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Article

Sectoral Performance and the Government Interventions during COVID-19 Pandemic: Australian Evidence

1
Department of Accounting, Economics and Finance, Swinburne Business School, Swinburne University of Technology, Melbourne, VIC 3122, Australia
2
Assurance Department, PwC Vietnam, Ho Chi Minh City 70000, Vietnam
3
School of Mathematics and Statistics, Faculty of Science, The University of Melbourne, Melbourne, VIC 3010, Australia
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2021, 14(4), 178; https://doi.org/10.3390/jrfm14040178
Submission received: 8 March 2021 / Revised: 28 March 2021 / Accepted: 8 April 2021 / Published: 12 April 2021
(This article belongs to the Section Economics and Finance)

Abstract

:
This study explores the contrasting impacts of the COVID-19 pandemic on various industries in Australia. Considering all daily announced information, we analyzed the diverse impacts of COVID-19 on the sectoral stock returns from 26 January to 20 July 2020. Sixteen out of twenty examined stock indices negatively react to the daily rise in COVID-19 confirmed cases. Several actions from the Australian government to control the pandemic are relatively ineffective in boosting the overall financial market; however, some positive interactions are captured in five sectors of industrials, health care, metals and mining, materials, and resources. The result shows that all industries that benefited from government financial assistance are either shielded or less severely affected by the pandemic. While sectors that did not directly receive financial remedies relatively showed no enhancement in their overall performance. Having achieved short-term success in helping the economy, the government recorded an all-time high deficit since 2004 that might eventually lead to adverse effects on the overall economy. The Australian equity market is found to be rationally distinct to the crude oil price risk, while positive correlations between AUD/USD rate and real estate-related sectors are reported.

1. Introduction

The overall economies, especially, the financial markets speedily reflect the information of all major events. In line with the efficient market hypothesis, the reactions of the stock market to several circumstances have been explored by many prior studies. These findings include terrorist attacks (Choudhry 2005; Karolyi and Martell 2006; Corbet et al. 2018), market disasters (Wachter 2013; Kowalewski and Śpiewanowski 2020), natural and environmental disasters (Wang and Kutan 2013; Guo et al. 2020), and political actions (Kim and Mei 2001; Vuchelen 2003; Shanaev and Ghimire 2019). Especially, the pandemics’ effects on the financial market performance are also documented in various studies, including the 2002 severe acute respiratory syndrome (SARS) outbreak (Chen et al. 2018), the 2009 influenza A (H1N1) (Peckham 2013), and the 2013 Ebola virus disease (Del Giudice and Paltrinieri 2017; Ichev and Marinč 2018). In 2020, an ongoing global pandemic of coronavirus disease 2019 (COVID‑19) has caused the worst crashes across world economies since the turmoil of the 2007 global financial crisis (GFC). Since the first confirmed case of coronavirus in Wuhan, China in December 2019, this deathly disease has rapidly spread out internationally. As of March 2021, there have been more than 125 million confirmed cases globally, including over 2.7 million deaths1. In the June 2020 report of the International Monetary Fund (IMF), the global growth is projected at −4.9% in 2020, which is the lowest rate since the 2007 GFC (1.7%). When the first wave of COVID-19 outbreak stroke from January to March, the US, UK, and Australian stock indices experience the fastest fall (more than 20%) in history amid extraordinary volatility (Banerji 2020). The governments, as well as international organizations, have hastened to find optimal measures to contain the outbreak. As its unpredictable and complicated movements, the economic consequences of the COVID-19 pandemic will probably exceed those of the 2007 GFC (Ilzetzki et al. 2020).
For Australia, the second wave of this pandemic started in July since the first infected case was reported in February 2020. With stricter lockdown policies, the government strived to control the pandemic. The Australian economy has been devasted by the spread of COVID-19 from the international trade, tourism, airline industry, retail, and service sectors to many other industries. In opposition, a few sectors can benefit from the pandemic such as healthcare, biotech, or household staples as they are always essential, even during the recession. As people are required to isolate themselves, the segment of information technology is less likely to be impacted as it could provide services that support working and studying from home. Data from the Australian Bureau of Statistics (ABS)2 reveals that the 2020 first quarter GDP has diminished by 0.3%, amid the severe effect of the bush fires in 2019 and the first stage of the COVID-19 pandemic. The greatest obstacle to the Australian economy is that the demand for household spending fell (by 1.1%) for the first time since 2008. The ABS also identified the most affected sectors by the pandemic including transportation, art and entertainment, and retails. Consequently, it is exceedingly anticipated that the COVID-19 pandemic will have ominously unpredictable effects across the Australian industries. This contagion also worsens the level of uncertainty and confidence, augments the risk aversion, and accumulates the disorder in overall financial markets (Zhang et al. 2020). To secure the current financial positions, many investors are trying to liquidate their assets including their stocks; thus, it simultaneously distresses the stock market performance (Okorie and Lin 2021). These economic consequences will directly and inversely demonstrate the performance of sectoral indices of the financial market (Liu and Sinclair 2008).
This study seeks to examine the contrasting impacts of COVID-19 on the Australian economy based on sectoral analyses. This study includes main market-cap indices as well as sectoral indices listed on the Australian Stock Exchange (ASX). In this study, we employ the main indicator of the daily number of confirmed cases to comprehensively investigate varying impacts of the outbreak on the country’s overall economy from January 2020. We also capture the effects of COVID-19 on the financial market by including the interactions between infected rate and three indicators of Australian government intervention, the foreign exchange market, and Brent crude oil prices.
Our findings indicate that the overall Australian stock markets react intensely with negative returns to the daily increase in COVID-19 confirmed cases. The levels of negative impacts were diverse among different industries depending on its characteristics and the economical stimulations from the government. Our findings suggest that financial supports are more effective than other policies in uplifting sectoral performance. Further, all Australian industries were possibly separated from the crude oil price risk during the pandemic. More interestingly, the positive correlations between AUD/USD rate and real estate-related sectors are captured during the financial downturn.
This study contributes to the extant literature in two folds. From different regimes in terms of sectoral analyses, this study explores the overall Australian financial market with respect to the COVID-19 pandemic. Hence, our study extends the current finance literature regarding the stock market reactions during extreme events. Additionally, the sectoral analyses also propose implications for suitable policy adjustments for each sector to minimize the impacts of extreme events on the overall financial market. Considering the interventions of the Australian government, this paper sheds light on the overall opposing interactions between how different industries performed. From a broader perspective, this study proposes perceptions to improve and strengthen the current policies required for the financial markets and the overall economy.
This study proceeds as follows. Section 2 depicts data required for the study, as well as the methodology to investigate the influence of COVID-19 on the performance of Australian industries. Section 3 reports the key findings of the empirical analysis and Section 4 concludes the study.

