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The pivotal role of computer technology in augmenting crop productivity, optimizing supply chain management in food production, and reducing wastage through precision agriculture techniques is undeniable. The utilization of computers has significantly transformed the field of food production, enhancing effectiveness, environmental sustainability, and economic viability. This study examines the asymmetric and long-term effects of computer usage on grain output in the selected Chinese provinces. Additionally, it investigates the impact of other variables, such as energy use and the application of pesticides and fertilizers on grain yields. To analyze the dataset spanning from 2002 to 2020, the researchers employed the FGLS, D-K, and Dumitrescu-Hurlin causality methods. The study's findings underscore the substantial positive impact of computer utilization on grain production. Besides, fertilizer application and adoption of irrigation practices positively influence grain yields. Conversely, the utilization of pesticides, power consumption, and rural labor engagement exhibit a negative impact on grain output. Therefore, evaluating the potential of investing in sophisticated technologies, considering multiple elements including local conditions, the availability of financial resources, and the role of agricultural industrialization in regional development is imperative. We discuss the policy implications of these findings in detail in the Conclusion section. • The purpose of this study is to investigate the long-term effects of computer use on grain production. • We employ the FGLS method proposed by Reed and Ye (2011). • The results demonstrate that the use of computer significantly increases grain production. • Agricultural inputs such as fertilizers and the effective irrigated area contribute significantly to the enhancement of grain production. • While the use of pesticides negatively impacted grain production. [ABSTRACT FROM AUTHOR]

This study examined the impact of agricultural credit and farm size on the technical efficiency of rice productivity in Sindh, Pakistan. A cross-sectional random sampling technique was used to collect data from 180 rice growers through a face to face interview. The stochastic production frontier technique was employed to analyse the survey data. The results of Maximum Likelihood Estimation (MLE) showed that credit, farm size, fertilizer, and labor significantly influenced the rice productivity in Sindh, Pakistan. Additionally, larger and significant scale of elasticity was found on credit while larger and significant marginal effect was found on farm size. Further, the mean technical efficiency was 0.97, which implies that 97 percent of rice farmers are technically efficient. Therefore, agricultural credit and farm size are the dominant factors in the improvement of rice production as well as the technical efficiency of smallholder farmers in Sindh, Pakistan. [ABSTRACT FROM AUTHOR]

Agriculture is an important sector of Pakistan's economy, accounting for approximately 26 percent of the country's gross domestic product (GDP). The aim of this study was to use an econometric analysis to investigate the relationship between agricultural gross domestic product (AGDP) and variables such as cropped area, fertilizer consumption, credit distribution and water availability in Pakistan Data were explored from 1978-2015; we used time series data collected from secondary sources, including the Pakistan Bureau of Statistics, Statistical Year Books and the Economic Survey of Pakistan. Data were analysed by using the Phillips-Perron (P-P) and Augmented Dickey Fuller (ADF) test, and results were interpreted by using the Johansen co-integration test. The Cobb-Douglas Production Function was used to examine the impact of these major factors on agricultural productivity in Pakistan. We found that fertilizer consumption, improved seed distribution, and credit distribution had a positive and significant influence on AGDP, whereas water availability had a negative but insignificant influence on AGDP. Based on our results, we suggest that the Government of Pakistan should formulate policies and funding schemes for the development and improvement of water availability including irrigation systems. [ABSTRACT FROM AUTHOR]

Abstract This study is designed to assess the factors that affect smallholder rice farmer's participation in market. In addition it also examines the effect of commercialization on the welfare of smallholder farmers. The method of Heckman two-stage model is used to obtain the desired objectives. Random sampling technique is used to collect data from 249 smallholder farmers. Result of the study indicates that gender of the household head, age, number of family member who assist in farming, household size, vocational training, and the farmer being landlord and farm size were the major determinants of market participation. The welfare of the farmer depends whether the farmer participate in the rice output market. The result also indicated that rice output, off-farm income, access to credit, and income from the sale of rice were important factors influencing the welfare of the household. The participation in market can be increased by providing subsidized prices for their production, cold storage houses, vocational training, introducing new technology, increasing contact with extension agent and providing genetically modified seeds. [ABSTRACT FROM AUTHOR]

