"DISCUSS THE EFFECTS OF COVID 19 ON LABOR MARKETS AND THE ECONOMY"

Provide an introduction and the background of your study, and clearly state what your research question or objective is. What real world issue are you going to research; ie your research idea or objective: III. Briefly explain how the economic theory is related to your real world topic.

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ANSWER THE FOLLOWING:

1. Why did the unemployment rate increase in the year 2020?

2. How Did COVID-19 Unemployment Insurance Benefits Impact Consumer Spending and Employment?

3. How has the pandemic impacted inflation?

4. How did Covid-19 effect the stock market?

Check for updates Research Paper Impact of COVID-19 Outbreak on Business Perspectives and Research 1-15 the Stock Market: An Evidence from @ 2022 K.J. Somaiya Institute of Management Studies and Research Select Economies Cc Reprints and permissions: in.sagepub.com/journals-permissions-india DOI: 10.1 177/227853372 1 1073635 journals.sagepub.com/home/bpr OSAGE Irfan Rashid Ganie' (D, Tahir Ahmad Wani'D and Miklesh Prasad YadavD Abstract COVID-19 quickly spread all over the world and dramatically affected the financial markets in almost everycountry. Its spread created havoc in the market, and investors fearing risk suffereda significant amount of financialloss in a very short time. This article aims to analyze the impact of COVID-19 on stock markets in the top six affected countries based on the total number of cases confirmed. In addition, it also analyzes the stock market volatility caused by the virus and the abnormal returns generated by the markets during the pandemic. We employevent study methodology in different sub-periods to examine the most volatile event periods with the daily rise in the Covid cases and subsequent returns generated by the markets during these sub-periodsin relation to the daily rise in the case. The increase in volatility and the presence of significant abnormal returns among the sample indices show the impact of COVID-19 on stock markets. The result reveals that Brazilian stock indices show the highest decline among the selected countries, with a fall of more than 50% during the pandemic, while Mexican indices show the lowest fall of around 30% during the same period. Keywords COVID-19 outbreak, stock market, volatility, event study methodology Introduction Globally, COVID-19 cases have crossedthe 100 million mark with more than 2 million deaths. This is one of the deadliest pandemics in recent times, which not only caused loss of human lives but also led to billions of dollars of loss to world economies. Many economies saw historic contractions and disruptions Department of Humanities, Social Sciences & Management, National Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, India 2ACCF, Amity University, Noida, Uttar Pradesh, India Corresponding author: Miklesh Prasad Yadav, ACCF, Amity University, Noida, Uttar Pradesh 201301, India. E-mail: miklesh 12@gmail.com2 Business Perspectives and Research in financial and labor markets. At the beginning of 2020, the virus was believed to be a China-specific problem, and people outside China hardly discerned it as a major concern. But with the rapid spread of the disease and the subsequent declaration of the virus as a pandemic by (World Health Organization [WHO], 2020', Sohrabi et al., 2020) on March 11, 2020, the attention shifted dramatically and people were gripped by fear and uncertainty. Investors all around the world initially shunned stocks with China's exposure, and with the spread of disease, markets weighedthe economic consequences of these crises on firms (Ramelli & Wagner, 2020). The first half of the year 2020 saw one of the most dramatic stockmarket crashes in history. The crash was caused by the virus that originated in Wuhan, China. The first case of COVID-l9 was reported in December 2019 in Wuhan city. Initially, it was not believed that this virus could be deadly and could spread to every part of the world. The rapid spread of the virus across the globe and the subsequent fear it created finally led to the halt ofvarious economic activities. Many countries imposed strict lockdowns to contain the further spread of the virus and halted all major economic operations, which ultimately were received negatively by stock markets, hence the inevitable market crash in March 2020. Stocks generally react to events that may be perceived either positively or negatively by investors and traders, depending on the type of event. But black swan events like COVID-19 are rare, unlike corporate events, and very limited research has been carried out to study the impact of such events. Stocks across the sectors reacted differently to COVID-19 based on the effect it has on the operations of the business, for example, in S&P 1,500 sample sectors like natural gas, food, healthcare, and software stocks earned positively higher returns as compared to shares in petroleum, real estate, entertainment, and hospitality sectors which fell drastically (Mazur et al., 2020). Similarly, the effect of COVID- 1 9 on the US economy is more lethal than that of the Spanish Flu of 191871919 (Baker et al., 2020). These kinds of events provide us with an opportunity to learn more about the psychology of investors and hum an behavior in the context of crises. COVID-l 9 not only created havoc around the world but also shattered the lives of people. Many people lost their loved ones, many lost their jobs and millions of people around the world were pushed into poverty. At the macro level, many economies shrunk by a quarter or more of their GDP values. The uncertainty and fear created by COVID-19 remain due to the non-availability of vaccines so far in many countries. This study aims to analyze the effect of COVID-19 on six major indices from the most affected countries by the virus. These countries include the USA, India, Brazil, Mexico, Russia, and Spain. Even though Peru and Columbia also fall into the top affected countries by COVID-19, due to the inconsistent data availability for major stock indices in these countries, we have omitted them. COVID-19 increased volatility and led to panic trading in many major indices. US S&P 500 was halted many times during March 2020 when it fell by 7% or more (Bloom et al., 2020', Shieber & Crichton, 2020). Similarly, the Indian indices NIFTY 50 and Sensex were halted twice in 15 days in March 2020 when the market fell by 10% (Dasgupta, 2020).Therefore, this study tries to document the overall market response by applying event study methodology in these six affected countries. The remainder of the article is structured as follows: the second section discusses a detailed review of the literature, followed by the data and econometric model in the third section. The fourth and fifth sections present the results and discussion, and conclusion and policy implications, respectively. Literature Review The World Health Organization (WHO) declared the COVID-19 virus a global pandemic on March 11, 2020 (WHO, 2020), and this pandemic severely impacted the financial markets all over the world, Game 9: a]. 