The Impact of the Establishment of National High-tech Zones on Total Factor Productivity of Chinese Enterprises

The National High-tech Zone(NHTZs)is an important strategic platform for cultivating high-tech industries and realizing high-quality economic development in China.Based on the combined data from 2006 to 2014 of the industrial enterprise database,the customs database,and the China Development Zones Audit and Announcement Catalogue(abbreviated asthe Catalogue),this paper systematically investigates the influence of the construction of NHTZs on enterprise’s total factor productivity(TFP).Results show that NHTZs have a positive impact on the TFP of enterprises in the zone,and this conclusion is still valid after considering endogeneity problems.Furthermore,the above productivity effects of NHTZs are heterogeneous in terms of enterprise ownership,external environment and establishment time,and NHTZs have greater stimulation effects on enterprise productivity after comparing with other types of functional zones.An investigation of the specific mechanisms at play shows that NHTZs promote the TFP of enterprises in the zone through the release of preferential policies,strengthening the“technology spillover effects”of imported intermediate goods,enhancing enterprise’s innovation ability and attracting talent.In addition,based on the decomposition of industry productivity,this paper also investigates the impact of NHTZs on changes in industry productivity and finds that NHTZs promote the overall productivity of specific industries mainly by stimulating the productivity improvement of incumbent enterprises and expanding the market share of high-productivity enterprises.Moreover,the preferential policies of NHTZs do not significantly stimulate high-productivity enterprises to enter the zones,nor do they cause low-productivity enterprises to exit.This research is helpful in objectively evaluating the economic effects of the NHTZs in China and in providing a theoretical basis for its further adjustment.

Analysis of the Contribution of Total Factor Productivity to Agricultural Yield in Anhui Province

By analyzing data concerning agricultural development from 1981 to 2010 in Anhui Province,the total factor productivity and growth rate of agriculture from 1981 to 2010 are estimated empirically.By dividing years from 1981 to 2010 into several subintervals,this paper evaluates and analyzes initial stage of reform and opening up,soft landing stage,the stage of financial crisis,the stage of subprime mortgage crisis and the impact of all factors on total factor growth rate of agriculture.Then it analyzes the contribution of growth of total factor productivity to total yield of agricultural economy.The research finds that the growth of total factor productivity in Anhui Province is significant to agricultural development.

An Empirical Study on the Influence of Agricultural Public Infrastructure on Total Factor Productivity of China’s Grain Production

A critical method of ensuring grain production is to increase the total factor productivity(TFP),and the key measure to increase the TFP of grain production lies in the construction of agricultural public infrastructure.For this topic,existing literature lacks systematic and empirical analysis.Therefore,research on the influence of agricultural public infrastructure on the TFP of China’s grain production has relatively strong policy implications and theoretical value.For this study,we collected panel data for grain inputs and outputs as well as for agricultural public infrastructure in China’s provinces(autonomous regions/municipalities)from 1990 to 2017,and adopted the stochastic frontier function(SFF)approach to measure the TFP of provincial-level grain production.Through this empirical study,we analyzed the influence of agricultural public infrastructures,such as irrigation,roads,and electric power facilities on the TFP of China’s agriculture.We found that such facilities have a positive influence on the TFP of grain production.Specifically,when the input for irrigation facilities is increased by 1 percent,the TFP of grain production will rise by 5.74 percent.Based on this finding,policy recommendations are proposed for enhancing grain TFP through agricultural public infrastructure construction.

Agricultural Total Factor Productivity and Income Gap between Urban and Rural Residents--An Empirical Study Based on Provincial Panel Data

Taking the relevant data of 27 provinces in China during 2013 and 2017 as samples,this paper firstly measured the agricultural total factor productivity( TFP) using Malmquist index method. Then,it built the panel data model,and empirically tested the impacts of agricultural TFP on the income gap between urban and rural residents. The results show that the improvement in agricultural TFP can promote the narrowing of the income gap between urban and rural residents,and the factors such as urbanization level and industrial structure also have significant impacts on the income gap between urban and rural residents. On the basis of these,it came up with recommendations,including increasing agricultural human capital investment and establishing agricultural production research institutions.