Abstract The basic objective of this paper was to investigate and enumerate the relationship between cotton crop output, agricultural gross domestic product (AGDP), area under cotton crop and fertilizer consumption in Pakistan over the period 1970–2015. Time series data were used in this study from 1970 to 2015, and these data were collected from Economic Survey of Pakistan and Pakistan Bureau of Statistics annual reports. Cotton crop data were analyzed using Augmented Dickey Fuller (ADF) test, co-integration test and Ordinary Least Square (OLS) method. The results of co-integration test show that there exists a long-term relationship between output of cotton crop, area under cotton crop, fertilizer consumption and agricultural gross domestic product of Pakistan. Regression analysis results showed that output of cotton and fertilizer consumption has positive relationship with agricultural gross domestic product of Pakistan while area under cotton crop has a negative relationship with agricultural gross domestic product (AGDP) of Pakistan. [ABSTRACT FROM AUTHOR]

Abstract The data for this empirical study were collected from three major cropping systems of Sindh province, and a total of 240 farmers were selected by simple random sampling technique. Cobb-Douglas production function was applied to analyze the data. Results show that in mixed cropping zone wheat yield increased with increasing ploughing, seed and plant protection. The dominant factors behind yield increase in the cotton-wheat cropping zone were ploughing, seed, fertilizer, and irrigation. Wheat yield in the Rice-wheat zone increased linearly with increasing ploughing, seed and fertilizer as well as plant protection measures. Further the results show that salinity and water logging are the driving threats leading to high water table in most regions of upper Sindh. Due to poor land management and improper irrigation strategies, the coefficient of irrigation shows negative value. Contrarily, lower Sindh needs canal irrigation water (i.e. Mixed and cotton-wheat zone), because most of the areas have unfit ground water for irrigation, thus increasing the soil erosion and salinity in lower Sindh. Furthermore, the cost of production estimated in cotton-wheat zone's grower spends more USD$841/ha as compared to rice-wheat zone's grower and Mixed cropping zone's grower spend USD$827/ha and USD$780/ha. The growers of the whole Sindh spend USD$816/ha. In case of gross income cotton-wheat zone's grower received higher than 1287, followed by the growers of mixed cropping zone and rice-wheat zone received USD$1248/ha and USD$1132/ha due to high cost of production. The overall Sindh growers received USD$1222/ha. In the case of net return grower of mixed cropping zones received higher USD$481/ha, compared to cotton-wheat zone's and rice-wheat zone's grower received USD$451/ha and USD$308/ha, respectively. The growers of the whole Sindh province received USD$413/ha net return from wheat crop. The production of wheat is lower as compared to cost. Therefore, net income of per acre and the production cost of per acre reduce with farm size, so increasing the use of inputs should assure the quantity and quality by the approach of growers. [ABSTRACT FROM AUTHOR]