2. Data and Methodology

To capture the effects of the COVID-19 pandemic on the Australian stock market, we use three daily indices based on the market capitalisation, including: ASX All Ordinaries, S&P/ASX50, and the S&P/ASX300 (See Appendix A for detailed information). This study also examines the performance of 17 sectoral stock indices on daily basis to compare contrasting movements during the outbreak. The sectoral classifications are based on the Global Industry Classification Standard (GICS). Data for sectoral indices is the S&P/ASX 300, which covers the large-cap, mid-cap, and small-cap components of the S&P/ASX Index Series to prevent a possible bias toward domination of large-cap stocks. All stock index data is obtained from the S&P Dow Jones Indices Database. Figure 1 indicates the daily growth in COVID-19 confirmed cases in Australia and the ASX All Ordinaries returns from 25 January until 20 July 2020. Considering the COVID-19 impacts on the overall Australian economy, we only examine the data from January to July 2020 as the second wave of infections largely localized in Melbourne, Victoria from July to September.
The corresponding COVID-19 data in Australia is obtained from the Our World in Data. We prefer to use the daily number of confirmed cases per million to compute the daily growth rate to avoid possible biases toward extreme case numbers. We also collect the COVID-19 Government Response Index (GRI) from the Oxford University database to estimate the response of the Australian government during the pandemic. This study also includes two control variables, which are obtained from the Investing.com Database. The first indicator is the AUD/USD exchange rate, which is obtainable on daily basis. The second indicator is Brent crude oil prices in USD per barrel to capture the oil price risk exposure (Elyasiani et al. 2011; Akhtaruzzaman et al. 2020). All daily nominal data in this study spans from 26 January 2020 to 20 July 2020. Table 1 features the list of examined stock market indices, their abbreviations, and basic statistics (See Appendix A for detailed explanations of the indices).
The extent to which the catastrophic impact of the pandemic on the economy is still evolving unpredictably, therefore we do not employ the method of a classical event for this study. The approach of Ordinary Least Square (OLS) regression is employed in this study. This method is considered appropriate to recognize and measure the consequences of the independent variables since there are no interactions between the chosen variables, which is shown in the correlation matrix in Table 3. The dependent variables (stock index returns) are regressed on the lagged values of the independent variables, which are daily growth in COVID-19 confirmed cases and controlling for the COVID-19 Government Response Index (GRI). We also include two control variables as the parameter of foreign exchange market—daily AUD/USD exchange rate (FX) return, and the oil price risk—crude oil price return (OIL). As the stock market data is available for the trading days only (excluding the weekends and Australian public holidays), the COVID-19, GRI data in day (t−1) of Monday is the average of the previous three days (Friday, Saturday, and Sunday). This method is to take into account the reaction of the stock market regarding all information announced during the weekends.
In our models, the interaction variables of GRI t 1 × CASE t 1 show whether the equity market reactions to the growth in COVID-19 confirmed cases depend on government actions. In this study, we also consider the daily lagged returns crude oil price ( OIL t 1 ) and AUD/USD rate   ( FX t 1 ) to capture the oil price risk and forex market exposure to the performance of Australian stock index returns. Using the Ordinary Least Square (OLS) regression, we estimated the stock indices in the following econometric models:
R E T i , t = c   +   α 1 C A S E t 1 + ε i , t
R E T i , t = c   +   α 1 C A S E t 1 + β 1 ( G R I t 1 × C A S E t 1 )   + ε i , t
R E T i , t = c   +   α 1 C A S E t 1 + β 1 ( G R I t 1 × C A S E t 1 ) + β 2 O I L t 1   + γ F X t 1   + ε i , t

