Unveiling the impact and mechanism of digital technology on agricultural economic resilience

Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However,existing research predominantly focuses on traditional agricultural factors and technologies.Therefore,the impact of digital technology on agricultural economic resilience within the broader context of the“production-operation-industry”system in agriculture has not been comprehensively explored.To bridge this gap,this study analyzes panel data from 30 Chinese provinces from 2011 to 2020.It employs the static Van Dorn’s law and a dynamic spatial panel model to examine how digital technology empowers agricultural resilience.The findings indicate a continuous strengthening of digital technology development in China,albeit with significant polarization and spatial imbalances.Moreover,the resilience of the agricultural economy undergoes notable fluctuations,initially narrowing and subsequently displaying an upward trend.Digital technology clearly plays a pivotal role in empowering resilience through agricultural scale operation,industrial transformation,and technological progress.Its impact,particularly on the promotion of resilience in the eastern region and non-grain-producing areas and on high-level agricultural economies,also shows regional and technological variations.

Dynamic change of agricultural energy efficiency and its influencing factors in China

In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization.Based on the panel data of 28 provinces from 1995 to 2018,this paper calculated China’s agricultural energy input from two categories of direct energy and indirect energy,and used EBM(Epsilon-based Measure)mixed distance function model to measure the energy efficiency of agriculture in China.The nuclear density function and spatial autocorrelation were used to analyze the dynamic evolution of agricultural energy efficiency,and the dynamic panel model was used to analyze the influencing factors of agricultural energy efficiency.The results showed that:①From 1995 to 2018,the total agricultural energy input had increased year by year in China,with an average annual growth rate of 2%.Energy input structure changed from indirect energy-based to direct energy-based.Agricultural energy efficiency showed an evolutionary trend of‘rising-stagnating-rising rapidly’in China.The agricultural energy efficiency was generally low in China,and there was a large space for improvement in agricultural energy efficiency.②From 1995 to 2018,the average annual growth rate of agricultural energy efficiency in the eastern,central and western regions was 2.7%,1.9%and 1.4%respectively.In 2018,the agricultural energy efficiency in the eastern,central and western regions was 0.81,0.71 and 0.59 respectively.The gap between regions was expanding rapidly,and the agricultural energy efficiency in the central and western regions needed to be improved.③From 1995 to 2018,the agricultural energy efficiency of each province was polarized and the absolute gap was widened.There was obvious improvement in agricultural energy efficiency in Guangdong,Shandong,Jiangxi,Jiangsu,Liaoning and Tianjin,while the agricultural energy efficiency of Xinjiang,Guizhou,Zhejiang,Shanghai,and Inner Mongolia deteriorated.④From 1995 to 2018,there was no global spatial correlation of China’s agricultural energy efficiency.However,local‘high-high’concentration gradually appeared in the eastern region since 2010.⑤The first lag of energy efficiency had a significant positive impact on agricultural energy efficiency,and agricultural energy efficiency improvement had a time lag.The level of human capital,per capita net income of farmers and the level of urbanizaton had a significant positive impact on agricultural energy efficiency.The disaster rate,the level of development of secondary and tertiary industries,and the level of opening up had a significant negative impact on agricultural energy efficiency.In the implementation of the strategy of rural revitalization,we should focus on the central and western regions,take the cultivation of professional farmers as the key,focus on improving agricultural production conditions,enhance the level of cooperation between regions,exert the leading role of the secondary and tertiary industries,and enhance the ability of agricultural disaster prevention and mitigation.

Spatial spillover effects of official development assistance on environmental pressure in sub-Saharan African(SSA)countries

Impoverished sub-Saharan Africa(SSA)is under increasing environmental pressure from global environmental changes.It is now generally accepted in academic circles that economic development in SSA countries can cause environmental pressure in other countries.However,there is research gap on the impact of economic assistance on environmental pressure in SSA countries and whether economic assistance causes spatial spillovers of environ-mental pressure between SSA countries.To better understand the impact of economic assistance on environmental pressures in SSA,a dynamic spatial Dubin panel model was developed.It helped us explore the spatial spillover effects of economic assistance on environmental pressures in recipient countries based on the panel data from 34 SSA countries.The results show that economic assistance had a positive stimulating effect on environmen-tal pressures of recipient countries,which means that the degree of human disturbance to the environment has deepened.Due to the regional correlation effect,neighboring countries were saddled with environmental pres-sures from the target country.Moreover,environmental pressures have time inertia,which can easily produce a snowball effect.The decomposition of effects shows that the impact of economic assistance on environmental pressures is relatively minor.Environmental pressures have spillover effects,so to deal with diffuse risks,joint regional prevention and control policies should be developed.

An analysis of Chinese urban residents＇ consumer demand employing a dynamic semi-parametric panel data model

Using data for China for the years 1991 to 2005 by province and employing the semi- parametric panel data model estimation method developed by Horowitz （2004） and Henderson et al. （2006） and Hubler＇s non-parametric generalized method of moments （GMM） estimation （2005）, this article constructs a dynamic semi-parametric panel data model and describes the dynamic changing trajectory of the effect on consumption of income disparity among urban residents. Our findings show that there is a significant ＂ratchet effect＂ in the consumption of urban residents; that income disparity among urban residents has a clear negative influence on consumption; and that the trajectory of this influence shows a roughly bimodal curve.

