The impact of the Rural Minimum Living Standard Guarantee(Rural Dibao)Program on child nutrition outcomes

The Rural Minimum Living Standard Guarantee(Rural Dibao)is an important unconditional cash transfer program to alleviate poverty in rural China.Despite the importance of children’s nutrition in breaking poverty cycles,little is known about the impact of Rural Dibao on child nutrition outcomes.Using China Family Panel Studies(CFPS),this paper examines the effects of Rural Dibao on child nutrition outcomes and investigates potential pathways and heterogeneous effects.We exploit propensity score matching and difference-in-differences techniques to evaluate the effects of the Rural Dibao program on child nutrition outcomes.Our results suggest that Rural Dibao significantly impacts the nutrition outcomes of children up to 15 years of age.Specifically,our results suggest that Rural Dibao improves child height-to-age z-scores by 1.05 standard deviations and lowers the probability of stunting by 11.9 percentage points.Additional analyses suggest that increased protein intake is the main pathway through which Rural Dibao participation contributes to better nutrition outcomes.We also find that the effect of the program is more pronounced among girls,children who are non-left-behind or live with highly educated mothers,and those from low-income families and poor areas.Our findings suggest that Rural Dibao participation helps improve child nutrition outcomes through improving diet quality.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

Digitalization’s Effects on Income Growth and Distribution-Evidence from the CHDES Database

Using the CHDES database,we created the CIDI to comprehensively quantify digital adoption at the individual level and examine digitalization’s impact on individual income.Empirical analysis results indicate that increasing the CIDI by one standard deviation(0.13)improves individual income by 5.93 percentage points,which remains true after a series of endogeneity and robustness tests.In the heterogeneity analysis,we discovered that when digital adoption grows,residents in the countryside and county seats can earn more money through internet business operations and other channels.This helps to decrease the urban-rural income divide,but it has also pushed those digitally skilled into high-paying sectors,widening the income gaps between sectors.In the mechanism analysis,we developed an income function that takes into account the individual level of digitalization to show that digitalization can boost income by increasing working hours or labor participation and adjusting the portfolio of individual material,human,and social capital.In this paper,we have expanded the system for measuring the individual levels of digitalization by offering basic data,research methodology,and policy suggestions for the digital economy’s inclusive development.

Are cities greener because of innovation?Independent innovation policy and green economic efficiency

The national independent innovation demonstration zone(NIIDZ)is an independent innovation policy that plays a crucial role in implementing strategies.Given the importance of the NIIDZ,this study uses panel data of 278 prefecture-level cities in China from 2006 to 2020 and empirically examines the effect and internal mechanism of the NIIDZ on green economic efficiency(GEE)using the difference-in-difference model(DID).The results show that the NIIDZ effectively enhances the growth of GEE,and the results remain valid through several robustness tests,such as year-by-year propensity score matching.The transmission mechanism suggests that the NIIDZ indirectly drives GEE by accelerating scientific and technological investment,promoting talent concentration,and optimizing the industrial structure.Moreover,heterogeneity analysis reveals that the promotion effect of the NIIDZ on GEE is more prominent in the eastern region and high green development level areas.The study’s findings can serve as a reference for China to further utilize the policy effectiveness of the NIIDZ and accelerate the high-quality development of the green economy in the future.

Urban Dynamics and Emergence of New Centers in the Dakar Region (Senegal)

Due to the status of the Dakar region as the former capital of AOF (French West Africa) and current capital of the Republic of Senegal, it is home to a very large part of the population and most of the socio-economic, administrative and cultural activities on a very small area of the country (0.28%). This situation makes it a very attractive region and subject to strong land pressure. The objective of this article is to study past and current urban dynamics as well as changes in natural spaces, in order to identify new urban centers. The methodological approach consists in analyzing satellite images to understand the evolution of different forms of spatial occupation in the Dakar region, and to study population movement flows and urban forms in order to reveal new urban centers. The results of the study show that the Dakar urban space is characterized by diverse forms which express a heterogeneous set of spaces. They also revealed the emergence of new clusters between 1986 and 2016, notably Ngor, Grand Yoff, Parcelles Assainies in the North-West, and Keur Massar and the North of the communes of Rufisque in the eastern part of the Dakar region.