• We assessed the climate change impact on wheat production in China. • We employed the FGLS, DOLS, and D–K estimation techniques. • Temperature negatively affected wheat production in the long–run. • Precipitation contributed positively to wheat production in the long-run. • Agro–chemical input (fertilizer use) enhanced wheat production in the long–run. Northern and Southern regions are the two major wheat production belts of China. Agro–climatic resources have changed significantly in recent years, threatening staple food production in these regions. As a result, it is critical to investigate the long–term effect of climate change and agri–inputs on wheat production in China's top six wheat producing provinces (Hebei, Shandong, Henan, Jiangsu, Anhui, and Hubei) from 1995 to 2020. The estimated long-run results from the FGLS, DOLS, and D–K estimators revealed that climatic factors, specifically temperature, had a negative impact on wheat production, while precipitation had a positive impact. The findings also revealed that agrochemical inputs, such as fertilizer, increases wheat production, whereas pesticide use decreases wheat production significantly. The results from the Dumitrescu–Hurlin panel causality test showed a bidirectional causality between rainfall, fertilizer use, and cultivated area with wheat production, while a unidirectional causality association is running from labor force to wheat production. The current study provides several critical policy recommendations for China's sustainable food production through green agricultural practices and robust climate mitigation strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Adoption of certified and improved high-yielding crop varieties is important avenue for increasing agricultural productivity and improving the living standard of the farmers in developing countries. The main objective of the current study was to examine factors affecting adoption of improved rice varieties by smallholder farmers in Northern Sindh, Pakistan. The random sampling technique was used to collect data from 220 smallholder rice farmers through the face to face interview. Data were analyzed using descriptive statistics and probit regression model. The empirical results showed that year of education ( P ≤ 0.093), farming experience ( P ≤ 0.043), soil quality ( P ≤ 0.077), farm machinery ownership ( P ≤ 0.000), access to market information ( P ≤ 0.055) and contact with extension agents ( P ≤ 0.006) had significantly positive influence on adoption of improved rice variety, while age ( P ≤ 0.053) had significantly negative effect. [ABSTRACT FROM AUTHOR]

The climatic events and increasing population are impacting the food system's resilience. The significance of a looming food crisis may be more pronounced in a country like Pakistan. Therefore, to manage farm production sustainably, this research infers the Value-Belief-Norm (VBN) theory to analyze small growers' pro-environmental adaptation and mitigation behaviors on the farm. The data of 250 samples were collected from the Sindh province of Pakistan. We applied the partial least squire modeling (PLS-SEM) to examine the farmers' pro-environmental behaviors towards climate change mitigation and adaptation practices in farm productions. The results provide evidence that farmers' pro-environmental personal norms R2(80.2%), explain mitigation attitudes (41.2%), and (29.0%) adaptation behaviors of growers. All antecedents of VBN theory reveal robustness and significantly positive relationships except for egoistic values. Thus, pro-environmental personal norms predicted the farmers-orientation behaviors significantly toward the climate variability adaptation practices and mitigation attitudes. Moreover, findings indicate that the VBN theory enacts well when expounding altruistic values and biospheric values of farmers' mitigation attitudes and adaptation behaviors. Despite guaranteeing food security, this research suggests designing policy tools to encourage small growers' pro-environmental behaviors in response to climatic changes to increase sustainable agricultural production in the region. • This research used the Value-Belief-Norm (VBN) theory in the context of climate change mitigation and adaptation behaviors in farm production. • This study empirically examines the determinants of growers' pro-environmental personal norms towards mitigation and adaption via partial least squares structural equation modeling (PLS-SEM). • The VBN theory provides evidence that farmers' pro-environmental personal norms R2(80.2%) explain mitigation attitudes (41.2%) and (29.0%) adaptation behaviors toward climate change. • Thus, pro-environmental personal norms predicted the farmers-orientation behaviors significantly toward the climate variability adaptation practices and mitigation attitudes. • This study implicates future policies that promote effective and sustainable pro-environmental behavioral changes in agriculture while ensuring regional food security. [ABSTRACT FROM AUTHOR]

Agricultural entrepreneurship significantly improves farmers' livelihoods and it also contributes toward poverty reduction. In the present study, we used the data of the China Household Finance Survey (CHFS 2019) as a sample, and empirically examined the dynamic linkages between adoption of digital technology (ADT) and farmers' agricultural entrepreneurial willingness (AEW). The findings of this study reveal that (1) the ADT significantly improved farmers' AEW by 18.5%; (2) the ADT more significantly affected the entrepreneurial willingness of farmers who live in less developed rural areas, or who preference for risk, or whose households have not been affected by major adverse events, or who belong to the rural elite; (3) digital financial participation plays a partial mediating effect of 11.7% in the effect of the ADT on farmers' AEW, with financial literacy and subjective well-being having moderating effects and reinforcing the effect of the ADT on farmers' AEW. Finally, we put forward several policy recommendations, such as narrowing the 'three-level digital divide', improving digital human capital, and developing digital inclusive finance to provide new ideas for farmer entrepreneurship, to enhance farmer's livelihood and to promote rural economic development. • The dynamic linkage between adoption of digital technology and farmers' agricultural entrepreneurial willingness is examined. • Probit model and two-step method of the ivprobit model are used. • The ADT significantly improved farmers' AEW. • Digital finance participation plays a mediating effect among ADT impact on farmers' AEW. • Financial literacy and subjective well-being play a moderating effect on the relationship between ADT and AEW. [ABSTRACT FROM AUTHOR]