3 including stock markets, commodity markets, and debt markets. Amidthe pandemic, the oil price war between Saudi Arabia and Russia resulted in an oil market crash and a subsequent stock market crash all over the world. Needless to mention markets all over the world reacted to such news very resentfully. As per the report of the World Economic Forum (W EF, 2020), by the end of February 2020, the volatility in financial markets had increased manyfold due to the sell-off by investors and traders to protect their capital. This led to a crash in equity markets amounting to a loss of 30% to market capitalization which is higher compared to the global financial crises of 2009. The reaction of stock markets to different global events has been documented by various prior studies, for instance, natural and manmade disasters (Kowalewski & Spiewanowski, 2020), events about sports CBuhagiar et al., 2018), politics (Bash & Alsaifi, 2019) and disease outbreaks like Ebola and severe acute respiratory syndrome (SARS) (Chen et al., 2007', lchev & Marine, 2017). Uncertain events like the assassination of .Tamal Khashoggi strongly affected the returns in Saudi stocks. This reaction was majorly found to be driven by local investors (Bash & Alsaifi, 2019). Withstanding the fact that there is adequate research available regarding the behavior of stock markets in pandemic outbreaks/diseases. It is quite obvious that some of these events have hugely impacted certain industry sectors, leaving the others with marginal impact, for instance, the effect of SARS on Taiwan's economy showed that the tourism sector was badly affected as compared to other sectors (Chen et al., 2007). Similarly, aviation sector stocks were more reactive to news about the SARS outbreak as compared to non-aviation stocks (Loh, 2006). However, not all events have a negative impact on stock markets. Chen et a1. (2009) found that hospitality sector stocks were sensitive to SARS but the stock returns of biotech companies in Taiwan had positive surprises during the SARS period. SARS was the first deadly disease of the twenty-first century. It also originated in China in November 2002 in Guangdong province. By mid-2003, it had spread to around 29 countries and 3 regions across the globe, causing 916 deaths among more than 8,000 confirmed cases. The overall impact of SARS on economic activity was short-lived, and it did not cause much disruption to trade exports, specifically for the imports of goods from mainland China (Siu & Wong, 2004). But its impact on the Chinese economy was not negligible. The estimated total loss to the Chinese tourism industry due to SARS could be US$60 billion and the total loss to the Chinese economy could be US$253 billion in 2003 amounting to about 2% of Chinese GDP in 2003 (Hai et al., 2004). Many other black swan events impact the stock market. Political events like regime change in a country give shift in economic policies and these policies changes may be perceived either way by the investors and ultimately reflect in the stock prices of firms. In a similar stance,Ang and Timmermam (2011) analyzed regime change usinga regime-switching model and suggested that with a change in regime volatility, autocorrelation and cross covariances across asset returns also change, signifying the change in investor expectations and stock returns. Murtaza et al. (2015), using event study methodology, analyzed nine political events in Pakistan from 2007 to 2012 and found that political events which brought change in government policies have shown a significant impact on stock markets in Pakistan. Incidents of terrorist attacks have been evident across the globe, and hence these kinds of events also affect the stock markets. The number of hum an lives lost may also affect the stock returns. Any increase in the loss of hum an life leads to a decrease in the market return (Aslam & Kang, 2013). In disease outbreak events, the severity of the disease also defines the magnitude of the effect on market volatility and returns. The daily growth rate of confirmed cases and the total number of deaths related to COVID-19 significantly affected the stock returns across the Chinese stock markets (Al-Awadhi et al., 2020). Further, it is contended that the impact of disease outbreaks has never been as drastic as caused by COVTD-19, including the famous Spanish flu. In this vein, the severity of reaction from US stock markets can be attributed to guidelines and restrictions imposed by the govemm ent on commercial activities with voluntary maintaining of social distancing to contain the spread of 4 Business Perspectives and Research COVID-19 which led to a crash of service dominated economy CBaker et al., 2020). The unprecedented impact gradually stabilized and recovered to some extent, but not before markets have perform ed badly and generated negative returns (Singh et al., 2020). A study by (Ram elli & Wagner, 2020) suggests that stock market members foresaw the genuine economic impacts of the COVID-l9 wellbeing emergency being intensified by financial channels, but it is not yet clear that the continued policy interventions and liquidity injections would change the economic disruptions caused by this virus. Globalization has made markets work in co-integration. Bhuyan et al. (2010) found a significant co-integration among the Asian equity markets in their study during and after-SARS periods. More recently, Narayan et al. (2020) examined the effects of government policies regarding lockdowns, stimulus packages, and the ban on travel on stock returns in G7 countries. Although the effectiveness of all three policies could not be compared because all the policies were in force simultaneously, the aggregate impact of policies did have a positive effect on market returns. An event study (Liu et al., 2020) evaluated the short-term impact of COVID-l9 on 21 stock indices of major affected countries across the globe. The results indicate that stock markets\" reaction were quick, which led to their fall immediately, and Asian stock markets generated more negative abnormal returns as compared to other countries. The increased number of confirmed cases also added to investors' worries about future returns and unexpected future market behavior. Data and Econometric Model Data We examine the impact of COVlD-19 on selected stock exchanges inthe six most affected countries based on the total number of confirmed cases of the virus. The study uses one major index for each of these countries, and the data for daily index close price data for each of these countries has been obtained from an open access Yahoo Finance website (www.finance.yahoo.com). Data for daily confirmed cases of COVlD-19 has been obtained from the WHO website (www.covid19.who.int). This study considers daily confirmed cases as against trading day index prices and non-trading day daily confirmed cases have been omitted for the reason that index prices are not available for the same. Table 1 shows the