Economic Consequences of Covid-19 Pandemic: An Analysis of Exchange Rate Behaviour

This paper examines the effect of Covid-19 on currency exchange rate behaviour by taking a sample of 37 countries over a period from 4th January 2020 to 30th April 2021. Three variables, such as daily confirmed cases, daily deaths, and the world pandemic uncertainty index (WPUI), are taken as the measure of Covid-19. By applying fixed-effect regression, the study documents that the exchange rate behaves positively to the Covid-19 outbreak, particularly to daily confirmed cases and daily deaths, which implies that the value of other currencies against the US dollar has been depreciated. However, the impact of WPUI is insignificant. On studying the time-varying impact of the pandemic, the study reveals that the Covid-19 has an asymmetric impact on exchange rate over different time frames. Further, it is observed that though daily confirmed cases and daily deaths show a uniform effect, WPUI puts an asymmetric effect on the exchange rate owing to the nature of economies.

Revisiting the food security system in India in the pandemic era: the case of a Southern Indian state

Purpose The objective of this paper was twofold-revisiting the in-kind public distribution system (PDS) - India's flagship food security intervention and seeking beneficiary perspectives on its efficacy. The feasibility of cash transfers as an alternative mechanism is also examined, especially in the context of the COVID-19 pandemic. Design/methodology/approach Primary and secondary data from the southern Indian state of Tamil Nadu were used. In-depth interviews with beneficiaries using phenomenology were conducted to evaluate their perception and willingness to shift to a cash-based PDS in the pre and post-pandemic periods. Secondary district-level data were also used to ascertain institutional preparedness for this shift. Findings In-depth interviews of 105 beneficiaries revealed valuable insights, which seem to have significantly changed post-pandemic. Beneficiaries in the post-pandemic period seem much more inclined toward cash transfers, though a combination of cash plus in-kind benefits seems to be strongly preferred. Secondary results pointed out to the lack of institutional preparedness in financial inclusion. The research suggested that while the existing PDS needs to be overhauled, policymakers should look at a model of cash plus in-kind transfers as a probable alternative to pure cash transfers. Originality/value There is a dearth of in-depth state-specific studies on beneficiary perception of PDS, and this is important since the economic and sociocultural milieu in each region is unique. Being the only state with universal food security, its experience could yield important insights for other states or even middle or low-income countries similar to India.

IMPACT OF COVID-19 LOCKDOWN ON INVESTOR RETURNS: EVIDENCE FROM INDIAN FINANCIAL MARKETS

This research investigates the consequences of COVID-19 on the relationship between stocks and bonds in Indian financial markets using Event Study Methodology. The study has been conducted around the lockdown phases to better analyze the effects of the crisis. The findings revealed that the stock market saw positive abnormal returns during the lockdown phases which is attributed to the existence of high market volatility at times that attracted trading volumes leading to certain significant returns to the investors. Whereas bond market did not see much ups and downs as a result of lack of investor confidence due to continuous economic slowdown and unstable fiscal status of the government. This study observes a positive correlation between stock and bond market movement at the time of COVID-19 where both the markets are declining and proves it to be affected greatly by the investor sentiment. However, as tested by the significance of Pearson Correlation Coefficient, the correlation is not as strong to be replicated for other crisis periods indicating again that the correlation between stock and bond returns differs with the economic conditions.

Sentiment Identification in COVID-19 Specific Tweets

In 2020, our world has been hit by a global pandemic of COVID-19, belonging to the family of Coronavirus. Due to the rapid increase in the infection and the death rate, people have started to develop mixed feelings regarding this situation. Therefore, in this study, our sole focus is to analyze the emotions expressed by people using social media such as Twitter etc. Accumulating and studying the concerning tweets will provide aid to elicitate the real emotions during this hard time. The goal of this study is to present a domain-specific approach to understand sentiments manifested within people around the globe regarding this situation. In order to attain this, corona-specific tweets are acquired from twitter platform. After gathering the tweets, they are labelled and a model is developed which is effective for detecting the actual sentiment behind a tweet related to COVID-19. The substantial assessments are performed in bi-class and multi-class setting over n-gram feature set along with cross-dataset evaluation of different machine learning techniques in order to develop the model. Our experiments reveal that the proposed model performs well in perceiving the perception of people about COVID-19 with a maximum accuracy of about 93%. © 2020 IEEE.