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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.

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.

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research attempts to evaluate the linkage among climatic change factors such as average temperature and rainfall patterns and non-climatic factors such as the area under major yield crops, fertilizer consumption, and formal credit on major food crop yield from 1985 to 2016 in Pakistan. For the first step, we checked the stationarity of the series by utilizing the unit root tests. An autoregressive distributed lag (ARDL) model was employed to identify the linkages between variables after verifying the properties over a specific period of time. The consequences of this study confirmed the long-run association between climatic and non-climatic factors to the major food crop yield in Pakistan. Furthermore, the outcomes of the study revealed that temperature has a diverse impact on major food crop yields. Whereas, the area under major food crops, average rainfall, fertilizer consumption, and formal credit have a positive impact on major food crop yield in Pakistan. For the second step, we used the Granger causality test to verify the causal linkage for the variables. The outcomes reveal a significant effect of climatic and non-climatic factors on major food crop yield. The bidirectional causality causal associations are found to be significant among variables including average temperature, fertilizer consumption, and formal credit disbursement. The empirical results further indicated that major food crop yields are more affected by climatic factors such as average temperature as compared to non-climatic factors. Based on the study findings, few recommendations are made to cope with factors of climate change. Invent such agricultural-specific adaptation policies for farmers which possess the ability and resilience to tackle climate change. Research and development in agriculture should focus on major varieties of food crops that can endure high temperatures. The agriculture industry will be able to sustain long-term production and distribution efficiency attributable to these strategies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the impacts of climate change on yield of selected cereal crops (wheat and maize) in the northern climatic region of Khyber Pakhtunkhwa (KP) province of Pakistan for the period 1986-2015. The first-generation unit root tests such as the Levin, Lin, and Chu (LLC), augmented Dickey-Fuller (ADF)-Fisher, and the second-generation unit root tests such as cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional ADF (CADF) are used to check stationarity of the series. The cointegration among the variables is discovered via Pedroni test and Westerlund method. The long- and short-run impacts of climatic variables (average precipitation, maximum temperature, and minimum temperature) on yield of wheat and maize crops are assessed through the autoregressive distributed lag (ARDL) model. The empirical findings reveal that average precipitation has a significantly positive impact on yield of both crops in long- as well as short-run. The results further reveal that the effect of average minimum temperature on both crops is insignificant in long-run. However, the short-run effect of average minimum temperature is significantly positive on yield of maize crop but insignificant on yield of wheat crop. In long-run, an increase in average maximum temperature negatively affects crop yield. In short-run, however, it positively affects the yield of wheat and maize crops. The study recommends that increase in area under cultivation, development of advanced irrigation system, and farmers' access to metrological information will help in lowering the drastic impacts of climate change on crop productivity., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study assessed the long-run (LR) and short-run (SR) impacts of climatic and non-climatic factors, i.e., CO 2 emissions (CO 2 e), average level of temperature (ALT), average level of precipitation (ALP), area harvested of wheat and rice crops (AHW and (AHR), domestic credit (DCR), and agricultural labor (ALB) on wheat and rice production (WP and RP) in Turkey by using annual time series data ranging from 1980 to 2016 and by employing several econometric techniques. The autoregressive distributed lag-bounds (ARDL) approach and the Johansen and Juselius cointegration (JJC) test confirmed a valid long-term connection among underlying variables. The estimation results from the ARDL model reveal that climatic factors such as CO 2 emissions and temperature adversely affected wheat production in the long run as well as in the short run, whereas precipitation positively improved wheat production in both periods. Further results indicate that non-climatic factors like area harvested of wheat and domestic credit positively and significantly enhanced wheat production in the long run and short run. Similarly, CO 2 emissions also adversely affected rice production in both periods, while temperature and precipitation positively contributed towards rice production in both cases. In addition, area harvested of rice positively and significantly boosted rice production in the long run as well as in the short run, while domestic credit negatively influenced rice production in the long run but in the short run positively improved rice production. Additionally, the outcomes of the VECM Granger Causality for both rice and wheat production confirm that both climatic and non-climatic variables have a strong influence on the production of both crops. This study found that climate change has a deleterious influence on both wheat and rice production; therefore, the study suggests that temperature-resistant varieties of both crops should be developed and introduced by agricultural research institutions. In addition to this, up-to-date information is more needed related to climate change, and in the farming communities, it should be provided by agricultural extension workers., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research has examined the dynamic linkages among climate change factors, such as CO 2 emissions, temperature, rainfall, and cereal yield in Turkey from 1968 to 2014. At first step, we tested stationary properties of the climatic factors and crop yield by using both traditional and breakpoint unit root tests. After the confirmation of given properties, we used the autoregressive distributed lag (ARDL) model to capture the dynamic relationship among the variables in the given span of time. The empirical results show that there is a long-run equilibrium relationship that exists between climate change factors and cereal yield. CO 2 emissions and average temperature have a diverse effect on the cereal yield, whereas average rainfall has a positive effect on the cereal yield in both the long run and short run. To check the causality, we use the Granger causality test that reveals a significant effect of climate change variables on the cereal yield. The unidirectional causal link is significant among temperature and rainfall factors. The results show that the cereal yield is affected by more climate factors like rain fall and temperature due to CO 2 emissions as compared to land and labor use. Based on the findings of the study, few suggestions have been made to address the climate change factors. Devise agriculture-specific adaptation policy for the farmers to build their capacity and resilience to tackle climate changes, for example, farm practices. Agriculture research and development should work on cereal crop varieties that can tolerate the high temperature and precipitation. These policies could help the agriculture sector to sustain production and allocation efficiency in the long run.