3. Results and Discussion

3.1. Empirical Results

This section describes the employed methodology and the according empirical results. The average daily returns of all examined variables are reported in Table 2. Overall, all indices experienced negative returns during the pandemic. The results of unit root test (ADF and PP tests) suggest that all data series (except GRI3) are stationary, which means that those variables follow the random walk. Hence, our data is suitable for further time-series analyses in the OLS regression.
The correlation matrix for the four main dependent variables and four independent variables in this study is reported in Table 3. All stock indices are strongly and negatively correlated with the growth in COVID-19 confirmed cases. The graphical correlation matrix for all variables is reported in Appendix B.
The OLS regression results for three Australian market cap indices during the COVID-19 outbreak are tabulated in Table 4. The market capitalised index returns are negatively correlated with the daily growth in confirmed COVID-19 cases in Australia in three regressed models. Both small stocks and blue chip stocks are critically impacted by the pandemic. We also consider how the Australian government interventions interact with the impact of COVID-19 on the stock market returns in Model 2 by using the interaction term of Government Response Index × Growth in confirmed cases. This statistically insignificant interaction term in Model 2 indicates that the overall Australian financial market still sharply deteriorated regardless of the government reactions. This result remains robust when we consider the influence of oil price risk and foreign exchange market on the stock index returns in Model 3. Hence, the Australian government reactions may not be enough in maintaining investor confidence during the pandemic. Our findings also reveal that the market capitalised index returns are not exposed to the fluctuations of crude oil and the forex market.
The data shown in Table 5 indicates the levels of impacts of COVD-19 on Australian industries. Overall, all sectors were adversely affected by the increase in the number of COVID cases. However, the magnitudes of impact vary in different industries. Four sectors of Gold, Consumer Staples, Real Estate, and Communication are insignificantly associated with the growth in COVID-19 confirmed cases. This result corroborates that gold is considered as the haven asset for the financial markets during the crisis period (Akhtaruzzaman et al. 2021; Ji et al. 2020). Three sectors; Health Care, Financial excluding REIT, and Bank were likely less affected by the outbreak while the remaining ten sectors were harshly affected by the coronavirus outbreak in the country. Our findings remain robust in Model 2 and 3 when we include the factor of government interventions and two control variables of oil price and forex rate returns.
In the second model, we also look at how government measures to curb the increase in COVID-19 cases affecting the sectoral returns. The interaction term of Government Response Index × Growth in confirmed cases only enters positive and statistically significant for five sectors, including Health Care, Industrials, Materials, Metals and Mining, and Resources. This result suggests that the negative impacts of the rise in COVID-19 cases on those sectoral index returns are alleviated when the Australian government increases the levels of responses. We also consider the influences of exchange rate and oil price risk on the performance of Australian sectors during the COVID-19 pandemic in Model 3. We find that the performance of the Australian equity market is reasonably unconnected to the oil price risk exposure during the COVID-19 outbreak. For the foreign exchange market, all but A-REIT and Real Estate indices are not affected by the AUD/USD rate fluctuations. Both REIT and Real Estate index returns are positively and significantly associated with the variations of AUD/USD rate.

3.2. Result Summary and Discussion

All in all, the subsection summarises the results of overall Australian financial market performance during the COVID-19 pandemic in Table 6. All Australian market-cap indices performed abysmally during the examined period regardless of the market capitalizations. For the sectoral analysis, ten of seventeen Australian sectors are severely distressed by the growth in COVID-19 confirmed case. The ten sectors are Technology, A-REIT, Consumer Discretionary, Industrial, Information Technology, Materials, Metals and Mining, Utilities, Resources, and Energy.
Unsurprisingly, the Gold index seems not to be significantly affected by the pandemic. This is consistent with studies of Akhtaruzzaman et al. (2021) and Ji et al. (2020), which show Gold index remains robust during crisis periods as it is considered a haven asset. Remarkably, Consumer Staples, and Communicating Services, and Real Estate are also the group of least suffered industries in Australia. Consumer Staples did not suffer much due to their essential and irreplaceable nature even at the peak of the coronavirus outbreak. The consequences of travel restrictions and the social distancing caused by the pandemic have motivated the development of online connection services. Additionally, the Federal and State Governments spent a significant amount of money on advertising to inform the public on how to stop the spread of the virus. Therefore, the communication service industry still has great potentials to develop in the complicated pandemic situation. Likewise, the Federal Government introduced the First Home Loan Deposit Scheme in January 2020 and Home Builder Grant in June 2020. State and Territory Governments issued various land tax and rent relief measures to help commercial landlords and tenants, which is reported in Table 7. Together, these policies may have helped to relieve the downward pressure on the Real Estate sector.
All Australian sectors are not exposed to the crude oil price risks during the pandemic. Previous findings suggest that sectors which heavily consume oil or are directly associated with oil production are significantly exposed to oil price risk (Elyasiani et al. 2011; Akhtaruzzaman et al. 2020). In terms of the exposures to AUD/USD rate fluctuations, Real estate investment trusts (A-REITs) and mortgage REITs, and Real Estate sectors show positive associations. This result is incomparable to those findings of (Hiang Liow et al. 2006) and Ngo (2017), which suggest that REIT and Real Estate returns are adversely influenced by the increase of the home currency. However, our study is conducted in the COVID-19 period, which negatively crashed down the foreign consumers’ demand, regardless of the depreciation of the Australian dollar against other currencies. In the situation of international travel restrictions and financial turmoil, the loss of international investors means lower cash flows and returns for REIT and Real Estate sectors. Further, a weakening Australian dollar also poses a significant risk the overseas landlords as it diminishes their rental revenue yield. Hence, the depreciation of the Australian dollar during the COVID-19 pandemic cannot be the driving force to improve returns on investment in the real estate and rental sectors.
Three industries of Health Care, Financial excluding REIT, and Banks still experience negative impact from the COVID-19 but at lower levels. This can be plausibly explained by various policies taken by the Australian Federal Government just before and after the outbreak struct. All detailed information about the government policies is available in Table 7. The heavy spending on medical equipment and research ($2.4 billion in March 2020) and pledging of further spending on healthcare may instil confidence in investors to invest more in the Healthcare sector. Banks and Financial excluding REIT may also stand to benefit from actions taken by the government to prop up the housing market as people are likely to take out more loans to purchase or build houses. The Australian Government also introduced the Coronavirus Small and Medium Enterprises (SME) Guarantee Scheme which enhances lenders’ ability to issue new loans for small and medium businesses by guaranteeing 50 percent (up to $40 billion in total) of these new loans.
Our findings indicate that the influences of daily government interventions were only significant for Health Care, Industrials, Materials, Metals and Mining, and Resources sectors. However, the effectiveness of these policies on the stock returns measured by the GRI index is not well materialized. Industries that fare better are those of haven assets, household staples, and sectors that receive significant financial support from the government. Despite showing some positive responses to the government actions to stop the spread of COVID-19, Industrials, Materials, Mining, and Resource indices still perform very poorly. The justification for these mixed results can be viewed from different angles. On one hand, non-financial interventions designed to reduce infected cases may fasten the reopening of borders, which is crucial for these four industries as their main business activities involve interstates travel of the workforce and exports. This may have sustained a level of investor confidence in the viability of these sectors. On the other hand, the unpredictability of this pandemic has put these industries on hold indefinitely, which causes their revenues to plummet considerably during our examined period. Hence, the optimism of resuming business alone cannot enhance the overall performance of those industries when new revenues are not being generated. In summary, measures taken to curb the spread of the virus can only partially improve investor confidence, and financial supports from governments are more crucial in enhancing the sectoral performance during the pandemic.
The overwhelming positive effects of the government stimulus package on the financial market raise competing implications for policy development during global crises. On one hand, the success of government financial supports is undeniable; however, it comes at an enormous cost Figure 2 graphically presents the data for Expenses and Fiscal Balance of the Australian Federal Government from 2019 to 2020, which is obtained from the Australian Bureau of Statistics (ABS). The government spending for each of the second and third quarter of 2020 is about $77 billion (equate to approximately 44%) higher than the average quarterly spending ($176 billion) of the previous four quarters. The average ratio of consolidated Fiscal Balance of the Australian Government over the nominal GDP from 2003 to 2020 is only −2.2% according to ABS reports. However, the recorded deficit ratio is approximate 7.27% in the third quarter of 2020. The fiscal deficit reached an all-time high of 11.47% in the last quarter of 2020, which was relatively explained by the financial provisions during the COVID-19 outbreak. The finance deficit can eventually lead to either higher taxes or inflation and punitive economic austerity.