A Blind Spot in the Reframing of a Universe of Possibles: Towards a Suitable Model for Decision-Making Theory and A.I.

Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.

Is there regional convergence between Morocco and its OECD partner countries in terms of well-being?

Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries(Morocco and 35 of its partner member countries in the Organization for Economic Co-operation and Development(OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains(economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model by taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we found that β-convergence of regions is significant for well-being and three of its domains(economic, social, and governance). These convergences are made by a spatially autocorrelated error model(SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.

High day and night temperatures impact on cotton yield and quality——current status and future research direction

Heat waves,and an increased number of warm days and nights,have become more prevalent in major agricultural regions of the world.Although well adapted to semi-arid regions,cotton is vulnerable to high temperatures,particularly during flowering and boll development.To maintain lint yield potential without compromising its quality under high-temperature stress,it is essential to understand the effects of heat stress on various stages of plant growth and development,and associated tolerance mechanisms.Despite ongoing efforts to gather data on the effects of heat stress on cotton growth and development,there remains a critical gap in understanding the distinct influence of high temperatures during the day and night on cotton yield and quality.Also,identifying mechanisms and target traits that induce greater high day and night temperature tolerance is essential for breeding climate-resilient cotton for future uncertain climates.To bridge these knowledge gaps,we embarked on a rigorous and comprehensive review of published literature,delving into the impact of heat stress on cotton yields and the consequential losses in fiber quality.This review encompasses information on the effects of heat stress on growth,physiological,and biochemical responses,fertilization,cotton yield,and quality.Additionally,we discuss management options for minimizing heat stress-induced damage,and the benefits of integrating conventional and genomics-assisted breeding for developing heat-tolerant cotton cultivars.Finally,future research areas that need to be addressed to develop heat-resilient cotton are proposed.

Review of multi-objective optimization in long-term energy system models

Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multi-objective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multi-objective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed.

A review of uncertain factors and analytic methods in long-term energy system optimization models

A larger number of uncertain factors in energy systems influence their evolution.Owing to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource allocation.This study focusses on long-term energy system optimization model.The important uncertain parameters in the model are analyzed and divided into policy,economic,and technical factors.This study specifically addresses the challenges related to carbon emission reduction and energy transition.It involves collecting and organizing relevant research on uncertainty analysis of long-term energy systems.Various energy system uncertainty modeling methods and their applications from the literature are summarized in this review.Finally,important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed,and future research directions are proposed.

Tax avoidance and earnings management:a neural network approach for the largest European economies

In this study,we investigate the relationship between tax avoidance and earnings management in the largest five European Union economies by using artificial neural network regressions.This methodology allows us to deal with nonlinearities detected in the data,which is the principal contribution to the previous literature.We ana-lyzed Compustat data for Germany,the United Kingdom,France,Italy,and Spain for the 2006–2015 period,focusing on discretionary accruals.We considered three tax avoidance measures,two based on the effective tax rate(ETR)and one on book-tax differences(BTD).Our results indicate the presence of nonlinear patterns and a posi-tive,statistically significant relationship between discretionary accruals and both ETR indicators implying that when companies resort to earnings management,a larger tax-able income—and thus higher ETR and lesser tax avoidance–would ensue.Hence,as also highlighted by the fact that discretionary accruals do not appear to affect BTD,our evidence does not suggest that companies are exploiting tax manipulation to reduce their tax payments;thus,the gap between accounting and taxation seems largely unaf-fected by earnings management.

Is a correlation‑based investment strategy beneficial for long‑term international portfolio investors?

