in China. They noted that although the amount of human capital in China is increasing, it is still low compared to other middle-income-level countries. Increasing aging leads to a decline in the labor force population, and a shortage of human capital in the age-appropriate labor force can lead to a stagnation of the country’s economic development. The second view is that the aging of the population can promote human capital. Some scholars have studied the relationship between aging and human capital investment, stating that aging promotes increased opportunities for human capital investment, thereby reducing the dampening effect of aging on per capita output [
26]. It has also been shown that population aging increases the productive capacity and significantly reduces the economic cost, thereby creating incentives for human capital investment through the overlap of generations (OLG) model [
27]. In the early stages of aging, a higher share of the middle-aged population will provide society with a large amount of skilled labor, which will reduce the demand for young labor, while the current high level of aging will provide more skilled labor for the future, thus increasing the productive capacity of society and reducing the cost of aging. Čiutienė and Railaitė [
28] argue that population aging will shift social attitudes, thus making young people more education-oriented. The aging population can make fuller use of their experience and contribute to deepening human capital. Other arguments propose that the impact of the populace getting older on human capital is complex. Zhang et al. [
29] used an overlapping generations model based on imperfect public education and pension systems and found a hump-shaped relationship between population aging and human capital investment. When aging is high, most people tend to reduce public human capital investment by lowering tax rates, resulting in a trend where human capital investment initially rises and slowly declines over time. Gradstein et al. [
30] also found that population aging has a mixed effect on human capital investment and is not a simple monotonic curve.
Renewable energy consumption is also one of the essential factors influencing the total green factor in agriculture. Established studies have analyzed the relationship between renewable energy consumption and human capital, indirectly demonstrating the correlation between renewable energy consumption and green total factors in agriculture. Ozcan et al. [
31] analyzed the dynamic impact of renewable energy consumption in Turkey using panel data, and the results showed a significant positive relationship between renewable energy consumption and human capital stock. Alvarado et al. [
32] found through their study that human capital reduces the consumption of non-renewable energy. This finding is in line with Yao et al. [
33], whose findings indicate that human capital promotes the use of renewable energy. The relationship between population aging and renewable energy consumption is not uniformly answered by academia. Bano et al. [
34] found through a study of BRICS countries that population aging is one of the positive factors that promote renewable energy consumption. Zhang et al. [
35], through a study of China’s aging population, point out that there are significant differences in energy consumption habits between older and younger people, but overall, both have a positive impact on renewable energy consumption. On the other hand, in a study by Willis et al. [
36], it was found that older people are less receptive to renewable energy and are less likely to adopt renewable energy compared to younger people. Tarazkar et al. [
37] obtained the same conclusion by studying how young people contribute more to renewable energy consumption than older people.
By combing the literature, we found that the definition of green total factor productivity in agriculture is more relevant, and it is mainly influenced by technological progress [
15,
16]. Among the many factors that influence technological progress, human capital is, again, the most direct factor [
17]. Most scholars have indirectly demonstrated the impact that these factors bring to green total factor productivity in agriculture by verifying the relevant factors that affect human capital. However, when discussing population aging and renewable energy consumption, there is no uniform academic proof of its unidirectional relationship with human capital. As far as the method is concerned, the accuracy and reliability of the obtained estimation results are low. In contrast, few scholars have directly discussed the effects of population aging and renewable energy on green total factor productivity in agriculture. Based on the above gaps, this paper uses provincial panel data from 2000 to 2019 in China to test the relationship between population aging, renewable energy consumption and green total factor productivity in agriculture using vector autoregressive (VAR) models to provide a reference for the government to formulate relevant policies to enhance green total factor productivity in agriculture.
5. Conclusions and Policy Implications
In this study, we examined the effects of population aging and renewable energy consumption on green total factor productivity in agriculture by analyzing panel data from 30 provinces in China for 20 years (2000 to 2019) using impulse response models. We first performed cross-sectional correlation tests and unit root tests on the data and then verified the long-run cointegration relationship between the three variables using the ADF test. The empirical consequences exhibit that there is a long-run cointegration relationship between population aging, renewable energy consumption and agricultural green total factor productivity. However, in contrast, the aging population has a more significant impact on agricultural green total factor productivity. In addition, based on the above analysis, we also found that the effect of renewable energy consumption on agricultural green total factor productivity is weakly positive. However, population aging has an inverse inhibitory effect on renewable energy consumption, and there is a negative relationship between the two. In the case of China, the trend of population aging cannot be changed in the short term, and the process of population aging in China will begin to hinder the increase in the agricultural green total factor rate, which will have a suppressing effect on agricultural green total factor productivity in the short term, but its impact on agricultural green total factor productivity is still positive in the long term.
Based on the above study results, we put forward the following policy recommendations: First, local governments ought to supply full play to their role in agricultural infrastructure construction, and perfect agricultural infrastructure provides a good platform for agriculture production. Second, local governments should continue to increase technological investment; develop high technology, high mechanization and efficient agriculture; create a high-quality workforce; and effectively promote agricultural modernization and reform. Third, the quality of the existing labor force should be improved, mainly for the young labor force, to enhance its absorption and application of new technologies, thus increasing the stock of human capital and improving its agricultural production efficiency. In addition, it is necessary to attract highly qualified personnel from other fields to enter the field of agricultural production to inject fresh and developmental blood into the field of agricultural production. Finally, learning from advanced foreign experience and introducing advanced management strategies will help to improve China’s human capital stock.
The research in this paper innovates on the basis of previous studies and focuses on population aging, an important issue in agricultural production, but there are some limitations: the research between the three factors of population aging, the degree of renewable energy consumption use and agricultural green total factor productivity improvement is not systematic enough. In addition, different provinces and cities in China have different levels of economic development, population size, living concepts and habits, and there are also differences in agricultural production. It is suggested that we can focus on multi-faceted, wide-ranging and multi-level research in the future, refine the factors influencing green total factor productivity in agriculture and implement differentiated management according to local conditions.