4. Conclusions

This study examines the impacts of COVID-19 on the Australian financial market by considering the adverse impacts of twenty stock market indices over the period 26 January–20 July 2020 by considering all information of COVID-19 and government responses. We comprehensively explore the erratic influences of the pandemic on the sectoral performance of the Australian economy. Encompassing the rich literature in this field, we find that this pandemic interacts deleteriously with stock index returns for all levels of market capitalization. Contemplating the authority interventions, foreign exchange, and the oil price risk, this paper sheds light on the overall opposing interactions between how different industries performed. We demonstrate that sixteen out of twenty sectoral indices in Australia are significantly stricken by the increase in COVID-19 confirmed cases. The four least deteriorated industries during the pandemic are due to their unique characteristics and the stimulus packages from the government. Further, the financial supports from the Australian government were relatively more effective in enhancing the financial market performance compared to other measures.
Our analysis also proposes that the Australian equity market is rationally distinct to crude oil price volatilities during the COVID-19 outbreak. As heavy oil consumers or oil producers are significantly exposed to the oil price risk, further studies need to dissect the sub-sectors to clearly determine the levels of this exposure. Our findings also suggest that depreciation of the Australian dollar cannot improve the performance of real estate-related sectors during the phase of international travel being constricted and financial chaos. Due to data constraint, the study levered index data as a proxy to implement the analysis. The limitation of this study is identified as potential bias arising from the utilization of aggregate indices. Since, this will not allow a thorough measurement of the pandemic’s impacts on sub-sectors as compared to sectoral-portfolio data, which is suggested as a more sufficient alternative for the latter research. Despite the inherent limitations, this study also opens up paths for future studies on the ongoing pandemic while contributing to the blooming literature on the collisions of COVID-19 on the financial market. From the starting point of studies in the impacts of this pandemic on the financial market, the short-term measures and long-term resilience should be premeditated to assist the overall economic recovery.

Author Contributions

Conceptualization, N.H.; methodology, N.H.; software, N.H.; validation, N.H., D.N., and A.D.; formal analysis, N.H., D.N., and A.D.; investigation, N.H., D.N., and A.D.; data curation, N.H.; writing—original draft preparation, N.H., D.N., and A.D.; writing—review and editing, N.H., D.N., and A.D.; visualization, N.H., D.N., and A.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Variables

