13 research outputs found
Impact of COVID-19, Political, and Financial Events on the Performance of Commercial Banking Sector
No full textThis paper employs a structural empirical model to gauge the possible effects of COVID-19, political and financial events on the returns and volatility of commercial banks. It observes that insured and run-prone uninsured depositors choose between differentiated commercial banks, which appears to be significantly impacted from the present pandemic, especially for the case of Pakistan’s commercial banking sector. The estimated volatility series for commercial banks is measured through the GARCH model, which explains the current financial and political distress for the case of shocks from COVID-19. We calibrate by Impulse Indicator Saturation (IIS) to detect the structural breaks formed by these events in the returns and volatility series of commercial banks. It is observed that the calibrated model possesses almost all financial events that have had a prominent impact on the returns and volatility series whereas two out of eighteen political events are unimpacted
Impact of Money Supply and Exchange Rate on Agricultural Prices in Pakistan
No full textThis study analyzed the impact of the long-run neutrality of money supply and exchange rate on Pakistan's agricultural prices using data from 1975 to 2019. Engle and Granger and Johansen and Jusileius techniques were used to analyze the data. The results showed that the exchange rate's neutrality does not hold in the long-run. Simultaneously, the money supply coefficient was found to be insignificant in the long-run, emphasizing money's neutrality. The study concluded that monetary authorities can control the exchange rate by designing and implementing appropriate policies to overcome the overshoot problem of agricultural prices in Pakistan
Impact of COVID-19, Political, and Financial Events on the Performance of Commercial Banking Sector
No full textThis paper employs a structural empirical model to gauge the possible effects of COVID-19, political and financial events on the returns and volatility of commercial banks. It observes that insured and run-prone uninsured depositors choose between differentiated commercial banks, which appears to be significantly impacted from the present pandemic, especially for the case of Pakistan’s commercial banking sector. The estimated volatility series for commercial banks is measured through the GARCH model, which explains the current financial and political distress for the case of shocks from COVID-19. We calibrate by Impulse Indicator Saturation (IIS) to detect the structural breaks formed by these events in the returns and volatility series of commercial banks. It is observed that the calibrated model possesses almost all financial events that have had a prominent impact on the returns and volatility series whereas two out of eighteen political events are unimpacted
A Quest for Equality: Examining Women\u27s Empowerment in Pakistan
No full textWomen are underrepresented in practically every element of society, especially in poorer countries. Women depend on other people in many different ways. Education and a change in how society views women are excellent ways to empower women. Raising awareness and empowering girls in society can also be accomplished through using decision-making authority in the family, economy, and healthcare. In decision-making, money, and access to healthcare, the situation is evolving, and women are becoming more powerful. The study’s main objectives were to understand the socioeconomic and financial aspects of female empowerment in Pakistan. For this, 12,364 married women (15–49 years old) were selected from the PDHS 2017–18. Generally, women in AJK have greater authority than women elsewhere, while FATA women have much less influence. Regression research, however, revealed 16 variables that significantly affect women\u27s empowerment. We used four proxies to empower people. According to this study, most married women were responsible for their homes, finances, and health care. Additionally, this study discovered that respondents from urban areas reported higher levels of empowerment than those from rural areas. Women actively seeking employment have greater influence over their personal, social, and financial lives than women who are not. This study recognizes the close relationship between women\u27s empowerment and decision-making authority
Vulnerability to Climate Change and Socio-Economic Factors: A Comparison of Selected Districts of Punjab
No full textThis study analyzes ten districts of the province Punjab of Pakistan to investigate and compare the vulnerability of selected districts. Total Three sub-groups (socio-economic variables, adaptive capacity, bio-physical variables) are generated by using the data from Pakistan Social & Living Standard Measurement Survey (PSLM) and Pakistan Meteorological Department of the years 2014-15, to calculate total vulnerability. Using primary variables at the district level, this study determines each district’s rural and urban areas' total vulnerability score. The results show that few districts, e.g., Rawalpindi has 0.74 total vulnerability score out of 1, are highly vulnerable compared to other districts despite having a better socio-economic situation. On the other hand, few districts, like Multan, have a low vulnerability to climate change and socio-economic factors.
Keywords: CO2, socio-economic, bio-physical, environment, Vulnerability.