Using negative to low-correlated assets to manage short-term portfolio risk is not uncommon among investors,although the long-term benefits of this strategy remain unclear.This study examines the long-term benefits of the correlation strategy for portfolios based on the stock market in Asia,Central and Eastern Europe,the Middle East and North Africa,and Latin America from 2000 to 2016.Our strategy is as follows.We develop five portfolios based on the average unconditional correlation between domestic and foreign assets from 2000 to 2016.This yields five regional portfolios based on low to high correlations.In the presence of selected economic and financial conditions,long-term diversification gains for each regional portfolio are evaluated using a panel cointegration-based testing method.Consistent across all portfolios and regions,our key cointegration results suggest that selecting a low-correlated portfolio to maximize diversification gains does not necessarily result in long-term diversification gains.Our empirical method,which also permits the estimation of cointegrating regressions,provides the opportunity to evaluate the impact of oil prices,U.S.stock market fluctuations,and investor sentiments on regional portfolios,as well as to hedge against these fluctuations.Finally,we extend our data to cover the years 2017–2022 and find that our main findings are robust.

Evolution of the Spatial Distribution of Basic Infrastructures and Services in the Niakhar Area (Fatick), Senegal

Basic infrastructures and services present an important socio-economic and territorial equity issue, because the availability of these makes it possible to improve the living conditions of populations, makes territories attractive and stimulates their development. The objective of our study has been achieved, so our results provided information on the rate of propagation of basic infrastructures and services, as well as the evolution of the forms of spatial distribution of the latter. The data used comes from the census and geolocation of basic infrastructures and services in the Niakhar area, carried out by the IRD in 2018. Centrographic measurements were used to describe the overall spatial distribution and the use of chi-square statistics confirmed the existence of a preferential direction of distribution. To verify the existence of a spatial structure of infrastructure and service seeding, the Ripley statistic is used. Our results can be useful for land use planning and spatial resource allocation policies. Indeed, the identification of different types of spatial aggregates and the highlighting of the preferred directions of the distribution of basic infrastructures and services, make it possible to correct disparities in the spatial distribution of basic resources.

我国制造业能源消耗强度变化的因素分解——基于结构份额和效率份额视角

在借鉴已有研究成果基础上,将能源消耗强度分解为结构份额和效率份额两个因素,并测算了1994-2006年我国制造业中能源消耗强度中两个因素的变化情况,分析了制造业产业结构调整和能源效率提高对能源消耗强度的影响。研究结果表明:我国制造业能源消耗强度在不断下降,原因是产业结构调整和能源使用效率提高的综合影响。两者对降低能源消耗强度都有正面作用,同时,能源使用效率提高作用略大于产业结构调整作用。

中国农户经营风险与借贷选择的关系研究--基于陕西的案例

本文建立风险平衡模型,以陕西农户为例,研究农户经营风险与农户借贷选择间的关系。GLM模型回归结果显示,农户普遍使用非正规借贷方式获取资金;农户生产风险与农户使用借款之间存在显著的负相关关系;农户承担风险的态度和风险厌恶倾向以及家庭收益对农户借贷选择的影响不显著。

农民市民化及其土地权益保障——文献评述与今后公共政策选择

本研究旨在通过对已有文献进行系统的归纳、总结与评述,梳理出农村劳动力城乡迁移与土地权益二者间的相互作用关系,并给出相应的公共政策选择建议。研究发现,在中国的劳动力城乡迁移过程中,由于二元体制带来的外生约束,劳动力在难以获得务工地平等市民权利的情况下,依托集体土地权益来形成务工—务农的灵活就业模式,这种不彻底的城乡迁移模式,能够实现其家庭收入最大化与风险规避的权衡。所以,不同于传统劳动力城乡迁移理论的预期,土地权益对中国农民的迁移行为有着不可忽视的支撑作用。而且,推动彻底的迁移劳动力市民化,相对应的土地权益放弃,其前提应是市民权利的平等,使得迁移者的土地权利与保障功能脱钩、向单纯的财产权利还原;而非是以土地财产权利置换市民权利的错位交换。因此,未来的公共政策应充分认识到土地权益对劳动力迁移的重大作用,合理地考虑农民工群体的土地权益保护与退出。