In Australian stock market, all ASX listed entities are reclassified according to GICS meet the global standard. GICS is cooperatively established by MSCI and S&P Dow Jones to systematize the international industry descriptions. The detailed classifications of all are the ASX website. The information for all dependent variables is summarised by authors from the S&P Dow Jones Indices Database and the ASX website.
Dependent Variable
Market-Cap IndexDescriptionSource
ASX ALL ORDINARIESThe index represents the 500 largest companies in the Australian equities market. Index constituents are drawn from eligible companies listed on the Australian Securities Exchange. Liquidity is not considered as criteria for inclusion, except for foreign domiciled companies.S&P Dow Jones Indices Database
S&P/ASX 50The S&P/ASX 50 is Australia’s most prominent large-cap equity index and is designed to represent 50 of the largest and most liquid stocks listed on the ASX by float-adjusted market capitalization.S&P Dow Jones Indices Database
S&P/ASX 300The S&P/ASX 300 is designed to provide investors with broader exposure to the Australian equity market. The index is liquid and float-adjusted, and it measures up to 300 of Australia’s largest securities by float-adjusted market capitalization. The S&P/ASX 300 index covers the large-cap, mid-cap, and small-cap components of the S&P/ASX Index Series. This index is designed to address investment managers’ needs to benchmark against a broad opportunity set characterized by sufficient size and liquidity.S&P Dow Jones Indices Database
Sectoral Index
S&P/ASX All Ordinaries Gold IndexS&P/ASX All Ordinaries Gold Index includes companies in the gold sub-industry of the All Ordinaries Index. The index includes a wide range of companies within the GICS® gold sub-industry, and therefore, serves as an ideal broad market indicator for the gold industry.S&P Dow Jones Indices Database
S&P/ASX All Technology IndexThe S&P/ASX All Technology Index is designed to be a comprehensive measure of technology-oriented companies listed on the ASX that meet certain investability constraints. It includes companies classified under the GICS® Information Technology sector, as well as additional relevant sub-industries in other sectors.S&P Dow Jones Indices Database
S&P/ASX 300 A-REITA sector subindex of the S&P/ASX 300, this index tracks the performance of Australian real estate investment trusts (A-REITs) and mortgage REITs.S&P Dow Jones Indices Database
S&P/ASX 300 Consumer DiscretionaryThe S&P/ASX 300 Consumer Discretionary provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® consumer discretionary sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 Consumer StaplesThe S&P/ASX 300 Consumer Staples provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® consumer staples sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 EnergyThe S&P/ASX 300 Energy provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® energy sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 Financials excluding A-REITs IndexA sector sub-index of the S&P/ASX 300, this index contains companies involved in activities such as banking, mortgage finance, consumer finance, specialized finance, investment banking and brokerage, asset management and custody, corporate lending, insurance, and financial investment, excluding Australian real estate investments trusts (A-REITs), mortgage REITs, equity REITs, and real estate management & development companies.S&P Dow Jones Indices Database
S&P/ASX 300 Health CareThe S&P/ASX 300 Health Care provides investors with benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® health care sector and sub-industriesS&P Dow Jones Indices Database
S&P/ASX 300 IndustrialsThe S&P/ASX 300 Industrials provides investors with sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® industrials sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 Information TechnologyThe S&P/ASX 300 Information Technology provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® information technology sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 MaterialsThe S&P/ASX 300 Materials provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® materials sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 Metals and MiningThe S&P/ASX 300 Metals and Mining Index is based on the S&P/ASX 300 Index, and is comprised of companies that are classified as being in the Metals and Mining industry1. It includes producers of aluminium, gold, steel, precious metals and minerals and also diversified metals and minerals.S&P Dow Jones Indices Database
S&P/ASX 300 Real EstateThe S&P/ASX 300 Real Estate comprises stocks included in the S&P/ASX 300 that are classified as members of the GICS® real estate sector.S&P Dow Jones Indices Database
S&P/ASX 300 ResourcesA sector sub-index of the S&P/ASX 300 Index, this index provides investors with a sector exposure to the Resources sector of the Australian equity market as classified as members of the GICS® resources sector. Resources are defined as companies classified in the Energy sector (GICS® Tier 1), as well as companies classified in the Metals and Mining Industry (GICS® Tier 3)S&P Dow Jones Indices Database
S&P/ASX 300 Communication ServicesThe S&P/ASX 300 Communication Services provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® communication services sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 UtilitiesThe S&P/ASX 300 Utilities provides investors with a sector benchmark that reflects those companies included in the S&P/ASX 300 that are classified as members of the GICS® utilities sector and sub-industries.S&P Dow Jones Indices Database
S&P/ASX 300 BanksThe S&P/ASX 300 Banks (Industry) provides investors with a benchmark that is designed to measure constituents in the S&P/ASX 200 that are classified as members of the GICS® Banks industry and sub-industries.S&P Dow Jones Indices Database
Independent Variable
Daily growth in COVID-19 confirmed casesThe growth rate in coronavirus-related data is calculated from the Coronavirus Pandemic (COVID-19) data on daily basic.Our World in Data: https://ourworldindata.org/coronavirus-data
COVID-19 Government Response IndexOxford COVID-19 Government Response Tracker (OxCGRT), systematically collects information on several different common policy responses that governments have taken to respond to the pandemic on 17 indicators such as school closures and travel restrictions. The higher value, the more references to levels of pandemic in the country. Blavatnik School of Government database, University of Oxford
Control Variables
AUD/USD exchange rateDaily exchange rate between Australian dollar and U.S dollar on daily basic.Investing Database
Brent crude oil prices per barrel (USD)Brent crude oil prices in USD per barrel on daily basic.Investing Database

Appendix B. Graphical Correlation Matrix

Jrfm 14 00178 g0a1

Notes

1
The data was retrieved on 27th March 2021 from the World Health Organization (WHO): https://covid19.who.int/ (accessed on 27 March 2021).
2
The data was retrieved from the Mar 2020 Issue—Australian National Accounts: National Income, Expenditure and Product on the Australian Bureau of Statistics (ABS) website.
3
The data for GRI is not stationary as the index increases overtime during the pandemic and gradually falls according to the updated government policies.

