An important task of China’s agricultural development is to achieve modernization in all respects. The rural revitalization strategy was first introduced in the report to the 19th National Congress of the Communist Party of China. This strategy now stands as the general guiding principle and central task of China’s agricultural initiatives in the new era and serves as a pivotal move toward advancing agricultural modernization. Taking into consideration the current situation of China’s agricultural development, the authors analyze the factors driving agricultural modernization and project the trajectory of agricultural modernization by 2035. The findings indicate that China has created a conducive institutional and development environment in production, consumption, industry, science and technology, trade, etc., thereby laying a solid foundation for its agricultural modernization. Projections suggest that by 2035, China will establish itself as the world’s preeminent nation in agricultural production and consumption, a powerhouse in agricultural industrialization and agricultural product trading, and a leading country in agricultural science and technology. However, China still faces tremendous challenges in terms of consumption structures, quality requirements, industrial development, format innovation, production methods, service functions, scientific and technological levels, and personnel structure. Therefore, on the path to agricultural modernization, China still needs to advance the structural reforms on the agricultural supply side, shift its agricultural production and operation methods, elevate its level of opening up in agriculture, and foster a deeper integration between urban and rural areas.

The Guangdong-Hong KongMacao Greater Bay Area (the Greater Bay Area, the GBA) aims to facilitate in-depth cooperation among the Guangdong, Hong Kong, and Macao regions to create a worldclass bay area-based urban agglomeration. This endeavor seeks to guide China’s economy toward high-quality development and comprehensive opening-up. This paper examines the challenges and obstacles faced by Guangdong, Hong Kong, and Macao regarding regional coordinated development, thus putting forward the following standpoints. It proposes enhancing infrastructure interconnectivity to establish the GBA 1-hour Express Traffic Circle, thereby driving the construction of a worldclass international shipping and logistics hub. Furthermore, the paper advocates for establishing an industrial collaborative development system in the GBA, jointly creating a pilot zone for industrial transformation and upgrading, and further advancing market integration. Creating an international innovation corridor and innovation center for science and technology (S&T) industry is also essential. This initiative would center around critical sectors, improving S&T innovation chain, and building a talent cooperation demonstration zone. The paper also emphasizes the establishment of a transport and logistics hub for the Belt and Road Initiative, along with the joint development of a cultural, economic, and trade exchange platform under the “Belt and Road” framework. Leveraging the comparative advantages of the three regions, the paper underscores the importance of innovative collaboration models, fostering a mutually beneficial and complementary mechanism for synergistic development. These approaches aim to realize the integrated and innovative development of the GBA.

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives—spatial pattern and influencing factors—to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a mountainshaped” spatial pattern of the high-level homogeneous regions with “highhigh correlation” and the lowlevel homogeneous regions with “low-low correlation.” The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting “high-high correlation.” The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city’s location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations.

In the face of an increasingly complex and unstable external development environment, enhancing economic resilience has become a key task in the construction of the Guangdong-Hong Kong-Macao Greater Bay Area. This paper analyzes the changes in the economic resilience of the Guangdong-Hong KongMacao Greater Bay Area and its constituent cities after the 2008 global financial crisis by virtue of the regional economic resilience assessment method proposed by Martin et al. It constructs an economic connection network for the Guangdong-Hong KongMacao Greater Bay Area using the data from corporate headquarters and branches of A-share listed companies to analyze its impact on the economic resilience of the Area. The study reveals the three following conclusions. Firstly, the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area generally outperforms the national average level, seeing a rapid boost over the recent years and exceeding the level witnessed during the 2008 financial crisis. However, there are marked disparities in the economic resilience of various cities within the Greater Bay Area, with Shenzhen, Guangzhou, and Dongguan emerging as the most robust in this regard. Secondly, the economic connection network has a positive impact on the economic resilience of the cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Specifically, there is a positive correlation between a city’s economic resilience and its centrality in the economic connection network. Such centrality exerts a positive spillover effect on the economic resilience of surrounding cities. Thirdly, from the perspective of industryspecific networks, circulation and service industry networks are more conducive to improving the economic resilience of a city. Given the significant role of the economic connection network in shaping regional and urban economic resilience, it is imperative for the Guangdong-Hong Kong-Macao Greater Bay Area to prioritize ensuring economic development security and enhancing economic resilience,promote the development of the economic connection network, and enhance the network centrality of its constituent cities. This can improve the economic resilience of itself and its constituent cities in an effective manner.

The green transformation of agricultural production plays a crucial role in promoting the high-quality development of agriculture and achieving rural revitalization. In order to create favorable conditions for this to occur, it is essential to establish effective connections, transformation, and mutual support between capital endowment, external environment, and farmers’ green concepts. Additionally, the contracting of agricultural production facilitates service-oriented scale operations, while the deep integration of “Internet +” and agriculture with the advancement of green agricultural technology provides an inexhaustible impetus for it. However, China’s current green transformation of agricultural production continues to encounter challenges such as the depletion of a high-quality labor force, obstacles to building trust in the promotion of technology, and an underdeveloped green agricultural products market. To address these challenges, it is imperative to promote embedded agricultural technology which can catalyze the green contracting of agricultural production. Furthermore, advocating for the consumption of green agricultural products will also be beneficial in overcoming these challenges.