data description in the form of the highest total number of confirmed cases country-wise as of September 24, 2020, along with the corresponding index for the country. Table I. Data Description of Sample Countries. Country Name Total Conrmed Cases Index USA 6,960,| 52 S&P 500 India 5,992,532 NIFTY 50 Brazil 4,689,6 I3 IBOVESPA Russia |,| 5| ,438 MOEX Mexico 720,858 IPC 35 Spain 7|6,48| IBEX 35 Source: World Health Organization (WHO). Ganie et al. Econometric Model: Event Study Methodology Event study methodology has been employed to analyze how the stock markets react after the occurrence of an outbreak of a disease like coronavirus. An event study is primarily used to analyze the behavior of security with the occurrence of an event or any information announcement. The event can be earnings reports, corporate actions, deals, mergers, etc. The impact of the event on stock prices can either be positive or negative. Many researchers have used event study as an important tool to examine the returns on securities post the occurrence of an event (Mackinlay, 1997; Warner & Brown, 1983). Also, there have been many studies that employed event studies for non-corporate events like diseases (Al-Awadhi et al., 2020; Albulescu, 2020; Chen et al., 2007; Liu et al., 2020). Event Window The number of days in the window period ranges from 143 to 172 days based on available trading days for eachcountry in the sample from the date when the first case of COVID-19 was confirmed in the countrytill September 24, 2020. We argue that the daily number of confirmed cases may have affected stock markets differently. Therefore, to examine the impact of a daily rise in confirmed cases, we take the peak date as a 15% or more increase over the cumulative confirmed cases on the previous day and examine the abnormal return 3 days post the peak date in comparison to an average return of 3 days before the peak date with sub-periods amounting to a total of 7 days. In case there is a rise of more than 15% within the sub-period, the date with the highest rise over the previous day is taken as the peak date. Each country's number of peak dates is determinedby applying the criteria of a 15% or more increase in daily confirmed cases till September 24, 2020. Estimation Window An estimation period of 150 days, as used by (Al-Awadhi et al., 2020; Singh et al., 2020), beforethe event day for each country, has been used to calculate the average return and standard deviation. Event date Estimation window 1-150 -1 0+1 +172 The sub-period estimation window. Estimation window Peak date6 Business Perspectives and Research Estimation Model Returns: Dailyindexreturn(Rt) : Ln[P:3t 1 ] x100 (l) where Ln is the natural logarithm, Pt close price of the index on a given day, and Pt , 1 denotes the close price of the index on the day prior. Expected return: + N ' Rt, 150 A mean return is calculated by taking an average of estimation periods (,1 to 7150) An abnormal return (ARt) is calculated by subtracting the mean return E from daily index returns Rt. Meanreturn : l, 2,3,\" .,N (2) AR, : RtE (3) Cumulative abnormal return (CAR): CAR of the index for the window period to to :1 is calculated using Equation (4) r1 CAR(t0,t1) = EAR, (4) IziO tStatistic AR: r-Statistic for abnormal return is calculated using the abnormal return on a day divided by the standard error of the estimation period returns as given in Equation (5) t-TestAR= 1:1; (5) I GAR where standard error (SE) : J n Volatility is calculated using the standard deviation of log returns. Results and Discussion To check the pattern of constituent series, the average return and standard deviation are shown in Table 2. All six countries provided positive mean returns before the outbreak of the coronavirus. The standard deviation also remains under 1 except for Brazil, as denoted by IBOVESPA. The post-event return is negative for all the indices except for Mexico, denoted by lPC 35. The standard deviation has also increased many folds post-outbreak of COVlD-lQ. This signifies the increase in stock market volatility due to the outbreak of deadly COVID-l9. The major impact is evident from Spain, followed by India, Brazil, Russia, and the USA, as these indices generated negative mean returns of 0.21 1, 0.052, 0.069, 0.034, and 0.009, respectively. Mexico shows a positive mean return during the event that could be attributed to better virus containment by its government compared to other countries in the long run. Compared to other studies, the mean return is calculated over a longer period during the event window Ganie et al. Table 2. Returns and Standard Deviation for Top Six COVID-19-affected Countries. Pre-event Country Index No. of Trading Days Mean Return (%) Standard Deviation (%) India NIFTY 50 50 0.025 0.914 USA S&P 500 150 0.095 0.753 Brazil IBOVESPA 150 0.056 1.078 Russia MOEX 150 0.076 0.729 Mexico IPC 35 150 0.026 0.834 Spain IBEX 35 150 0.006 0.82 Source: The authors. Table 3. Abnormal Returns on and After the Event Day. Country Index Event Date* 10 (% tl (% India NIFTY 50 January 30, 2020 0.80 -0.64 USA S&P 500 January 21, 2020 -0.36 -0.07 Brazil IBOVESPA February 26, 2020 -7.32 -0.06 Russia MOEX January 31, 2020 -1.13 -0.28 Mexico IPC 35 February 28, 2020 -4.67 -0.78 Spain IBEX 35 February 3, 2020 0.36 1.64 Source: The authors. Note: t0 = Event day (first confirmed case of COVID-19), tl = day after event day. *In case of the day when the first COVID-19 case was confirmed is a holiday, the next available trading day has been taken as the event day. sample period, but the impact of the outbreak disease is still evident as denoted by negative mean returns in 5 out of 6 indices. An abnormal return with significant values for sample companies is presented in Table 3. Referring to the event date and abnormal return of the stock exchange in India, the first case of COVID-19 was reported on January 30, 2020. The abnormal return for the NIFTY 50 index on the event day is -0.80% and -0.64% on the day after the event day. In the USA, the first COVID-19 case was reported on January 21, abnormal return for S&P on that event day is -0.36% and -0.07% the day after. Brazil's IBOVESPA has the highest negative abnormal return of -7.32% on event day, followed by IPC 35 Mexico withan abnormal return of-4.67% and MOEX Russia withan abnormal return of -1.13%. The abnormal returns for these three indices for the day after the event are also negative, -0.6%, -0.78%, and -0.28%, respectively. The only exception to the negative abnormal returns is the IBEX 35 index Spain, which has a positive abnormal return of 0.36% on event day and 1.64% on the day after event day. The reason for the positive negative return could be attributed to the fact that the first case of COVID-19 in Spain was reported on Sunday, February 2, 2020, which is a holiday and a non-trading day. And, due to time gap shock absorption (Frank & Sanati, 2017), the effect is less evident on Monday, February 3, 2020, and almost negligible on the day after.8 Business Perspectives and Research Table 4. Abnormal Return of Sample Countries with their Significant Values. Event Window India USA Brazil Russia Mexico Spain Event window I -3 0.73% -0.28% 1.71% (1.92) 0.65% (1.4) -1.28% .07% (1.94) (-1.49) (-1.47) (-0.98) -2 -0.2% (-0.41) 0.36% (1.91) -1.29% 0.25% (0.54) 2.6% (2) 0.31% (-1.45) (-0.57) -1 0.93% (1.9) -0.08% 0.42% -0.9% (-1.94) -1.32% 0.76% (-0.43) (-0.47) (-1.02) (-1.38) 0 0.45% -0.73% 6.88% -1.28% -2.48% 0.8% (1.46) (-0.92) (3.84** ) (7.72** ) (2.76* *) (-1.91 ) - -0.29% -0.44% (-2.3) 0.37% (0.42) -0.44% 1.41% (1.09) 2.08% (-0.59) (-0.95) (3.79* * ) N -1.83% -0.35% -2.24% 0.62% (1.32) 4.1% (3. 