Our preliminary research reveals that a significant emphasis has been placed by foreign direct investors on the institutional quality of host countries. Previous studies have primarily concentrated on investigating the correlation between Foreign Direct Investment (FDI) and institutional factors. In parallel, numerous studies have explored the connection between FDI and a critical determinant—ICT (Information and Communication Technology) infrastructures. However, there lies a gap in the existing research landscape. Despite the wealth of studies, none have investigated the conditional relation between ICT infrastructures, FDI, and institutional quality. This study tries to examine the role of ICT infrastructure in negotiating the role of Institutions in bringing FDI flows. The strength of our study lies in the fact that we try to measure the joint impact of institutions and ICT infrastructure on FDI inflows for 20 African countries over the period 2000-2019. The hypothesis of the study indicates that countries with strong institutional quality and good ICT infrastructure would attract more FDI. On the contrary, countries with low ICT infrastructure and low quality of institutions will struggle to bring FDI into the country. The results of the model strongly support our hypothesis. Our results are robust to the alternative measures of quality of institutions and ICT infrastructure. From the policy point of view, countries are expected to improve their quality of ICT infrastructure and institutions in the country to get more FDI.

Keywords: FDI, Institutions, ICT infrastructure, African Continent
JEL Classification: O14, O25, O31, O55.

The border trade of Myanmar is important to its economy as a large proportion of external trade takes place through it. However, the COVID-19 pandemic and the military coup in 2021 posed a big challenge to this vibrant trade. The strict zero-COVID policy of China, its biggest trading partner, hampered trade while the border gate at Moreh in India remained closed after the military takeover of the country. The paper explores how the country is navigating through these difficult times so that border trade remains as vibrant as before. It is observed that one single export item that remained insulated from the pandemic and continues to earn precious foreign exchange for the country is natural gas. Further, a decline in trade with China and India is offset by more trade with Thailand. It needs to enter into trade negotiations with its neighbouring countries, especially with India and Bangladesh, where trade has not been high, indicating untapped potential.

Keywords: COVID-19, border trade, tourism, employment, agriculture
JEL: I15, F23, O53.

This paper investigates the long-run relationships and short-run dynamics between loanable funds and their key determinants in Nepal's banking system. Utilising monthly data from January 2021 to December 2024, the study employs the Johansen Cointegration Test and the Autoregressive Distributed Lag (ARDL) model to examine these interactions. The findings reveal that government expenditure and the balance of payments exert a strong and statistically significant influence on the availability of loanable funds in the long run, while consumption expenditure and planned industrial investment have relatively weaker effects. Inflation appears to have no significant impact on loanable funds in either the short or long run. In the short term, the central bank's open market operations and the capital base of banking and financial institutions (BFIs) play a critical role in shaping loanable fund flows. Additionally, the study finds that changes in all variables—including past values of loanable funds—significantly affect current-month loanable fund levels. The Error Correction Mechanism (ECM) indicates that deviations from the long-run equilibrium are corrected at an average monthly rate of approximately 8 per cent. Overall, the empirical results and model diagnostics confirm that the ARDL approach effectively captures both the long-run relationships and short-run adjustments between loanable funds and their major determinants within Nepal's banking sector.

Keywords: Loanable Funds, Banking System of Nepal
JEL Classification: E32, E44 and E52

This study examines intra-state and inter-state migration patterns in India, along with changes in labour force participation growth rates before, during, and after the COVID-19 pandemic. It highlights that small traders and labourers were disproportionately affected by the lockdown, facing severe job losses, while the agricultural sector absorbed over five million workers. Several states, including Bihar, Delhi, Himachal Pradesh, Uttar Pradesh, Tamil Nadu, and Uttarakhand, witnessed negative labour force participation growth during the pandemic. A Difference-in-Differences (DiD) analysis reveals the substantial effect of the COVID-19 pandemic on rural unemployment. The study finds that while high-MGNREGA states had relatively better employment conditions before the pandemic, they experienced a more significant rise in unemployment during the pandemic compared to low-MGNREGA states. Despite MGNREGA generating more person-days for informal workers during the pandemic than in normal years, the program was insufficient to fully absorb the unemployment shocks. Its limited funding, bureaucratic delays, and inability to accommodate the massive influx of reverse migrants further constrained its effectiveness as a safety net during the crisis.

Keywords: migrant workers, Covid-19 pandemic, unemployment, MGNREGA.

The growth of telecommunications infrastructure and telecom performance is at the heart of the digital economy that is so essential for information dissemination and citizen-centric services. Though India has made rapid strides in the provision of telecommunications networks, the teledensity is uneven across the states of India. This paper analyses the determinants of teledensity and its distribution dynamics across 18 Indian states over the years 2000 to 2023 using kernel density plots and the dynamic panel fixed effects Arellano-Bond GMM estimation technique. The AB-GMM estimates show that network externality, NSDP per capita, service sector share in NSDP and literacy rate are the important determinants of relative teledensity across the states of India. The kernel density plots indicate a gradual reduction of disparity and convergence of teledensity across states over the years. The half-life estimate suggests that the speed of convergence is 1.13 years, i.e. it takes 1.13 years to converge in teledensity across the states of India.

Keywords: Telecommunications, teledensity, convergence, kernel plots, panel Arellano-Bond GMM estimation.

