Category Archives: Corona crisis

The cost of the second wave

Early December 2020, I presented my calculation of the expected cost of the corona crisis in Denmark, taking into account both economic and health-related costs (link). Since then, the situation has turned to the worse, and the expected cost of the crisis has increased by something like 50%. The calculation here is done for Denmark, but given similar types of waves in the US, the UK, and many other countries in Europa, I would expect similar types of consequences.

This graph shows the sad development in the number of people dying with corona in Denmark since March 11, 2020, on a daily basis.

Daily Covid-19 associated deaths in Denmark. Blue columns: March 11, 2020 through November 26, 2020. Red columns: November 27, 2020 through January 6, 2021.
Source: https://en.ssi.dk/.

The blue columns show the daily number of deaths up until November 26, 2020, when I did my initial calculation. The red columns show the numbers since then. From March through November, i.e. including the summer months when few people got infected, approximately 100 people died with corona per month. During the past six weeks, approximately 100 people died per week. During December, more people died with corona than during April.

Economic activity suffers

As a consequence of the dire situation, tough restrictions have been introduced: Max. five people are allowed to meet, people are working from home, “everything” (bars, restaurants, schools, universities, most retail shops, etc.) is closed, etc. Similar restrictions have been imtroduced in many other countries.

Because of the restrictions, economic activity suffers. Forecasts for economic activity have been revised.

In my calculation from early December, I used forecasts from the independent Danish Economic Councils (link). I used their “main scenario” from their autumn 2020 report. The Councils also published a negative scenario. Many economists, including the Council itself, and including myself by the way, now expect that this is a much more likely path for economic activity going forward.

Danish GDP forecasts.
Source: Danish Economic Councils

In their “main scenario”, the Councils expected GDP to fall by 3.6% in 2020, strongly rebound by 3.8% in 2021, and grow by 2.3% per year on average during 2021-2025. Now, a more likely path for Danish GDP is that it falls by 4.2% in 2020, grows by 1.5% in 2021 and by 2.5% per year on average during 2021-2025. In other words, due to the worsening of the situation since late November, the fall in economic activity during 2020 will probably be larger and, in particular, the rebound during 2021 will be smaller and delayed. Given that we start out 2021 in lockdowns, it is more reasonable to expect something like 1.5% growth in 2021, instead of 3.8%.

This figure collects the expected path of GDP without the coronacrisis (“Structural GDP w.o. corona”), the path expected in autumn, and the path that I and many other economists expect now (“Negative scenario”)

Danish GDP forecasts. DKK billion. Main and negative scenarios from Autumn 2020 projections vs. expected path of structural Danish GDP assuming no corona crisis.
Source: Danish Economic Councils

As is obvious from the graph, the expected reduction in GDP is just so much bigger now. More precisely, the expected loss in GDP due to corona (the reduction in GDP due to corona) is now app. DKK 400bn. This is basically two times the loss of economic activity expected just one month ago. This illustrates the costs of an additional wave of the coronacrisis.

Health-induced costs

Health-induced costs depend on the number of deaths, as described in my December blog post (link). In my December post, I assumed that the rate of deaths prevailing at the time of writing would continue for one more year. This was an assumption similar to the one used by Cutler & Summers for the US. This accumulated to 2100 expected deaths in total in Denmark. I argued that this was an aggressive assumption, given that I hoped vaccines were about to be rolled out, but it was the one used by Cutler & Summers, so I used that, too, such that I could compare costs for the US and Denmark.

Now, unfortunately, the assumption does not look that far off. During the past six weeks only, the number of deaths has increased by 75% in Denmark, from 800 to 1400. Given the severity of the current wave, and the slow roll-out of the vaccines, I do not feel comfortable changing my assumption with respect to the health-induced costs.

Updated expected cost of the crisis

This table collects my updated expected economic costs of the corona crisis in Denmark, together with my December expectation:

My estimate of the expected total cost of the crisis has increased from DKK 336bn to 536bn. This corresponds to 25% of pre-crisis Danish GDP, up from 16%. It also corresponds to app. DKK 90,000 per Dane (app. USD 15,000), compared with my best guess of DKK 60,000 per Dane in late November/early December (app. USD 10,000). In just six weeks, due to a terrible second wave of the corona crisis, the cost of the crisis has increased by something like 50% on a per-capita basis.

Conclusion

Obviously, there is a lot of uncertainty surrounding calculations such as these. The mere fact that six weeks of new data can change the economic outlook so much bear this out. Also, I use forecasts from the independent Danish Economic Councils. I expect all forecasters to agree that the economic outlook has turned to the worse, but exactly how much probably differs from forecaster to forecaster.

It is good with one number, DKK 536bn, as we then have something to remember and compare with. With so much uncertainty, on the other hand, we should not be surprised if the final cost will differ from this forecast. In general, whether we talk about forecasts of costs of crises, general economic forecasts of GDP, interest rates, exchange rates, or whatever, it is seldom that forecasts are spot on.

Forecasts such as these help us, though, to understand the magnitude of the crisis. The cost of the crisis (in Denmark) will be in the hundreds of billion Danish kroner. Of this, I am confident. Right now, I believe that something like DKK 500bn, or 25% of GDP, is a good estimate. This estimate might change, but I am reasonably confident that the cost of the crisis will end up being measured in double-digit percentages of GDP. This is the important take-away, not the exact number.

Given these high costs, we should do everything possible to try to reduce them. In particular, the faster vaccines are rolled out, the better. What is difficult to comprehend, I think, is that measures to expand vaccine production capacities were not taken in autumn, when everybody could see that the vaccines were on their way (e.g., by licensing production of vaccines to factories with spare production capacity, etc.). I thus cross my fingers that the rate of vaccination will increase significantly within a not too distant future, thereby helping to contain the otherwise very high cost of this crisis. A Danish newspaper had this cartoon yesterday, link, showing me arguing for the importance of a fast rollout of the vaccines.

2020

It’s this time of the year. This post recalls events of 2020. It has been such an unusual year, so different from what we expected. Luckily, there seems to be light at the end of the very long and dark tunnel, and – I hope – that 2021 will be considerably more joyful than 2020.

2020 started out so well. The roaring twenties and all that. Wuhan was a city I had not heard of, corona a beer people tell me is best served ice-cold with a slice of lime (I do not drink beer, tough I do enjoy wine), and social distancing words we would only get to know too well. Today, we know that Wuhan is a Chinese city with more than eleven million inhabitants and a marketplace where it presumably all started, corona also means something terrible, and social interaction is an activity we have come to miss so dearly.

At the time of writing, app. 75 million cases of corona/COVID-19/SARS-CoV-2 have been confirmed globally and app. 1.7 million people have passed away because of corona. Most countries have been in lockdowns, many still are (again), and the social and economic costs of the crisis have been enormous.

I started this blog in April 2020. This had nothing to do with corona. I had wanted to set up a blog for some years (people ask me where I find time for this, and I really do not know, but seemingly I simply like writing economic stories and analyses). Starting the blog in April this year, however, naturally implied that many of the blog posts have dealt with various economic and financial aspects of the pandemic. In this post, I will review some of the learnings from 2020.

The worst recession on record. With the highest growth rate on record

The recession started in February 2020 in, e.g., the US. Initially, it was caused by a supply shock: lockdowns were imposed and firms could not sell their goods and services and households could not go shopping. In April, when the IMF released their Spring Outlook, they labelled it “The Great Lockdown”. This was a suitable label. The IMF also noted that “This is a crisis like no other” and that “many countries now face multiple crises—a health crisis, a financial crisis, and a collapse in commodity prices, which interact in complex ways”. As unemployment and bankruptcies increased, households and firm got nervous, and demand suffered, too.