16**) 2.02% (3.72* *) (-1.85) (2.51** ) (3.67** ) W 2.62% -1.38% 1.52% (1.71 ) 0.28% (0.61) 2.34% ( 1.8 ) 1.37% 15.32* * ) -7.20* *) 2.49* *) Event window 2 -3 -2.82% -1.36% 0.38% (0.2) 3% (1.95) -5.48% -2.18% (-1.83) (-1.82) -1.88) (-1.53) -2 0.34% (0.22) 1.22% (1.63) 2.99% (1.62) -0.92% (-0.6) 4.47% (1.53) -0.51% (-0.35) -1 2.48% (1.61) 0.14% (0.18) -3.36% -2.08% 1.01% (0.35) 2.69% (1.88) (-1.83) (-1.35) 0 0.5% (0.32) 0.54% (0.72) -2.83% 1.81% (1.18) 1.29% (0.44) -1.64%% (-1.54) (-1. 15) - 1.12% (0.73) -1.56% -11.58% 4.5% ( -2% (-0.69) 0.99% (-2.08**) (-6.28**) 2.93 * * * * ) (-0.69) N -1.55% 0.95% (1.26) 8.3% (4.50*) 2.74% (1.79) 10.6% 2. 19% (1.53) (-1.01) (3.64* ) W -4.06% 1.71% -6.54% 2.1 1% (1.37) 5.59% (1.92) 2.78% (1.94) -2.64* * ) 2.28**) (-3.55**) Event window 3 -3 -4.88% -0.22% -7.37% 0.56% (0.23) -5.1% (-1.7) 2.25% (1.28) (-1.44) (-0.83) (-1.91 ) -2 -1.62% 0.54% 5.68% (1.47) -4.39% 5.28% (1.76) 1.22% (0.69) (-0.48) (1.99* *) (-1.84) 6.5% (1.92) -0.3 1% 1.69% (0.44) 3.83% (1.6) -0. 18% -3.47% (-1. 16) (-0.06) (-1.97) 0 -13.07% -0.99% -1.8% (-0.47) -4.58% -0. 18% 1.57% (0.89) (-3.86**) (-3.66* (-1.92) (-0.06) (Table 4 continued)Ganie et al. 9 (Table 4 continued) Event Window ndia USA Brazil Russia Mexico Spain Event window 3 3.31% (0.98) -3.34% 2.8% 5.37% -5.32% 4.49% (-12.36**) (3.32** ) (2.25** ) (-1.77) (2.55** 2 7.25% -3.01% 10.78% 1.91% (0.8) -0.35% -10.32% (2. 1 4* * ) (-1 1.13** ) (2.79* * ) (-0.12) (-5.87**) 3 4.65% (1.37) -0.31% 7.16% (1.86) 2.19% (0.92) 1.37% (0.46) 8.49% (-1. 15) (4.83* * Event window 4 -3 0.39% (0.16) 4.48% (1.95) -3.59% (-1.7) -6.73% 0.93% (1.74) 4.67% (1.66) (-1.84) -2 -4.31% -3.1 1% 3.71% (1.76) 5.87% (1.6) -0.92% -5.04% (-1.81) (-1.35) (-1.72) (-1.79) -1 3.92% (1.65) -1.37% (-0.6) -0.12% 0.86% (0.24) 0.01% 0.37% (0.13) (-0.06) (-0.02) O -3.91% -7.56% 0.78% -4.98% -1.49% -0.8% (-0.28) (-1.64) (-3.29**) (-0.37) (-1.36) (-2.78**) -1.91% (-0.8) 5.17% 3.87% (1.84) 5.4% (1.47) -0.62% -4.9% (-1.74) (2.25** (-1. 15) N 8.57% 4.66% -1.76% -0.06% -0.77% 5.99% (3.60** ) (-2.03**) (-0.83) (-0.02) (-1.44) 2.13**) w -0.33% -9.65%% 8.39% -0.06% -2.84% 1.76% (0.63) (-0.14) (-4.20* *) 3.98**) -0.02 (-5.30* * ) Event window 5 -3 -1.76% 8.23% (1.22) 0.99% (1.06) -3.89% -2.47% -2.5% (-1.53) (-1.61) (-1.94) (-1.75) -2 -0.24% -13.41% 0.87% (0.94) 1.08% (0.54) 2.42% (1.71) -0.56% (-0.22) (-1.98**) (-0.34) O L 2% (1.83) 5.18% (0.77) -1.86% (-2) 2.8% (1.4) 0.05% (0.04) 3.06% (1.88) -1.05% -5.97% -1.79% -1.66% -2.4% (-1.7) -1.89% (-0.96) (-0.88) (-1.93) (-0.83) ( - 1. 16 ) - -4.07% -0. 18% 1.01% (1.09) 2.63% (1.31) 0.61% 1.12% (0.68) (-3.72** ) (-0.03) (-0.43) N 1.27% (1.16) -5.08% -0.51% 0.78% (0.39) 0.64% (0.45) 1.31% (0.8) (-0.75) (-0.55) W 0.37% (0.34) -3.62% 1.66% (1.78) 1.69% (0.84) 0.97% (0.69) 5.1 1% (3.13) (-0.54) Event window 6 2.13% (0.75) -0. 1 1 % 0.3 1% -0.53% -0.04) (-0.31 ) (-1.97** ) (Table 4 continued)I0 Business Perspectives and Research (Table 4 connuieaD EventWindow India USA Brazil Russia Mexico Spain Event window 6 2 3.47% (L23) 4.8% (L75) L86% (I .87) 0.34% (L28) | 5.6%( 4.68% | 55% O.|9% (0.7) |.98"") (|.7|) (|.56) O O.64% 2.04% (0.74) 5.89% |.BB% (0.2 3) (5.9 | M\") (7.0 | W) | |.02% (0.36) 2.87% 3.5% (3.5 |**) 2.84% (|.05) (|0.58**) 2 O.47% 5.77% 3.57% 0.88% (0.| 6) (2.| I\") (3.58\") (3.27\"") 3 0.88% (0.3 |) |% (0.36) |.97% 6. |7% (I 98*") (23.00**) Event window 7 3 0.28% (0.79) 2 0.43% (L2) | 0.7|% (4.99\") 0 |.B7% (4.20%) I 3.02% (8.39%) 2 0.65% (LB) 3 |.B|% (4.02\") Source: The authors. Note; AR is signicant at \"p L96. The increase in volatility in stock markets around the world started in the last week of January 2020, with many countries reporting the first cases of novel coronavirus. After January 30, 2020, India's NIFTY 50 showsan increase in volatility. In the first event window, day 1 does not show any significant abnormal returns, but days 2 and 3 show daily returns of 2. 15% and 2.29% with an abnormal return of 71.83% and 72.62%, respectively. This signifies the impact of the occurrence of COVID-l9 in India and the presence of abnormal returns in the market during event window 1. Event window 2 shows significant abnormal returns of 4.06% on day 3. Accordingly, event window 3 shows significant and highest abnormal returns of 713.07% on event day and 7.25 % on day 2 of the event period. This is the biggest fall in the NTFTY 50 in its history. Similarly, during event window 4, the index shows the presence of abnormal returns of 8.57% on day 2. On this day,the NIFTY 50 index has the highest rise in its history. In event window 5, the index shows the presence of abnormal returns on day l. Last,event window 6 does not show the presence of abnormal returns during the event period but during the estimation period (day l) which are significant and the reason for the same could be attributed to the trailingimpact of previous dates. After the 5May 2020, rise Game 9: a]. | | in COVID-l 9 in India stabilized and remained ata daily increase of 15%, which also ledto the stabilization of markets and a decrease in volatility. The first case of COVID-l9 in the USA was reported on 21 January 2020. In event window 1, the S&P 500 index provides daily returns of 70.27% on the event day with significant abnormal returns of 70.73% for the same day.Postevent day, onlyday 3 shows 70.91% daily returns with significant abnormal returns of 71.38%. This signifies the reaction of US markets towards the news of the arrival of COVID-l9 in the USA and the subsequent start of a downward trend in the market. With the increased number of cases, the markets started tumbling further. Event windows 4 6 show the highest volatility in the market with the index falling by 712.77% on March 16, 2020, which is the third-highest fall of the S&P 500 in its history (Herron & Hajric, 2020). The USA reported the highest rise in the daily case in the world in March and April 2020, but the daily increase rate stabilized from the first week of April onwards and remained under the daily rise of 15%, which also stabilized the volatility in equity markets in the USA. Brazil reported its first case of COVID-19 on February 26, 2020, with IBEVOSPA tumbling by 77.26% on the same day with a significant abnormal return of 76.88%. This is one of the sharpest reactions seen among the countries under study, and the reason for this decline in the index can be attributed to the fact that most of the countries reported the arrival of novel coronavirus at the end of January 2020 and the first half of February 