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Figure 1. Australian COVID-19 data, stock market, gold index, and independent variables.
Figure 1. Australian COVID-19 data, stock market, gold index, and independent variables.
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Figure 2. Expenses and fiscal balance of the Australian Federal Government.
Figure 2. Expenses and fiscal balance of the Australian Federal Government.
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Table 1. Variable.
Table 1. Variable.
Market-Cap IndexAbbreviationSource
ASX ALL ORDINARIESASX S&P Dow Jones Indices Database
S&P/ASX 50ASX50 S&P Dow Jones Indices Database
S&P/ASX 300ASX300 S&P Dow Jones Indices Database
Sectoral Index
S&P/ASX All Ordinaries Gold Index Gold S&P Dow Jones Indices Database
S&P/ASX All Technology IndexTechnology S&P Dow Jones Indices Database
S&P/ASX 300 Real estate investment trusts (A-REITs) and mortgage REITsREIT S&P Dow Jones Indices Database
S&P/ASX 300 Consumer Discretionary Con-discretionary S&P Dow Jones Indices Database
S&P/ASX 300 Consumer StaplesConsumer Staples S&P Dow Jones Indices Database
S&P/ASX 300 EnergyEnergy S&P Dow Jones Indices Database
S&P/ASX 300 Financials excluding A-REITs Fin Ex S&P Dow Jones Indices Database
S&P/ASX 300 Health CareHealth Care S&P Dow Jones Indices Database
S&P/ASX 300 IndustrialsIndustrials S&P Dow Jones Indices Database
S&P/ASX 300 Information TechnologyIT S&P Dow Jones Indices Database
S&P/ASX 300 MaterialsMaterials S&P Dow Jones Indices Database
S&P/ASX 300 Metals and MiningMetals and Mining S&P Dow Jones Indices Database
S&P/ASX 300 Real EstateReal Estate S&P Dow Jones Indices Database
S&P/ASX 300 ResourcesResources S&P Dow Jones Indices Database
S&P/ASX 300 Communication ServicesCommunication S&P Dow Jones Indices Database
S&P/ASX 300 UtilitiesUtilities S&P Dow Jones Indices Database
S&P/ASX 300 BanksBank S&P Dow Jones Indices Database
Independent Variable
Daily growth in COVID-19 confirmed casesCASEOur World in Data
COVID-19 Government Response Index GRIBlavatnik School of Government database, University of Oxford
Control Variable
Daily AUD/USD exchange rate returnFXInvesting Database
Daily Brent crude oil prices returnOILInvesting Database
Table 2. Basic statistics.
Table 2. Basic statistics.
Market-Cap IndexObsMeanS.D.Jarque–Bera TestADF TestPP Test
ASX122−0.0010.02541.51 *−3.734 *−13.942 *
ASX50122−0.0010.02540.69 *−3.947 *−14.676 *
ASX300122−0.0010.02542.18 *−3.776 *−14.151 *
Sectoral Index
Gold1220.0020.03390.78 *−5.446 *−8.223 *
Technology1220.0010.03127.23 *−3.627 *−12.466 *
REIT122−0.0020.03499.35 *−4.120 *−11.250 *
Con-Discretionary122−0.0010.02841.33 *−3.837 *−12.303 *
Consumer Staples1220.0000.020112.13 *−6.948 *−16.417 *
Energy122−0.0030.039205.67 *−3.848 *−12.009 *
Fin Ex122−0.0010.03223.80 *−3.932 *−13.456 *
Health Care1220.0000.02971.45 *−4.839 *−20.482 *
Industrials122−0.0020.027143.41 *−3.904 *−11.603 *
IT1220.0010.03118.57 *−3.607 *−12.181 *
Materials1220.0000.02643.31 *−4.173 *−13.378 *
Metals and Mining1220.0010.02753.78 *−4.438 *−13.303 *
Real Estate122−0.0020.034107.10 *−4.084 *−11.417 *
Resources1220.0000.02878.16 *−4.088 *−13.356 *
Communication122−0.0010.02049.08 *−5.036 *−14.518 *
Utilities1220.0000.019157.42 *−5.189 *−12.171 *
Bank122−0.0020.03519.41 *−4.045 *−13.201 *
Independent Variable
CASE1220.0770.1794363.54 *−1.929−7.374 *
GRI12252.52529.25515.70 *−1.4210.188
Control Variable
FX1220.0000.00955.17 *−4.726 *−8.680 *
OIL122−0.0300.311294.59 *−4.336 *−7.675 *
Note: This table presents the basic statistics for all examined variables in this study. The results of Jarque–Bera test, Dickey–Fuller test (ADF—stationary), and Phillips–Perron test (PP—no intercept) results. * indicates significance at the 5%.
Table 3. Correlation matrix.
Table 3. Correlation matrix.
VariableASXASX50ASX300GOLDCASEGRIFXOIL
ASX1.000
ASX500.993 *1.000
ASX3000.999 *0.9961.000
GOLD0.1060.0740.1001.000
CASE−0.327 *−0.277 *−0.314 *−0.0841.000
GRI0.1630.1460.1590.161−0.1221.000
FX0.0980.0790.0960.164−0.0660.1571.000
OIL0.0000.0060.002−0.0440.061−0.0860.1171.000
Note: The Pearson coefficients are reported, and * indicates significance at the 5%.
Table 4. Impacts of COVID-19 and government interventions on market cap indices.
Table 4. Impacts of COVID-19 and government interventions on market cap indices.
ModelVariableMarket-Cap Index
ASXASX50ASX300
Coefficientt-StatCoefficientt-StatCoefficientt-Stat
(1)Constant0.003(1.10)0.002(0.80)0.002(1.03)
CASE t 1 −0.045(−3.79) **−0.039(−3.16) **−0.044(−3.63) **
F-stat14.33 **9.97 **13.17 **
R-square0.1070.0770.099
(2)Constant0.003(1.25)0.002(0.97)0.003(1.19)
CASE t 1 −0.071(−3.15) **−0.069(−2.93) **−0.071(−3.10) **
GRI t 1 × CASE t 1 0.000(1.35)0.001(1.48)0.000(1.39)
F-stat8.13 **6.14 **7.60 **
R-square0.1200.0940.113
(3)Constant0.003(1.20)0.002(0.94)0.003(1.15)
CASE t 1 −0.068(−3.00) **−0.067(−2.81) **−0.068(−2.95) **