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Academic News

The extreme weather caused by the global warming effect has triggered huge losses to agricultural production. A hot issue for governments and scholars is how to effectively reduce carbon emission intensity in agriculture. The agricultural farming practices that are high pollution and high energy cosuming have exacerbated the vulnerability of regional agroecosystems. The sustainable development of agriculture is faced with the two dilemmas of a low utilization rate of green resources and the serious pollution of farmland. Further, environmental and ecological carrying capacities have reached their limits, seriously hindering the high-quality development of low-carbon agriculture in China. Thus, based on the panel data of 282 cities, the Spatial Dubin Model (SDM) is employed to examine the impact of agricultural mechanization on carbon emission intensity in agriculture. It is found that from 1999 to 2019 carbon emission intensity in agriculture showed an overall downward trend; as of 2019, the agricultural field had completed the target of carbon emission reduction, one year ahead of schedule. From a local perspective, approximately 14.89% of agricultural industries in prefecture-level city have still not achieved carbon emission reduction targets, and agricultural carbon emission reduction tasks were better completed in major grain-producing areas than in nonmajor grain-producing areas. Agricultural mechanization has significantly reduced carbon emission intensity in local agriculture production. The impact of agricultural mechanization on carbon emission intensity in agriculture has not only a significant negative spatial spillover effect but also a significant effect on spatial carbon emission reduction. Compared with non-major grain-producing areas, agricultural mechanization plays a greater role in reducing spatial carbon emissions in major grain-producing areas. Further studies find that agricultural mechanization is conducive to overcome difficulties, such as instability of property rights and land fragmentation, and to achieve large-scale agricultural production, thereby reducing agricultural carbon emissions in nearby regions. However, the transfer of rural labor, adjustments to the structure of agricultural cultivation, and the centralized use of rural land restrict the development of the crossregional service market for agricultural machinery, which in turn weaken its contribution to spatial carbon emission reduction. At the end of this paper, it is suggested that Chinese governments at all levels should introduce subsidy policies for the cross-regional operation of agricultural machinery to solve the problem of their service market failure. Efforts should be made to stimulate the market to develop more energy-efficient and environmentally friendly agricultural machinery products while strictly controlling changes in the use of arable land in non-grain-producing areas, which aims to serve further agricultural mechanization and boost the high-quality development of low-carbon agriculture.

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Book Excerpt

In light of China’s generally backward agricultural mechanization levels, it becomes crucial to shore up this weak link with endogenous driving force. The digital financial inclusion offers a approach to addressing the challenges related to agricultural mechanization. This study, collecting data from 1,869 counties and using the Spatial Autoregressive Model with Spatial Autoregressive Disturbances (SARAR model), analyzes the equilibrium and disequilibrium effects of digital financial inclusion on agricultural mechanization, as well as the mechanisms through which digital financial inclusion operates. The findings indicate that both digital financial inclusion and agricultural mechanization exhibit spatial spillover effects. The development of digital financial inclusion emerges as a significant driver for promoting agricultural mechanization. Furthermore, the impact of digital financial inclusion on agricultural mechanization varies based on the level of agricultural economic development, with counties characterized by less developed agriculture, plain topography, and strong agricultural sectors benefiting more from digital financial inclusion. Additionally, digital financial inclusion indirectly boosts agricultural mechanization by increasing farmers’ income and encouraging investment in fixed assets. Therefore, it is crucial to harness the benefits brought by the development of digital financial inclusion while promoting agricultural mechanization, and regions should tailor their approaches to promote digital financial inclusion development according to their local conditions.

The Guangdong-Hong KongMacao Greater Bay Area comprises a regional economy encompassing nine cities located in the Pearl River Delta region, in addition to the two special administrative regions of Hong Kong and Macao. The process of regional economic integration within the Guangdong-Hong KongMacao Greater Bay Area traces its origins back to the commencement of China’s reform and opening up policies in 1978. It evolves from an initially spontaneous collaborative model, where front-end commercial activities are paired with rearend manufacturing facilities, to a deliberate form of collaboration underpinned by institutional interventions. This paper examines the fundamental characteristics of the regional economic integration within the Guangdong-Hong Kong-Macao Greater Bay Area. It specifically delves into an extensive analysis of the construction and development of this area. The discussion encompasses four significant theoretical and practical facets that shape the progress of the Greater Bay Area’s construction. These aspects include the synchronization of market integration within the Greater Bay Area, the harmonization of institutional frameworks, the convergence of the eastern and western sections of the Pearl River Estuary, and the amalgamation of regional innovations. Furthermore, the paper engages in an exploration of strategies designed to propel the advancement of the Greater Bay Area’s development. These strategies encompass collaborative initiatives, such as the joint development of the Shenzhen-Hong Kong adjacent region, the cooperative advancement of Hengqin Island by Zhuhai and Macao, the approach to integrating adjacent areas, and the interlock strategy aiming to connect the two pivotal urban centers of Guangzhou and Shenzhen.

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Book Excerpt