JEL Classification Codes: Q3, O13, P28
Role of Islamic Credit Availability for Women Entrepreneurship Rural Areas of Punjab, Pakistan
No full textThe only religion that values women and recognizes their contributions to society is Islam. Given that they make up more than a quarter of the population, women are a vital and powerful force in the nation's development. Due to marketing and manufacturing limitations, women have unique challenges when running a business, including social and managerial concerns. This study was conducted to demonstrate the accessibility of Islamic loans to female business owners in Punjab, Pakistan. Out of the 36 districts that make up Punjab, two (Lahore and Faisalabad) were chosen for this study. Multistage sampling is not used to gather the data. 25 entrepreneurs were chosen randomly from the five villages chosen from each district, for a total sample size of 200. A well-structured interview was conducted to gather data on socioeconomic traits and the availability of Islamic loans. The data were analyzed using binary logistic regression after descriptive analysis. According to the statistics, 31% of women were single and 39% of women were married. In terms of experience, 40% of women had just begun their businesses, whereas 58% of women had experienced. Women were more likely than males to use Islamic credit, with 52% saying they would do so and 45% saying they would not. 61 percent of women agreed that problems arise from a lack of credit. They struggle with this issue alone
Enhanced car number plate recognition (ECNPR) system by improving efficiency in preprocessing steps
No full textGreen HRM and Resource Optimization in the Public Sector: A Pathway to Achieving Sustainable Environmental Policy Goals
No full textThe study discusses the role of Green Human Resource Management in optimizing resources and achieving environmental policy goals within public sector organizations. In view of increasing pressure to use more sustainable practices, Green HRM emerged as a core determinant in enhancing environmental performance and efficiency in operations. The study examines three influential Green HRM practices, that is, green recruitment, green training, and environmental performance management, in light of assessing the impact of their influence on the consumption of resources, energy, and waste management. A quantitative study was performed by the author based on a survey with the sample size consisting of 200 respondents from 25 public sector organizations. There also seems to be a strong positive relationship found between Green HRM practice and the optimization of resources in particular-through green recruitment and particularly green training. Furthermore, the study indicated that resource optimization served as a mediator between realizing sustainable environmental policy goals and Green HRM. Thus, effective Green HRM practices help an organization decrease its environmental footprint while at the same time improving its operations' efficiency. The study demonstrates that public sector organizations should also use the strategic frameworks designed to set up sustainable long-run sustainability goals with Green HRM practices. This way, research supports literature on Green HRM with its importance and in avenues for potential future research directions towards integrating the practice into the public sector
Artificial Intelligence in Population-Level Gastroenterology and Hepatology: A Comprehensive Review of Public Health Applications and Quantitative Impact.
No full textArtificial intelligence (AI), which includes machine learning and deep learning, is fundamentally changing public health in gastroenterology and hepatology-fields grappling with a significant global disease burden. This review focuses on the population-level applications and impact of AI, highlighting its role in shifting healthcare strategies from reactive treatment to proactive prevention. AI demonstrates substantial improvements across many different areas. In colorectal cancer, AI models significantly boost detection rates, successfully identifying a large majority of high-risk individuals often missed by traditional screening methods. For metabolic dysfunction-associated steatotic liver disease (MASLD), advanced non-invasive tests offer a high degree of reliability in detecting liver fibrosis. The identification of viral hepatitis is enhanced with excellent accuracy, and gastrointestinal infection surveillance benefits from wastewater analysis that provides an early warning system weeks ahead of clinical case reporting. Furthermore, AI improves the diagnosis of upper GI cancers, such as gastric cancer, with higher diagnostic capability, and facilitates precision public health in inflammatory bowel disease (IBD) through highly accurate risk prediction models. Despite these important advances, significant hurdles remain. Key challenges include ensuring diverse and representative data to prevent algorithmic bias, protecting patient privacy, establishing robust regulatory frameworks for new technologies, and successfully moving innovations from research settings into practical, real-world deployment. The unequal distribution of AI development and access between high-income countries and low- and middle-income countries risks exacerbating existing health disparities. To fully realize AI's transformative potential for global public health in gastroenterology and hepatology, these cross-cutting issues must be actively addressed through ethical design, rigorous validation, and equitable worldwide deployment. [Abstract copyright: © 2025. The Author(s).
Artificial Intelligence in Population-Level Gastroenterology and Hepatology: A Comprehensive Review of Public Health Applications and Quantitative Impact.
No full textArtificial intelligence (AI), which includes machine learning and deep learning, is fundamentally changing public health in gastroenterology and hepatology-fields grappling with a significant global disease burden. This review focuses on the population-level applications and impact of AI, highlighting its role in shifting healthcare strategies from reactive treatment to proactive prevention. AI demonstrates substantial improvements across many different areas. In colorectal cancer, AI models significantly boost detection rates, successfully identifying a large majority of high-risk individuals often missed by traditional screening methods. For metabolic dysfunction-associated steatotic liver disease (MASLD), advanced non-invasive tests offer a high degree of reliability in detecting liver fibrosis. The identification of viral hepatitis is enhanced with excellent accuracy, and gastrointestinal infection surveillance benefits from wastewater analysis that provides an early warning system weeks ahead of clinical case reporting. Furthermore, AI improves the diagnosis of upper GI cancers, such as gastric cancer, with higher diagnostic capability, and facilitates precision public health in inflammatory bowel disease (IBD) through highly accurate risk prediction models. Despite these important advances, significant hurdles remain. Key challenges include ensuring diverse and representative data to prevent algorithmic bias, protecting patient privacy, establishing robust regulatory frameworks for new technologies, and successfully moving innovations from research settings into practical, real-world deployment. The unequal distribution of AI development and access between high-income countries and low- and middle-income countries risks exacerbating existing health disparities. To fully realize AI's transformative potential for global public health in gastroenterology and hepatology, these cross-cutting issues must be actively addressed through ethical design, rigorous validation, and equitable worldwide deployment. [Abstract copyright: © 2025. The Author(s).