Cereal and oilseed crops possess significance in meeting global food security. China, housing the most number of people, remains the top importer of oilseed crops (i.e., soybeans) to produce energy and meet its food needs. With such significance, the present study investigates the impact of meteorological factors on soybean production in China using the annual data from 1978 to 2020. It also incorporated other essential determinants of soybean production, such as agricultural subsidy, cultivated area, and fertilizer use. For data analysis, it employed the autoregressive distributed lag (ARDL) method and the Quantile Regression (QR) technique. The findings from an ARDL model unveiled meteorological factors such as the yearly average temperature and CO 2 emissions declined soybean production in the long–run and short–run analysis, whereas the yearly average precipitation improved soybean production. Besides, agricultural subsidy, cultivated area, and fertilizer use also enhanced soybean production in the long–and short–run analyses. In addition, the findings from the Quantile Regression (QR) technique showed that temperature and CO 2 emissions negatively affected soybean production in each quantile (i.e., 0.1–0.90), while precipitation and agricultural subsidy positively augmented soybean production across all quantiles (i.e., 0.1–0.90). Based on these results, the study provides clear policy implications, such as governments should provide crop-specific subsidies instead of input-based subsidies to embolden the impact of agricultural subsidies. Also, ecological improvement campaigns should be launched to attract farmers' attention to sustainable agriculture practices to meet meteorological challenges. [Display omitted] • Impact of climate change on soybean production is examined. • The role of agricultural subsidy for soybean production is investigated. • Agricultural subsidy increases soybean production. • Rainfall augments soybean production. • Temperature and CO2 negatively affected soybean production. [ABSTRACT FROM AUTHOR]

This article evaluated the urban land use efficiency (ULUE) of 57 cities in the Yellow River Basin (YRB) from 2005 to 2017 with the super epsilon based measure (Super-EBM) model, analyzed its difference characteristics and evolution trend by using the Theil index and kernel density function, revealed its spatial correlation by Moran index and LISA clustering, and also explored its influencing factors by the Tobit model. The results show that the ULUE of the YRB first declined and then increased, with the highest in the upstream areas, followed by the downstream areas, while the lowest in the middle reaches of the YRB. The ULUE in the YRB presented the characteristics of continuous distribution, and the ULUE in the cities south of the Yellow River was significantly higher than that in the cities north of the Yellow River. Secondly, the imbalance of ULUE in the YRB was aggravated, and the difference between groups was small while the difference within the group was absolutely dominant. The imbalance of ULUE in the midstream areas of the YRB dominated the whole basin. Thirdly, the ULUE of the YRB had a significant spatial correlation. In 2017, the local spatial correlation was mainly low-low aggregation, and the clustering area was concentrated in resource-based cities in Shanxi Province. Finally, the impact of economic development on ULUE in the YRB presented a "U" curve relationship. The proportion of secondary industry, population density, introduction of foreign capital, innovation level and traffic facilities can significantly promote the ULUE in the Basin, while land urbanization and environmental regulation had a negative impact on the ULUE of the YRB. This paper is important to realize the intensive use of urban land and achieve high-quality development in the YRB. • The urban land use efficiency, its spatial-temporal features and influencing factors of the Yellow River Basin were analysed. • The urban land use efficiency of the Yellow River Basin first declined and then increased during 2005–2017. • The urban land use efficiency had a significant spatial correlation and mainly low-low aggregation in 2017. • The economic development level had a "U" shaped impact on the urban land use efficiency. • Population density, foreign capital, innovation level and traffic facilities positively affect urban land use efficiency. [ABSTRACT FROM AUTHOR]

