臺灣博碩士論文加值系統

本研究旨在观察政府对 COVID-19 的反应对股票市场回报的影响，并根据摩根士丹利资本国际 (MSCI) 的市场分类，以 50 个国家为样本调查发达市场和新兴市场之间影响的可能差异) ) 数据库。在政府对 COVID-19 的反应方面，本文将主要关注三个总体方面：遏制和卫生措施、严格性和经济支持。这项研究希望通过对 Fama 和法国三因素模型 (Fama & French, 1993) 和 Zaremba 等人的文献进行为期 2 年的研究来扩大文献中可能存在的空白。 （2020 年）和 Chang 等人，（2021 年）。
1200个观察结果表明，更严格的人员流动政策导致股市收益下降，当政府响应与收益同时发生时，观察到负收益，而当政府响应从先前的政府响应生效时，对股市收益产生正影响时期。政府对 COVID-19 的反应和 COVID-19 病例的增加似乎并未影响股市回报。然而，根据 (Chang et al., 2021;潘和纳拉扬，2020）。进一步观察，这种影响在新兴市场而不是发达市场很明显。尽管政府在限制行动和遏制大流行方面做出了相应的反应，但当病例数量仍在增长时，COVID-19 病例的增长对新兴市场产生了负面影响，这可以解释为一种负面情绪。由于 COVID-19 仍被认为是最近出现的现象，因此存在重大数据限制，特别是由于每月观察而不是每日观察。对未来研究的建议可能是调查投资者对政府回应的情绪和政府对 COVID-19 的回应公告，或者评估不同的政策，例如新兴市场的疫苗接种和疫苗接种政策。

This research aims to observe the effects of governmental responses to COVID-19 on stock market returns, and to investigate possible dissimilarities in the effects between developed and emerging markets over a sample of 50 countries, with market classification from the Morgan Stanley Capital International (MSCI) database. In terms of government responses to COVID-19, this paper will mainly focus on three aggregate aspects: containment and health measures, stringency, and economic support. This research would like to extend possible gaps in literature by researching over a period of 2 full years with the Fama and French Three Factor Model (Fama & French, 1993) and literature from Zaremba et al. (2020) and Chang et al., (2021). Results from 1200 observations showed that stricter policies concerning people’s movements caused decreases in stock market returns, and that negative returns were observed when the government responses are concurrent with returns but had positive effects on stock market returns when the government responses had taken effect from the previous period. Government responses to COVID-19 and the growth of COVID-19 cases did not seem to impact stock market returns. However, when divided into developed and emerging markets, lockdown and containment health policies were the most effective responses of the government for emerging markets, generating a positive effect on stock market returns, in line with research done by (Chang et al., 2021; Phan & Narayan, 2020). On further inspection this effect is apparent in emerging markets rather than developed markets. The growth of COVID-19 cases had a negative effect in emerging markets when the number of cases were still growing despite corresponding government responses in restricting movement and in containing the pandemic, which can be interpreted as a form of negative sentiment. Due to COVID-19 still considered a recent phenomenon, there are major data limitations, especially due to taking monthly observations instead of daily observations. Suggestions for future research could be by investigating investor sentiment towards government responses and announcements of government responses towards COVID-19, or by assessing different policies such as vaccinations and vaccination policies on emerging markets.

Table of Contents
TITLE PAGE
摘要 I
ABSTRACT II
ACKNOWLEDGEMENTS III
Table of Contents IV
List of Tables V
1 INTRODUCTION 1
2 LITERATURE REVIEW 4
2.1 Virus Outbreaks on the Stock Market 4
2.2 Government Responses to COVID-19 6
2.3 Fiscal Policy 9
2.4 Developed and Emerging Markets 11
3 DATA AND METHODOLOGY 12
3.1 Hypothesis Construction 12
3.2 Data Collection 13
3.3 Empirical Model 18
4 RESULTS 23
4.1 Descriptive Statistics 23
4.2 Regression Results 25
4.3 Governmental Measures between Developed and Emerging Markets 30
5 CONCLUSION 37
REFERENCES 39
 
List of Tables

Table 1 - List of countries and their stock indices. 14
Table 2 - Full table of the Oxford COVID-19 Government Response Tracker as per (Hale et al., 2021). 16
Table 3 - Indicators comprising the aggregate indices from Oxford COVID-19 Government Response Tracker as per Hale et al. (2021). 17
Table 4 - Descriptive statistics of the variables used in the equation (top) along with the division of developed and emerging markets (below). 23
Table 5 - Category statistics showing differences between the means of developed and emerging markets. 24
Table 6 - Results of the correlation test of variables. 25
Table 7 - Results of the panel data equation modelling with random effects. 26
Table 8 - Results of the lagged panel data equation modelling with random effects. 28
Table 9 - Results of the panel data equation modelling of developed markets with random effects. 30
Table 10 - Results of the panel data equation modelling of emerging markets with random effects. 30
Table 11 - Results of developed markets with lagged panel data generalized least squares equation modelling with random effects from 1 January 2020 to 31 December 2021. 34
Table 12 - Results of emerging markets with lagged panel data generalized least squares equation modelling with random effects from 1 January 2020 to 31 December 2021. 35

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