COVID-19 对印度各行业的不同影响:制药业和汽车业的复原力与 IT 业和房地产业的负面影响形成鲜明对比--ARIMA-GARCH 分析

Debanjalee Bose, Sakthi Srinivasan K.
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引用次数: 0

摘要

COVID-19 大流行对包括印度在内的全球金融市场产生了深远影响,并导致波动性增加,对各行各业产生溢出效应。本研究采用 ARIMA-GARCH 模型,深入分析了 COVID-19 对印度各行业的不同影响。研究利用从 2017 年到 2023 年的每日数据来考察 COVID-19 大流行期间的行业反应,划分出三个不同的时期:2017 年到 2021 年,表示大流行前时期;2020 年到 2023 年,包括 COVID 期间的动荡阶段;2021 年到 2023 年,代表 COVID 后时期。在本研究中,IT 和房地产行业被视为因变量,而汽车和制药行业被视为自变量。研究的主要目的是揭示 IT 行业在这些时间段内对汽车、医药和房地产行业的复杂影响,并阐明房地产行业如何对这些行业产生相互影响。我们的实证分析深入揭示了溢出效应的非对称传导机制。通过将整体冲击分解为影响所有行业的宏观经济影响和特定行业独有的产业影响,我们发现宏观经济冲击而非产业冲击是溢出效应非对称传导动态的主要决定因素。这项研究有助于全面了解各行业如何应对大流行病带来的前所未有的挑战,为后 COVID-19 时代的战略决策和政策制定提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Differential impacts of COVID-19 on Indian sectors: Resilience of pharmaceuticals and automobiles, contrasting with negative effects on IT and real estate - An ARIMA-GARCH analysis
The COVID-19 pandemic had a profound impact on financial markets worldwide, including those in India, and it has resulted in increased volatility with spillover effects across various industries. This study provides insights into the differential impact of COVID-19 on various industries in India by employing the ARIMA-GARCH model. The study utilized daily data spanning from 2017 to 2023 to examine industry responses during the COVID-19 pandemic, delineating three distinct periods: 2017 to 2021, denoting the pre pandemic era; 2020 to 2023, encompassing the turbulent during-COVID phase; and 2021 to 2023, representing the post-COVID era. In this study, the IT and real estate sectors are considered dependent variables, while the automotive and pharmaceutical sectors are regarded as independent variables. The primary aim is to uncover the complex influence of the IT industry on the automotive, pharmaceutical, and real estate sectors during these time frames; and to elucidate how the real estate industry reciprocally affects these sectors. Our empirical analysis provides insights into the asymmetric transmission mechanism of spillovers. By disentangling overall shocks into macroeconomic impacts affecting all sectors and industrial influences exclusive to specific sectors, we discern that macroeconomic shocks, rather than industrial shocks, primarily dictate the asymmetry in spillover transmission dynamics. This study contributes to a comprehensive understanding of how industries responded to the unprecedented challenges posed by the pandemic, offering valuable insights for strategic decision-making and policy formulation in the post-COVID-19 era.
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