Examining the impact of farm management practices on wheat production: Does agricultural investment matter?

Over the years, the allocation of public funds toward agriculture has consistently played a pivotal role in facilitating the modernization and commercialization of the agricultural industry. Similarly, the integration of technological breakthroughs plays a pivotal role in guaranteeing the sustainability of food production, not solely for the present populace but also for subsequent generations. The present study examines the impact of public investment in agriculture and farm management practices, specifically focusing on cultivated area, fertilizer use, pesticide application, total agricultural machinery, and rural labour force on wheat production in nine provinces of China. The study encompasses the period from 1995 to 2020. This study employs advanced econometric techniques, such as second-generation unit root procedures (CADF and CIPS) and the Westerlund cointegration method, to investigate the stationarity properties and cointegration of the variables. The findings derived from the AMG and CCEMG methods indicate that public investment plays a statistically significant influence on wheat production. In the context of production-related variables, long-term wheat production is statistically and substantially influenced by the total area under cultivation, fertilizer use, and pesticide application. Besides these results, the Dumitrescu and Hurlin causality test reveals a unidirectional causality from agricultural machinery power consumption to wheat production. Furthermore, bidirectional causality exists between public investment, cultivated area, fertilizer use, labour, and wheat production. These results provide vital implications and valuable insights for policymakers in China, which may furnish novel policymaking options for sustainable food production through strategic investments in research and development, irrigation systems, and technological advancements.

Do Farm Subsidies Effectively Increase Grain Production? Evidence from Major Grain-Producing Regions of China.

The purpose of this paper is to investigate the impact of agricultural subsidies on grain production in major grain-producing regions. We use an empirical model and data from fixed observation points in rural areas collected by the Ministry of Agriculture and Rural Affairs in 2016-2017. Our findings show that agricultural subsidies in major grain-producing regions have significantly increased rural household grain yield. Furthermore, findings show that agricultural subsidies and the cost of fertilizer and pesticides for rural households have a mediating effect on grain production. In addition, the effect of agricultural subsidies varies by type: income subsidies have a greater promotion effect on grain production, whereas subsidies for purchasing agricultural machinery have no significant promotion effect on grain production. These findings show that agricultural subsidies promote grain production in China's major grain-producing regions, and have a mediating effect on different types of subsidies.

Impact of Agricultural Mechanization Level on Farmers' Health Status in Western China: Analysis Based on CHARLS Data.

Agricultural mechanization is an important component of agricultural modernization, as it contributes to the improvement of agricultural technology and the rapid transformation of agricultural development. However, research on the connection between agricultural mechanization and farmers' health status is scarce. Thus, using the 2018 China Health and Retirement Longitudinal Survey (CHARLS) data, this study explored how agricultural mechanization can affect farmers' health. OLS and 2SLS models were used for the study's analysis. Furthermore, we used a PSM model to check the robustness of our analysis. The findings showed that: (1) the current state of agricultural mechanization in western China harms the health of rural residents; (2) agricultural mechanization can mitigate the adverse effects on health by increasing farmers' living expenditure and improving their living environment; and (3) agricultural mechanization's effects on farmers' health are regionally and income-heterogeneous. Agricultural mechanization has a more significant impact on health in Tibetan areas and high-income regions. It has an almost minimal effect in non-Tibetan and low-income areas. This paper suggests approaches that can be used to encourage the rational development of agricultural mechanization and improve rural populations' health.

How do carbon emissions, economic growth, population growth, trade openness and employment influence food security? Recent evidence from the East Africa.

East Africa has a substantially greater rate of food insecurity than other regions of the world. Scenarios of climate change and other macroeconomic variables are important contributors to food insecurity in East Africa. Using data spanning from 1990 to 2020, this study looked into the influence of carbon dioxide (CO2) emissions, economic growth, population growth, trade openness, and agricultural employment on food security in the East Africa. The fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models were used in this study. The heterogeneous panel cointegration test's findings indicated that the study variables have an equilibrium long-term connections. The estimation findings from the FMOLS and DOLS models showed that an increase in CO2 emissions increases food security in the East Africa over the long term. According to other findings, long-term food security is positively impacted by economic expansion, population growth, trade openness, and employment in agriculture. However, trade openness has a detrimental long-lasting effect on food security. Future research directions, research limitations, and policy implications are discussed.