2020. Therefore, already existing fear among the markets and investors, pulling out their moneynot to further their losses, made the arrival of COVID-l9 in Brazil in the last week of February 2020 weigh heavy on indices. With the increase in cases,the IBEVOSPA index fell by 712.98% with significant abnormal returns of 711.58% on the day of event window 2 dated March 10, 2020. Event windows 3 and 4 further show the high volatility in the overall period. From April 28, the markets stabilized and provided some continuous days of positive returns. Russia reported the first case of COVID-l9 on January 31, 2020, and the MOEX index fell by 71.03% on the same day, generating abnormal returns of 7l 28%. After this initial reaction of the index towardsthe arrival of a novel coronavirus,the remaining event days in event window 1 are stable and do not show abnormal returns. In event windows 2 and 3, the index shows abnormal returns on event day 1 for each. This signifies that the arrival of COVID-l9 in Russia did not impact the stock markets in the country muchinitiallyas compared to other countries in the sample. Event windows 4 and 5 do not show any significant abnormal returns,but event window 6 shows the impact of rising COVID-19 cases with significant abnormal returns on all days throughout the event window. Similarly, event window 7 also provides abnormal returns throughout the event window except for day 3 dated April 23, 2020. Post April 2020, the daily rise in COVID- 19 cases in Russia remained under 15%, and markets also stabilized with the decrease in volatility. Mexico confirmedthe first case of COVID-19 on February 28, 2020 and the IPC 35 index fell by 74.59% on the same day. Event window 1 shows significant abnormal returns of 4.10% on event day 3, followed by abnormal returns of 10.60% on event window 2 day 2. This signifies the impact of the arrival of COVID-l9 in Mexico on the stock markets. Event windows 3 and 5 do not provide any evidence of the presence of abnormal returns, but event window 4 shows the presence of abnormal returns on event day and event day 3. Hence, after the end of April 2020, COVID-l9 cases in Mexico remained under a 15% daily rise, and hence overall market volatility also decreased and market returns stabilized. Spain reported its first case of COVID-l9 on Sunday, February 2, 2020. There was no immediate reaction to this news on the IBEX35 index because of time gap shock absorption (Frank & Sanati, 2017), and therefore, we believe the impact of news is less evident on the event day of the event window. All other event days (173) show the presence of positive abnormal returns in the window, signifying the impact of the news. Event window 2 does not show any presence of abnormal returns, but event window 12 Business Perspectives and Research Table 5. Volatility During Event Windows. Sub-period India (% JSA (%) Brazil (%) Russia (%) Mexico (%) Spain (%) Event window I 2.26 0.57 .93 0.54 1.36 0.39 Event window 2 2.59 1.71 10.34 1.24 6.35 ..03 Event window 3 2.00 1.66 2.86 1.92 3.47 9.91 Event window 4 5.65 7.54 5.08 3.15 1.24 0.00 Event window 5 2.86 2.52 .II 0.93 0.83 2.25 Event window 6 0.82 3.40 0.00 2.68 Event window 7* 2.41 Source: The authors Note: *Event window not available has been assigned with "-". 3 shows the presence of abnormal returns from event day 1 to day3 with abnormal returns of 4.49%, -10.32%, and 8.49%, respectively. This window period has shown the highest volatility (see Table 5) with a standard deviation of 9.9% in daily returns during the overall event period. Event window 4 shows the presence of abnormal returns on event day 2 and volatility for this event period decreased to 4.87%. In the last event window, there was no sign of abnormal returns in the market, and after the first week of April 2020, the daily rise in cases remained under 15%, and overall volatility also decreased in the market. Cumulative Abnormal Return Figure 1 shows the CAR for the indices during the entire event window starting from January 21, when the USA reported its first case of COVID-19, till September 24, 2020. The downtrend in global markets started in the last week of February 2020, and the majority of indices touched bottom levels from March 15, 2020 to March 25, 2020. On March 16, 2020, IBEX 35 index Spain fell by 8.21%, and the Index shows the lowest CAR of -47.05% for the same day. MOEX Russia saw its lowest point on March 18, 2020, with a CAR of -44.65%. On the same day, IPC 35 Mexico showeda CAR of -42.08%. During the same period NIFTY 50 India and S&P 500 US indices fell to their lowest levels on March 23, 2020 with CAR of negative 47.50% for NIFTY 50 and CAR 43.94% for S&P 500, respectively. The lowest CAR value in the event window is for IBOVESPA Brazilon March 24, 2020 when it fell by 5.36% with a CAR of -55.98%. Post March 25, 2020, Indices show the recovery from the bottom levels and decrease in the volatility. Figure 1 shows the upward trend of indices at the end of the first week of April 2020. On September 24, 2020, it appears that the indices have recovered from the downfall caused by the pandemic, but these indices are still below the pre-January 2020 levels with continuing negative CAR. The least recovered index during the event is IBEX 35 Spain with a CAR of -36.86%, followed by MOEX Russia with a CAR of -23.58, Brazil's IBOVESPA with a CAR of -20.68, Mexico's IPC 35 with a CAR of -19.08%, India's NIFTY 50 with a CAR of -15.57% and USA's S&P 500 with a CAR of -15.25%, respectively. Spain's IBEX 35 has underperformed duringthe last decade. Even after the Global Financial Crises of 2008-2009, the index never recovered to pre-crisis levels. It has followed a similar pattern with the COVID-19 pandemic as well and has been underperforming among the sample indices as well.Gam'e et 0!. I3 Cumulative abnormal] return for indices NIFTY 5056213 500 IBOVESPA MOEX_~IPC 35- \\ IBEX 35 g 135"de l Racmxy E :.=' :9~-~' W- 1/ 20.00% ll] 00%- I] 00% %i% an arm. ' 720.00% 730.00% 740.00% .50 00% -6000% JanllJ Feb 21] MarZEl' AprZU May 2!] Jun20 Julll] AngZEl Sepll] Figure I. Cumulative Abnormal Return for Indices in Six Countries for the Entire Event Window. Source: The authors. Conclusion and Implications We examine the impact of the COVlD-19 outbreak on the stock market in the top six most affected countries by thecumulative number of confirmed cases of the virus. The outbreak of COVTD-l9 disease has had a devasting impact on world economies. Most countries initially responded with lockdowns to stop the spread of the novel coronavirus, which in turn paralyzed economic activityand further trembledeconomic growth. The majority of stock markets were open for trading during the lockdown period, and the impact of COVlD-19 on economic activities created fear among market participants.lt was found that the initial reaction of markets was mild, but with the arrival of the virus in new places, an environment of fear was created. Therefore, it furnished motivation to examine the impact of COVID- l 9 on stock returns. First, we check the summary