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International journal of health care quality assurance
Feb 17, 2025;38 (1): 39-50.

The response of the benchmark healthcare index of India to COVID-19 pandemic: a return volatility approach.

Peeyush Bangur
Author Information
  1. Peeyush Bangur: Institute of Management Studies, Devi Ahilya Vishwavidyalaya, Indore, India.
PMID: 39704011 DOI: 10.1108/IJHCQA-01-2023-0005

Abstract

PURPOSE: From poor healthcare infrastructure to vaccine donors, India has traveled a long way. In this study, the author tried to find the investment certainty and persistence of volatility in the Indian healthcare system due to COVID-19.
DESIGN/METHODOLOGY/APPROACH: Using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH 1,1) model, this study quantifies the change in the conditional variance after the first case report of COVID-19. The author has used the S&P BSE HEALTHCARE index time series to analyze India's healthcare infrastructure and practices.
FINDINGS: The author found evidence of a decrease in investment certainty in investments related to India's healthcare infrastructure and practices after the first case report of COVID-19. Furthermore, the estimation of the econometric model suggests the presence of a large degree of volatility persistence in the S&P BSE HEALTHCARE index.
ORIGINALITY/VALUE: This research would be the first of its kind where the return volatility of the Indian healthcare sector has been discussed. Also, this research quantifies the return volatility of the healthcare sector during the pre- and post-COVID-19 period.

Keywords

Autoregressive conditional heteroskedasticity (ARCH) model B23 COVID-19 G11 Generalized autoregressive conditional heteroskedasticity (GARCH) model Healthcare infrastructure and practices I10 I11 Investment certainty Volatility

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MeSH Term

India
Humans
COVID-19
Benchmarking
SARS-CoV-2
Delivery of Health Care
Pandemics
Models, Econometric
Journal Article

Word Cloud

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