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The rapid development of digital finance has effectively reduced financial challenges in rural regions and created new prospects for agricultural production. This article examines the impact of digital financial development on rice production in Sichuan Province using the 2011–2021 Peking University Digital Financial Inclusion Index and data from 20 prefecture-level cities, as well as a fixed effects model. The mechanism of action is also discussed. The findings reveal that the advancement of digital finance plays an important role in boosting the expansion of rice production, and that digital finance influences rice output by increasing farmers' willingness to participate in insurance and increasing the availability of credit. A heterogeneity analysis reveals that digital finance has a substantial effect on mountainous and economically poor areas. As a result, this article suggests that the breadth and depth of usage of rural digital finance, as well as the development of rural digital financial services in underdeveloped areas, should be expanded. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates the impact of board funds, banking credit, and economic development on food production in the context of South Asian economies (India, Pakistan, Bangladesh, Sri Lanka, and Nepal). Design/methodology/approach: This study used data from the World Development Indicators covering the years 1991–2019. To investigate the relationship between the variables of the study, we employed the panel unit root test, panel cointegration test, cross-sectional dependence test, fully modified least squares (FMOLS), and panel dynamic least squares (DOLS) estimators. Findings: The empirical results indicate that board funding significantly increase food production; however, banking credit had a negative impact. Furthermore, the findings indicate that economic development, Arable land, fertilizer consumption, and agricultural employment play a leading role in enhancing food production. The results of the Dumitrescu-Hurlin causality test also show substantiated the significance of the causal relationship among all variables. Practical implications: South Asian countries should prioritize board funding, bank credit, and economic development in their long-term strategies. Ensuring financial access for farmers through micro-credit and public bank initiatives can spur agricultural productivity and economic growth. Originality/value: This study is the first to combine board funding, banking credit, and economic development to better comprehend their potential impact on food production. Instead of using traditional approaches, this study focuses on these financial and developmental aspects as critical determinants for increasing food production, using evidence from South Asia. [ABSTRACT FROM AUTHOR]

A better understanding of the dynamics involved in grain production is critical for food security and poverty reduction. To this end, several factors influence grain production, including capital (i.e. R&D investment and agricultural credit), agriculture environment (i.e. CO2 emissions), and technical progress (i.e. fertilizers and agricultural machinery). This paper analyses the combined effects of these factors on China's grain crops output from 1990 to 2017 by using the autoregressive distributed lag (ARDL) approach. The ARDL‐bounds testing approach provided the long‐run connection amid the variables. The findings include: (i) agricultural R&D spending has an encouraging and meaningful influence on grain crops yield in the long‐run and short‐run; (ii) agricultural credit significantly and positively stimulates grain crops output; (iii) CO2 emissions negatively impact grains' output in the short‐ and long‐run; (iv) area under grain crops and fertilizers used also endure a positive spur on grain crops production in the long‐run and short‐run; and (v) short‐run nexus among the variables is navigated for robustness rationale via the vector error correction model Granger causality practice. Hence, the strategy specialists should also acquaint finances through prescribed organizations on comfortable provisions and minimal interests. In addition, the Chinese Governments and agricultural extension organizations should support the easy acquisition of high‐tech cultivating machinery to harvest crops swiftly and explore substantial markets for further business. [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]

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. [ABSTRACT FROM AUTHOR]

This study aims to examine the impact of financial development on agricultural production in the case of China. The study used country level time‐series data for the period 1989 to 2016. We applied the autoregressive distributed lag (ARDL) approach to investigate the long‐term cointegration relationship between underlying variables and the fully modified ordinary least squares (FMOLS) for robustness check. Results of this study confirm the existence of a long‐term relationship among the variables. The ARDL estimation results reveal that financial development has a significantly positive impact on agricultural production in both long‐run and short‐run. The fully modified OLS confirm the robustness of the findings. This study suggests that the Chinese government should pay more attention on long‐run policies to enhance agricultural growth through improving banking sectors, efficient rural credit markets, and increasing township banking infrastructures in the country. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study assessed the long-run (LR) and short-run (SR) impacts of climatic and non-climatic factors, i.e., CO2 emissions (CO2e), 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 CO2 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, CO2 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. [ABSTRACT FROM AUTHOR]