statistics of the various stock exchanges of sample countries and find the positive mean return of each stock exchange before the pandemic COVID-l9 outbreaks, while post- event, each country is witnessed with a negative average return except Mexico. Second, we examine the impact of the COVlD 19 outbreak on the stock return using event study methodology. For it, seven-event windows have been identified. The overall results indicate that COVTD19 affected stock markets severely and elevated the volatility many folds, especially in March 2020. Brazilian stock indices show the highest decline among the selected countries, with a fall of more than 50% during the pandemic, while Mexican indices show the lowest fall of around 30% during the same period. The highest volatility during the event is also seen for Brazilian indices, followed by US indices, with standard deviations above 3.5% and 2.5%, respectively. US and Indian markets were the first to recover from the crash by more than 85% by September 2020. While Spanish markets are least recovered with IBEX 35 index continuing to underperform by more than 35% till last week of September 2020. Even though the effect of COVlD-19 is evident among all the sample country indices, the severity of the effect varies across indices and the same could be attributed to the adoption of different policies regarding lockdown types and timely declaration of packages by governments during the pandemic. The markets are also responsive to the scale of economic activities in an economy and the disruption that COVlD- 19 created to these activities. The findings of the results obtained from this article have three different implications for investors. First, investing in the Mexican stock market will give a robust return in a pandemic like COVlD-19 as it generated a positive return comparatively (see Table 4). Second, every economic crisis brings an 14 Business Perspectives and Research opportunity. Hence, one should invest during such a time to capitalize on the opportunities created by the downfall of the stock market. The crisis is realized by stock markets because of COVID-19 and the same is witnessed by the negative return of the majority of the stock markets. Third, an investor can analyze the market based on volatility because risk propensity is aligned with an individual's risk appetite, which helps to decide whether one has to invest or exit from an investment. The present study corroborates the study of Singh et al. (2020). Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The authors received no financial support for the research, authorship, and/or publication of this article. ORCID IDs Irfan Rashid Ganie iD https://orcid.org/0000-0003-3505-9988 Tahir Ahmad Wani iD https://orcid.org/0000-0003-0885-3692 Miklesh Prasad Yadav (iD https://orcid.org/0000-0001-7851-5803 References Al-Awadhi, A. M. Alsaifi, K. Al-Awadhi, A. Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 100326. https://doi.org/10. 1016/j.jbef.2020.100326 Albulescu, C. T. (2020). Coronavirus and financial volatility: 40 days of fasting and fear (p. 02501814). CRIEF Centre de Recherche sur l'Integration Economique et Financiere, Universite de Poitiers. https://arxiv.org/ abs/2003.04005 Ang, A. Timmermann, A. (2011). Regime changes and financial markets. Columbia University and NBER. Aslam, F. Kang, H. G. (2013). How different terrorist attacks affect stock markets. Defense and Peace Economics, 1-15. https://doi.org/10.1080/10242694.2013.832535 Baker, S. R. Bloom, N. Davis, S. J. 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Why do some soccer bettors lose more money than others? Journal of Behavioral and Experimental Finance, 85-93. https://doi.org/10.1016/J.JBEF.2018.01.010 Chen, M.-H. Jang, S. C. Kim, W. G. (2007). The impact of the SARS outbreak on Taiwanese hotel stock per- formance: An event-study approach. International Journal of Hospitality Management, 200-212. https://doi. org/10.1016/j.ijhm. 2005.11.004 Chen, C. D. Chen, C. C. Tang, W. W. Huang, Y. B. (2009). The positive and negative impacts of the Sars outbreak: A case of the Taiwan. The Journal of Developing Areas, 43, 281-293.FOR FINANCIAL ADVISORS Nationwide' By Nationwide Economics How Has the Pandemic Impacted Inflation September 14, 2021 After a decade of muted price gains, inflation fears have cropped up again as the costs of many goods and services have spiked this year. The ongoing pandemic has played a leading role in the jump in inflation as lingering COVID- induced supply chain disruptions have made it difficult to find some items while driving up consumer prices. Predicting future inflation can be difficult as current readings only reflect where prices have been trending rather than where they are headed. Moreover, temporary supply or demand shocks within specific industries (L.e. - oil and gasoline) can swing inflation for periods of time. For these reasons, tracking the longer-term influences on price gains can provide a clearer picture of the inflation outlookPost-pandemic inflation spike among the highest in 30 years 6.0 - Current level 5.0 4.0 3.0 2.0- 1.0 -10 - -2.0 3.0 1988 Source: Bureau of Labor Statistics Historical impact of pandemics on the economy Historically, health pandemics have caused significant shocks to the U.S. economy. Flu pandemics in 1957 and 1968 were followed by economic downturns while the 1918 Spanish flu was extremely disruptive to the entire society at the time. The nature of a pandemic causes both a demand shock as consumers pull back on activity and a supply shock as businesses shut down or reduce operations. Moreover, there is little to no warning for consumers, businesses, or governments that an extreme shock will occur, making for a sharp shift in overall economic conditions. The supply shock component of the pandemic has the largest impact on inflation as the productive capacity of the economy falls. For example, the oil supply shocks of the 1970s helped to cause the highest spikes in consumer inflation seen over the past 70 years. As the economy comes out of the pandemic, demand will increase, potentially sharply, surpassing the ability of businesses to supply products. This could lead to shortages of goods and services and higher prices for the items that are available. Short term impact of the pandemic on inflationInflation typically increases coming out of downturns as demand outpaces supply early in the recovery, but this tendency has been exacerbated by COVID- 19 impacts. Demand for many goods dropped in 2020 and remained lower into 2021 as further waves of COVID cases led to government restrictions on consumer behavior. As cases waned in the spring of 2021, these restrictions were mostly lifted, driving a surge in demand. Supply conditions of many inputs (l.e. - lumber, steel, and microchips) were depressed during the pandemic, too in anticipation of reduced demand with the downturn and due to pandemic limits on the number of workers. Once the economy reopened more fully, total production within many industries lagged as businesses had