The path of economic activity has been highly unusual. This graph shows the quarterly percentage changes in US real GDP since 1947:

Quarterly percentage changes in US real Gross Domestic Product. 2020 encircled.
Source: Fed St. Louis Database

2020 is very much an outlier. On average, from 1947 through 2020, real GDP has grown by 0.8% per quarter. Until 2020, quarterly growth had never exceeded 4%. Economic activity had never contracted by more than 2.6%. Then came the Great Lockdown. During the second quarter of this year, economic activity contracted by 9%. This is almost four times more than the otherwise worst contraction on record. In this sense, it was the worst recession ever.

It has also been the weirdest recession ever. During this recession, we have also witnessed the highest growth rate on record: economic activity expanded by 7.4% during Q3. This is twice as much as the otherwise highest growth rate on record.

This puzzling feature of the recession led me wondering what a recession really is (link). I expressed sympathy with members of the NBER Recession Dating Committee. They face a particularly difficult task this year. Should they conclude that we had one V in spring, with the recession ending in late April, and then a new V now, i.e. two separate Vs (VV), or that we have had one long recession with a double dip, i.e. a double-V (W)? Does it make sense to call it a recession when we experienced the fastest rate of growth in economic activity on record? If you conclude that the economy cannot be in recession when it expands at its fastest growth rate ever, then you must conclude that the recession ended during Q2. But, the NBER Recession Dating Committee has not called the end of the recession yet, i.e., officially, the recession is still ongoing.

You may ask why it is important to know whether the recession ended in April or whether it is still ongoing. The development in economic activity is what it is, whether we call it recession or not. It is important because a “recession” is such an important concept in economics. We inform the public, business leaders, students, and others about the characteristics and consequences of recessions. If a recession can contain the by-far strongest expansion of economic activity on record, we need to change our understanding of recessions.

The very unusual behavior of economic activity during Q2 and Q3 caused very unusual, and scary, developments in unemployment and related aspects of economic activity. This graph shows the monthly change in the number of unemployed in the US:

Monthly changes in the number of unemployed in the US. Millions. 2020 encircled.
Source: Fed St. Louis Database

During March, unemployment in the US increased by 16 million. Again, this was beyond comparison. Until March 2020, the number of unemployed had never increased by more than one million over one month. In March 2020, it increased by 16 million.

As the virus contracted during summer, unemployment fell. There has never been as fast a reduction in the number of unemployed as the one occurring during this summer. In May, the number of unemployed dropped by more than three million. Until May 2020, the number of unemployed had never fallen by more than one million over one month. In May 2020, it fell by more than 3 million. So, within a year, we have had the strongest-ever increase in unemployment, but also the largest-ever fall in unemployment. By far.

Such dramatic events happened all around the world. I documented this here (link) and here (link).

Inspired by these events, I did something admittedly nerdy. I calculated the probability that we would experience events such as these, given the historical data (link). I found the unconditional likelihood that we could see the increase in newly registered unemployed that we saw in spring to be 0.97 x 10^(-841). This is a zero followed by 841 zeroes and then 97. For all practical purposes, this is a zero-probability event. But it did happen. It was just very, very unusual.

The stock market

I use some of my time (a significant part, by the way) to try to understand the stock market. This has not been a straightforward task this year.

Today, the global stock market is 13% percent above its January 1 value, the US stock market is 18% higher, and the Danish stock market 29% higher (MSCI country indices). Given that we have been through the worst recession ever, and that the recession is not officially over yet, this is not what one would have expected prior to the events.

Then, on the other hand, in hindsight it is perhaps not so strange. The recession has been the worst on record, yes. But, we have also had the fastest growth in economic activity on record. I argued (link) that if we imagine that the recession ended in late April, when economic activity bottomed out, the behavior of the stock market fits perfectly well with the historical evidence on the behavior of the stock market.

Central banks have certainly played their role, too. When markets melted down in March, central banks intervened heavily. In contrast to the financial crisis of 2008, it was not banks that were in trouble this time, but firms. Firms could not sell their goods and services due to the lockdown. The limitless purchases of government bonds that central banks have become used to during and after crises thus probably did not do much good (evidence came out that central bank purchases of government bonds are less effective than we are often told, link ). What turned things around, instead, was the announcement on March 23 that the Fed would facilitate credit to firms (link). This was a new policy tool. It led to a complete turnaround of events. I produced this graph (I still think it is a supercool graph): 

Difference between yields on ICE BofA AAA US Corporate Index and 3-month Treasuries (Left hand axis) as well as the SP500 inverted (Right hand axis). Both series normalized to one on January 2, 2020. Vertical line indicates March 23.
Source: Fed St. Louis Database

The graph shows how the stock market lined up with credit spreads. Firms were suffering, and their credit spreads started widening, in late February. The stock market suffered. The Fed announced it would provide credit to firms on March 23. Credit spreads tightened. The stock market cheered. The graph summarizes how the Fed saved credit and equity markets. And, strikingly, the Fed did so by merely announcing they would intervene. Up until today, the Fed has not intervened a lot. In this sense, it was a “Whatever it takes moment of the Fed”.

It should be mentioned that the Fed announced other initiatives on March 23, too, such as the Main Street Lending Program (link) and the Term Asset-Backed Securities Loan Facility (link). The Corporate Credit Facilities were the ones that directly targeted corporate bonds, though. Due to the nature of this crisis, the stock market lined up with credit spreads during this crisis, as the above graph reveals, emphasizing the importance of the announcement of the Corporate Credit Facilities.

Eurozone troubles, or rather no Eurozone troubles

The fact that we have not had to talk a lot about the risk of a Eurozone breakup since summer has been a positive surprise. In spring, there was talk about the risk of a Eurozone crisis. Like so often before, Italian sovereign yields rose relative to German sovereign yields. There was reason to be anxious. I argued that “Some kind of political solution at the EU level would be needed” (link).

This we got. The European Union agreed on a “Recovery and Resilience Facility” (link) that includes both loans and grants. EU has moved one inch closer towards a common fiscal policy. Who will pay is not clear, but EU has shown solidarity. I believe this is positive. At the same time, the European Central Bank continued its interventions and bought a lot of Italian debt. This has kept yields on sovereign bonds low. Here is the Italian-German yield spread during 2020:

Italian yield spread towards Germany. Ten-year government bonds. Daily data: January 2, 2020 – December 21, 2020.
Data source: Thomson Reuter Datastream via Eikon.

Italian yields have been falling continuously since summer, when the EU agreed on its recovery plan. It is positive that we have not had to discuss Eurozone troubles. We have had so many other troubles. Whether this means that we do not have to discuss Eurozone troubles again at some point, I am less sure. But, that is for another day.

Banks have been doing OK

The risk of a Eurozone breakup did not materialize. Another risk that did not materialize was the risk of systemic bank failures. This is positive as well, as economic activity suffers so much more when banks run into trouble and credit consequently does not flow to its productive uses.

During the worst days in March, stress in the banking system intensified. For instance, the spread on unsecure interbank lending increased relative to secure lending:

The TED spread. Difference between 3-Month USD LIBOR and 3-Month US Treasury Bills. Daily data: January 2, 2000 – December 14, 2020. 2020 encircled.
Data source: Fed St. Louis Database.

Stresses lasted only a few days, though. During the financial crisis in 2008, on the other hand, spreads remained elevated for much longer. This time, trust in the banking system was quickly reestablished.

