This study aims to examine the degree of financial literacy and practices of financial knowledge among MBA students in Nepal. Four prominent universities were selected for study: Tribhuvan University, Kathmandu University, Pokhara University, and Purbanchal University. The descriptive and analytical research approach was applied to analyze the data. Data were collected through questionnaires from 320 students by using convenience and stratified sampling methods. The analysis was conducted using the SPSS software system. The results highlight the complex interplay of factors influencing financial behavior and literacy among MBA students, emphasizing the importance of education, familial influence, and media exposure in shaping financial attitudes and decision-making. The study delves into several key aspects of financial behavior, influence, attitude, literacy, and knowledge sources among MBA students. Notably, respondents displayed positive financial behaviors such as reading for knowledge enhancement and prudent spending practices. Parental influence emerged as the most significant factor shaping financial decisions, followed by media and internet exposure. Respondents generally exhibited a favorable financial outlook and demonstrated understanding in various financial literacy domains, though areas for improvement, particularly in investment risk comprehension, were identified. The study shows how education, family influence, and media exposure affect MBA student’s financial think, how people handle finance, like their education and where they get information from. This is seen as reflected in financial literacy scores ranging from 1.43 to 3.86, with an average of 2.405 and a standard deviation of 0.449, suggesting below-average scores and reduced unpredictability.

This research aims to determine an Auto-Regressive Integrated Moving Average (ARIMA) model and forecasting the National Consumer Price Index (NCPI) in Nepal, using annual data from the fiscal year 1972/73 to 2022/23. The research utilized secondary data collected from the online bulletin published by Nepal Rastra Bank, aiming to enhance understanding of NCPI patterns and contribute to predictive modelling techniques for economic indicators. Adopting the Box-Jenkins technique and using E-Views statistical software, this study identifies ARIMA (1, 2, 8) as the most suitable model for NCPI forecasting. This selection is validated through meticulous diagnostic tests, affirming the appropriateness of the model, as evidenced by residuals exhibiting white noise characteristics. The research findings suggest a rapid increase in the National Consumer Price Index for the coming years. Implications of this research extend to both academic and policy-oriented audiences. A successful ARIMA model development holds significant potential for providing accurate predictions of future price trends in Nepal. This, in turn, can assist policymakers in making informed decisions regarding economic strategies, monetary policies, and inflation control measures. Moreover, the study's outcomes offer a foundational framework for future research endeavours in the domain of economic forecasting and modelling, contributing to the broader field of economic analysis and policy formulation.

This study aims to examine the key economic indicators with private sector credit and economic growth in Nepal. Commercial banks and other financial institutions lend money to businesses and individuals for investment and consumption. This study aims to analyze key economic indicators in Nepal, including Real Gross Domestic Product (RGDP), Private Sector Credit (PSC), and Gross Capital Formation (GCF), spanning from 1975 to 2022. Employing a quantitative methodology, econometric techniques such as time series analysis, regression modeling, and hypothesis testing were utilized to examine the long-term relationships among these variables, with a particular focus on the impact of Private Sector Credit on Economic Growth (EG). The findings, derived from comprehensive econometric analyses including co-integration tests and vector error correction models, reveal significant insights into Nepal’s economic performance and financial system. Results indicate that Private Sector Credit plays a crucial role in stimulating economic growth, with approximately 40.07% of the previous year’s imbalance influenced by the long-term elasticity of independent variables. These findings offer valuable insights for policymakers, businesses, and investors, facilitating informed decision-making to promote sustainable economic development in Nepal. Further research is recommended to explore the correlation between the diversification of Private Sector Credit types and economic growth more comprehensively.

The capacity of foreign trade to substantially raise GDP via increased exports, heightened competition, and enhanced efficiency holds the key to bolstering economic growth and prosperity. Recognizing this transformation underscores the importance of shaping Nepal’s economic policies and development strategies for achieving lasting sustainable growth. The objective of this study is to investigate how trade openness has affected Nepal’s economic growth, given its importance in the nation’s overall development. By analyzing the correlation between trade openness and economic expansion, policymakers and researchers can uncover the role of international trade in driving Nepal’s economic advancement. The research methodology involves constructing a regression model using the Autoregressive Distributed Lag bound test, with variables analyzed in growth form and subjected to the Augmented Dickey-Fuller and residual tests. The study’s results indicate a strong positive relationship between trade openness and economic growth in Nepal from 1975 to 2020, with a long-term equilibrium observed. Short-term deviations from equilibrium are quickly corrected at 38.23% annually, highlighting the importance of balanced export and import growth for economic development. The study concludes that trade openness drives Nepal’s economic growth for sustainable development and environmental protection. It offers valuable insights for policymakers and stakeholders to enhance economic growth and overall development of the country.

This study aims to examine the relationship between CO2 emissions, forest area, and GDP in each South Asian Association for Regional Cooperation (SAARC) country. This study uses a panel dataset that spans South Asian countries from 1990 to 2020 for econometric analysis. The Fully Modified Least Squares (FMOLS) method adds annual forested area to the regression model. The study results show that India, Nepal, Pakistan, and Sri Lanka must prioritize decoupling CO2 emissions from economic growth, as their strong correlation shows significant environmental costs of development. Although Bangladesh, Bhutan, and the Maldives are in a slightly better position, they need strategies to manage emissions as they progress economically. The study once again revealed a relationship between a 1% increase in GDP and a 0.68% rise in CO2 emissions, whereas a 1% increase in forest area led to a slightly higher 0.79% rise in CO2 over the period. The hypotheses testing results confirm a positive correlation between economic growth and carbon dioxide emissions in SAARC countries, indicating that emissions rise as economies expand. Additionally, a negative relationship was found between forest area and carbon dioxide emissions, where larger forest coverage is linked to lower emissions. The conclusion is that an increase in forest area is associated with a relatively small increase in CO2 emissions, indicating that the relationship between forest area and CO2 emissions is less pronounced compared to GDP.

Nepal’s non-life insurance sector holds immense potential to drive economic growth and boost the nation towards a secure financial future. Embracing this potential is a goal and a pivotal catalyst for substantial change. The study aims to determine how the non-life insurance sector can drive economic growth in Nepal. The methodology of this study uses quantitative analysis of financial data from 2013 to 2022 from 20 non-life insurance companies in Nepal and econometric modeling to assess the sector’s impact on economic growth. Using Panel EGLS (Estimated Generalized Least Squares) regression analysis, the findings show that with one-unit increments in total investment, total premium, and total tax paid, GDP is expected to change by approximately 591.52, –920.54 and 8,470.65 units, respectively. In contrast, the coefficient for total profit is –910.3477 and is not statistically significant. The study’s main conclusion implies that the insurance sector contributes to the country’s economic growth by investing in productive activities and paying taxes to the government. Still, it also imposes a cost on the economy by charging high premiums to the insured. The profitability of the insurance sector does not affect the GDP, which indicates that the insurance sector is competitive and efficient or that other factors determine the GDP besides the insurance sector. This study contributes to a deeper understanding of the non-life insurance sector’s role in Nepal’s economic development and informs evidence-based policy decisions.