数字普惠金融对农业GTFP的影响效应研究——兼论产业集聚的调节作用

提高农业GTFP是推行乡村振兴战略的关键,数字普惠金融作为驱动农村高质量发展的新动力,或能结合产业集聚推动农业GTFP提升。本文采用空间杜宾模型,通过对2011—2020年30个省份的面板数据进行分析,实证研究了数字普惠金融及其分维度指数对中国农业GTFP、技术效率和技术进步的空间作用,并进一步分析了农业产业集聚对两者关系的调节作用。研究结果显示:数字普惠金融水平的快速提升对农业GTFP产生了积极影响;空间溢出效应表明,邻近地区数字普惠金融的增长抑制了本地区农业GTFP的增长;调节效应表明,农业产业集聚在数字普惠金融推进农业GTFP提高的过程中起负向抑制作用。因此,要促进农业GTFP增长要充分发挥数字普惠金融的动力引擎作用,并引导农业产业合理布局,以提高金融资源在农业领域的配置效率,促进农村高质量发展。

Assessing Total Factor Productivity for Soybean Production in China Based on DEA-Malmquist Index: 2005-2017

The low and slowly increasing soybean yield restricts the development of soybean production. Accurate measures of total factor productivity (TFP) for soybean production can be helpful in identifying conditions, institutions or policies that promote soybean production development in China. In this paper, TFP growth for soybean production was estimated for a panel data of 10 major soybean producing provinces from 2005 to 2017. Results reveal that TFP grew at an average rate of 1.3% over the whole period, with technical progress contributing 2.3% and efficiency change providing the other -1.0%. The change of TFP for soybean production over that time, whether increase or decline, was mainly derived by technical change except in three years (2005-2007). Positive TFP growth in the provinces of Liaoning and Inner Mongolia, and negative TFP growth in Hebei and Anhui were mainly driven by efficiency change, specifically scale efficiency change except pure technical efficiency in Liaoning.

Agricultural Policy, Climate Factors and Grain Output: Evidence From Household Survey Data in Rural China

This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivity （TFP） growth at the farmer level. The empirical results show that the major contributor to the grain output growth for farmers is input growth and that its average contribution accounts for 60.92% of farmer’s grain production growth in the period of 2006-2009, whereas the average contributions sourced from TFP growth and residuals are only 17.30 and 21.78%, respectively. The growth of intermediate inputs is a top contributor with an average contribution of 44.46%, followed by the planted area （18.16%）, investment in fixed assets （1.05%）, and labor input （-2.75%）, indicating that the contribution from the farmer’s input growth is mainly due to the growth of intermediate inputs and that the decline in labor inputs has become an obstacle for farmers in seeking grain output growth. Among the elements consisting of TFP growth, the contribution of technical progress is the largest （32.04%）, followed by grain subsidies （8.55%）, the average monthly temperature （4.26%）, the average monthly precipitation （-0.88%）, the adjusted scale effect （-5.66%）, and growth in technical efficiency （-21.01%）. In general, the contribution of climate factors and agricultural policy factor are positive and significant.

Total Factor Productivity with Chinese Characteristics

Although total factor productivity(TFP)is a common concept in mainstream Western economics,its origins are actually embedded in Marx's understanding of improving labor productivity.As an important element of labor productivity under socialized production conditions,TFP is further reflected in the category of"socially necessary labor time"in two distinct senses.Re-examining TFP from the perspective of Marxist political economy and incorporating it into the theoretical system of political economy of socialism with Chinese characteristics vividly illustrates the essence of"adhering to original principles,assimilating foreign concepts,and embracing a forward-looking vision"within political economy of socialism with Chinese characteristics.In practice,it is necessary to start with Marx's theory of productive labor and delineate the sectors involved in productive labor so that TFP and its fluctuations can be measured in a more relevant way.In the context of the new era and the new journey,as the key to achieving high-quality economic development in China,efforts are needed to increase TFP.This requires balancing economic factors such as the long term and short term,supply and demand,and gross quantity and structure,and promoting transformative changes in the quality,efficiency,and dynamism of economic development.