I think I am allowed to claim that this was one of the predictions I got reasonably right. In autumn 2019, when nobody knew about the upcoming crisis, I wrote a policy paper on the Nordic financial sector. It was presented in December 2019 and finally published in June this year (link). I argued that banks are safer today, compared to 2008. Some doubted my conclusion and said, “just wait until the next crisis, then you will see that banks are not safer today”. Well, few months later we had the worst recession ever. Luckily, though, we have not had bank-rescue packages and we have not had to bail out banks. Banks have been withering the storm. In some instances, banks have even been part of the solution by showing flexibility towards troubled firms. I am not saying everything is perfect, but I am saying that the situation has been very different from the situation in 2008. On a personal note, this made me happy, too, as it would have been somewhat embarrassing if banks had failed at the same time I published an analysis arguing that the banking sector is safer. This, luckily, did not happen. Instead, the banking system turned out to be far more resilient than in 2008, as I predicted.

You may add that the Fed rescued markets during spring, as mentioned above, and thereby rescued firms and subsequently banks. True, but there was certainly also tons of rescue packages in autumn 2008. Banks nevertheless failed in large numbers in 2008. They did not this time around. Perhaps, thus, we did learn something from the financial crisis of 2008, and have gotten some things right. This would be no small achievement.

US election and Brexit

There have been other events, for instance the US election and Brexit negotiations. In normal years, such events would potentially have been among the most important events for markets and the economy. This year, the pandemic has certainly been more important. I did manage to write a post on the US election and the stock market, though (link). I discussed evidence that stock markets perform better under Democratic presidents. Only time will tell whether the same will happen under Biden.  

I did not manage to find space to discuss Brexit, but we got a trade agreement on Dec. 24 (link). Hopefully, the EU and UK can now move on.

The cost of the crisis

It is impossible to summarize the pandemic in one number or one word. Hence, I will not attempt to do so. But, I did present a calculation of the expected cost of the crisis in Denmark (link). I arrived at DKK 336bn, or app. USD 10,000 per Dane. This calculation generated some attention in Denmark.

One can discuss every single assumption one needs to make when calculating the expected cost of a crisis: What is the value of a statistical life? What is the value of a statistical life of those who pass away due to COVID-19, i.e. who are typically above 80? What is the past loss as well as the expected future loss in economic activity due to the crisis? Does it make sense to present one number when there is so much uncertainty? And so on. These are all fair points, but if we want to have a meaningful discussion of the impact of the crisis, we have to start somewhere.

In my calculation, I closely followed the assumptions of Cutler & Summers, such that US numbers and Danish numbers can be compared. This allowed me, for instance, to conclude that the cost of the crisis in Denmark, most likely, will be much lower than the cost of the crisis in the US.

Conclusion

I must admit I find it difficult to end this last post of 2020 on a happy note. Right now, at the time of writing, the situation is bad in the country I live, Denmark, and in many other countries in Europe and around the world. Numbers of new cases and deaths have been rising recently, or are on the rise again, and more and more restrictions and lockdowns are being imposed. Days are grey and short. The crisis has already been tremendously costly and it is clearly not over yet.

Nevertheless, I will try to end the post on a positive note. It gives me hope that several countries have started vaccinating people, and it seems to be working well. Finally, the EU also starts vaccinating people now. This has taken way too long, however, given the severity of the crisis and the fact that other countries started weeks ago. And, yes, every day counts. If it is correct, though, and I deliberately write if, that the EU has failed when it comes to the approval process and purchase of vaccines, as the normally well-informed and serious magazine Der Spiegel claims (link), it is a scandal. Biden aims to vaccinate 100m Americans within his first 100 days in office (link), close to a third of the US population. As things look now, it seems unlikely that we will be able to achieve the same in Europe. Christmas is all around us, though, so let us hope that somehow things will develop in the right direction.

Therefore, let me focus on the bright side. With the jabs, the situation will most likely start to improve within a not too distant future. I will try to convince myself that I see weak light at the end of the long and dark tunnel, even when we probably have to wait many months before things really calm down. Days are at least getting longer. I will focus on this, then.

With this, which is meant to be a positive message, let me thank you all for reading this blog and for sending me many encouraging mails with feedback. Please keep on doing so – it is highly appreciated.

I conclude by expressing hope that next year will be considerably more joyful than the one we leave behind.

Happy New Year!

The cost of this crisis

The corona crisis has caused a loss of economic activity. To calculate the total economic cost of this health-induced crisis, we must factor in health-related costs. Based on calculations for the US by Cutler & Summers, this post calculates the economic cost of the crisis in Denmark. Many uncertainties surround such calculations, and I discuss those. It seems a robust conclusion, though, that the cost of the crisis in Denmark will be considerably smaller than the cost of the crisis in the US. The broader implication of this result is that there is considerable variation across countries in the economic cost of the pandemic.

Economic activity suffered dramatically during spring, and it will take time before economic activity has recovered to its pre-crisis growth trend. In addition to the loss of economic activity, we must take into account health-related costs, if we want to estimate the total economic cost of the crisis. This is no easy task. Inevitably, it will be based on a number of assumptions. In a recent Journal of the American Medical Association article, Harvard University Professors David M. Cutler and Lawrence H. Summers (link, link) present a calculation of the total economic cost of the corona crisis in the US. Their calculation takes into account both the cost of lost economic activity as well as the economic value of premature mortality, the economic value of health impairments, and the economic value of mental health impairments.

Cutler & Summers (CS) find huge economic costs of the corona crisis in the US. They estimate the economic cost at USD 16 trillion. This is 90% of US GDP. This exceeds the cost of the financial crisis in the US by a wide margin, Cutler & Summers argue.

This post presents the first calculations of the cost of the crisis in Denmark. I follow the procedure of Cutler & Summers, but use Danish data. Knowing results from other countries, we will be able to better judge whether results for the US are globally representative.

I stress that these are first calculations and that uncertainties surround them. But, if we want to have a meaningful discussion of the cost of this crisis, we have to make assumptions, and then discuss their robustness. I do so.

Lost GDP

The first component of the calculation of the economic cost of the crisis is loss of economic activity. CS look at forecasts for US Gross Domestic Product from the Congressional Budget Office right before the crisis and compare it with the latest forecasts. The difference is the loss of economic activity. CS calculate a loss of USD 7,600bn. This corresponds to 35% of US pre-crisis GDP.

In Denmark, the Danish Economic Councils publish independent forecasts for Danish GDP. In their latest autumn 2020 report, the Councils publish figures for the expected development in structural Danish GDP, had there been no corona crisis. They also estimate expected GDP as of now. The results are here:

Danish GDP forecasts. DKK billions. Autumn 2020 forecast (“GDP”) vs. expected path of structural Danish GDP assuming no corona crisis.
Source: Danish Economic Councils

The difference between now-expected GDP developments and expected GDP developments without the corona crisis is the loss of Danish economic activity due to the crisis. This amounts to DKK 214bn (app. USD 40bn) for the years between 2020 and 2024, when Danish GDP is assumed to have recovered to its without-corona crisis structural trend. This loss of economic activity corresponds to approximately ten percent of Danish 2019 GDP.

One reason why the loss of economic activity in Denmark is expected to be considerably smaller than the loss in the US (10% in Denmark vs. 35% for the US) is that the Congressional Budget Office (CBO) expects the loss of economic output to persist in the US. CS reproduce this figure from the CBO:

US GDP forecasts. July 2020 forecast vs. January 2020 forecast.
Source: Cutler & Summers (2020).

Even ten years out, in 2030, US GDP is expected to be lower than its pre-crisis expected growth path. This is different in Denmark. In Denmark, the most recent forecast indicates that economic activity will have recovered in 2024. This reduces the loss of GDP in Denmark, relative to the US.

