Brazilian banking cycle synchronization during COVID-19 crisis.
| Autor | Costa, Paulo Icaro |
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Introduction
Since the end of 2019, a respiratory disease identified in China has evolved into a truly global pandemic. More than two years later, society around the world continues to suffer the impacts of what can be seen as the biggest threat to public health issue since World War II. A first difference in relation to war is in the geographic distribution of deaths around the world. According to the WHO database, as of February 17, 2022, more than 416 million cases and 5.8 million deaths had been recorded in virtually all localities. Specifically in Brazil, there have been more than 27 million cases--more than 10% of the entire population--and almost 640 thousand deaths from COVID.
Regarding the consequences, on the one hand, we still need time, to be able to identify the differences between a pandemic and a war. On the other hand, we already know that the COVID-19 pandemic has had catastrophic effects in several areas in most countries, including the real economy. According to Goodell (2020), one of the first contributions on this issue, the main concerns arise from increasing costs for health systems, loss of job productivity, social distancing that disrupts economic activity, depressed tourism and impacts on foreign direct investment. With such a considerable impact on the real economy, the banking sector may be affected for instance by possible reflects on credit delinquency. Indirectly, banking liquidity may be impacted by expansionist fiscal and accommodative monetary policies implemented by authorities as a pandemic consequence.
In these 2 years of pandemic, the specific literature on the impacts on socioeconomic and financial variables is extensive. Possibly, one of the consensual aspects in this vast literature is that the current pandemic generates uncertainties that are strongly affecting the global financial markets. Considering only the first wave of the pandemic, for a broad panel of 64 countries, Ashraf (2020) finds that stock market returns declined as the number of confirmed cases increased and that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths.
More recently, Karamti and Belhassine (2022) analyze the connectedness between the COVID-19 pandemic and major financial markets within a wavelet framework, which enables them to identify the differences between the short and long run markets' reactions. In the short run, they find strong co-movements during the first and second waves of the pandemic. During the first wave, longer-term investors were driven by the belief of future pandemic demise, so it seems that they make use of time diversification that results in positive returns.
Considering that US became the COVID-19 epicenter, and its economic relevance, a large part of the literature has focused on studying the impacts in this country. Some relevant contributions are Baker et al. (2020), Sharif et al. (2020), Matos, Costa and da Silva (2021a), and Costa et al. (2022), for instance.
We add to the discussion of COVID-19 financial impacts, but we analyze the specific case of the financial sector of Brazil, one of the largest emerging economies. Concerning our choice, this country is a record holder among the emerging economies, from its first wave. To be specific, as of February 17, 2022, globally, Brazil presents the third highest number of cases behind the US and India, and the second highest number of deaths only behind US.
One of the most informative contributions about the pandemic in that country is Costa et al. (2021). They propose two empirical exercises. First, the purpose is to better understand the conditional relation between the stock market returns and COVID-19 series and, if any, which lead-lag conditions can be drawn, based on wavelet partial coherences and partial phase-differences After having showed how COVID-19 deaths and cases in different localities are related to returns on Brazilian stock index (IBOV), they study the presence of contagion and the pass-through among Brazilian economic sectors, based on returns on the Brazilian stock sectoral indices: Basic Materials (IMAT), Electrical Energy (IEE), Industrials (INDX), Consumption (ICON), Financials (IFNC), Public Utilities (UTIL), and Real State (IMOB).
Their main findings on the financial sector add to the discussion on the long and short run linkages among financial markets, suggesting the relevance of monitoring banking systems around the world during periods of health crisis, since this economic sector is one of the most vulnerable due to contagious effects. Banking crises are costly, and a great deal of prudential effort is undertaken to mitigate them. Bordo et al. (2001) estimate losses of around 6% of GDP due to banking crisis in the last quarter of the 20th century, while Laeven and Valencia (2013) report losses of about 30% of GDP during the Global Financial Crisis of 2007. According to OECD (2012), financial contagion shocks increase countries' risk of suffering an economic crisis: annual crisis probability is slightly above 1% without financial contagion and more than 28% in periods with financial contagion.