Transportation Infrastructure and Productivity Growth:Effects of Railway Speed-Up on Firm's TFP in China

Improvement of transportation infrastructure quality will lead to more sufficient market competition and promote the flow of resources with greater efficiency. This paper considers China's railway speed-up in 2007 as a quasi-natural experiment on China's transportation infrastructure quality improvement. With the initial operation of electric multiple units(EMUs) as the basis of grouping, this research examines the effect of railway speed-up on corporate total factor productivity(TFP) growth by the differencein-differences(DID) method. Overally, the results reveal positive effects both on firms' technological change and efficiency improvement, which lead to the increase of TFP. Based on subsamples divided by different regions and types of enterprises, further analysis indicates that the productivity of exporter, non-state and coastal firms has been mostly affected by the railway speed-up. These conclusions are verified by a placebo test. Besides, firms within "one-hour economic circle" have been shown more sensitive to the effect of railway speed increase.

Do ICTs Boost Agricultural Productivity?

Based on panel data from the Rural Fixed Point Survey of the Ministry of Agriculture over the period 2004-2016 and supplementary survey data on information and communications technology(ICT)applications in the countryside,this paper employs the difference in differences(DID)method to analyze the effects of ICT applications on rural households’agricultural total factor productivity(TFP)with mobile phone signal,internet and 3G mobile network connections as indicators,and decomposes and evaluates the constituent factors.Our findings reveal a positive effect of ICTs on rural households’TFP,which primarily stemmed from rising agricultural technical efficiency.However,ICTs exerted no significant effect on agricultural technical progress during this paper’s data period due to limited rural human capital.These findings are consistent with robustness test results based on counterfactual and matching methods.

全要素生产率视角下数字经济对农业碳排放影响——来自中国农业的经验证据

数字经济在蓬勃发展的同时表现出碳减排效应。理论上,数字经济可以通过提升农业全要素生产率,从而赋能农业碳减排。实际操作中,利用熵值法测度了2014—2020年中国30个省份农业农村数字经济发展指标,利用中介模型分析农业全要素生产率在数字经济影响农业碳排放的过程中的中介效应。在此基础上进行计量分析结果表明:中国农业数字经济蓬勃发展的同时呈现出区域发展不均衡态势,东部的农村数字经济发展水平高于中西部。数字经济能够显著降低农业碳排放强度,但是这种减排效应具有明显的区域差异,西部地区减排效果明显优于东部和中部地区。数字经济在降低农业碳排放强度的过程中,农业全要素生产率发挥了部分中介效应,中介效应占比为31.1%。这一结论在进行一系列的稳健性检验后仍然成立。

数字普惠金融如何赋能乡村产业振兴

厘清数字普惠金融发展赋能乡村产业振兴的作用机制,有助于缓解农村金融资源配置效率不高、金融基础设施不完善和金融服务体系薄弱与日益增长的乡村产业发展需求之间的矛盾。现有文献对数字普惠金融与农村经济现代化做了较为丰富的研究,但是鲜有将其与乡村产业振兴联系起来进行理论与实证的研究。本文从乡村产业生产、乡村产业延伸、乡村产业功能和乡村产业支撑四个维度构建我国乡村产业振兴水平评价指标体系,并多维度实证检验了数字普惠金融对乡村产业振兴的影响。主要有三点发现:一是数字普惠金融发展对乡村产业振兴水平和乡村产业振兴速度均具有显著的正向促进作用;二是数字普惠金融发展覆盖广度、使用深度和数字化程度对乡村产业振兴的边际效应呈现明显差异;三是数字普惠金融不仅可以直接缓解经营主体约束和激活市场活力促进乡村产业振兴,还可以通过农业科技创新、乡村产业融合和农业全要素生产率间接影响乡村产业振兴。

