Stock returns, government response strategies, and daily new case bursts during COVID‐19: A cross‐country perspective

Abstract

The purpose of the current research is to examine the influence of COVID‐19 pandemic related governmental policies and the bursts (e.g., drastic increases in cases during certain periods) of COVID‐19 cases on the abnormal returns of 725 hospitality and entertainment companies from the United States (US), China, the United Kingdom (UK), India, Thailand, Turkey, Mexico, and France. The study uses daily data from January 1, 2020, to November 20, 2021 and event study methodology. Our results offer the following insights. First, the response in the early days of COVID‐19 was negative for both the hospitality and entertainment sectors. Second, regarding government response strategies: (1) announcements of stimulus packages negatively affected China's entertainment and the UK's hospitality and entertainment sectors, but positively impacted the US's hospitality sector; (2) lockdown announcements adversely affected abnormal returns only in the US's hospitality and entertainment sectors; and (3) travel restrictions affected the US hospitality and Chinese and Indian entertainment sectors in the early stages of the pandemic. Third, regarding COVID‐19 case bursts, the results showed more negative abnormal returns during the first burst in the developed countries compared to undeveloped countries, while in the second burst, investors reacted more rationally, resulting in less negative abnormal returns. Conversely, more negative abnormal returns were found in the second bursts in India and Turkey. We conclude that COVID‐19's impact differed between developed and developing countries. Our findings suggest that investors should consider these differential effects when devising their portfolio strategies during COVID‐19 or the similar situations.

The economic impact of international travel measures used during the COVID-19 pandemic: a scoping review

“…Six studies report on low-income and middle-income countries (LMICs), specifically Thailand,32 Malaysia,33 Ethiopia,16 Poland,34 Czech Republic35 and the African Continental Free Trade Area (ACFTA) countries 36. Ten cross-country studies did not select a specific group of countries based on income 37–46. For example, one study looked at the stock volatility of 67 countries whose stock market data are reported by Datastream Global Equity Indices 45…”

“…Most studies identified in our review focus on the effects of international travel restrictions implemented during early 2020 (n=12) 16 24 26 27 30 32 34–36 41 44 47. The second most studied is the intensity of ITMs in general, using the stringency index of travel measures from the Oxford Coronavirus Government Response Tracker (OxCGRT) 33 39 42 43 45.…”

“…The outcomes reported in the included studies can be grouped into five broad categories: (1) financial market performance (n=13)24 27 30 31 33 37–40 43–45 47; (2) economic growth (n=4)25 28 32 37; (3) economic activity, measured by high-frequency data including nitrogen dioxide emissions39; (4) performance of industries central to international travel (n=9), namely the airline industry,40 tourism industry,28 29 32 46 retail industry,26 hospitality industry,24 global supply chain,34 agriculture16 and international trade36; (5) household-level economic status (n=3), including individuals’ financial stress,41 remittance42 and work life experience for cross-border workers35; and (6) consumer behaviour (n=1), measured by a consumer panic index 48. Some studies examined multiple outcomes, for example both stock market performance and the subsequent impact on GDP 37.…”

“…Several empirical methods were used in the included studies: (1) multiple linear regressions (n=17)24 26 27 29–31 33 37–40 42–45 47 48; (2) mathematical modelling (n=3)25 32 46; and (3) mixed methods, including surveys, summary statistics, in-depth interviews and case studies (n=6) 16 28 34–36 41. The most frequently used data source for ITMs is OxCGRT, which reports the stringency index for ITMs for each country over time.…”

“…36 Ten cross-country studies did not select a specific group of countries based on income. [37][38][39][40][41][42][43][44][45][46] For example, one study looked at the stock volatility of 67 countries whose stock market data are reported by Datastream Global Equity Indices. 45 What ITMs have been studied?…”