In order to ensure sustainable use of water for irrigation, enhance food security, as well as a consistent increase in farmers’ income, India is concentrating on diversification to pulses and oilseeds to reduce import dependency. So the change in cropping pattern in India takes place to overcome several critical issues, notably rice and sugarcane, which are water-intensive crops that consume about 80 per cent or more of the country’s fresh water but contribute only less than 25 per cent to agricultural GDP. The drought-resistant crops are now an option as an alternative because climate change leads to irregular monsoon patterns, affecting crop yields and necessitating a shift from one crop to another. In the present context, diversification of agricultural activities is an important matter to address the issue of changing agricultural production and productivity in India. In accordance with the data from 1973-74 to 2022-23, the study examines cropping patterns with the help of data collected from Handbook of Statistics on Indian States published by Reserve Bank of India (RBI) and analyses changes in cropping patterns, focusing on area, gross cropped area elasticity, and instability in area, production, and yield for various crops. The study reveals that there is a modest growth in rice area and significant yield improvements, increasing production by 2.14 per cent. Wheat production growth has been driven by yield improvements (1.92 per cent) and moderate area increase (0.91 per cent). Rice and wheat show  moderate substitution effects on other crops and moderate instability, while pulses and oilseeds like groundnut, rapeseed, and soyabean exhibited high instability. The analysis suggests the need for extension and development packages, including credit systems and policies like Farmer-Producer Organisations (FPOs), to support Indian farmers.

Keywords: Cereal cropping, Change in productivity, Instability Index, Decomposition analysis.
JEL Classification: Q01, Q13, Q17.

The research seeks to explore the key macroeconomic contributors influencing foreign exchange reserves in Bangladesh from FY2014 to FY2024. Data were obtained from the Statistics Department of the Bangladesh Bank. The research utilises an Autoregressive Distributed Lag (ARDL) technique to measure the effect of the regressors on reserve assets in Bangladesh. Findings from the ARDL bounds test state that the variables are co-integrated and that the regressors make a substantial contribution to changes in reserve assets in both the short and long term. Moreover, remittances and exports play a pivotal role in sustaining Bangladesh’s foreign exchange reserves. In the long run, a 1% enhancement in remittances leads to an 88% rise in foreign exchange reserves. Similarly, foreign exchange reserves boost by 56% due to a 1% rise in exports. Therefore, remittances and exports are the key macroeconomic factors driving foreign exchange reserves in Bangladesh over the sample period. Finally, the study’s policy implications recommend that the government, in coordination with Bangladesh Bank, focus on initiatives that enhance workers’ remittances, exports, and foreign direct investment (FDI) to strengthen foreign exchange reserves in Bangladesh.

Keywords: ARDL, Export, Foreign exchange reserves and Remittance.
JEL classification: F29, F24, F31.

The research aims to test the principles of ecophysics in the interpretation of financial time-series data, namely the Nifty 50 index during the period 2015-2025 (January). The study has a methodological foundation in its application of power-law distributions and fat tails to give a broad explanation of complex market returns. The descriptive statistical analysis of the market data indicates that the classical assumption of a Gaussian distribution does not hold. The heavy tails of extreme market events are addressed in the power-law paradigm, and the market's fat tails are addressed by kurtosis. Using the highest level of statistical methodology and
the concept of ecophysics, the research can be a helpful step toward understanding the nature of market dynamics. It propagates the notion that financial analysis procedures must account for market nonlinearity and extreme market behavior.

Keywords: Ecophysics, Financial time series, Power law, Fat tails, Kurtosis analysis,Nifty 50.
JEL: C22, G12, C14, G17, C63.

The study examines the causal relationship between economic growth and government expenditures on education and healthcare in the North-Eastern states during 1990?91 to 2022?23, applying the Vector Error Correction Model. The results of the Augmented Dickey-Fuller test revealed that all variables are stationary at their first order difference. The results of the co-integration test and Vector Error Correction Model showed that there is a long-run relationship among variables in all the states. The Granger causality test indicated that there is a bidirectional causality between the variables used in all the selected states. The Variance Decomposition results indicate that fluctuations in Gross State Domestic Product (GSDP) are primarily explained by educational expenditure, with a relatively lesser contribution from total health expenditure, in the states of Arunachal Pradesh, Manipur, and Meghalaya. The study’s findings may be helpful for the policy-makers to amend the existing policies and budgetary allocation for the healthcare and education sectors in the selected states of India.

Keywords: Economic growth, Human Capital Expenditure, Granger Causality Test, VECM.
JEL Codes: C32, C35, H51, H52, J24.

The outbreak of the corona virus suddenly struck the globe in December 2019. With no drugs or vaccines immediately in our hands, it was very much evident to the global leaders that we were not in a position to handle the epidemic immediately. Negative outlook, lack of immediate proper actions and incorrect programmes on the part of the global leaders increased the fatality rate. Both public health and societal costs of the pandemic were very large, and it was felt across the world. The virus spread to more than 200 countries. According to WHO (as of May 3, 2020), the World had already witnessed 3356205 confirmed cases, among which 238730 deaths had been reported. The vaccine was developed subsequently to control the spread of the virus as it plays a crucial role in saving human lives, improves the health of the population and helps in economic recovery. The spread of infectious diseases can be checked through vaccination. Successful administration of vaccines, however, is a major challenge as vaccines are identified as unsafe and redundant in different parts of the world. Lack of faith in vaccines is believed to be a threat to the success of vaccination programmes. This review provides an overall picture of COVID-19 in India and around the globe and sheds light on vaccine hesitancy. Novelty of this work lies in that we have calculated Spearman’s Rank correlation coefficient between the percentage death rate with some determinant variables.

Keywords: COVID-19, India Scenario, Vaccine, Vaccine Hesitancy, World Scenario.