Considering the significant impact of climate change on major staple food crops in Nepal, this study aims to estimate the influence of climatic factors (i.e., CO 2 emissions, average temperature, and average precipitation) and technological factors (i.e., fertiliser consumption and improved seeds) on rice production in Nepal from 1990 to 2016 using the autoregressive distributed lag (ARDL) approach. While controlling for cultivated rice areas, agricultural credit variables are likely other essential rice production factors. This study reveals a long-run cointegration connection among the variables. The ARDL results indicate that CO 2 emissions decreased rice production by 0.13%, while average temperature and average precipitation improved rice production by 0.72% and 0.01%, respectively, in the long run. Further results show that cultivated rice area, fertiliser consumption, and agricultural credit enhanced rice production by 2.26%, 0.05%, and 0.02%, respectively, in the long run. Unidirectional causality among cultivated areas, fertilisers, seeds, temperature, CO 2 emissions, and rice production was confirmed. Additionally, impulse response and variance decomposition verified the substantial impacts of climate and technological factors on rice production and variations. This study empirically confirmed that the use of agricultural technology (i.e. fertiliser consumption) significantly enhanced rice production; therefore, this study suggests that the Nepalese government should expand subsidised fertilisers so as to increase rice production and improve the income of farmers. In addition, agricultural credit plays a vital role in enhancing rice production in Nepal; to cope with climate change, the study also suggests that there is a need to launch carbon/weather financing schemes through financial intuitions in the country. [Display omitted] • The impacts of climate change is examined on rice production. • The ARDL approach is used to explore long-way relationship between the variables. • Temperature and precipitation positively affected rice production in the long-run. • CO2 emissions adversely influenced rice production in the long-run. • Area, fertilizer use, and credit positively improved rice production in the long-run. [ABSTRACT FROM AUTHOR]

The current study examines the effect of global climate change (CO 2 emissions), financial development, and technical progress (fertilizer consumption and improved seed distribution) on cereal production in Pakistan over the 1977–2014 period. The study undertakes the autoregressive distributed lag (ARDL) bounds testing approach to investigate the long-term interrelation among the variables. The outcomes of the ARDL bounds-testing approach confirmed the presence of a long-term relationship among the variables. Empirical results revealed that CO 2 emissions have a negative impact on cereal production in the short-run and long-run. It means that increase in global climate change will decrease cereal production. Findings further showed that financial development has a positive impact on cereal production in both cases. It suggests that increasing financial development will enhance cereal production, which will ensure the country's food security. In addition, technical progress has a significantly positive impact on cereal production in both cases. The dynamic OLS, fully modified OLS, and the canonical cointegrating regression estimators confirmed the robustness of the findings. Financial development is essential for sustainable agriculture production; therefore, policymakers should devise a comprehensive agriculture policy that addresses the financial needs of the agriculture sector and attracts investment. The financial institutions may use carbon financing as a tool to intervene in the financial market to generate funds for the application of cleaner production principles and the use of best practices for agriculture development and sustainable production. Image 1 • We examined the impact of financial development, climate change, and technical progress on cereal production. • The ARDL approach is employed to explore the long-run relationship among the variables. • Findings reveal that financial development improves cereal production in both long-run and short-run. • CO 2 emissions have adverse impact on cereal production in both cases. • Technical progress will leads to increase cereal production in both long-run and short-run. [ABSTRACT FROM AUTHOR]

