The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron (MLP), recurrent neural network (RNN), and autoregressive integrated moving average (ARIMA) on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA‐MLP and ARIMA‐RNN. Because of the complicated and noisy nature of financial data, we combine novel machine‐learning techniques such as MLP and RNN with ARIMA model to predict the three stock market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA‐MLP and ARIMA‐RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root‐mean‐square error and mean absolute error. Apart from this, ARIMA‐MLP outperformed the ARIMA‐RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA‐RNN beat the ARIMA‐MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time‐series forecasting.

The objective of this paper is to ascertain the impact of Chinese FDI on economic growth in Pakistan. This study documents the exploration of the determinants of economic growth in Pakistan by emphasizing the significant role played by Chinese FDI and investments in renewable energy in particular. This paper employs time series data analysis to examine the relationship between GDP and Chinese FDI, inflation, trade openness, exchange rates, interest rates, remittances, and renewable energy consumption from 1990 to 2019. The study involved performing the ARDL bounds test, and it was determined that the dependent and independent variables are linked in the long term. Furthermore, the error correction model is negative and noteworthy, which checks the long-run relationship between variables. According to the findings of the autoregressive distributed lag (ARDL) model, Chinese FDI has a substantial favorable effect on Pakistan’s economic growth. Furthermore, renewable energy usage has a long-term favorable and significant association with Pakistan’s economic growth. This study established that FDI, and particularly renewable energy, will stimulate the economic growth of Pakistan. Our research has substantial policy implications, especially when it comes to the relationship between FDI and renewable energy.

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.

This study investigates the relationship between news media and public opinion on Belt and Road Initiative (BRI) projects in Myanmar since media liberalization in 2011, using first-level agenda-setting theory. A mixed-method approach was employed: a quantitative content analysis of 217 articles from ELEVEN and The Irrawaddy, identifying 1436 distinct frames on ten BRI-related issues, and a survey of 385 respondents to assess public opinion. Spearman’s rank-order correlation analysis was used to examine the relationship between media coverage and public opinion. A strong positive correlation (rho = 0.87, p < 0.05) was found between increased media coverage and public opinion alignment regarding BRI-related issues. The findings highlight the significant influence of the media on the public perception of BRI projects in Myanmar, and contribute to media effects and agenda-setting theory, offering insights for stakeholders investigating the interplay between the media, public opinion, and international development. Further research is needed to explore the media’s agenda-setting role in BRI project policy decisions in Myanmar.

Increasing farmers’ income and ensuring food security remain significant challenges in Pakistan’s agricultural sector. Social media adoption offers new opportunities for knowledge sharing, market access, and productivity gains; however, its impact on agricultural income remains underexplored. This study investigates the impact of social media usage during the production stage on crop farmers’ income in Punjab, Pakistan, and explores the underlying mechanisms, including improvements in technical efficiency, land productivity, and agricultural labor efficiency. Using survey data from 480 crop farmers, an endogenous switching regression model is employed to estimate the causal effect of social media usage on agricultural income. Mediation analysis further examines how productivity improvements drive income growth. Social media usage significantly increases agricultural income, with results remaining robust across alternative estimation methods. These income gains are primarily driven by improved technical efficiency and land productivity. They are especially evident among farmers with higher education levels, larger landholdings, and greater initial income. These findings underscore the transformative role of social media in rural development by facilitating better access to information and improved farm performance. To amplify these benefits, policymakers should prioritize expanding digital infrastructure, promoting digital literacy, and improving access to agricultural information, particularly for smallholder and low-income farmers.

This study investigates the impact of the media’s secondary agenda-setting on public perception and policy priorities regarding the Belt and Road Initiative (BRI) projects in Myanmar from to 2011–2024. Three hypotheses (Hs) were examined: H1 posits that media coverage aligns with public and policy perspectives; H2 proposes that media emphasis on specific attributes influences their prominence in public opinion and policymaking; and H3 suggests that public opinion mediates the relationship between media coverage and policy priorities, indicating an indirect media influence on policymaking. This study employed a cross-sectional research design, utilizing both quantitative content analysis and survey methodologies. The content comprises the analysis of two news outlets’ coverage (n = 144), surveys with 385 respondents (n = 385), and in-depth interviews with 30 participants (n = 30), and the findings revealed a significant positive correlation between media coverage and public opinion and policy priorities (r = 0.86, r = 0.81, respectively). SEM path analysis reveals that the media agenda indirectly shapes the policy agenda through the public agenda, with an indirect effect path coefficient of 0.718, highlighting the media’s role in policymaking processes. This is evidenced by a significant correlation between media coverage and public opinion (p < 0.05), and a strong direct association between public opinion and policy priorities (p < 0.05). This study extends the agenda-setting theory by empirically demonstrating the media’s indirect effect on policy formation in global infrastructure projects within a developing Southeast Asian country. Future studies should examine the evolution of media patterns across different administrations, including the current one. The results also suggest examining the broader media portrayal of governance issues and conducting extensive research on the media’s impact on public opinion.