difficulty finding inputs and workers. The resulting supply crunch led to higher costs for producers which were passed into many of the prices seen on shelves, with the annual change in the consumer price index spiking to 5.4 percent in mid-2021. While the pandemic remains disruptive for many parts of the global supply chain, including shipping and ground transportation, these impacts should fade in the second half of 2021 and into 2022. As such, the Federal Reserve and many economists feel that the recent rise is an example of transitory inflation. What is transitory inflation? This is a period where prices spike temporarily due to an imbalance between supply and demand in the market, as has occurred over the past year. Once the shock passes and supply chains heal, inflation should settle at a lower level that is more in line with long-term trends. Most forecasts project that inflation will fall to around 2.5 percent by the end of 2022. Long term post-pandemic outlook on inflation Not all the recent price increases are gpected to be transitory, however, as lingering pandemic impacts could drive up wages and housing costs for several more years. Average inflation over the next five years could be slightly higher than the pre-COVID trend as a result, running between 2.5-3.0 percent. Still, it is expected that inflation expectations will remain in check as longer-term price depressants caused by increased online purchases (the so-called \"Amazon effect\") and the offshoring of production should continue. Moreover, one of the objectives of the Federal Reserve is long-run price stability which they define as an average of 2.0 percent annual inflation. While the Fed will likely let inflation run above its 2.0 percent target for a short period of time, economic conditions should improve enough to prompt interest rate increases by late 2023. The eventual tightening of monetary policy will act to slow the economy and, thus, prices keeping inflation near its long-run average. The COVID-19 pandemic has been highly disruptive for the U5. economy with effects that could linger for years. While price gains have increased sharply this year, much of the recent inflationary pressure is expected to be transitory as COVID impacts on supply chains fade heading into 2022. There is a risk that inflation could run hotter than expected in the future, but long-term price depressants and eventual Fed action should keep inflation in check beyond the current spike. Still, given the uncertainty around forecasting inflation, these trends bear watching for an unexpected shift in prices. NFM-21213AO Keywords: #COVlD-19 #economic growth #habits #pandemic Congressional Research Service I I . , . (is. Informing the Ioglslatlvo debate SII1061914 June 24, 2022 How Did COVID-19 Unemployment Insurance Benefits Impact Consumer Spending and Employment? The COVTD-19 pandemic dramatically disrupted the economy with mass layoffs and business closures. The economy was shocked with stay-athome and shutdown orders designed to limit person-to-person contact. These restrictions on the ow of labor and commerce reduced economic demand. They also increased the number of workers unable to work. Additionally, the increased workplace hazards created by the COVTD-19 pandemic further limited certain jobseekers' options for employment, creating unusual shifts in the labor market. Congress recognized the potential threat that such massive earnings losses posed to the national and global economy and responded by augmenting the joint federalstate Unemployment Insurance (UT) system to maintain the economy, among many other measures that provided income support. Recent studies have examined the impact of these UT expansions on consumer spending and em ploym ent. UI Benets During the Pandemic Congress enacted key changes in the UT system in response to the high levels of unemployment resulting from the COVTD19 pandemic and recession (February 2020 through March 2020). Typically, the UT system provides income support to unemployed workers through weekly benefit payments. UT payments help (1) provide temporary partial wage replacement to involuntarily unemployed workers and (2) stabilize the economy during recessions. Permanent-law JT programsUnemploym ent Compensation (U C) and Extended Benefits (313)7automatically respond to layoffs and business closures. However, unprecedented job loss during the COVTD- 9 pandemic prompted Congress to enact a series of extraordinary measures: Federal Pandemic Jnemploym ent Compensation (FPUC), Pandemic Emergency Unemployment Compensation @EUC), and 3andemic Unemployment Assistance (PUA). These UT measures helped to maintain consumer spending and stabilize the economy during this period. PEUC was similar to congressional actions taken in previous recessions as it extended the availability of regular UC benefits (available for up to 26 weeks) for up to an additional 49 weeks. However, two of these interventions, FPUC and PUA, were unprecedented when compared to responses during previous recessions. 0 FPUC provided a weekly supplement on top of all UT benefits. FPUC provided a $600 weekly supplement between April and July 2020 and was reauthorized at $300 weekly from January 2021 through the beginning of September 2021. FPUC payments from April 2020 through September 6, 2021, totaled $442.3 billion. 0 PUA uniquely expanded the population eligible for UT to include the self-employed, gig workers, and others not previously eligible for UT or those unable to work for certain COVID-lQrelated reasons. PUA payments totaled $131.2 billion. Research on the COVI D- I 9 UI Benets An emerging research literature leverages new and rich sources of data to examine both (1) the role that COVTD19 UT benefitsparticularly FPUC and PUAplayed in boosting spending and consumption in US. households that experienced unemployment and (2) whether the supplemental UT benefits decreased the likelihood that unemployed workers found work. A strength of recent studies is their use of new sources of data to evaluate UT impacts, particularly on personal consumption patterns. Measuring the personal consumption response to government programs is traditionally challenging. Data on consumption are scarce and often contain significant measurement error, which makes statistical inference difficult and imprecise. The research discussed below, however, benefits from new proprietary data sources that harness anonymized bank account and lending data to provide weekly information on income, spending, and employment. Additionally, the research uses another new source of household level data: the Household Pulse Survey, an experimental weekly survey conducted by the Census Bureau in collaboration with several federal agencies that includes information on individuals' employment status, spending patterns, food security, housing, physical and mental health, access to health care, and application for and receipt of benefits. Some studies of employment effects are also strengthened by the ability to analyze job applications to an online jobs