GRI t 1 × CASE t 1 0.000(1.24)0.001(1.40)0.000(1.29)
OIL t 1 0.001(0.11)0.001(0.16)0.001(1.12)
FX t 1 0.164(0.71)0.119(0.62)0.159(68)
F-stat4.15 **3.10 **3.88 **
R-square0.1240.0960.117
Note: This table presents the regression results for three market-cap indices performance during the pandemic from 26 January to 20 July 2020. The dependent variable is daily returns ( R E T i , t ) of three main market cap indices are regressed on two independent variables and two control variables. One-day lagged values of all independent and control variables are used in the models. t-statistics are reported in parentheses with their associated coefficients, ** indicate significance at the 1%.
Table 5. Impacts of COVID-19 on Australian stock market sectoral returns.
Table 5. Impacts of COVID-19 on Australian stock market sectoral returns.
SectorModel 1Model 2Model 3
Constant C A S E t 1 F-StatR-SquareConstant C A S E t 1 G R I t 1 × C A S E t 1 F-StatR-SquareConstant C A S E t 1 G R I t 1 × C A S E t 1 O I L t 1 F X t 1 F-StatR-Square
Gold0.003−0.0150.850.0070.004−0.0330.0000.640.0110.003−0.0250.000−0.0060.0561.130.037
(1.03)(−0.92)(1.09)(−1.04)(0.66)(0.91)(−0.79)(0.46)(−0.65)(1.74)
Technology0.006−0.06318.35 **0.1330.006−0.0910.0019.95 **0.1430.006−0.0860.0000.0010.3815.45 **0.157
(1.99)(−4.28) **(2.13) *(−3.29) **(1.21)(2.04) *(−3.07) **(1.03)(0.16)(1.35)
A-REIT0.004−0.07220.44 **0.1460.003−0.0570.00010.31 **0.1480.003−0.0460.0000.0000.8827.29 **0.200
(1.16)(−4.52) **(1.08)(−1.90)(−0.55)(0.93)(−1.54)(−0.90)(0.00)(2.73) **
Consumer Discretionary0.004−0.05818.57 **0.1340.004−0.0710.0009.44 **0.1370.004−0.0680.0000.0020.2835.02 **0.147
(1.45)(−4.31) **(1.51)(−2.79) **(0.63)(1.46)(−2.61) **(0.48)(0.26)(1.08)
Consumer Staples0.001−0.0162.740.0220.001−0.0220.0001.430.0230.002−0.0260.0000.005−0.2211.170.038
(0.59)(−1.66)(0.62)(−1.18)(0.37)(0.78)(−1.34)(0.49)(0.84)(−1.15)
Energy0.003−0.07516.10 **0.1180.003−0.1290.0019.88 **0.1420.003−0.1280.001−0.0080.0385.00 **0.146
(0.73)(−4.01) **(0.94)(−3.69) **(1.83)(0.85)(−3.60) **(1.81)(−0.70)(0.11)
Financial excluding REIT0.003−0.05914.34 **0.1070.003−0.0740.0007.32 **0.1090.003−0.0700.0000.0020.3083.91 **0.118
(1.01)(−3.79) **(1.07)(−2.50) *(0.60)(1.01)(−2.32) *(0.47)(0.17)(1.01)
Health Care0.001−0.0100.480.0040.001−0.0610.0012.650.0430.002−0.0650.0010.007−0.3051.740.056
(0.18)(−0.69)(0.44)(−2.24) *(2.19) *(0.59)(−2.37) *(2.29) *(0.81)(−1.09)
Industrials0.002−0.04814.14 **0.1050.003−0.0920.0019.54 **0.1380.002−0.0860.0010.0010.4295.62 **0.161
(0.84)(−3.76) **(1.09)(−3.82) **(2.13) *(0.99)(−3.55) **(1.90) *(0.09)(1.76)
Information Technology0.005−0.05714.90 **0.1100.005−0.088−0.0018.37 **0.1230.006−0.0830.0000.0010.4044.72 **0.139
(1.88)(−3.86) **(2.03) *(−3.16) **(1.32)(1.94)(−2.93) **(1.13)(0.14)(1.42)
Materials0.003−0.0326.11 *0.0480.003−0.0780.0015.75 **0.0880.003−0.0770.001−0.0050.0282.95 *0.092
(1.14)(−2.47) *(1.41)(−3.26) **(2.27) *(1.31)(−3.18) **(2.25) *(−0.67)(0.12)
Metals and Mining0.003−0.0284.42 *0.0350.004−0.0790.0015.03 **0.0780.003−0.0790.001−0.006−0.0122.63 *0.083
(1.13)(−2.10) *(1.42)(−3.12) **(2.34) *(1.32)(−3.07) **(2.33) *(−0.75)(−0.05)
Real Estate0.004−0.07321.38 **0.1510.003−0.0600.00010.76 **0.1530.003−0.0480.0000.0000.8027.43 **0.203
(1.17)(−4.62) **(1.10)(−1.98) *(−0.52)(0.95)(−1.63)(−0.86)(0.02)(2.67) **
Resources0.003−0.0387.65 **0.0600.004−0.0910.0016.86 **0.1030.003−0.0910.001−0.006−0.0093.54 **0.108
(1.05)(−2.77) **(1.34)(−3.53) **(2.40) *(1.24)(−3.47) **(2.39) *(−0.77)(−0.04)
Communication Services0.001−0.0203.730.0300.001−0.0230.0001.870.0310.001−0.0230.0000.0020.0570.990.033
(0.41)(−1.93)(0.43)(−1.18)(0.20)(0.45)(−1.13)(0.15)(0.40)(0.28)
Utilities0.003−0.03715.90 **0.1170.003−0.0560.0008.91 **0.1300.003−0.0580.0000.003−0.0954.51 **0.134
(1.47)(−3.99) **(1.62)(−3.24) **(1.34)(1.68)(−3.27) **(1.38)(0.47)(−0.53)
Banks0.003−0.05912.24 **0.0930.003−0.0750.0006.27 **0.0950.003−0.0710.0000.0010.2933.31 *0.102
(0.88)(−3.50) **(0.95)(−2.34) **(0.59)(0.89)(−2.81) *(0.47)(0.10)(0.89)
Note: This table presents the OLS regression for the Australian stock market sectoral performance during the COVID-19 pandemic from 26 January 2020 to 20 July 2020. The dependent variables are 17 the sectoral stock index returns ( RET i , t ) are regressed on two independent variables and two control variables. One-day lagged values of all independent and control variables are used in the models. t-statistics are reported in parentheses under their associated coefficients, **, and * indicate significance at the 1% and 5%, respectively.
Table 6. Result summary.
Table 6. Result summary.
Significantly Negative ImpactNegative ImpactNo Significant Impact
All market-cap indicesMaterials aHealth Care aGold
TechnologyMetals and Mining aFinancial excluding REITConsumer Staples
A-REIT bResources aBanksCommunication services
Consumer DiscretionaryUtilities Real Estate b
Industrials aEnergy