The dynamic change trends and internal driving factors of green development efficiency: robust evidence from resource-based Yellow River Basin cities.

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009-2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin.

Technology innovations impact on carbon emission in Chinese cities: exploring the mediating role of economic growth and industrial structure transformation.

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO2 emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO2 reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO2 emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO2 emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO2 emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO2 emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO2 emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking.

Exploring the dynamic nexus between renewable energy, poverty alleviation, and environmental pollution: fresh evidence from E-9 countries.

The present study aims to scrutinize the long- and short-run relationship along with the direction of causality among environmental pollution (CO2), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation in E-9 countries of continent Asia, using a panel dataset from 1990 to 2018. The current study used pooled mean group autoregressive distributed lag (PMG ARDL) and Dumitrescu-Hurlin (D-H) causality test after affirming a stable long-run association among environmental pollution and all the explanatory variables. However, ECM (error correction mechanism) was specified to explore short-run dynamics. The study's outcomes confirmed strong co-integration among environmental pollution (CO2), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation. Moreover, uni (bi) directional causality runs from non-renewable energy, exchange rate, and income disparity (poverty alleviation and renewable energy) to environmental pollution (CO2). Results also revealed that poverty alleviation, exchange rate, and renewable energy usage substantially negatively influence environmental pollution (CO2). Contrarily, income disparities and non-renewable energy usage positively influence long- and short-run environmental pollution. Therefore, from the policy perspective, the current study focused on twofold; first, there is a desire to alleviate poverty, the decline in non-renewable energy use and income disparity among upper and lower-income quintiles. Second, boost exchange rate and renewable energy use to control environmental pollution in the described least developed countries (LDCs).

The role of climatic changes and financial development to the ASEAN agricultural output: a novel long-run evidence for sustainable production.

This paper examines the impact of climate variables and financial development on agricultural value-added and cereal production in selected Southeast Asian economies from 1970 to 2016. The current research applies second-generation advanced techniques to accomplish robust and reliable outcomes. The findings from the FM-OLS estimation disclose that climatic factors, for instance, CO2e and average temperature, impact both agricultural value-added and cereal production negatively, and financial development has an inverted U-shaped influence on both agricultural value-added and cereal production. Meanwhile, other important factors, including cropped area, income level, and rural labor force, significantly improve agricultural value-added and cereal production. Furthermore, the FM-OLS estimator's D-H panel causality test outcomes are reliable. The findings of our study reveal that both the short- and long-run risks of climatic changes to the agricultural sector pose a large-scale threat to food security in Southeast Asian economies. As a result, a robust and stable financial development in terms of governance of climate change finance in the agriculture sector must be achieved to enhance farmers' ability to adapt to current and future climate change adverse impacts.

How do clean fuels and technology-based energy poverty affect carbon emissions? New evidence from eighteen developing countries.

Clean fuels and technology-based energy is an essential source to achieve sustainable economic growth and development. Therefore, the relationship between all types of poverty and other socioeconomic indicators has been studied extensively; nevertheless, clean fuels and technology-based energy poverty, adjusted for carbon emissions, has not been studied. The current study examines the impact of clean fuels and technology-based energy poverty on carbon emissions (Co2e). Using System-Generalized Method of Movement (SGMM) estimators, this study utilized panel data from eighteen developing countries in Asia from 2006 to 2017. The empirical findings obtained from econometric model suggest the presence of clean fuels and technology-based energy poverty and its curse on environment, i.e., energy poverty positively affects Co2e growth in Asian developing countries. Furthermore, economic growth (GDP), trade, and population are also positively associated with Co2e growth and negatively affect environmental quality. Based on the empirical findings of the current study, we recommend robust policy implications that the governments of targeted countries should invest more to increase clean fuels and technologies.

Measuring the Effects of Climate Change on Wheat Production: Evidence from Northern China.

The current study examines the long-run effects of climatic factors on wheat production in China's top three wheat-producing provinces (Hebei, Henan, and Shandong). The data set consists of observations from 1992 to 2020 on which several techniques, namely, fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical co-integrating regression (CCR) estimators, and Granger causality, are applied. The results reveal that climatic factors, such as temperature and rainfall, negatively influenced wheat production in Henan Province. This means that Henan Province is more vulnerable to climate change. In contrast, it is observed that climatic conditions (via temperature and rainfall) positively contributed to wheat production in Hebei Province. Moreover, temperature negatively influenced wheat production in Shandong Province, while rainfall contributed positively to wheat production. Further, the results of Granger causality reveal that climatic factors and other determinants significantly influenced wheat production in the selected provinces.