数字乡村建设、资源要素错配与农业绿色全要素生产率

数字乡村建设与农业绿色发展深度融合是推动农业高质量发展的新动力引擎。本文选取2011-2021年中国31个省级面板数据,构建数字乡村建设和农业绿色全要素生产率的评价体系,多维度分析数字乡村建设对农业绿色全要素生产率的影响及作用机制。研究发现,数字乡村建设既可以直接促进农业绿色全要素生产率提升,也可以通过带动绿色技术进步而促进农业绿色全要素生产率提升,还可以通过降低土地资源错配、资本资源错配、劳动力资源错配程度而间接促进农业绿色全要素生产率。数字乡村建设对农业绿色全要素生产率的影响异质性明显,东部地区、南方、粮食主产区的数字乡村建设的正向推动作用较强。

农产品贸易促进了中国农业绿色发展吗?——基于农业绿色全要素生产率视角

农业绿色全要素生产率的提高有助于农业绿色化转型与可持续性发展。基于2006—2020年中国30个省份数据,选择SBM-ML指数法,利用MaxDEA软件测算农业绿色全要素生产率,使用系统GMM模型与动态面板门槛模型实证检验农产品贸易对农业绿色全要素生产率的影响。研究发现:农产品贸易能够有效提升农业绿色全要素生产率并且其影响效应存在区域异质性,在东部地区较为显著;农产品贸易对农业绿色全要素生产率的影响存在地区经济发展水平的门槛效应,地区经济发展水平越高,农产品贸易对农业绿色化发展的正向溢出作用越明显。因此,各省份要推动农产品贸易的持续健康发展,政府应当依照地区贸易发展状况与经济发展水平因地制宜地制定有关农产品贸易政策,充分发挥农产品贸易的正向溢出作用,促进农业绿色发展。

农地流转提升了农业绿色全要素生产率吗?

在2006-2021年中国30个省份的面板数据基础上,本文通过SBM-GML超效率模型测算中国各省份农业绿色全要素生产率。采用双向固定效应模型和工具变量模型等方法,实证分析农地流转和农业绿色TFP之间的内在联系,并分析其影响路径机制。研究发现,中国农业绿色全要素生产率能够持续增长的主要原因在于技术进步。而农地流转能够推动农业绿色全要素生产率增长则是得益于技术效率改进。从异质性分析来看,农地流转对农业绿色全要素生产率增长的促进作用最显著的是东部地区和非粮食主产区,但在西部地区却正好相反。因此,中国应当加快推进农地流转工作进展,促进农业生产和经营管理模式变革,加快研发、推广和应用农业绿色生产技术,构建区域协作互助机制促进地区交流,进而促进农业绿色全要素生产率的提高。

生产性服务数智化对农业绿色全要素生产率的影响——兼论政府环境规制的调节作用

为推进农业农村现代化,亟需以生产性服务业数智化为契机,对传统农业生产方式进行全方位改造,提高农业综合生产能力。在理论阐述农业生产性服务数智化影响农业绿色全要素生产率(AGTFP)的内在机制基础上,构建包含金融服务、科技信息服务和商贸流通服务三部分的农业生产性服务数智化综合评价指标体系,并通过回归模型对2014—2020年我国29个省(区、市)的面板数据进行实证检验。结果表明:生产性服务数智化改造对AGTFP水平的提升具有显著的促进作用。具体来讲,金融服务和商贸流通服务的数智化改造对AGTFP的影响呈现当期有效的特征,而科技信息服务数智化改造在较长的时间内仍可以保持对AGTFP的显著促进效应;农业生产性服务数智化促进作用存在明显的区域异质性,从强到弱依次为粮食主产区、粮食产销平衡区、粮食主销区;政府环境治理能够强化农业生产性服务数智化对AGTFP的影响。基于此,应大力推进现代信息技术对传统农业生产方式的改造,构建以科技信息服务为基础,金融服务、商贸流通服务为引领,拉动农业绿色全要素生产率提升的长效增长机制。

