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India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

Although both central and state governments in India took the decisions to impose hard paternalistic policies of lockdown/shutdown to manage the spread of COVID-19, new cases were rising even after the first and second waves. Reverse migration, lack of social distancing, and failure to adhere to appropriate covid behavior are attributed as the leading cause of COVID-19 spread. The policy measures like 'Pradhan Mantri Gareeb Kalyan Yojana,' financial assistance, and series of lockdowns and shutdowns by the government of India have not significantly controlledthe spread of disease owing to a lack of understanding of individual's reaction to the pandemic and their reactive behavior. This paper used daily COVID-19 positive cases data to show the overall picture of COVID-19 in India. It used the explorative method to review articles related to behavioral biases involved in the decision-making process of migrant workers and individuals during the pandemic. The paper's findings show that different behavioral biases like base rate neglect, herd behavior, anchoring effect, availability bias are responsible for creating chaos, trauma, and anxiety among the migrant workers and leading to reverse migration in India. Despite knowing that COVID-19 is a fatal disease, some individuals' reaction to it was casual mainly because of hyperbolic discounting bias, optimism bias, overconfidence bias, confirmation bias, status quo bias, and loss aversion. Taking behavioral economics lessons, the paper suggests different nudging techniques for guiding people to maintain social distancing during this pandemic. Nudging has been proved to be an inexpensive tool in bringing desired behavioral changes in health economics. The paper concludes that nudging techniques can influence human behavior to control the spread of the disease. In the end, it gives direction for future work in this area to explore how behavioral economics can help policymakers to tackle the spread of infectious diseases such as COVID-19. [ABSTRACT FROM AUTHOR]