Household clean energy consumption and health: Theoretical and empirical analysis.

The impact of energy consumption on health has become a widely debated topic around the world. However, much of the current research on this topic lacks a theoretical basis. As a result, this paper employs both theoretical and empirical analysis to investigate the impact of household clean energy consumption on residents' health. First, based on the theories of health economics and energy economics, this paper believes that the usage of clean energy can improve the health of residents. Then, the sample for this study is comprised of data from the 2018 China Health and Retirement Longitudinal Study, and the Order Probit Model is applied for the empirical analysis. The outcomes of basic regression, robustness testing, and the treatment of endogenous factors reveal that the usage of clean energy has greatly benefited the health of residents. Furthermore, the heterogeneity analysis shows that long-term use of clean energy greatly improved the health of non-religious people and had a more pronounced impact on the health of women and low-income residents. In addition, the mechanistic analysis indicates that subjective happiness and air quality played a partial mediating role in the impact of cleaner energy consumption on health. Finally, cleaner household energy reduced the prevalence of hypertension, hyperlipidemia, lung disease, asthma, and depression. The conclusion of this paper supports the view of some existing literature, and several policy recommendations are made based on the research findings.

The Impact of Technological Progress and Climate Change on Food Crop Production: Evidence from Sichuan-China.

Agriculture is an integral sector in China mandated to feed over 1.3 billion of its people and provide essential inputs for many industries. Sichuan, a central grain-producing province in Southwest China, is a significant supplier of cereals in the country. Yet, it is likely to be threatened by yield damages induced by climate change. Therefore, this study examines the effects of technological progress (via fertilizers usage and mechanization) and climatic changes (via temperature and precipitation) on the productivity of main food crops, such as rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays) in Sichuan province. We employ the generalized method of moments (GMM) model to analyze Sichuan provincial data from 1980 to 2018. Our findings show a positive nexus between fertilizers use and yields of main food crops. Only rice and maize yields are significantly improved by mechanization. Increased average temperature reduces rice and wheat yields significantly. Rainfall is unlikely to have a significant impact on agricultural production. The study suggests that the Chinese government should consider revising its strategies and policies to reduce the impact of climate change on food crop production and increase farmers' adaptive ability.

Does Cleaner Household Energy Promote Agricultural Green Production? Evidence from China.

Cleaner household energy for agricultural green production can significantly alleviate energy poverty and food security, thus contributing to global sustainable development. Using survey micro-data collected from Sichuan Province, the ordered probit model, OLS model, and instrumental variables approach were applied for empirical analysis. The results show that: (1) cleaner household energy significantly enhances farmer's agricultural green production awareness and improves agricultural green production levels, which is still significant after treating endogenous issues with the conditional mixing process estimation method and 2SLS model; (2) health plays a partially mediating effect of cleaner household energy on agricultural green production awareness and agricultural green production levels; (3) environmental protection awareness and digital literacy have a moderating effect and reinforce the positive impact of cleaner household energy on agricultural green production awareness and agricultural green production levels. This research suggests that governments can enhance the impact of cleaner household energy on agricultural green production through price and subsidy mechanisms.

How Does Clean Energy Consumption Affect Women's Health: New Insights from China.

The United Nations (UN) has identified the promotion of cleaner energy and improving women's health as two important elements in achieving the global sustainable development goals. However, the impact of household clean energy consumption on women's health needs to be further analyzed and improved based on new methods, new data, and new perspectives. This paper used the data from the 2018 China Health and Retirement Longitudinal Study as the sample, and the Ordered Probit model, the instrumental variable (IV) approach, the conditional mixed process (CMP) method, and the mechanism analysis model were applied to empirically investigate the impact of cleaner household energy consumption on women's health. The findings are the following: (1) It is found that cleaner household energy consumption improved women's health, and after selecting "respondent's regions of residence" as an IV to overcome endogenous issues, the estimated results remained significant. (2) The mechanistic estimation showed that air quality, social contact, and well-being play a mediating role in the effects of cleaner household energy consumption on women's health, while digital ability plays a moderating role in the cleaner household energy consumption impact on women's health. (3) This study further explored that cleaner household energy consumption significantly reduced the likelihood of women being diagnosed with hypertension, hyperlipidemia, cancer, lung disease, asthma, and depression. The conclusion of this paper that "cleaner household energy can enhance the level of women's health" supports the viewpoints of some present literature. At the same time, this paper puts forward four policy recommendations based on the research conclusions.