This study aims to explore the dynamic association among crop production, livestock production, power consumption in agriculture, forest area, and carbon dioxide (CO2) emissions. Based on the annual data of China, spanning the period 1990 to 2016, the study applied the auto-regressive distributed lag (ARDL) bounds testing approach. In addition, the fully modified ordinary least squares (FMOLS) canonical cointegration regression (CCR) and the Granger causality tests are employed to check the robustness of the ARDL estimations. The ARDL-bounds testing approach indicated that all variables share a long-run connection. The long- and short-run ARDL estimations confirmed that crop production, as well as livestock production, has a significant positive effect on CO2 emissions in both cases. However, power consumption in agriculture and forest area has a negative effect on it, indicating that both variables reduce CO2 emissions in the long and short run. These results stood robust under various regression estimators and confirmed the findings of the ARDL method. Additionally, the results of the causality approach specified that a unidirectional causality is running from crop production, power consumption in agriculture, and forest area to CO2 emissions. The causality between livestock production and CO2 emissions is bidirectional. Therefore, the directions of this connection also validate the outcomes under various techniques used for robustness. These findings suggest that the government must reconsider its policies related to agricultural and livestock production and adopt environment-friendly practices in the agriculture sector that may reduce the carbon footprints in the long run. [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]

[Display omitted] • This study examined the impact of Internet use on rice production in China. • We employed the FGLS technique and a novel method of MMQR. • Empirical findings reveal that Internet use significantly improved rice production. • Fertilizer, planting area, and energy use enhanced rice production substantially. ICTs play an increasingly crucial role in ensuring food security and sustainable agricultural production, particularly in emerging economies. The majority of survey-based literature focuses on Internet use and farmers' income, technical efficiency of agricultural production, the economic well-being of smallholder farmers, and market information, respectively. The present study, on the other hand, investigates explicitly the long-term effects of Internet use on rice production using panel data from the main rice-producing provinces of China for the period 2011–2020. Other key factors of rice production included in this study are chemical fertilizer, sown area, power consumption, public spending, and labour force. Using the cross-sectional time-series FGLS approach to control endogeneity issues, the results show that Internet use improves rice production in the long run, while the remaining determinants (chemical fertilizer, sown area, power consumption, and public spending) stimulate rice production in the long run. The D-K-SE and MMQR approaches confirm the substantial impact of important factors of rice production. Policymakers should improve Internet access and encourage the use of modern techniques to increase rice output in China. [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]

In this study, we examine the effects of technological development (via fertilizer and pesticide consumption) and information and communication technology (ICT) on cereal production in four ASEAN countries (Indonesia, Malaysia, the Philippines, and Thailand) from 1991 to 2018. For empirical investigation, this study used advanced econometric methodologies. The estimated results demonstrate the long-run co-integration relationship between the variables. Pooled mean group (PMG)-based empirical results show that technological development (via fertilizer consumption and pesticide use) significantly increases cereal production in the long-run after confirming the long-run association among the variables of interest. Similarly, ICT also significantly enhances cereal production in the long-run. It has been thoroughly demonstrated that technological development and ICT play an important role in increasing cereal production and ensuring food security in the selected ASEAN countries. Furthermore, the findings of the Dumitrescu-Hurlin (D-H) causality test show unidirectional causality from fertilizer consumption and pesticide use to cereal production, as well as bidirectional causality between ICT and cereal production. In this regard, it is critical for local farmers to produce high added value through technological development while also serving as a regional base and supply center in agriculture. To ensure that technological innovations enhance productivity, ICT-based agriculture, and the adoption of technology in the production of agricultural products, governments should promote locally sustainable ICTs, such as mobile phones and Internet-based digital tools and services. [Display omitted] • The impacts of technological advancement and ICT on cereal production are examined. • Technological advancement and ICT enhance cereal production in the long-run. • Bidirectional causality is discovered between ICT and cereal production. • Unidirectional causality is shown from fertilizer and pesticide to cereal production. [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]