Cost of premature mortality

Deaths add to the economic cost of the crisis. CS note that 190,000 Americans had passed away due to Covid-19 by late September 2020. This is 0.06% of the US population.

In late September, when CS wrote their report, 5,000 Americans passed away per week as a result of Covid-19. CS expect this to continue for another year, i.e. an additional 260,000 deaths. CS estimate excess non-Covid-19 deaths at 40% of Covid-19 deaths. This means 1.4 x 450,000 = 625,000 American deaths.

In the US, a statistical life is estimated at USD 10m. CS reduce this by 30% to be conservative. All in all, this results in an economic costs of USD 4.4 trillion due to premature mortality. This is 20% of US GDP.

In Denmark, 816 have passed away as a result of COVID-19, at the time of writing this post (early December). In late September (to compare with the CS US figures), 650 had passed away. This is 0.01% of the Danish population.

This figure shows daily deaths due to Covid-19 in Denmark since March 2020:

Daily Covid-19 associated deaths in Denmark.
Source: https://en.ssi.dk/.

During the last couple of weeks, around 25 Danes have passed away because of Covid-19. Assuming, like CS, that this will continue for another year, this accumulates to 1,300 additional deaths. Assuming 40% excess non-Covid-19 deaths, like CS, results in 2,900 deaths over the next year.

In Denmark, a statistical life is estimated at DKK 34m (link). This corresponds to app. USD 5m. In other words, the value of a statistical life in Denmark is only half the value of a statistical life of an American. To be conservative, like CS, I use 70% of this. This gives an economic cost resulting from premature deaths of DKK 79bn. This is around 4% of Danish GDP. I.e., again, the loss in Denmark seems to be considerably smaller than the comparable loss in the US (4% of GDP vs. 20% of GDP). This is because fewer Danes are expected to pass away because of Covid-19 and because the value of a statistical life is assumed to be considerably smaller in Denmark.

Health impairments

Some of those surviving Covid-19 will face significant long-term health complications. CS mention that there are approximately 7 times as many survivors from severe or critical Covid-19 diseases as there are Covid-19 deaths, and that a third of these will experience long-term complications. CS assume that the cost of this is 35% of a statistical life and that it lasts for one year. This adds USD 2.6 trillion, or 12% of US GDP.

In Denmark, using the procedure of CS, expect 2,100 deaths, as mentioned above. This means 4,900 individuals with long-term health impairments over the next year. Assuming that the complications last for one year, and assuming an economic cost of complications of 35% of a statistical life, this means an economic loss of DKK 41bn, or 2% of GDP. Notice, like CS, I use the conservative value of 70% of a statistical life, i.e. 35% of 0.7 x 34m.

Mental health impairments

Many people get anxious or fell depressed during the pandemic. This could be because people need to isolate at home, and thus face loneliness, because of fear of losing your job, i.e. economic insecurity, fear of contracting the virus, etc. CS report that 40% of American adults have reported symptoms of depression or anxiety during the corona crisis. Normally, CS report, 11% of Americans report these symptoms. CS report that previous studies evaluate the one-year cost of depression and anxiousness at USD 20,000 per case. This amounts to an additional cost of USD 1.6 trillion, or 7.5% of US GDP, for the corona crisis.

In Denmark, we do not have official data on the number of people feeling anxious or depressed during the corona recession. What we do have, on the other hand, is the comprehensive health report of the Danish population from 2015 that also estimates the economic costs of a number of diseases in Denmark (link).

This report mentions that 136,000 Danes suffer from anxiousness and 91,000 from depression (in 2012). In total, around 4% of the Danish population. The report calculates an aggregate cost of lost economic activity of DKK 8.6bn for anxiousness and DKK 3bn for depression, primarily as a result of early retirements. These costs relate to 2012. Since then, inflation has been 7% in Denmark, i.e. the 2020 value is DKK 12.4bn (app. USD 2bn), assuming the same number of depressed and anxious individuals. CS assume an almost fourfold increase in the number of individuals facing depression and anxiousness because of the corona crisis. Given that this number is associated with a large degree of uncertainty in Denmark, and because one might hope that many people will recover, as this is a temporary crisis, such that not all of them will enter into early retirement, I double this number (in contrast to CS who assume a fourfold increase). I.e., I assume that the economic cost of mental health impairment amounts to DKK 24bn (app. USD 4bn), or app. 1% of Danish GDP.

Total costs

In total, taking into account the loss of economic output as well as health costs, reflecting both premature deaths, long-term health impairments, and mental health impairments, the economic cost of the pandemic in Denmark amounts to DKK 336bn, or 16% of Danish GDP:

This corresponds to approximately DKK 60,000 per Dane (app. USD 10,000). For a family of four, this means that the economic cost of the crisis is app. DKK 240,000 (app. USD 40,000).

Implications

A number of implications follow from these calculations:

  • A cost to society of 16% of GDP is an enormous cost.
  • With this in mind – that a 16%-GDP cost is enormous – it also follows immediately, on the other hand, that the cost of the pandemic in Denmark is considerably smaller than the cost of the pandemic in the US. CS find, as mentioned, that the cost of the pandemic in the US will amount to 90% of US GDP. For Denmark, I find it will be 16% of Danish GDP. This implies that there is considerable variation across countries in the expected cost of the pandemic. Or, in other words, that it would be a mistake to assume that the cost of 90% GDP found for the US is a globally representative figure.
  • There are several reasons why the cost of the pandemic is considerably lower in Denmark:
    • Danish GDP is expected to recover faster than US GDP. Danish GDP is expected to have recovered in 2024. On the other hand, US GDP is not expected to recover (reach its pre-crisis growth trend) within the next ten years. This implies a larger negative effect of the pandemic on the US economy.
    • Fewer individuals have passed away in Denmark due to the pandemic. In late September, 0.06% of the US population had passed away. In Denmark, “only” 0.01% had passed away. This reduces the cost of premature mortality in Denmark.
    • The value of a statistical life is lower in Denmark. According to CS, in the US, it is USD 10m. In Denmark, it is USD 5m. This also reduces the cost of premature mortality in Denmark.
    • The numbers indicate that fewer people in Denmark will face health impairments, compared to the US. This also reduces the economic costs in Denmark, compared to the US.
  • CS find that the cost of the pandemic exceeds the cost of the financial crisis by a large margin. In 2012-2013, I chaired the official committee investigating the causes and consequences of the financial crisis in Denmark (link). We found that the financial crisis – at the time of writing the report in 2013 – had caused a DKK 200bn reduction in GDP. In 2008, when entering the financial crisis, Danish GDP was DKK 1,800bn, i.e., the accumulated loss up until 2013 amounted to 11% of pre-financial crisis GDP. Given that Danish GDP had not recovered to its pre-crisis trend in 2013, the final loss of the financial crisis is larger. It seems that the economic cost of the financial crisis and this pandemic will be, more or less, equal.

Uncertainties and assumptions

Many uncertainties surround the calculations presented above. In this section, I discuss some of them and their consequences. Notice as a starter, though, that by relying on the assumptions of CS above, I am able to compare results for Denmark with results for the US. If using other assumptions than CS, this is less straightforward. This – that it is easier to compare across countries when using the same underlying assumptions – is an argument for using the CS assumptions. Nevertheless, to see how sensitive results are, let us discuss what happens if using other assumptions.

Will Danish GDP have recovered in 2024, as the Danish Economic Councils expect? If not, the cost will be higher. If sooner, the cost will be lower.