Reflections of Pro-Poor Growth across Agro-Climatic Zones for Farming and Non-Farming Communities: Evidence from Punjab, Pakistan.

The basic objective of the existing study was to inspect the triangular association between economic growth, poverty, and income disparity in farming and non-farming communities across agro-climatic zones in Punjab province, Pakistan. The cross-sectional Household Integrated Economic Survey (HIES) data and Poverty Equivalent Growth Rate (PEGR) methodology were applied from 2001-2002 to 2015-2016. Outcomes of the study found that in a short period, 2001-2002 to 2004-2005; 2004-2005 to 2005-2006; 2005-2006 to 2007-2008; 2007-2008 to 2010-2011; 2010-2011 to 2011-2012; 2011-2012 to 2013-2014; and 2013-2014 to 2015-2016, economic growth has presented hybrid (pro-poor and anti-poor) pattern across both communities of all agro-climatic zones of Punjab province in different periods. In the longer period of 2001-2002 to 2015-2016, economic growth has been pro-poor across both communities of all the zones apart from zone III (Cotton-Wheat Punjab); there is an anti-poor pattern of economic growth. Results for the decomposition of change in poverty further indicate that economic growth is a dominant factor in reducing poverty for all investigated zone. Moreover, a positive redistribution component reduces the beneficial impacts of economic growth for the poor more than for non-poor, that ultimately makes economic development patterns anti-poor in zone III. In the present study, we proposed two-fold policy implications. First, improve the living standard of households in each agro-climatic zone by increasing their incomes. Second, develop a precise taxation system that helps to reduce income disparities among upper-pro to lower-income groups.

Modeling the Impact of Climatological Factors and Technological Revolution on Soybean Yield: Evidence from 13-Major Provinces of China.

In recent years, the changing climate has become a major global concern, and it poses a higher threat to the agricultural sector around the world. Consequently, this study examines the impact of changing climate and technological progress on soybean yield in the 13 major provinces of China, and considers the role of agricultural credit, farming size, public investment, and power of agricultural machinery from 2000 to 2020. Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied to assess the long-run effect, while Dumitrescu and Hurlin's (2012) causality test is used to explore the short-run causalities among the studied variables. The results revealed that an increase in the annual mean temperature negatively and significantly affects soybean yield, while precipitation expressively helps augment soybean yield. Furthermore, technological factors such as chemical fertilizers accelerate soybean yield significantly, whereas pesticides negatively influence soybean yield. In addition, farming size, public investment, and power of agricultural machinery contribute remarkably to soybean yield. The causality results endorse that chemical fertilizers, pesticides used, agricultural credit, public investment, and power of agricultural machinery have bidirectional causality links with soybean yield. This study suggests several fruitful policy implications for sustainable soybean production in China.

Non-adoption decision of biogas in rural Pakistan: use of multinomial logit model.

In 2009, Pakistan introduced a subsidized biogas program to disseminate clean and affordable energy in rural areas. However, the adoption rate did not appear as expected. Therefore, the present study aims to examine the determinants behind the non-adoption of biogas digesters. Detailed information via a structured questionnaire was obtained from biogas adopters and non-adopters, and analyses were performed in two levels. Initially, the study used the multinomial logit regression to elicit the non-adoption behavior. Results depicted family size, risk aversion, cook education (women), kitchen (inside the home), home structure, and non-availability of inputs as significant factors behind non-adoption. Detailed analysis also revealed that the factors like the age of household head, area of the house, cook education (women), location of the kitchen (inside the home), and the distance of the house to the bus stop (minutes) lead towards the potential adoption of biogas. The study also investigated the potential factors behind the long-term sustainability of biogas digesters with the help of binary logit. The results depicted that the kitchen's location (inside the house), cook education (women), training, and subsidy significantly and positively impact the biogas plant's probability of being functional. Based on these results, the study suggested that policymakers increase women's education in rural areas, provide a subsidy to reduce costs and risk, and arrange training for adopters.

