Professor Christos Koulovatianos ( explores the characteristics of the Covid-19 crisis and its potential national implications

“No red alert in Luxembourg”

d'Lëtzebuerger Land vom 30.10.2020

D’Lëtzebuerger Land: At what stage of the crisis are we standing ? Is it a U, V, √, W, VW, WW, WWW?

Christos Koulovatianos : Please, allow me to add the letter L to this alphabet soup, the possibility of an absolute GDP drop that can be persistent for longer than a decade. Letter L has been the experience of the Greek economy after the 2008 crisis, the worst known economic outcome during peace times, exceeding the deep and prolonged “U” of Indonesia from 1997 to 2007 (Asian crisis).

That’s an economic forecast then…

Predictions are very difficult, but I will attempt one. Let us start from the hands-on experience of China: a quick V shape within one year. China’s approach to the covid-19 crisis was early and drastic lockdowns, taking deep economic losses in the beginning, but enabling a quick restart of its industrial economy. The Chinese data released on October 19, 2020, reveal another key feature: capital formation, investment, fueled most of the Chinese recovery. This investment was largely triggered by fiscal policies stimulating bank lending. Hoping that this data is accurate, China’s recovery is very good news for the global economy. Few other economic regions in the world have the structural economic features of China and fewer implemented China’s covid-19 policies. I therefore doubt whether we will see such an impressive recovery forming letters like V or W within such a short time-span elsewhere.

What about Europe then?

In Europe, most governments had late responses to the emergence of the covid-19 pandemic, experiencing longer and often less effective lockdowns. In addition, these lockdown responses have not been coordinated across EU member states. More importantly, different EU members have quite diverse structural economic features and fiscal resilience. The 2008 financial crisis exacerbated these differences among EU member states, which persist to date. For example, Greece, Italy and Portugal have very high fiscal debt/GDP ratios and their economies have high or substantial dependence on services exports like tourism. Now EU countries are in the second covid-19 wave, but more prepared to flatten the curve of intensive-care bed use. Yet, economic activity cannot be as vibrant. With the hope of covid-19 vaccines on the horizon, and taking into account the diverse features among EU members, I would say that EU-core economies are likely to experience V shapes (V’s with longer time-span than this of China), and EU periphery countries are likely to experience U shapes, depending on the percentage of company bankruptcies. In my opinion, core EU countries, like Luxembourg, are already climbing the recovery leg of the V shape. Periphery countries may stay down for a while. Economics Nobel laureate Bengt Holmström has a recent study with statistical evidence on strong seasonality of covid-19. According to this study, the virus may become a bigger challenge for Europe this winter. Therefore, W shapes (with less deep peak-to-trough second-wave legs), are possible, too.

There’s no L scenario then?

For the periphery countries, I do not predict an L shape. Yet, I want to emphasize that we must be alert in order to fully prevent any L shapes, especially for the large economy of Italy. In December 2020, investors must be prepared to hear dreadful debt/GDP-ratio numbers for EU periphery countries. The investor response to these announcements of official statistics by Eurostat should be calm, because the European Stability Mechanism (ESM) has put enough money on the table for dealing with high fiscal debts. Continued coordination among EU member states on securing these funds is important. More coordination among EU member states even on the lockdown strategies seems also important to me.

Is there a way out of this?

We must take a big lesson from China : investments. The covid-19 crisis gives us time to build new things. As ECB Governor Christine Lagarde has emphasized, it is time to speed up building our Green Investments in the EU. I think this direction is correct. With so low interest rates, boosting a publicly funded component of Green Investments is likely to stimulate various private investments in the EU. Such a cross-country EU policy would be quite beneficial for Luxembourg, the home of EIB and a place where private Green Investments already flourish. Therefore, the government of Luxembourg should promote this Green-Investments EU economic policy through its external-affairs experts and politicians.

Is this crisis comparable to any other in history?

All past crises had different causes. Yet, all crises can teach us a lot about today’s situation and risks. In severe crisis, a period of dysfunctional banking has similar effects to these of heart attacks on the human body. Dysfunctional banks block central channels of private funds to productive investments, leading to misallocation of resources, such as unnecessary company bankruptcies and very high unemployment. Most academic research by economists on covid-19 has focused on seeking lessons from the Spanish flu pandemic of 1918, which had four successive infection waves and many similarities to the covid-19 pandemic shock (up to the two first waves, so far). However, the fact that the First-World War was ending around 1918, does not allow us to assess the economic impact of the 1918 Spanish flu pandemic: it is difficult to separate the economic effects of war from the economic effects of the pandemic.

So far the banking sector has not been affected.