platform. However, research findings related to the impact of the COVTD-l9 UT benefits may not be generalizable to other periods or labor market conditions. The COVTD-19 recession was created by an abrupt, exogenous shock attributed to public health and safety concerns rather than a series of economic stresses, which are associated with a more typical recession. Additionally, the federal response to the pandemic included several other forms of assistance to employers and employeesisuch as the Payment Protection Program, the Employee Retention Tax Credit, and Economic Impact Payments to householdsithat may also have affected personal consumption and the incentives for employment. COVTDlQspecific factors, such as the availability (or scarcity) of vaccines, childcare, and in person school, may have also contributed to unusual patterns in returning to work during this period. https:/lcrsreportscongressgov How Did COVID-19 Unemployment Insurance Benefits Impact Consumer Spending and Employment? Consumer Spending and COVID-19 UI Payments While the recent research studies did find that the expanded One of the primary objectives of UI is to alleviate the UI benefits had disincentive effects on working, the impact hardships that result from loss of wages during was smaller than expected when compared to estimates unemployment. Typically, UI benefits replace up to 50% of based upon models from prior recessions and non- previous earnings, temporarily supporting workers' basic recessionary periods. Marinescu et al. (2021) reported that needs, but UI benefit recipients' expenditures are often although the weekly $600 FPUC substantially decreased lower than when they were employed. Without UI, the applications to an online jobs platform, labor demand was unemployed are more likely to report that they are unusually depressed, and thus FPUC had little impact on experiencing food and housing insecurity and are more employment levels. Similarly, Ganong et al. (2021), using likely to exhaust personal savings, sell assets, draw upon bank account data, found a smaller negative impact on retirement savings, and further reduce expenditures. Using employment than expected. They observed that a high level a range of data sources, recent studies indicate that COVID- of employees being recalled to work by their former 19 UI payments played a key role in supporting employers helped reduce the disincentive effects of the consumption and general economic security of households. $600 FPUC payment on employment. Furthermore, they found that after the $600 payments ended, most individuals Using Household Pulse Survey data, Carey et al. (2021) did not exit unemployment despite a precipitous drop in found that unemployed individuals who did not receive UI their weekly income, suggesting that other factors were benefits were more likely (than those who received UI) to impeding employment. Coombs et al. (2021) found that it report food insecurity, housing insecurity, and difficulty in was the termination of the underlying UI benefit rather than meeting household expenses. A working paper by Ganong the loss of the $300 FPUC payment that increased the et al. (2021) using bank account data found that once likelihood of reemployment. Greig et al. (2021) found that COVID-19 UI payments were deposited into workers' PUA recipients were younger, had lower income, and were accounts, spending immediately rebounded at or above pre- more likely to have worked in non-traditional jobs or self- unemployment levels (a result that is in contrast to employment but had similar reemployment responses to generally suppressed consumption patterns in previous those receiving regular UC benefits. recessions). Holzer et al. (2021) found that, in states that terminated FPUC and PUA early, the unemployed were References five percentage points more likely to report difficulty CRS Report R46687, Unemployment Insurance (UI) paying for expenses than in states that continued the Benefits: Permanent-Law Programs and the COVID-19 benefits. Similarly, Coombs et al. (2021) used payday loan Pandemic Response. data to examine consumption patterns of low-income individuals who were receiving COVID-19 UI benefits Carey, Patrick et al. "Applying for and Receiving immediately before early state terminations of these Unemployment Insurance Benefits During the Coronavirus benefits. These researchers found that the loss of benefits Pandemic." Monthly Labor Review (September 2021). led to an average 20% reduction in consumption. Coombs, Kyle et al. "Early Withdrawal of Pandemic Unemployment Insurance: Effects on Earnings UI and Disincentives to Work Employment and Consumption." Harvard Business School, The timing, generosity, and duration of UI benefits can Working Paper (August 2021). influence job search behavior of the unemployed. There is Ganong, Peter et al. "Spending and Job Search Impacts of existing evidence that higher benefit levels and lower Expanded Unemployment Benefits: Evidence from thresholds for benefit eligibility can cause recipients to be Administrative Micro Data." Becker Friedman Institute, less willing to accept a job (and thus increase spells of Working Paper (February 2021). unemployment). However, previous economic research Ganong, Peter et al. "US Unemployment Insurance generally found that the employment disincentive effect of Replacement Rates During the Pandemic." Journal of UI during recessionary periods is relatively small, as job Public Economics, vol. 191, no. 104273 (September 2020). openings are limited; thus, Ul income is not a particularly large contributor to high unemployment rates. Greig, Fiona et al. "When Unemployment Insurance Benefits are Rolled Back: Impacts on Job Finding and the During the COVID-19 pandemic response, weekly UI Recipients of the Pandemic Unemployment Assistance benefits often provided significantly higher levels of Program." JPMorgan Chase & Co. Institute (July 2021). income replacement compared to previous recessions. Holzer, Harry J. et al. "Did Pandemic Unemployment Ganong et al. (2020) estimated that from April to July 2020, Benefits Reduce Unemployment? Evidence From Early the combination of the $600 weekly FPUC supplement plus State-Level Expirations in June 2021." NBER, Working the regular UI payment replaced more than 100% of pre- Paper no. 29575, December 2021. pandemic earnings for more than 75% of UI beneficiaries. Marinescu, Ioana et al. "The Impact of the Federal The estimated replacement rate for workers receiving the Pandemic Unemployment Compensation on Job Search and $600 FPUC varied significantly, with a median replacement Vacancy Creation." NBER, Working Paper no. 28567. rate of 145% and a median replacement rate of over 300% March 2021 for UI beneficiaries with the lowest 10% of earnings. These changes (if implemented during a typical recession) would Julie M. Whittaker, Specialist in Income Security have been expected to substantially dampen the incentive Katelin P. Isaacs, Specialist in Income Security for workers to find employment. IF 12143 https://crsreports.congress.gov