Does financial development mitigate the effects of climate variability on rice cultivation? Empirical evidence from agrarian economy.

This study is the first attempt to examine the effects of changing climate and financial development on rice cultivation in the context of agrarian economy like Thailand from 1969 to 2016. The current study also uses other important variables, such as cultivated area, organic fertilizers usage, and rural labor to determine the long-term connection amid variables. In this study, we applied several econometric techniques, for instance the autoregressive distributive lag-error correction model (ARDL-ECM), vector error correction model (VECM), impulse response functions (IMFs), and variance decomposition (VARD) method to estimate the most reliable and robust outcomes. The empirical results showed that in the long- and short-run, there is a reduction in rice cultivation as temperature increase. The carbon dioxide (CO2) positively affects rice cultivation in the long-run, while this association is negative in the short-run. The findings further revealed that in the long- and short-run, domestic credit provided by the financial sector significantly positive improved rice cultivation, while domestic credit to private sector by banks negatively affects rice cultivation. The important input factors, including cultivated area, organic fertilizers usage, and rural labor significantly positive contributed toward rice cultivation in the long- and short-run. The calculated long-run causal connection of all the studied variables with rice cultivation is validated. The estimated short-run causal relationship is unidirectional among temperature, CO2 emissions, financial development, rural labor, and rice cultivation. In addition, our outcomes are robust and also verified by IMFs and VARD method. The study offers some important policy suggestions to increase rice production with the help of sound and well-developed financial systems and climate controls.

How does economic complexity affect ecological footprint in G-7 economies: the role of renewable and non-renewable energy consumptions and testing EKC hypothesis.

The discussion concerning whether and how economic complexity (ECI) affects ecological footprint (EFP) has gained researchers' consideration, while there are slight empirical evidence to support the subject matter. In the support of theoretical argument, this study provides empirical evidence by investigating the impact of ECI on EFP along with the role of disaggregated energy consumptions by using a panel dataset of G-7 economies between 1996 and 2019. To this end, we applied panel techniques of Fully-Modify OLS and Dynamic-OLS models for cointegration analysis. The results obtained from Fully-Modify OLS and Dynamic-OLS models reveal that ECI deteriorates environmental quality by increasing EFP, while renewable energy reduces ecological pollution by decreasing EFP. In addition, the increasing demand for non-renewable energy and economic growth both degrades environmental quality in G-7 countries. More interestingly, the non-linear (ECI2) relationship between ECI and EFP confirms a U-shaped association (EKC hypothesis), which suggests that after achieving a certain threshold level, economic complexity mitigates environmental degradation in G-7 economies. The empirical results also suggest that other control variables such as population growth, inflation rate, foreign direct investment, and total trade intensity lead to environmental degradation by increasing ecological footprint. Based on empirical results, the following important policy implications are drawn; first, G-7 economies should speed up the level of economic complexity along with renewable energy consumption to protect environmental quality and maintain sustainable growth and development. Secondly, the governments of G-7 countries should introduce greener technologies and promote production that are environmental friendly for drastic reduction in environmental unsustainability.

Tracking the effect of climatic and non-climatic elements on rice production in Pakistan using the ARDL approach.

The present study aims to investigate the effect of climatic and non-climatic factors on rice production by employing an annual time series data from the period of 1970 to 2018. The study employed an ARDL (Autoregressive Distributed Lag) approach, and the long-term equilibrium linkages between the variables have been discovered. Additionally, the study also used a regression model to determine the robustness for the authentication of results. The Fully Modified Ordinary Least Squares (FMOLS), Canonical Cointegration Regression (CCR) methods, and the VECM (Vector Error Correction Model) technique confirmed the long-run causal relationships amid the variables. The empirical results further revealed that climatic factors including annual temperature negatively affect the rice crop production, while carbon dioxide emission positively influenced via long-run. Similarly, non-climatic factors like area under rice crop, fertilizer consumption, labor force, and water availability affect the rice production positively in the long-run analysis. Finally, the pairwise Granger causality test revealed that both climatic and non-climatic variables had a substantial impact on rice yield in Pakistan. Based on the study's findings, the government and policy makers should formulate alleviation polices to tackle with harsh effects of climate change and consistent adoption of measures to secure overall agricultural production including rice crop because it is a country stable food.