The COVID-19 has arguably fostered contagion, particularly on the financial sector (see, e.g., Akhtaruzzaman et al., 2021; Corbet et al., 2020; Matos, Costa and da Silva, 2021a; Costa et al., 2021). The theoretical related literature points out some reasons for the contagion mechanism in banking sector. The common lender assumption suggests the financial market imperfections as financial contagion source in turmoil periods. According to Kaminsky and Reinhart (2000), the transmission of shocks among countries may be associated with the fact that they share the same lenders. In this sense, a crisis that increases the default risk in one of debtor countries can cause a reduction in the services offers by lender for the other countries. Pavlova and Rigobon (2008) find out a considerable effect on market co-movements in periods where center's agents (lenders) face portfolio constraints. The liquidity problem is other financial contagion driver, and in this context, the turbulence in one country decreases the market value of the intermediaries' portfolio, generating a run for liquidity on the capital market (Jokipii and Lucey, 2007).
The initial turmoil may induce investor to sell off their holdings through the markets putting pressure on the international asset prices exacerbating the propagation mechanism of shocks. Finally, another stream of this literature concerns with the role of coordination view on the contagion path through. Calvo and Mendoza (2000) evaluates the effect of informational problem on investor behavior. They point that international information asymmetry can drive the removal of resources from investors across countries.
More recently during the pandemic period, this discussion has been promoted by Matos, Costa and da Silva (2021b). These authors revisit the discussion on banking system contagion by proposing a risk-based empirical analysis during the current pandemic period. They use daily returns on G7 banking sector indices from January 2015 to December 2019 (pre-pandemic), and from January 2020 to October 2020 (pandemic). Based on Value at Risk (VaR) ratio analysis, considering 21 possible pairwise combinations with the G7 financial indices, their findings suggest a stronger contagion between banking systems. Also, for G7 banking system, Matos, da Silva and Costa (2021) address contagion during the COVID-19 crisis using wavelet-based techniques. They find considerable increase in financial sector linkages--therefore, contagion--on the lowest frequencies during the pandemic period based on wavelet coherence analysis.
They still find that COVID-19 world cases and deaths are relevant to understand banking cycle co-movements, mainly from February to June of 2020. Their findings are confirmed by a statistical contagion test and still hold after controlling for oil prices.
In this paper, we add to this debate aiming to answer how the Brazilian banking sector has responded to the COVID-19 pandemic waves, based on the cases or deaths in the most affected countries, and in the world. We also provide results able to infer presence of contagion and describe the pass-through in the Brazilian banking sector.
In our first exercise we follow Aguiar-Conraria et al. (2018) by applying concepts as partial coherence and partial phase-difference to identify co-movements and lead-lag relationships between the financial index series and COVID-19 data. In the second exercise, we apply the same methods incremented by a time-frequency domain distance metric and granger causality to investigate banking sector behavior during the pandemic, particularly to infer contagion and drawn a pass-through.
We follow methodologically Matos, Costa and da Silva (2021a) by using Granger causality to draw a pass-through path between the banking stocks and to make a comparative static analysis considering these stocks before and after the pandemic. Forbes and Rigobon (2001) define contagion as a significant increase in cross-market links after a shock to an individual country (or a group of countries). Considering this definition, the Granger causality allied with the distance metric (Dissimilarity), approached in Aguiar-Conraria and Soares (2011a), give us insights about contagion inside the sector. Also, following Wu et al. (2020) we compare the intensity of the co-movements between the banks in the presence and absence of the COVID-19, extracting information about how relevant COVID-19 data is on the increase of co-movement.
Concerning the variables used, the health dataset is comprised of series of deaths and cases of COVID-19 in the most affected countries: US, Brazil, United Kingdom, Italy, and France. We also use data from China and its Hubei Province to allow analysis of early stages pandemic impacts. World data is...
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