During the last decade, the major South Asian countries (Pakistan, India, and Bangladesh) have effectively utilized wind electricity to avoid future energy predicament. However, the wind industry is being influenced by a diverse range of factors. The aim of this study is to develop a value chain model for the South Asian wind power industry, scrutinize both internal and external factors to analyze the viability of present condition and future roadmap to foster the wind energy sector by adopting Strengths, Weakness, Opportunities, and Threats (SWOT) model. Firstly, a novel value chain model was developed for the wind industry. Secondly, we identified the social, economic, and environmental factors, significantly influencing the competitiveness and development of the wind industry through clear and precise examination of strengths, weaknesses, opportunities, and threats in the South Asian perspective. A total of 19 factors were identified and analyzed. Research findings indicate the current situation and future projections of the wind industry in a competitive environment. Finally, we suggested essential policy measures to stabilize the wind industry's growth. This study will serve as a benchmark for the steady development of the wind power industry and towards a secure and sustainable South Asia. • Developed a novel value chain model for the South Asian wind power industry. • Critically analyzed internal and external factors and developed SWOT analysis model. • 19 factors were analyzed, influencing the competitiveness of South Asian wind industry. • Proposed essential policy guidelines to stabilize the wind industry's growth. [ABSTRACT FROM AUTHOR]

The economic conditions of rural households have changed because the extensive usage of the Internet technology in rural China. Hence, according to micro-survey data from the China Family Panel Studies (CFPS) in 2014, 2016 and 2018, in this work we use the Probit model to experimentally examine the association between cooking energy usage and Internet technology use in Chinese rural households. Research results showed that Internet technology use can significantly and positively influences the choice of Households' clean cooking energy, and further mechanism analysis reveals that off-farm employment as a partly mediator between the use of the Internet and the clean energy consumed by households. In particular, we further examine the region and age differences in Internet technology use and its household cooking energy consumption consequences. The assessment of the Internet technology used by rural residents' heterogeneity indicates that in the eastern region or the younger and middle-aged group of rural residents can better use the Internet technology to realize the households' cooking energy conversion. Therefore, in the context of global climate change and frequent catastrophic weather occurrences, we suggest that rural households should widely utilize the Internet, greatly expand off-farm employment channels, and accelerate the conversion and upgrading of cooking energy consumption in rural areas. • Impact of Internet use on rural households' fuel consumption in China is examined. • Data from the China Family Panel Studies (CFPS) in 2104, 2016 and 2018 is used in this study. • Probit model and the mediation effect model are applied. • Internet use significantly promotes household clean fuel consumption in rural China • Mechanism analysis reveals that non-agricultural employment plays a partial mediating role. [ABSTRACT FROM AUTHOR]

This paper investigates the electricity production from different sources in Pakistan, and the contribution of these sources to economic growth. An ADF (Augmented Dickey-Fuller) unit root test was used to check the variables stationarity, while an ARDL bounds testing approach was used to check the long-term relationship among the study variables. Results illustrate that electricity produced from coal, hydropower, natural gas and nuclear sources has a significant influence on the economic growth of Pakistan. [ABSTRACT FROM AUTHOR]

Participation in international industrial transfer (IIT) provides a significant opportunity and a motivation to improve China's industrial land production efficiency (ILPE). This study aims to investigate the overall role, heterogeneous impact and indirect mechanism of IIT in improving Chinese ILPE. This paper uses the Directional Distance Functions - Data Envelope Analysis (DDF-DEA) model to measure ILPE, economic output efficiency, and pollution reduction efficiency, the Global Malmquist Luenberger (GML) index to decompose the growth of ILPE into "technical efficiency change (EC)" and "technological change (TC)". The panel data of Chinese provinces from 2003 to 2018 and the Fixed-Effect model is used to examine the impact of IIT on ILPE. The primary outcomes suggest that participation in IIT has generally improved the ILPE in China. This promotion effect is evident after 2010, and IIT has a significant impact on the improvement of ILPE in extensive and inefficient areas. Similarly, IIT promotes the economic output efficiency of industrial land from the perspective of expected output and reduces unexpected output. This impact helps in improving pollution reduction efficiency of industrial land. The technology spillover brought by IIT improves the Chinese ILPE from two channels, including promoting technological progress and improving technical efficiency. However, the technology spillover mainly promotes the ILPE in land use high-efficient areas by promoting technological progress. Likewise, the ILPE is promoted by improving technical efficiency from a regional perspective in extensive and inefficient areas. This study provides valuable insights for the improvement of ILPE to optimize land resources. [ABSTRACT FROM AUTHOR]