The current empirical study explores the linkage between carbon dioxide (CO 2 ) emissions, average temperature, cultivated area, consumption of fertilizer, and rice production in Pakistan. For this research, the annual time series data from 1968 to 2014 were used to enhance the validity of the empirical outcomes. The cointegration analysis with the auto-regressive distributed lag (ARDL) bounds testing approach is applied to explore the effects of climate change on rice production. Additionally, the estimated long-run outcomes are verified by employing fully modified ordinary least squared (FMOLS) and canonical cointegrating regression (CCR) approaches. The empirical outcomes revealed that the selected important study variables are cointegrated demonstrating the existence of long-run linkages among them. The main fruitful outcomes of this study are that rice production in Pakistan is positively affected by the carbon dioxide (CO 2 ) emissions in both long-run and short-run.

This article explores the impact of farmers' livelihood assets and adaptation approaches on livelihoods. We proposed a new paradigm for the sustainable livelihoods of smallholders based on the grounded theory, to exploit seven household assets and used mixed methodological approaches of growers' livelihood assets and climatic adaptation strategies based on farmers' livelihood concerns in Sindh province of Pakistan and to better understand smallholder farmers' sustainable livelihoods and applied a partial least square path modeling. Considering central critical paths, psychological assets (PsyA) entail mediational factors into the sustainable livelihoods index. The findings show that the essential support of the livelihood of farmers' social, cultural, economic, and human assets positively impacts sustainable livelihoods, though physical and natural assets depict a nonsignificant impact on SLI. However, human and financial assets show comparatively substantial effects on smallholders' adaptation strategies; consequently, physical, social, and natural assets reveal significant impacts on farmers' livelihoods. The study further indicates that PsyA can, directly and indirectly, boost the human and physical assets and exploit the farmers' sustainable livelihoods index successfully. Lastly, this research proposed policy suggestions for poverty reduction and sustainable livelihoods of small-scale growers. [ABSTRACT FROM AUTHOR]

This study is the first effort to assess the long-term effects of change in climate on crop production in South Asian countries from 1991 to 2016 by employing the second-generation methods robust to cross-sectional dependence and slope heterogeneity. Using panel data with the panel dynamic least squares (PD-LS) method and several co-integration approaches, this study confirmed a long-term co-integration among considered variables. The long-run estimates revealed that climatic variables, including temperature and CO2 emissions, negatively affected crop production, suggesting that a 1% increase in temperature and CO2 emissions reduces crop production by 1.93% and 0.32%, respectively. Conversely, precipitation positively affects crop production in the long-run, indicating that a 1% surge in precipitation increases crop production by 0.52%. Moreover, non-climatic variables including cultivated area, income level, and financial development positively affected crop production in the long-run. Furthermore, a 1% surge in cultivated area, income level, and financial development enhances crop production by 0.29%, 0.13%, and 0.04%, respectively. The outcomes of the Dumitrescu-Hurlin causality test confirmed that the causal link among all variables is significant, and outcomes verify the previous findings. This study suggests that urgent attention should be given to various adaptation strategies, such as credit supply, cropped area expansion, irrigation infrastructure enhancement, and the introduction of improved kinds of major food crops to enhance agricultural productivity. Besides, agricultural extension authorities should provide information about climate change to farming communities to deal with the adverse impacts of sudden climate changes on productivity. [ABSTRACT FROM AUTHOR]