数智经济推动共同富裕的机制与效应研究

共同富裕是社会主义的本质要求,数字化、智能化是引领共同富裕的重要驱动力。本文从数字化和智能化两个维度出发构建了数智经济发展水平的指标体系,并利用2012~2022年我国省际面板数据,实证分析了数智经济推动共同富裕的作用路径与影响效应。研究发现:数智经济通过提高农业全要素生产率推动共同富裕。在区域经济发达程度较低时,数智经济的发展可能会妨碍共同富裕目标的实现,但这种抑制效果将进一步削弱,直到区域经济发展达到一定水平,数智经济发展才有助于促进共同富裕。同时,数智经济发展还存在明显的空间溢出效应,可以提高邻近地区的共同富裕程度。因此,各地区应加快数智经济发展进度,使数智经济的建设更有效地服务于共同富裕目标。

基于改进明瑟工资方程的河南省农业全要素生产率测算

【目的】探究河南省农业人力资本存量和物质资本存量的变化趋势,并以此为基础测算农业全要素生产率,分析促进河南省农业经济增长的主要因素。【方法】考虑到年龄对人力资本的影响,把年龄因素纳入到明瑟工资方程中,提出并利用改进明瑟工资方程估算了农业人力资本存量,结合永续盘存法估算了农业物质资本存量。在此基础上采用C-D生产函数模型测算出河南省农业全要素生产率。【结果】由于每年农业固定投资总额增幅较大,物质资本存量也在逐年增加。而由于农业从业人员转出较快,农业人力资本存量逐渐降低。在弹性系数作用下,物质资本存量与人力资本存量的乘积虽然在增长,但其增速低于农业产值的增速,进而农业全要素生产率呈现出上升趋势。【结论】继续强化农业物质资本的投入,提升农业从业人员的素质,以人力资本与物质资本组合的优化促进农业全要素生产率的提升,进而加快河南省农业强省战略的推进。

基于DSGE模型的科技信贷激励政策研究

通过构建基于全要素生产率厂商异质性的NK-DSGE(新凯恩斯—动态随机一般均衡)模型,模拟科技信贷激励政策的传导机制与政策效果,研究发现政策效果从大到小依次是常规货币政策、政府部门贴息、中央银行再贷款利率、中央银行定向降准、中央银行再贷款抵押率,与我国科技信贷激励政策的实践效果相吻合。进一步研究发现,政府贴息、再贷款利率的外生冲击波动幅度对政策效果影响弹性更大。建议地方政府应和银行加强联动,完善科技信贷风险补偿机制、贷款担保体系;另外,中国人民人行应加强常规货币政策实施精准性,并探索更加灵活的结构型货币政策机制。

农业发展影响农民减贫增收的作用机制——基于收入结构的实证分解与检验

在工业化、城镇化的进程中,中国农业发展是否影响、如何影响农民减贫增收的问题,在理论和实证上仍存在较多分歧。基于此,该研究采用1994—2021年中国省级面板数据,并与2010—2020年CFPS微观数据相匹配,通过构建两部门理论模型,分析农业发展给农民带来的增收效应与减贫效应,进一步检验农业发展影响农民减贫增收的具体机制及异质性。研究发现:①农业发展不仅直接影响农民务农收入与非农收入,还通过农业生产效应、生活成本效应和非农就业效应的中介传导途径作用于务农收入与非农收入,降低了农村居民贫困发生率和贫困深度,但对贫困强度影响不显著。②总体上,农业发展提升务农收入的作用占比为54.94%,提升非农收入的作用占比为45.06%。③农民减贫成效的23.36%源自农业发展提升务农收入所致,76.64%源自农业发展溢出作用实现的非农收入提升;但在粮食主产区内,农业发展通过提升务农收入对农民减贫成效的贡献超过40%。该研究为中国实现脱贫攻坚与乡村振兴有序衔接提供了理论和实证支撑。