[Display omitted] • Devolving the CO 2 emission influence on climatic change, forestry, livestock and crops production. • Forestry, rainfall and temperature exposed a positive effect on CO 2 emission in the long-run analysis. • Forestry, crops production, livestock, population growth, rainfall and temperature also showed a positive effect on CO 2 emission in the short-run dynamics. Global warming is an important issue from the last few decades and causing climate change due to carbon dioxide emission and greenhouse gases emission. The present study's key aim is to decouple the carbon dioxide emission influence on forestry production, crops production, livestock production, energy usage, population growth, temperature and rainfall in Pakistan. Time series data was utilized ranging from 1970 to 2017, and stationarity of the data was verified by using the unit root tests, while vector autoregressive model was applied to demonstrate the dynamic interaction amid study variables. Furthermore, the Granger causality test was applied to check the causal relation amid variables. The long-run dynamics results through the vector autoregressive model show that forestry production, rainfall, and temperature have a constructive effect on carbon dioxide emission, while crops production, livestock production, energy use, and population growth have a negative effect on carbon dioxide emission. Short-run analysis outcomes also demonstrate that forestry production, crops production, livestock production, population growth, rainfall, and the temperature have a positive effect on carbon dioxide emission, while energy usage has an adverse impact on carbon dioxide emission in Pakistan. Similarly, Granger causality test results also exposed that all variables have a unidirectional association. The Pakistani government needs to take the requisite measures to curb carbon dioxide emission in order to improve agricultural production. [ABSTRACT FROM AUTHOR]

This research examines the heterogeneous dynamic links among healthcare expenditures, land urbanization, and CO 2 emissions across the development levels of China. To this end, data of 27 Chinese provinces are considered from 1999 to 2018. Theoretically, this research developed a healthcare expenditures-augmented Stochastic Impacts of Regression by Population, Affluence, and Technology (STIRPAT) model to incorporate healthcare expenditures as a determinant of affluence. Empirically, this research established a system of simultaneous equations based on the healthcare expenditures-augmented STIRPAT model to estimate the links among the variables. As a pre-analysis, second-generation Westerlund cointegration is applied and found the long-term equilibrium association among the variables. The long-run estimations and short-run causality are done by employing dynamic common correlated effects mean group method (DCCEMGM) and Dumitrescu-Hurlin causality. A heterogeneous long-run equilibrium linkage is confirmed to exist among the variables of interest. Concerning the long-run estimates, firstly, the healthcare expenditures growth and land urbanization exhibited a bilateral positive link. Secondly, CO 2 emissions and healthcare expenditures growth manifested the existence of a bilateral positive link. And thirdly, a unilateral positive (negative) link is revealed to exist from a linear term (squared term) of land urbanization to CO 2 emissions. Concerning the short-run results, firstly, a bilateral causal bond exists between the land urbanization and healthcare expenditures growth. Secondly, a bilateral causal bond prevails between CO 2 emissions growth and healthcare expenditures growth. Finally, a unilateral causal bond is operational from land urbanization to CO 2 emissions growth. In terms of the nature of the link, the long-run findings are consistent across the data samples. However, considering the degree of influence, heterogeneity is confirmed across the development levels for both long- and short-run. It infers that relatively more (less) developed regions showed relatively strong (weak) influence. Based on empirical findings, relevant policies are recommended. Unlabelled Image • Integrated healthcare expenditures to STIRPAT model as a component of 'Affluence' • Westerlund's cointegration and dynamic common correlated effects mean group method were applied. • Healthcare expenditures, land urbanization, and CO 2 emissions were interlinked in the long-run. • Bilateral positive causal bond of healthcare expenditures with land urbanization and CO 2 emissions • Unilateral positive (negative) causal bond of land urbanization (squared land urbanization) with CO 2 emissions [ABSTRACT FROM AUTHOR]