• Impacts of climate change on major fruits production in Pakistan is examined. • The climatic variables such as temperature and CO 2 emissions negatively affected apples production. • Precipitation positively contributed towards apples production. • Furthermore, temperature also positively affected bananas production, while precipitation and CO 2 emissions have a negative impact on bananas output. • In addition, climatic variables all have a favorable impact on mangoes, guavas, and mangosteens production. The literature on the effect of climate change on agricultural products has grown over the years. However, evidence on how climate change affects fruit industry remains limited. This research fills the gap by estimating the effects of climatic parameters on major fruits production in Pakistan. In this study, the ARDL model is employed to estimate the long three decades of data. The ARDL Bounds testing approach confirmed the long-term co-integration of the variables under consideration. The findings show that climatological elements such as temperature and CO 2 emissions have a detrimental impact on apples output whereas precipitation has a favorable impact on both in the long and short run. Furthermore, the findings reveal that precipitation and CO 2 emissions have a negative impact on bananas output in Pakistan, both in the long and short run. Temperature, on the other hand, has a favorable and considerable effect on bananas output. In addition, the outcomes reveal that temperature, CO 2 emissions, and precipitation all have a favorable impact on mangoes, guavas, and mangosteens production in both the long and short run. The findings of this study guide the formulation of appropriate policies to mitigate the negative impacts of global warming on the fruits industry and ensure sustainable food production in the country to meet domestic demand and international trade goals. [ABSTRACT FROM AUTHOR]

• Impacts of climate change and technology on grain yields is examined. • In the presence of CSD, the second–generation estimation techniques are applied. • It is observed that temperature negatively affected grain yields across the quantiles. • Production inputs (i.e., fertilizer, pesticide, irrigated area) significantly improved grain yields across the quantiles. The adverse effect of rising temperatures on grain output is gradually spreading across China. On the other hand, technical developments have resulted in substantial changes in the agricultural production system over time. Hence, we assess the effect of temperature on grain yields in addition to the potential effect of some technological factors using a panel dataset spanning the period 1996 to 2020 for selected prominent grain-producing provinces in China: Anhui, Hebei, Heilongjiang, Henan, Hubei, Hunan, Jiangsu, Jiangxi, Jilin, Neimenggu, Shandong, Sichuan, and Liaoning. We apply a novel Method of Moments Quantile Regression (MM-QR) and second–generation estimation techniques, which generate consistent and robust results in the presence of cross–sectional dependency (CSD). The empirical findings from the MM-QR estimator reveal that climate change (via temperature) significantly decreases the grain yields in overall quantiles and the higher negative impact was observed in the 75th and 95th quantiles, while technical factors, irrigated area, and financial support play a substantial role in improving the grain yields in China. In addition, the findings from the D–H panel causality method show the various flows of causal links between the selected variables, considering the grain–producing regions of China: grain yields → temperature, pesticide usage → grain yields, and financial support → grain yields. A bidirectional causality association is observed to exist between fertilizer usage ↔ grain yields, pesticide usage ↔ grain yields, and irrigated area ↔ grain yields. To ensure food security, China's prominent grain–growing regions should strengthen their technological innovation efforts and invest in research and development to produce new varieties that can withstand heat and drought stress and produce better grain yields. [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]

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]

Vietnam is an important contributor to the world's food industry as a major exporter of rice, seafood, and coffee. Climate change poses a serious threat to Vietnam's agricultural sector since it adversely affects food security in Vietnam and globally. This study investigates the short- and long-term effects of climate change on Vietnam's agriculture, both in terms of production and values at the macro level. Using the Autoregressive Distributed Lag (ARDL) model and the Toda-Yamamoto (1995) Granger causality test with annual data from 1990 to 2019, we confirm the detrimental impacts of global warming on Vietnam's agricultural performance in both the short and long term. We also reveal the favorable effects of CO 2 emissions, land, and fertilizer on Vietnam's agricultural production and economics. Other factors, including rainfall and labor, however, adversely affect Vietnam's agricultural output and economic performance. Based on the study's results, we provide policy recommendations to assist the government limit the negative effects of climate change on the national economy, thereby promoting poverty alleviation and sustainable development in Vietnam. • Short- and long-term effects of climate change on Vietnam agriculture are assessed. • A long-term relationship exists between climatic factors and agriculture. • Global warming adversely impacts Vietnam agriculture in both short and long term. • CO 2 , land, and fertilizer positively affect agricultural production and economics. • Rainfall and labor have negative effects on Vietnam agricultural performance. [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 study attempts to investigate the effects of global climate change (via temperature and rainfall) on cereal production in Sichuan over the 1978–2018 period, whether agricultural credit combining with technical progress (i.e., mechanical farming rate) mitigate the effect of climate change. The present study empirically analyzed the short-term and long-term interrelation among all the considered variables by using the autoregressive distributed lag (ARDL) model. The results of the ARDL bounds testing revealed that there is a long-term cointegration relationship between the variables. The findings showed that temperature significantly negatively affected cereal production, while rainfall significantly contributed to cereal production in the context of Sichuan province, China. Agricultural credit, especially in the long run, significantly improved cereal production, implying that agricultural credit is used to invest in climate mitigation technologies in cereal production. Findings further indicated that the mechanical farming rate significantly enhanced cereal production, indicating that technical progress has been playing a vital role. This study suggests that the policymakers should formulate more comprehensive agricultural policies to meet the financial needs of the agricultural sector and increase support for production technology. [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]

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]

[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]