Productivity effect and overuse of pesticide in crop production in China

Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental externalities. This paper quantiifes the productivity effect and the optimal amount of pesticides in rice, cotton and maize production in China from the economic perspective. Using survey data col ected in 2012 and 2013, both Cobb-Douglas and Weibul damage control speciifcations are used to estimate the production function. Results show that pesticides have statistical y signiifcant pro-ductivity effect on crop yield. On the condition of Weibul damage control speciifcations, the marginal products of 1 kg of the active ingredients of pesticides for rice, cotton and maize are 71.06, 22.73 and 98.45 kg, respectively. However, 57, 64 and 17%of the actual amount of pesticides are overused for rice, cotton and maize, respectively. Moreover, the productivity effect of pesticides would be overestimated using Cobb-Douglas speciifcation without incorporating a damage control agent.

China’s alfalfa market and imports: Development, trends, and potential impacts of the U.S.-China trade dispute and retaliations

This study examines the development and trends of China’s alfalfa market and imports, identifies key factors for the rapid increase in China’s alfalfa imports, and discusses potential impacts of the U.S.-China trade dispute and retaliations on the alfalfa markets and trade in both nations. China’s rapid transition toward larger-scale commercial dairy production, with enhanced feed and cost management as well as quality and safety control, and its limited resources for high-quality alfalfa production are key factors for the dramatic increase in its alfalfa imports, from 19 601 metric tons in 2008 to 1.38 million metric tons(mmt) in 2018. While the United States dominated China’s alfalfa imports with an average share of 97.01% from 2007 to 2017, the share dropped to 83.76% in 2018 and 63.28% in January 2019 due to the trade dispute and retaliations started in 2018. China will likely remain a large importer of alfalfa because of both its growing demand and the comparative advantages of imported alfalfa in quality and price, but the imports from the United States will be highly affected by the ongoing trade dispute and negotiations. China is also expected to make more efforts to reduce its dependence on U.S. alfalfa through increased investment in domestic alfalfa production and identification of alternative sources of alfalfa and other hay imports.

Goal Evolution and Promotion Strategies of Rural Revitalization in the View of Common Prosperity

Rural revitalization is not only an important development goal for the Chinese government, but also a path to development. It is a crucial strategic choice of socialism with Chinese characteristics in a new epoch that to achieve both urban-rural and intrarural prosperity in the course of promoting rural revitalization. In the context of common prosperity, the key to achieving rural revitalization is to strive for the year 2050 long-term objectives of “robust agriculture, beautiful countryside and well-off farmers”, while also accelerating efforts to meet the mid-term targets of “improving the quality and efficiency of agriculture, making rural areas suitable to live and work, and ensuring farmers are affluent and well-off”. In terms of a strategic path, it is vital to combine endogenous growth with a sharing mechanism, with the former aiming to stimulate the internal vitality of rural areas and unleash their growth potential, and the latter to ensure that wealth is shared among all people and access to basic public services is made equal. To implement the strategy, it is suggested to take a regionally differentiated approach and a classification differentiated approach by scientifically grasping rural differences and identifying policy priorities, and explore innovative and diversified mechanisms of rural common prosperity.

Research on the Impact of New and Renewable Energy Replacing Fossil Energy Resource under Constraint of Carbon Emissions

For studying new and renewable energy as a substitute for fossil energy in primary energy consumption and its impact on carbon emissions to cope with economic uncertainties, a multi-sector DSGE model was employed to simulate the dynamic impact on carbon emissions and macroeconomic development. The structural adjustment of energy consumption and the carbon emissions mitigation policy were considered in the model. The simulation results showed that using new and renewable energy instead of fossil energy is an optimal choice for the firms to comply with the regulations of carbon emission mitigation policy. Structural adjustment of energy consumption is the best route to achieve the dual goal of economic development and carbon emission reduction. Unexpected sharp fall in free carbon quota has a negative impact on the economy.