Will 25 Danes pass away per week over the next year? This seems like a high number these days, given that we expect vaccines to be ready within the next few weeks. If “only” 650 (i.e. half the assumed number in the base-line calculations) additional Danes pass away, the cost of premature mortality will be reduced from DKK 71bn to DKK 49bn, and, all other numbers equal, the total cost will be reduced to DKK 300bn, or 14% of GDP. I.e., the baseline calculation is reasonably robust towards this adjustment.

The cost of mental health impairments in Denmark is associated with considerable uncertainty in this calculation, as we do not have official numbers for how Danes have been affected by depression and anxiousness during this pandemic. The overall baseline calculation is reasonably robust towards this number, though. For instance, I double the 2012 number in the baseline calculation. If I multiply with three, i.e. assume even more people are affected by mental health challenges, the total cost increases from 16% of GDP to 17% of GDP.

Finally, I, like CS, assume that the cost of premature deaths is 70% of the value of a statistical life. More than half – 52% – of Covid-19 related deaths in Denmark have been above 80 years old. Even when I, like CS, mark down the value of a statistical life by 30%, the number might still seem high. Reducing this further would of course lower the total cost of the pandemic marginally.

Conclusions and policy implications

This post presents first calculations of the expected economic cost of the Covid-19 pandemic in Denmark. Taking into account the direct effects on GDP, as well as the economic value of premature deaths and health consequences, I expect the economic cost of the pandemic to be 16% of Danish pre-crisis GDP. The calculation is based on a number of assumptions, but the overall figure seems robust to reasonably variations in these assumptions.

Harvard Professors Cutler & Summers expect that the cost of the pandemic in the US amounts to 90% of US GDP. The cost in Denmark will most likely be considerably smaller. Only a fifth of the cost in the US. This is due to a faster economic recovery in Denmark, a lower number of deaths in Denmark, a lower value of a statistical life in Denmark, and lower associated health costs. This large difference between the US and Denmark implies that there is considerable cross-country variation in the cost of the pandemic.

Cutler & Summers argue that the cost of this pandemic will exceed the cost of the financial crisis in the US. In Denmark, it seems that the cost of this pandemic will correspond, more or less, to the cost of the financial crisis.

Even when the cost of the pandemic in Denmark is considerably lower than the cost in the US, the cost is still enormous. 16% of GDP is a very large figure. For a family of four, it corresponds to DKK 240,000 (app. USD 40,000).

When the cost is high, it becomes even more important to roll out vaccines as fast as possible, as soon as health authorities have approved them. Call in retired doctors, call in retired nurses, use all available working personnel, and pay them all handsomely to work 24/7 in order to vaccinate as many as possible as quickly as possible, from a health perspective and an economic perspective. This will help contain the already very high cost of this pandemic.

VV or W: When did (or does) this recession end?

This corona recession started in February 2020. Officially, it is still ongoing. But, perhaps, it has in fact already ended. This might seem confusing but it helps explaining the performance of financial markets during this “recession”.

In my soon-to-be-released book From Main Street to Wall Street (link and link), I – among many other things – carefully examine the historical relation between the business cycle and financial markets. I verify that stock markets typically perform considerably better during expansions than recessions. In the book, I examine and explain why this is so. I also explain that this is not a bulletproof finding. It is not always so. Sometimes stock markets do fine during recessions. Is this recession one of them?

This recession

In the US, the Business Cycle Dating Committee (link) determines peaks and troughs in US economic activity. On June 8, 2020, the Committee announced that:

“The committee has determined that a peak in monthly economic activity occurred in the US economy in February 2020. The peak marks the end of the expansion that began in June 2009 and the beginning of a recession. The expansion lasted 128 months, the longest in the history of US business cycles dating back to 1854.”

This means that this recession started sometime in February 2020. It also means that the expansion preceding this recession became the longest on record.

The Committee has not declared the end of this recession yet. Officially, the US economy is still contracting, with the caveat that the Committee determines business-cycle turning points with a lag. E.g., it was in June only that the Committee concluded that the recession had started in February.

How has the stock market performed during this recession? As readers of this blog know, it has performed well since March 23 when the Fed had is “Whatever it takes moment” (link). During this recession, the US stock market has returned 10% up until today (total return on the MSCI USA index). This is particularly noteworthy in light of the fact that this recession has been unusually severe (link and link).

Perhaps the recession ended in April

This corona recession is special. Usually, recessions are caused by some economic imbalances that need to be corrected, such as an overvalued housing market or an implosion of the financial sector. This is not the case here. This recession was caused by the sudden arrival of a virus. The sudden arrival of the corona virus caused a sudden shutdown of economic activity.

The Business Cycle Dating Committee has traditionally relied on aggregate economic data when determining turnings points in the business cycle. Aggregate data, such as industrial production, GDP, etc., are available at the monthly or quarterly frequency. Given the underlying cause of this recession, which led to the closure of business activities from one day to the next, we need to look at higher-frequency data when searching for turnings points in economic activity.

One interesting new higher-frequency indicator is the Weekly Economic Index developed by the New York Fed (link). It summarizes information in ten weekly indicators of real economic activity. It is designed to track the four-quarter growth rate of real GDP. As the St. Louis Fed notices (link) ”This series is potentially a useful indicator to watch because James Stock (one of the authors of the study developing the index) is a member of the BCDC (Business Cycle Dating Committee).”

The interpretation of the index is that it is “scaled to the four-quarter GDP growth rate; for example, if the WEI reads -2 percent and the current level of the WEI persists for an entire quarter, one would expect, on average, GDP that quarter to be 2 percent lower than a year previously.” The Weekly Economic Index is available since January 2008:

FRED Graph
Weekly Economic Index for the US economy.
Source:
Fed St. Louis Database.

The index tracks the financial crisis well. In particular, as the figure shows, it bottoms out in Q2 2009 when the recession ended.

The indicator also tracks the beginning of this recession well. It fell like a stone from a rock when the recession started in February.

The interesting point here is that the indicator reaches its bottom during the last week of April 2020. I.e., if a recession ends when this indicator bottoms out, as in 2009, this recession ended in late April.

The idea that this recession ended in late April would also be consistent with the observation that US real GDP dropped dramatically from the first to the second quarter of 2020, and rebounded strongly from the second to the third quarter:

Quarterly percentage changes in US real Gross Domestic Product.
Source: Fed St. Louis Database

What about international evidence? I am not aware of a well-designed index that tracks, e.g., Eurozone economic activity at the weekly frequency. So, as an alternative when looking at data from other countries than the US, let us consider industrial production. Industrial production is a traditional business-cycle indicator. It is available at the monthly frequency:

Indices of industrial production, normalized to one in January 2019, for the US and the Eurozone.
Source: Fed St. Louis Database and Thomson Reuter Datastream via Eikon.

For the US, industrial production bottomed out in April, like for the weekly indicator above. The collapse in Eurozone industrial production is much larger than in the US, but the timing is the same. Also for the Eurozone, industrial production bottoms out in April. So, perhaps this recession really ended in April.

The stock market and the recession

Typically, stock markets tank during the early phase of a recession, and starts rebounding when the end of the recession is in sight, i.e. before the actual end of the recession. Furthermore, the stock market normally does well during the early phases of expansions.

This graph splits the cumulative return on the US stock market into a mid-February (start of recession) to late April (assumed end of recession) period, in red, and a period thereafter, in green:

Total return index for MSCI USA, normalized to one mid-February 2020. Daily data. Red line indicates assumed recession. Green line indicates assumed early phase of expansion.
Source: Thomson Reuter Datastream via Eikon.

