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Persistent electricity shortages in Pakistan, causing prolonged grid power load shedding, have adversely impacted various sectors, notably agriculture and the livelihoods of rural farmers. Literature suggests that adopting photovoltaic solar energy can mitigate these issues. This research aims to measure the impact of photovoltaic solar energy on the technical efficiency of food productivity in Khyber Pakhtunkhwa, Pakistan, applying data from 580 respondents. Addressing self-selective bias through ESR and stochastic frontier production function model is utilized to assess technical efficiency. The findings of this study reveal that farmers using solar energy experience a significant improvement in technical efficiency, with 15.8 percent of them achieving a 7.643 percent increase, after accounting for self-selection bias. Furthermore, the positive effects are more pronounced among larger farms and those with greater farming experience. This study underscores the importance of evidence-based approaches in implementing solar energy solutions, highlighting their potential to foster sustainability and equitable development at the grassroots level. The research culminates with policy recommendations that underscore the importance of promoting the photovoltaic solar energy use among farmers to improve food security and increase agricultural productivity. [ABSTRACT FROM AUTHOR]

Digital technology plays a crucial role in advancing sustainable farming and ensuring food security, especially in developing countries. This study evaluates the impact of Internet technology usage on technical efficiency in crop productivity, using data from 600 wheat farmers in rural Pakistan. It addresses the imperative need to enhance agricultural practices within the context of sustainable food production. To achieve this, a matched sample of Internet users and non-users was formed through propensity score matching. The study employs the stochastic frontier method with sample selection adjustment, ensuring a robust evaluation of technical efficiency between these groups. The findings reveal a positive influence of Internet usage on efficiency, persisting even after mitigating self-selection bias from observed and unobserved factors. Internet users exhibit a technical efficiency score of 0.62, surpassing the 0.55 score of non-users. Quantile regression analysis exposes varying impacts of Internet usage on technical efficiency, with less efficient farmers experiencing substantial improvements. Widespread Internet adoption holds the potential to significantly enhance agricultural production for growers. The research underscores the role of promoting Internet utilization to stimulate growth and improve farming efficiency within the evolving digital economy. Policymakers are advised to promote the adoption of modern technology to enhance crop production and support economic growth. [ABSTRACT FROM AUTHOR]

Fossil fuel and electricity-powered irrigation techniques boost the water availability expense and increase greenhouse gas emissions. Especially in developing countries, solar-powered irrigation is becoming more popular as a response to the growing energy and environmental issues associated with agriculture systems. The existing study used data from 1080 wheat farmers in Balochistan, Pakistan, to investigate the impact of solar-powered irrigation system (SPIS) usage on the technical efficiency (TE) of wheat production. The TE of wheat production is estimated using a stochastic frontier production function, and the potential self-selectivity bias is addressed using an endogenous switching regression model. The findings indicated that 13.7% of the wheat cultivators assessed used SPISs to produce their crops. Using an endogenous switching regression model shows that SPIS usage increases the TE of wheat growers by 6.657%, after controlling for self-selection bias. While using SPISs, wheat farmers with large farms and farming familiarity had stronger positive effects on TE. The results highlight the need for more investigation and research into evidence-based good practice for SPIS solutions at the site level to ensure that the rollout of modern equipment not only drives the energy sector forward but also contributes significantly to our level playing field and sustainable environment. [ABSTRACT FROM AUTHOR]

Climate change (CC) is a worldwide environmental issue affecting all economic sectors, especially agriculture. Pakistan is one of the countries most affected by CC due to the country's vulnerability to catastrophic events and limited ability to adapt. Assessing existing activities for adaptation to CC at the farm level is critical to understanding their success and recommending additional government measures. This study analyzes possible farming practice modifications that Pakistani farmers may adopt to reduce the loss of agricultural output due to the rising prevalence of dangerous weather events by CC. Data for the current research were gathered from 432 wheat farmers in rural Pakistan. This article investigates many factors that impact farmers' decisions to CC adaptation in crop production utilizing binary logit (BL) and multivariate probit (MVP) models. Gender, education level, farming experience, farm size, level of damage, access to finance, and training participation are characteristics that substantially affect farmers' likelihood of adapting to CC. Farm size and participation in CC training were the most critical factors influencing farmers' CC adaptation decisions. Policy recommendations were presented to increase the farmers' resilience in the study areas to CC. These comprise expanding CC training courses, developing regulations to encourage agricultural integration, and integrating CC and adaptation to CC principles into the operations of regional organizations. Finally, based on the findings, policymakers will be better equipped to address the challenges posed by CC and create a more resilient agricultural sector. This, in turn, will contribute to improving food security, ensuring sustainable agricultural growth. [ABSTRACT FROM AUTHOR]

Mobile internet technology (MIT) is considered a significant advancement in information and communication technology (ICT), due to its crucial impact on the financial system and social life. In addition, it is an essential technology to overcome the digital divide between urban and rural areas. In terms of agricultural advancement, MIT can play a key role in data collection and the implementation of smart agricultural technologies. The main objectives of this study were to (i) investigate MIT adoption and use in sustainable agriculture development among selected wheat farmers of Pakistan and (ii) examine the crucial factors influencing MIT adoption. This study selected 628 wheat farmers from four districts of Khyber Pakhtunkhwa Province (KPK), Pakistan, for sampling. This study used a bivariate probit method for sampling wheat farmers. The analysis of wheat farmer's data showed farmer's age, farm size, farm location, and knowledge about Internet technology (IT) are strongly correlated with MIT adoption in sustainable agriculture development. Results showed on average, 65% of wheat farmers have mobile devices supporting these Internet technologies, and 55% use MIT in agricultural environments. Since the extant research on MIT adoption for agriculture production in Pakistan is sparse, this study helps advance MIT adoption-based studies. These outcomes may draw the attention of decision-makers dealing with IT infrastructure and agricultural equipment who can support farmers adopting MIT. [ABSTRACT FROM AUTHOR]

Global climate change may result in major environmental issues that have already affected and will continue to affect agricultural sector in the future. A continuing effort to utilize and adopt new agricultural technologies is necessary to mitigate climate change and increase agricultural income. Agricultural cooperatives are gradually being used in emerging countries to encourage improved technology and reduce food insecurity and poverty. This research analyses the influence of cooperative supports (CS) and technology adoption (TA) on agricultural income in Pakistan. It applied the propensity score matching (PSM) technique to evaluate the productivity on survey data from 498 wheat growers to conduct counterfactual analysis for farmers in Pakistan. In addition, a dual selection model (DSM) was applied to resolve the bias in sample selection caused by observed and unobserved aspects of survey data. The results showed that, contrasted with non-membership and non-adopters, growers who joined CS and TA could boost agricultural income by 2.78% and 2.35%, respectively. Stimulatingly, the influence of less-revenue farmers on agricultural income was more substantial than that of high-income farmers. Agricultural income of growers who attached cooperatives and adopted improved agricultural technology enhanced by 5.45% and 4.51%, respectively. These results, among others, emphasize the optimistic role of growing CS and TA in boosting wheat farmer's income. The findings of the study showed strong relationships among education, age, skill, training, gender with CS and TA, and agricultural income. Overall, this study can be helpful in conducting similar studies in other emerging/developing countries for wheat or any other crop growers. [ABSTRACT FROM AUTHOR]