The outbreak of COVID-19 has affected the entire global financial market in an unprecedented way. Due to the disruptions that emerged in the global market; the financial market of India also reacted to the pandemic and witnessed sharp volatility. Given the COVID-19 situation, this paper empirically investigates the impact of COVID-19 on the Indian stock market. Using daily closing prices of indices such as Nifty and Sensex, this study examines the volatility of these indices over the period 3rd September 2019 to 10th July 2020. Further, the study has attempted to make a comparative analysis of the return of the stock market in pre-COVID-19 and during the COVID-19 situation. GARCH model is used to capture the volatility of the indices. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the results with that of the pre-COVID-19 period, we find that return on the indices is higher in the pre-COVID-19 period than during COVID-19. The return of both the stock market reached the bottom line during the first lockdown period, which is from24th March to 6th April.

Floods have threatened the agricultural productivity in Assam every year. Quality of soil, which is one of the important factors, that determines the production and income of farm, has been damaged by flood. Various study and secondary data reveal that deposition of sand due to flood has negative impact on farm productivity. This paper tries to investigate the impact of flood induced sand deposition and other factors on farm productivity in Dhemaji district, one of the mostly flood effected area of Assam. The study is based on primary survey which included 10 flood effected villages and 276 agricultural plots for testing the quality of soil. After testing the soil quality, the paper attempts to establish the relationship between quality of soil and paddy productivity. To identify the factors affecting the productivity of the paddy and estimate the damage due to flood induced sand deposition, the study used regression models by taking productivity of paddy as dependent variable. The regression model is estimated using Ordinary Least Square (OLS) method. In order to ensure the validity of OLS results, this study also tested a Tobit model. Results of the paper revealed that sand deposition created huge damage to the paddy fields and poor agricultural outcomes from the degraded lands were forcing people to look for other livelihood and opportunities.