If we decide that this recession ended in late April, instead of assuming that the recession is still ongoing, the behavior of the stock market makes perfect sense. In this case, the stock market lost 14% during the recession. Since May, i.e. since the assumed end of the recession, the stock market has gained 27%.

Zooming in on the correlation between the Weekly Economic Indicator and the cumulative return on the US stock market, it follows that the stock market bottomed out before economic indicators started improving. This again emphasizes that the reason for the turnaround in the stock market in March was the “Whatever it takes moment of the Fed on March 23” (link). Since late April, however, the stock market and economic conditions have moved in tandem, i.e. economic conditions have improved and so has the stock market:

Total return index for MSCI USA and Weekly Economic Index. Weekly data
Source: Fed St. Louis Database and Thomson Reuter Datastream via Eikon.

Did the recession really end in April, then?

We do not know. It is, as mentioned, the NBER Business Cycle Dating Committee that determines peaks and troughs in the US economy. They have not called the end of the recession yet. Hence, officially, the US economy is still contracting.

I am happy that I am not a member of the NBER Business Cycle Dating Committee. This time, it must be particularly difficult to decide whether the US economy (as well as the European economy, by the way) is really out of the recession or not. As we all know, numbers of new cases are on the rise again in the US and have been doing so for a while in Europe. This will hurt economic activity going forward. So, should one conclude that there was a recession from February through April, or should one conclude that the recession is still ongoing. This is no easy question.

VV (two single Vs) or W?

Did the recession start in February and stop in April? Are we now entering a new recession due to a rising number of corona cases and a subsequent slowdown in economic activity? Or, are we still in the recession that started in February? One way to try to judge this is via NowCasts, i.e. daily forecasts of what growth in economic activity will be the current quarter. This is related to, but different from, the Weekly Index above. It is an estimate of the growth rate of GDP during the current quarter, but based upon data available at a higher frequency. Here is the NowCast from the New York Fed:

NowCasts of US quarterly growth in real GDP. Daily forecasts of growth during the current quarter.
Source: New York Fed

It has a clear V-shape during the second quarter. During April/May/June, incoming data indicated that the fall in GDP during Q2 would be enormous, as it turned out to be (see figure above with actual GDP growth). Incoming data during Q3 indicated that Q3 growth would be high, as it turned out to be. Q4 growth is expected to be considerably lower than Q3 growth, i.e. a new V, but growth is still expected to be positive.

Why is it important whether the recession lasted from February through April only (one V), whether we left the recession in April/May but enter a new now (two Vs, i.e. VV), or whether we are still in the recession, but economic growth was high during Q3 but expected to be low during Q4 and possibly Q1 2021, i.e. W? The reason is that it influences how we should think of recessions and financial markets during recessions.

Conclusion

Historically, stock markets have suffered during recessions. This recession started in February. Since then, the US stock market has gained 10%, seemingly in contrast to its usual behavior during recessions. Economic activity bottomed out in late April, though. The US stock market lost 14% from February through April. Since then, it has returned more than 25%. So, whether you conclude that the stock market has suffered during this recession or not depends on your favorite definition of when the recession ended, if at all until today.

To get the official answer, we have to wait for the NBER Business Cycle Dating Committee.

For the future path of the stock market, the question will be how the number of new infections develop and their impact on economic activity.

For the history books, i.e. for the conclusion of whether the stock market performed surprisingly well during this recession or not, the question is whether the recession ended in April or hasn’t ended yet. Did we have one V from February through April, do we get a new V now, so this ends up being VV, or are we still in the recession, i.e. W?

The Fed’s “Whatever it takes” moment. Or, how the Fed saved equity and credit markets

Facing a looming recession and financial market panics, the Fed intervened heavily in late-February/early-March, lowering the Fed Funds Rate to zero and expanding its balance sheet dramatically. In spite of this, markets kept on panicking. Then, suddenly, on March 23, everything changed. Stock markets started their rally. This was not because the Fed lowered the rate or expanded its asset purchases even further, nor because the economic data improved. What happened? The Fed made an announcement. Nothing else. It is a fascinating illustration of how expectations can change everything on financial markets.  

Much has been written about the massive interventions of the Fed during February and early March. In my previous post (link), I list Fed interventions as one of the reasons why the stock market is back to pre-crisis highs. In this post, I dig one step deeper and explain the fascinating story of how the Fed said something and thereby rescued markets.

Asset purchases and rate reductions did not save markets in February/March

Let us start by illustrating how the actual Fed interventions (interest rate changes and asset purchases) did not save markets in March. The Fed lowered the (lower range of the) Fed Funds Target Range to 1% from 1.5% on March 2 and then again to 0% less than two weeks later, on March 14. At the same time, it bought Treasuries and mortgage-backed securities to the tune of USD 600bn per week. These interventions succeeded in lowering yields on government and mortgage-backed bonds, but did not cheer up stock markets.

This graph shows how Treasury yields came down significantly in February/March, by basically 1.5%-point (from close to 2% to close to 0.5%; I show yields on 10-year Treasuries in this graph), as a result of reductions in the policy rate (the Fed Funds Rate) and asset purchases by the Fed.

SP500 and yield on 10-year Treasuries. Daily data.
Source: Fed St. Louis Database

The graph also shows that the SP500 continued falling throughout February/March. In other words, the massive interventions by the Fed in late-February/early-March (and these interventions really were massive – buying for USD 600 bn per week and lowering rates to zero is indeed a massive intervention) did not convince stock markets that the situation was under control. And, remember, these were not minor stock-market adjustments. It was the fastest bear market ever (link).

What turned the tide?

On March 23, the SP500 reached its low of 2237, a drop of 31% compared to its January 1 value. Since then, everything has been turned upside down and markets have been cheering, as the above graph makes clear.

What happened on March 23? The Fed had its finest hour. It did not do anything. It merely said something. A true “Whatever it takes” moment.

As you remember, a “Whatever it takes” moment refers to the July 26, 2012 speech by then ECB-president Mario Draghi (link). The speech was given at the peak of the Eurozone debt crisis. The debt crisis pushed yields on Italian and Spanish sovereign bonds to unsustainable levels. Italy was too big to fail, but also too big to save. The pressure on Italy was a pressure on the Eurozone construction. Mario Draghi explained the situation and said the by-now famous words:

But there is another message I want to tell you. Within our mandate, the ECB is ready to do whatever it takes to preserve the euro. And believe me, it will be enough.

Investors understood that the ECB would be ready to buy sovereign bonds to save the Euro. Markets calmed down. Italian and Spanish yields fell. And this – and this is the point here – without the ECB actually intervening, i.e. without the ECB buying Italian or Spanish bonds. The announcement that the ECB would intervene was enough to calm down investors.

Why is this relevant here? Because on March 23 the Fed sent out a press release, announcing that:

“…the Federal Reserve is using its full range of authorities to provide powerful support for the flow of credit to American families and businesses.”

And, then, as one of the new features announced the:

Establishment of two facilities to support credit to large employers – the Primary Market Corporate Credit  Facility (PMCCF) for new bond and loan issuance and the Secondary Market Corporate Credit Facility (SMCCF) to provide liquidity for outstanding corporate bonds.

This statement turned everything upside down. The important thing is that this turn of events happened without the Fed using any money at all. It was a “Whatever it takes” moment (though, perhaps not as Dirty-Harry dramatic as Mario Draghi’s “And believe me, it will be enough”): The Fed announced what they would do, investors believed the Fed, and markets started cheering. It is a prime example of how investor expectations influence financial markets.

What are the PMCCF and SMCCFs, why did the Fed announce them, and why were their effects so dramatic?