A dynamic panel data approach and HCW's method:Assessing the effect of China(Shanghai)Free Trade Zone on local GDP

We propose a simple-to-implement dynamic panel data method to evaluate the impacts of place-based policies.The idea is to exploit both the cross sectional dependence and the serial correlation within a panel and implement a semi difference-in-difference decomposition.Different from the method by Hsiao et al.(2012),the proposed model is easy to implement statistical inferences and can incorporate multiple treated groups at different time thresholds.We use the proposed method to explore the effect of the Free Trade Zone(FTZ)policy implemented in Shanghai at the end of 2013 on local GDP growth rate and compare it with that from Hsiao et al.(2012).The empirical results show that the FTZ does have a positive effect on the local GDP growth rate and it adds 1:21:8 percent point to the growth rate of the GDP per capita for Shanghai in 2014 which is about one fourth to one third of the total GDP growth rate per capita.This effect largely comes from the growth of the tertiary sector.The results lend support to the duplication of FTZ policy to other cities and provinces in China.

Effect of China’s technology spillovers on energy intensity in Africa

Empirical studies on the effects of China-African economic relations on energy intensity in Africa are scarce.To fill the gap in the literature,this study investigates the technology spillover effects of the China-Africa trade and investment relations on energy intensity.It uses both linear and nonlinear dynamic panel estimation methods for 42 African countries from 2003 to 2015.The results show that China's technology spillover through imports significantly reduces energy intensity in Africa.The findings are consistent across specifications and sample groups.Moreover,the technology spillover coming from foreign direct investment(FDI)improves energy intensity,particularly in lower-middle-income African countries.The dynamic threshold estimation results show that countries'absorptive ability is important for technology spillover effects of FDI and imports on energy intensity.The results suggest that countries'absorptive capacity should be increased to maximize the benefits of trade and investment technology spillovers.

“Competition for Innovation”:Research on the Strategic Competition of Local Governments'Science and Technology Expenditure in China

By constructing a yardstick competition model of the performance equation,this paper analyzes the internal mechanism of local governments'competition of science and technology(S&T)expenditure in China.By using the Dynamic Spatial Panel Model,we analyze the competition empirically from five dimensions:geographical adjacency,geographical distance,administrative adjacency,administrative grade and economic distance.According to the results,the local governments'S&T expenditure showed a significant strategic competition phenomenon,that is,there is a“competition for innovation”,and the competition is more obvious between regions with close geographical proximity and administrative relations.“Competition for innovation”will be affected by political exogenous shocks such as those from the National People's Congress(NPC)of China;There is a“father-son competition”relationship between the superior and inferior governments.At last,the competition can promote the regional innovation significantly,which shows that“competition for innovation”is a kind of top-by-top competition.The conclusions may provide some useful suggestions for optimizing the relationship between local governments and promoting the construction of an innovative country.

Estimating the effect of minimum wage on firm profitability in China

Using the firm-level panel datasets and hand-collected data on county level minimum wage,this paper estimates the effect of minimum wage on firm profitability.As firms may take time to adjust in response to changes in minimum wage,this paper estimates a dynamic panel model with lagged minimum wage.To capture the heterogeneous effect of minimum wage on profitability,this paper further estimates quantile regression dynamic panel model.The estimation results suggest that the effect on firm profitability of minimum wage in the current year is negative across the whole conditional distribution of profitability and it exhibits an inverted-U shape across conditional quantiles.The effect on profitability of lagged minimum wage is positive at the 5th,10th,15th quantiles,negative at the 90th and 95th quantiles,and not significant at other quantiles.Turning to the overall effect on profitability of minimum wage,we find that minimum wage exerts significantly negative effect on profitability at the 5th quantile and quantiles higher than 40th and the absolute value of the effect of minimum wage increases with these quantiles.For other quantiles,the overall effect of minimum wage on profitability is negligible.

Uncovering the Relationship between FDI,Human Capital and Technological Progress in Chinese High-technology Industries

Using a panel dataset for 28 sub-industries from 5 Chinese industries from 1995 to 2006, this paper examines the impact of human capital, R＆D expenditure and FD1 spillover on the productivity improvement of Chinese high-technology industries. The whole industry sample results suggest that human capital promotes total factor productivity, technical change and technical efficiency change, but that FDI lowers all of these factors in Chinese high-technology industry. When we distinguish between types of ownership structure in the industries, we find that human capital improves technical change but lowers technical efficiency change, whereas FDI only improves technical efficiency change in state-owned and state-controlled enterprises but reduces technical change in state-owned and state-controlled enterprises and joint ventures.

How does Bank Capital Affect Bank Profitability and Risk？ Evidence from China＇s WTO Accession

This paper examines how bank capital affects bank profitability and risk in China, and how its impact differed before and after the nation entered the WTO. Our study uses the dynamic generalized method of moments approach with a panel database containing 171 Chinese commercial banks. We ftnd that bank capital has significant influence on bank profitability and risk, but its impact has declined since China joined the WTO in 2001. For different sized groups, the impact of capital on profitability exhibits a distinct trend. The effects of capital on bank risk are different for large and small banks depending on the risk variables used for the Chinese banking industry.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.