Information Technology
a Sectors are affected by the government interventions (using the GRI index).
b Sectors are exposed to the AUD/USD rate fluctuations.
Note: This table summarises the results from three regression models examining the Australian stock market performance during the COVID-19 pandemic from 26 January 2020 to 20 July 2020. The levels of impact of COVID on the sectors are classified into three groups according to the results of three models in Table 5: significantly negative impact (0.01 significance level), negative impact (0.05 significance level), no significant impact (statistically insignificant).
Table 7. Summary of the Australian government interventions during the COVID-19 pandemic.
Table 7. Summary of the Australian government interventions during the COVID-19 pandemic.
SchemeDescriptionDateSectors
First Home Loan Deposit SchemeThe package allows first home buyer to purchase a home with a deposit as small as 5% without needing to pay lender mortgage insurance. It guarantees to a participating lender up to 15 percent of the value of the property purchased that is financed by an eligible first home buyer’s home loan.
Source: www.nhfic.gov.au/what-we-do/fhlds/ (accessed on 15 January 2021)
1 January 2020Real Estate, Financial ex-REIT, Banks
Home Builder GrantIt is tax-free grant program to help the residential construction market to get through the Coronavirus pandemic. It will provide eligible owner-occupiers (including first home buyers) with a grant of $25,000 to build a new home or substantially renovate an existing home.
Source: www.sro.vic.gov.au/homebuilder-grant-guidelines (accessed on 15 January 2021)
4 June 2020Real Estate, Financial ex-REIT, Banks
COVID-19: Land tax relief for landownersStates and territory governments have announced a range of land tax measures:
  • Victoria: up to 50% reduction in land tax
  • New South Wales: 25% reduction in 2020 land tax for landlords of commercial and residential properties 25%
  • South Australia: up to 25% reduction in 2020 land tax
  • Western Australia: up to 25% reduction in 2020 land tax and interest-free payment arrangement and waive for late payment penalties.
  • Tasmania: deferral or payment arrangement for land tax in case of financial hardship
  • Queensland: up to 25% reduction in 2020 land tax
  • ACT: Land tax credit
  • Northern Territory: No land tax
Source: www.pitcher.com.au/land-tax-relief-landlords/ (accessed on 15 January 2021)
13 April 2020Real Estate
Coronavirus Small and Medium Enterprises (SME) Guarantee SchemeThis package provides up to $40 billions of lending to SMEs by guaranteeing 50 per cent of new loans issued by participating lenders. It also supports lenders’ ability to provide credit and ensure that SMEs benefit from low interest rates.
Source: treasury.gov.au/coronavirus/coronavirus-sme-guarantee-scheme (accessed on 15 January 2021)
23 March 2020 to 30 September 2020Financial ex-REIT, Banks
Relief for commercial tenantsIt includes temporary hold on evictions and a mandatory code of conduct for commercial tenancies to support small and medium sized enterprises (SMEs) affected by coronavirus.
Source: www.business.gov.au/risk-management/emergency-management/coronavirus-information-and-support-for-business/relief-for-commercial-tenancies (accessed on 15 January 2021)
29 March 2020Real Estate
Coronavirus (COVID-19): National Health Plan resourcesThe $2.4 billion package provides unprecedented support across primary care, aged care, hospitals, research and the national medical stockpile. It also includes $30 million for the Communication sector to support a national communications campaign across all media.
Source: www.health.gov.au/resources/collections/coronavirus-covid-19-national-health-plan-resources (accessed on 15 January 2021)
11 March 2020Healthcare, Communication
Note: This table presents the economic interventions of Australian authorities during the COVID-19 pandemic (From January 2020 to September 2020). The information is summarised from various the Australian government websites.
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Huynh, N.; Nguyen, D.; Dao, A. Sectoral Performance and the Government Interventions during COVID-19 Pandemic: Australian Evidence. J. Risk Financial Manag. 2021, 14, 178. https://doi.org/10.3390/jrfm14040178

AMA Style

Huynh N, Nguyen D, Dao A. Sectoral Performance and the Government Interventions during COVID-19 Pandemic: Australian Evidence. Journal of Risk and Financial Management. 2021; 14(4):178. https://doi.org/10.3390/jrfm14040178

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Huynh, Nhan, Dat Nguyen, and Anh Dao. 2021. "Sectoral Performance and the Government Interventions during COVID-19 Pandemic: Australian Evidence" Journal of Risk and Financial Management 14, no. 4: 178. https://doi.org/10.3390/jrfm14040178

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