The lowering of the Fed Funds Rate and the purchasing of Treasuries succeeded in lowering yields on safe assets, such as Treasury bonds, as explained above, but did not lower yields on corporate bonds. In fact, during the turmoil in late-February/early-March, credit spreads (the spread between yields on corporate bonds and safe bonds) widened dramatically. When yields on corporate bonds rise, it becomes more expensive for corporations to finance their operations. And, when yields rise a lot, as in February/March, investors get nervous about the profitability and survival of firms.

This graphs shows how yields on both the least risky corporate bonds (Triple A) and speculative grade bonds (Single B) rose dramatically in relation to 3-month Treasury Bills, with yields on lower-rated bonds (Single-B) naturally rising more than yields on higher-rated (Triple-A) bonds.

Difference between yields on ICE BofA AAA US Corporate Index and 3-month Treasuries as well as the difference between yields on ICE BofA Single-B US High Yield Index and 3-month Treasuries. Daily data.
Source: Fed St. Louis Database

The important point in the picture is that the spreads continued rising throughout late-February/March, in spite of the intensive interventions described above, i.e. in spite of Fed purchases of government and mortgage bonds. The Fed was happy that safe yields fell, but was concerned that credit spreads kept on rising. Volatility in corporate bonds markets also rose (link), making the whole thing even worse.

More or less all firms saw their funding costs increase, even when there were differences across firms in different industries, with firms in the Mining, Oil, and Gas, Arts and Entertainment, and Hotel and Restaurant sector hit the hardest, and firms in Retail and Utilities sectors less affected (link). The Fed became nervous because higher funding costs for firms affect firms negatively, causing them to cut jobs, reduce investments, etc.

The Fed decided to act. It announced on March 23 that it would launch two new programs, PMCCF and SMCCFs. The PMCCF is the ’Primary Market Corporate Credit Facility and the SMCCF the Secondary Market Corporate Credit Facility. Primary markets are where firms initially sell their newly issued bonds. The PMCCF should thus ease the issuance of newly issued corporate bonds, i.e. help firms raise funds. Secondary markets are where bonds are traded afterwards, i.e. the SMCCF should ease the trading (liquidity) of already existing corporate bonds.

The effect on equity and credit markets of the announcement of the PMCCF and SMCCFs was immediate and spectacular. Immediately after the announcement, credit spreads narrowed (see, e.g., link, link, and link).

Interestingly, stock markets reacted immediately, too. The stock market, thus, did not react to the lowering of the Fed Funds Rate and the extensive expansion of the Fed balance sheet in late-February/early-March, but reacted strongly to the announcement that the Fed would buy corporate bonds on March 23.

This (supercool, I think 🙂 ) graph shows developments on corporate bond and equity markets. The graph shows the spread between yields on AAA-rated corporate bonds and 3-month Treasury Bills and the stock market inverted, both normalized to one on January 1. The graph for the inverted stock market means that when the SP500 is at 1.45 on the y-axis on March 23, the stock price at January 1 was 45% higher than it was on March 23.

Difference between yields on ICE BofA AAA US Corporate Index and 3-month Treasuries (Left hand axis) as well as the SP500 inverted (Right hand axis). Both series normalized to one on January 2, 2020. Vertical line indicates March 23.
Source: Fed St. Louis Database

The parallel movements in equity and credit markets are striking. Equity and credit markets moved in parallel during January, when stock markets rose and credit spreads narrowed, in late-February/early-March when credit spreads widened dramatically and stock markets fell like a stone, as well as after March 23, when both credit spreads and stock markets improved spectacularly. Since then, stock markets have continued to rise and credit spreads have continued to narrow.

The correlation between the two series is an astonishing 0.93 for the January 2 through May 31 period.

The announcement effect

The Fed has experience with and a mandate to buy mortgage-backed securities and Treasuries. It had no such experience when it comes to purchases of corporate bonds and corporate bond ETFs. This means that the Fed could not start buying corporate bonds on March 23, it needed an institutional set-up. It created an SPV with capital injections from the Treasury and leverage from the New York Fed, it asked a financial firm (Blackrock) to help them purchase the bonds, etc. These things take time. The Fed only started buying corporate bond ETFs in mid-May and corporate bonds in mid-June.

Given that the Fed only started buying bonds and ETFs in May/June, the spectacular turnaround on March 23 really was due to the announcement only.

In slightly more detail, it played out as follows. The March 23 announcement primarily dealt with higher-rated corporate bonds (Investment Grade), and spreads narrowed immediately. On April 9, the Fed announced that they would expand “the size and scope of the Primary and Secondary Market Corporate Credit Facilities (PMCCF and SMCCF)”, buying bonds that were Investment Grade on March 22 but had been downgraded since then as well as corporate bond ETF. High-yield spreads tightened even more (link). Today, the Fed explains that the programs allow the Fed to buy “investment grade U.S. companies or certain U.S. companies that were investment grade as of March 22, 2020, and remain rated at least BB-/Ba3 rated at the time of purchase, as well as U.S.-listed exchange-traded funds whose investment objective is to provide broad exposure to the market for U.S. corporate bonds.”

The actual purchases began in May/June, several months after the announcement. Interestingly, the purchases themselves have had a modest impact only. First, the amounts of corporate bonds and corporate bond ETFs bought pale in comparison with the amounts of mortgage-backed securities (MBS) and Treasuries bought. The Fed has bought MBS and Treasuries to the tune of USD 3,000bn this year. It has “only” bought corporate bonds and ETFs for around USD 12bn. The amount used to buy corporate bonds thus corresponds to less than 0.5% of the amount used to buy MBS and Treasuries. This graphs shows the daily purchases. Using the latest figures from August 10, the Fed has basically stopped buying corporates.

Daily Fed purchases of corporate bonds and corporate bond ETFs. Daily data.
Source: Fed webpage. Thanks to Fabrice Tourre for collecting and sharing the data.

So, the Fed has not bought a lot of corporate debt. It has, however, the power to buy a lot. The PMCCF and SMCCF set-up is such that the Treasury has committed to make an USD 75bn investment in the SPV that buys the assets (USD 50bn toward the PMCCF and USD 25bn toward the SMCCF). The New York Fed then has the ability to level this up by a factor of ten, i.e. the Fed can buy corporate debt for up to USD 750bn. This is a sizeable fraction of the total US corporate bond market. This, that the Fed can potentially buy a lot, helps making the program credible and thus helps explaining its powerful impact.

Dilemmas

Given the success of the PMCCF and SMCCFs, commentators have started arguing that the Fed should be allowed to buy corporate bonds as part of its standard toolkit (link). This might be relevant, but purchases of corporate bonds by central banks raise a number of dilemmas:

  • Keeping zombie firms alive. By easing up stresses in corporate bond markets, the Fed calmed down markets. This was the intention of the PMCCF and SMCCF announcements and it worked. It eased access to funding for firms, and firms have raised a lot of cash as a consequence (link). It is positive that malfunctioning markets are stabilized, but if central bank intervention makes markets too cheerful it may allow firms that in principle should not receive funding to nevertheless get it. And, thereby, to keep firms alive for too long, and increase firm leverage too much. Basically, the fear is that programs such as the PMCCF and SMCCFs create too many zombie firms. My CBS colleague Fabrice Tourre and his co-author Nicolas Crouzet has an interesting paper that examines this (link). Fabrice and Nicolas find that when financial markets work perfectly (no disruptions), Fed intervention might be detrimental to economic growth. On the other hand, if markets are disrupted, Fed intervention might prevent a too large wave of liquidations. One thus needs to determine when markets are disrupted “enough” to rationalize interventions in credit markets. This is no straightforward task.
  • Distributional aspects. By buying some bonds but not others, the Fed exposes itself to the critique that it helps some firms at the advantage of other. To alleviate such criticism, the Fed has been very transparent and publishes a lot of information about the bonds it buys, the prices at which it buys the bonds, etc. (link). Nevertheless, it is easy to imagine that some firms at some point will start saying ‘Why did you buy the bonds of my competitor, but not my bonds’?
  • The Fed put. The more the Fed intervenes when troubles arise, the more investors get reassured that the Fed will also come to the rescue next time around. When the Fed saves markets, it is sometimes called the Fed exercises the “Fed Put”. The potential problem here is that if investors believe that the Fed will exercise the Fed put, investors will be tempted to take on even more risk. Those of us concerned about systemic risks get nervous.

