Purpose: The climate change effects on agricultural output in different regions of the world and have been debated in the literature of emerging economies. Recently, the agriculture sector has influenced globally through climate change and also hurts all sectors of economies. This study aims to examine and explore the impact of global climate change on agricultural output in China over the period of 1982-2014.Design/methodology/approach: Different unit root tests including augmented Dickey–Fuller, Phillips–Perron and Kwiatkowski, Phillips, Schmidt and Shin are used to check the order of integration among the study variables. The autoregressive distributed lag (ARDL) bounds testing approach to cointegration and the Johansen cointegration test are applied to assess the association among the study variables with the evidence of long-run and short-run analysis.Findings: Unit root test estimations confirm that all variables are stationary at the combination of I(0) and I(1). The results show that CO₂emissions have a significant effect on agricultural output in both long-run and short-run analyses, while temperature and rainfall have a negative effect on agricultural output in the long-run. Among other determinants, the land area under cereal crops, fertilizer consumption, and energy consumption have a positive and significant association with agricultural output in both long-run and short-run analysis. The estimated coefficient of the error correction term is also highly significant.Research limitations/implications: China’s population is multiplying, and in the coming decades, the country will face food safety and security challenges. Possible initiatives are needed to configure the Chinese Government to cope with the adverse effects of climate change on agriculture and ensure adequate food for the growing population. In concise, the analysis specifies that legislators and policy experts should spot that the climate change would transmute the total output factors, accordingly a county or regional specific and crop-specific total factor of production pattern adaptation is indorsed.Originality/value: The present empirical study is the first, to the best of the authors’ knowledge, to investigate the impact of global climate change on agricultural output in China by using ARDL bounds testing approach to cointegration and Johansen cointegration test.

Purpose: The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan.Design/methodology/approach: The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach.Findings: This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years.Research limitations/implications: In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well.Originality/value: This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

Purpose: The purpose of this paper is to examine the key risk components (probability and consequence) and their respective thresholds affecting agri-food supply chain operations in Ghana. In addition, it seeks to understand the relationship between the major risk sources and to fathom the risk/disruption impact on agri-food supply chain performance in Ghana.Design/methodology/approach: Cross-sectional survey data were collected using a structured questionnaire. The risks threshold associated with agri-food supply chain were categorized using the risk matrix scale and classification described in the Project Management Body of Knowledge (Project Management Institute, 2013). Next, the Pearson correlation was used to understand the relationship between the various risks and agri-food chain performance. Lastly, to investigate how firms’ supply chain operations have been affected by risks/disruptions, an ordinary least square regression model was employed to quantify the impact of some major risk sources on agri-food chain performance in Ghana.Findings: The results in this paper show variations in risks’ probability, impact and threshold in agri-food supply chain. While risk sources such as periodic change in interest/exchange rate policies and volatility in customer demand are high-rated risks, uncertain land policies/tenure and poor quality control are low rated risks in the operations of the chain. The performance of the agri-food chain significantly but negatively correlates with all the major risks studied. Whereas demand, supply, weather, logistics/infrastructure and financial risk sources significantly undermined the chain’s performance, risks emerging from biological/environmental, management/operational, policy/regulations and political-related issues insignificantly affect the performance of agri-food supply chain in Ghana.Research limitations/implications: This research is an area biased. However, some insightful managerial implications can be drawn from this paper to manage agri-food chain operations in a similar unstable environment. The result implies that risks are inevitable in agri-food chain but they differ in terms of menace to the chain’s operation. Therefore, to manage agri-food supply chain risks effectively, managers should periodically identify, quantify and categorize risk sources before making risk response decisions. In addition, the results show that risks account for about half of the overall agri-food chain performance in Ghana. This infers that managers/practitioners could improve the performance of the agri-food chain if limited resources are allocated to plan and effectively respond to major risks sources (such as demand, supply, finance, weather and logistical/ infrastructural services-related risks) undermining the performance of the chain.Originality/value: This research contributes to the agri-food chain risk literature and provides managers/practitioners with empirical evidence of risk thresholds and their corresponding major impact on agri-food chain’s performance. Since risks explained about half of agri-food chain performance in Ghana, this research would prompt decision makers to improve on their risk assessment and responds (e.g. by employing efficient demand, supply and weather forecasting systems, logistic/infrastructure services, hedge to finance, etc.) to improve the chain’s performance.

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.

This study analyzed the effects of internet use on farm income and household income using survey data from 478 rural farmers from two regions in Ghana. An endogenous switching regression (ESR) model and probit models were employed to achieve the aims of the study. The results revealed that internet use was influenced by off-farm employment, education, access to credit, non-fixed asset (NFA), age, and perception variables. We found that internet use increased farm income and household income by 20.1% and 15.47%, respectively. Regarding heterogeneous impacts, the estimates showed that internet use reduced farm income by 18.12% for farm households that participated in off-farm activities but increased farm income by 14.66% for households that had access to NFA. The estimates also indicated that internet use increased household income by 31.77% for farm households that engaged in off-farm employment and by 15.33% for those that had access to NFA. Furthermore, internet use increased the household income for households that did not engage in off-farm activities by 24.85%. The findings of this study will contribute significantly to the existing literature on information communication technology (ICT) in developing countries by providing a new reference for improving rural development and solving the problem of poverty.

People’s lives, particularly farmers’, have been affected by extreme weather conditions that have reduced the yield of numerous crops due to climate change. Climate-smart agriculture practices can reduce or eliminate greenhouse gas emissions and have the propensity to increase farm income and productivity. Therefore, the purpose of this study is to ascertain whether CSA practices impact farmers’ income. This study includes all cocoa farmers in the selected districts in the Ashanti Region. The population includes those who live in the six cocoa production villages. The multistage sampling procedure was considered based on the dominants of literature. The study used an endogenous switching regression framework to examine the effects of the adoption of climate-smart agricultural practices (CSAPs) on farmers’ income. While estimating treatment effects, telasso uses lasso techniques to select the appropriate variable sets. The results revealed that gender, farm experience, age, household size, and farm size do not significantly influence the adoption of irrigation and crop insurance. The study revealed a significant positive impact of access to credit on adopting irrigation and crop insurance. The adoption of climate-smart practices has a positive coefficient. This indicates that if all respondents in each region adopts these practices, their income would increase significantly. This study shows that adopting irrigation practices leads to an increase in household income of 8.6% and 11.1%, respectively, for cocoa farmers. Crop insurance has a positive coefficient and is statistically significant on household income, on-farm, and off-farm. This paper shows that climate-smart practices such as crop insurance can positively influence farmers’ income in Ghana. We also conjecture that crop insurance is the most effective and efficient climate-smart practice among the various agricultural practices. The study suggests that access to credit and mass awareness should be compulsory modules coupled with the consistent training of farmers on new technologies for effective policy implementation. Expanding access to extension officers could enhance farmers’ adaptive capacity and warrant the efficiency of implemented practices.