The covid-19 crisis is, thankfully, not similar to the severe 1929 and 2008 crises, because the banking sector is not directly involved. This non-direct involvement of banks means that the crisis does not have a systemic-risk component, a shock within the heart of the economic system. The covid-19 shock is an external shock, that obliges us to cease production temporarily, avoiding systemic risks through fiscal borrowing of some funds from the future. Nevertheless, it has been just twelve years after the 2008 crisis, and many western economies have accumulated quite high fiscal debt. Because bank regulation since 2010 has created balance-sheet buffers, my feeling is that banks will be resilient until a covid-19 vaccine slows down the pandemic. Yet, we must be concerned with highly indebted EU periphery states. EU member states should understand these fiscal risks and coordinate through optimally managing ESM funds.

What does the research in finance say?

While all crises are unique, there are common features and common lessons. All crises arrive as unexpected shocks, increasing the level of uncertainty, increasing the “unknown unknowns” factor. For example, in the summer of 2020, investors were not sure if there would be a covid-19 vaccine before a second wave, or the other way around. This additional uncertainty discourages investments. Yet, investments are the most crucial engines of a recovery. We therefore need to apply our policy lessons for stimulating investment. Today, thanks to the development of decision theory through robotics, we have a better understanding of decision-making and asset pricing under “unknown unknowns”. In addition, we live in times of developed financial markets, being able to measure the effects of this uncertainty through the outcomes of derivatives markets, such as the progression of the VIX index. Such measurements, combined with model simulations, tell us that big shocks, such as the covid-19 pandemic and lockdowns, can lead to misallocations. In the past few months, economists rapidly developed economic models of the pandemic (“SIR” models with forward-looking markets), incorporating the impact of lockdown expectations on asset pricing. These models can estimate the possibility of private-market failures that can lead to crises and serve as laboratories for assessing the role of fiscal and monetary policies.

Aren’t we approaching a contamination on the financial system?

I am happy to say that, so far, our data does not point at red alerts in Luxembourg. Nevertheless, it is too early to feel totally safe or relaxed. We are analyzing several databases, connecting many dots. The FNR-funded “Mortgage” project examines the potential impact of covid-19 on nonperforming mortgage loans, developing similar diagnostics to these used by medical doctors. The “Mortgage” team focuses on spotting socioeconomic groups that are likely to be stressed by mortgage obligations during a covid-19 shock, studying the economic interactions of these socioeconomic groups with the rest of the economy. It examines the pre- and post-covid-19 evolution of incomes in households with different occupations, linking these income changes to the home ownership profiles and loan-to-value ratios of these households. A highly specialized group from the University of Luxembourg collaborates with top Statec researchers in order to link data from new Statec surveys with past data from several databases. This task helps us measure quantitative differences across groups of households with different qualitative characteristics. Together with my PhD student, Maksim Nezhelskii, I am working on a simulated model that targets putting this detailed picture together through a model of different forward-looking households that trade assets, consumption goods, buy houses on mortgage loans, and service these loans.

What does the model say?

Importantly, house prices in this model are affected by the pressure that covid-19 lockdowns put on them. The model serves as a laboratory for studying two key issues. First, the model serves as a “stress test” laboratory, trying to spot households that might financially “collapse” first, due to covid-19 lockdown pressure or lack of sufficient government subsidies. Such unlucky households sell their houses at cheap prices, in order to survive financially (fire sales). Other households that are more unlucky may default on their mortgages (non-performing loans). Such a process, may lead to a big drop in house prices in the model. A big drop in house prices may affect the loan to value ratios in banks, putting pressure on the balance sheets of banks. So far, our simulations predict small slowdowns in house prices in Luxembourg. Yet, the model has the ability to detect conditions that may lead to a big drop in housing prices early. Second, the model serves as a policy laboratory, evaluating whether government policies for preventing the crisis have been sufficient, or whether there are better policies to be implemented in the future.

What would you look at as an investor in terms of economic aggregates?

Let me emphasize up front that the effects of lockdowns on the economy, are not a balanced aggregate shock. In our services-oriented economy, the lockdowns did not affect persons who could work from home as much as other persons in more social professions, such as restaurant owners, or hairdressers, etc. This simple example tells us that examining aggregates will not offer a complete or safe picture. Some aggregates can alert us to “elephants in the dark room”. Key problematic aggregates are fiscal debt/GDP ratios, non-performing loans of banks, stock prices of banks, and the relation of such aggregates to private investment and consumption of mostly durable goods (such as houses or cars). Yet, I must alert investors that, during the covid-19 crisis, the key is the evolution of these aggregates, not the observed levels of these variables at a given point in time. Having Eurostat announcing enormous debt/GDP ratios in this coming December, should not cause panic. The pandemic wave will pass, and a V-shape, even a U-shape GDP progression will improve such numbers vastly. Nevertheless, I would recommend hedging against investments in high fiscal-debt/GDP-ratio countries, keeping an eye on their banking sectors and on the EU policies announced for ensuring these countries through EU funds. Such announcements can turn investments in such countries into an opportunity after the covid-19 crisis.

This interview was made via emails

Pierre Sorlut
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