So, in the end, the announcement of the PMCCF and SMCCFs was crucial during this crisis. There are, however, important dilemmas that need to be addressed when evaluating whether such programs should be part of the standard toolbox. I am not saying they should not. I am saying that one needs to be careful.

Conclusion

The Fed launched massive “traditional” interventions in late-February/early March, lowering the Fed Funds Rate and buying mortgage and government bonds. In spite of these very large interventions, equity and credit markets kept on tail spinning. When firms struggle, it hurts economic activity and employment. The Fed got nervous.

The Fed announced – and this is the whole point here; they only announced – that they would start buying corporate bonds. Markets turned upside down. Credit markets stabilized, credit spreads narrowed, corporate bond-market liquidity improved, and stock markets cheered. And, all these things without the Fed spending a single dime until several months after the fact. Even today, the Fed has spent very little (some might say that USD 12bn is a lot, but compared to asset purchases of USD 3,000bn, it pales).

It was a “Whatever it takes” moment. It illustrates how managing investor expectations can be crucial. Understanding this announcement is thus important for understanding the behavior of financial markets during this pandemic.

The weird stock market. Part II: Potential explanations

The behavior of the stock market during this recession raises three main questions: (i) why did stock markets fall so spectacularly during February/March, (ii) why did stocks rebound so spectacularly during April/May, and (iii) why is the stock market currently at its pre-crisis level? My previous post (link) presented the stylized facts and addressed stories that cannot explain the facts. In this post, I provide some potential explanations.

I my previous post (link), I mentioned that the rebound in the stock market since its low in March cannot be explained by (i) revisions to the economic outlook – in fact, economic forecasts were revised down during spring, (ii) a preference for just a few (FAANG) stocks, as the rebound has been international and broad based, even when large-cap stocks have done particularly well, (iii) a hypothesis that this recession is not particularly bad – in fact, at least in the short run, this recession is much worse than the 2008 recession, or (iv) the fact that markets also recovered after 2008 – markets always recover, i.e. this is not an explanation.

What can explain it, then? First, a warning: I do not want to raise expectations too much (sorry). I will not be able to offer a full explanation of these puzzles in an app. 1,900 words blog post. Also, as you will see, puzzles remain, even if we can explain some things. Finally, I have not seen a good explanation of these puzzling stylized facts (though Gavyn Davies’ piece in the FT is a good place to continue after reading this post; link). Hence, it would not be serious nor academic if I claimed that I could explain everything. What I can do, though, is to provide some hints at what might be relevant parts of an explanation.

Explanations that contain elements of truth

Earnings suffered more in 2008               

In the end, earnings and not economic activity (GDP) determine stock prices. In the long run, there is a strong relation between earnings and economic activity, which is why we focus on economic developments when we try to understand stock markets. The relation is not one-to-one, though, in particular in the short run. Hence, let us discuss earnings.

Earnings suffered dramatically in 2008. Often, we look at 12-month earnings, as quarterly earnings are volatile. 12-month reported earnings per share for the S&P500 came in at 6.86 in Q1 2009, which is app. 10% of 12-month reported earnings in Q1 2008. I.e., earnings fell by a mind-blowing 90% during the financial crisis of 2008.

Earnings fell in Q1 2020, too, but much less: From USD 139 per share in Q4 2019 to USD 116 (12 month reported earnings), i.e. by 17%. At the time of writing, around 90% of companies in the S&P500 have reported earnings for Q2 2020. Earnings (12-month reported) seem to be coming in at close to USD 96 per share, which is a drop of 17%, too, compared with Q1. Earnings have thus dropped by 17% during each of two consecutive quarters. But, and this is the main thing, these drops pale in comparison with autumn 2008. In autumn 2008, earnings dropped by 68% from Q3 to Q4 and then again by 54% from Q4 2008 to Q1 2009. This figure shows the quarterly percentage changes in 12-month reported earnings of the S&P500 in 2008 versus 2020. “0” on the x-axis is Q2 2020, respectively Q4 2008. The drop in earnings was just so much larger in 2008.

Quarterly changes in 12-month reported earnings per share, S&P500. “0” is Q2 2020, respectively Q4 2008. For Q3, 2020 and forward, these are expected earnings.
Source: https://www.spglobal.com

“1” on the x-axis in the figure is thus Q1 2009 and Q3 2020, i.e. firms’ expected earnings in Q3 2020 (and actual earnings in Q1 2009). If these expectations hold true, earnings are expected to do relatively fine going forward.

Earnings do fall from Q1 to Q2 this year. Earnings surprises matter, too, though, i.e. whether actual earnings are higher (or lower) than expected. At the time of writing, around 80% of companies have reported positive earnings surprises for Q2. This, that actual Q2 2020 earnings are better than expected, helps explaining why stock prices rise currently.

If investors primarily look at earnings, this helps explaining why stock prices fell considerably more in 2008 than they have done during this recession and why the stock-market recovery took longer in 2008. Earnings have simply not suffered so much this time around. For that reason, stock prices have not suffered so much this time around either.

Monetary and fiscal policies have been aggressive

Another factor that helps explaining why stock prices today are at pre-crisis levels, in spite of the severity of the recession, is that policy interventions have been aggressive. Immediately, at the onset of the crisis, monetary policy turned very expansionary. This can be illustrated by the weekly changes in the Fed balance sheet, as in this graph:

Weekly changes in the Fed balance sheet. USD mio.
Data source: Fed St. Louis Database

The figure plots the weekly changes in the Fed balance sheet due to purchases of financial assets, in millions of USD. The Fed balance sheet changes when the Fed buys/sells financial assets. During March this year, there were weeks when the Fed intervened to the tune of USD 600bn. This is an enormous amount of money. It is, by way of comparison, more than twice the weekly amounts spent during the financial crisis of 2008, the figure also shows.

At the same time, yields are very low. This forces investors to buy risky assets if they want some kind of return, supporting stocks.

In addition to very aggressive monetary policy, fiscal policy has also been very aggressive.

Why did stock prices fall during February/March?

OK, so earnings have not fallen as much as in 2008, earnings for Q2 2020 have surprised positively, monetary and fiscal policies have been very aggressive, central banks pump liquidity into the system, and interest rates are very low, implying that investors need to invest their money in risky assets if they want a positive expected return. These features help explaining why stock prices today are not much lower than in the beginning of the year. But, if this is the story, why did stock markets drop so dramatically in March?

Changes to expectations to earnings

Earnings have dropped in Q1 and Q2, even if considerably less than in 2008. Perhaps the stock-price drop in February/March was simply due to a downward revision in expected earnings. Alas, this is not the case. Landier & Thesmar (link) have an interesting analysis where they look at analysts’ expectations to the earnings of S&P500 companies during Q1 and Q2 2020. They find that analysts cut their expectations to earnings of S&P500 firms, but not so much that it can account for the drop in stock prices during February/March. In other words, the drop in stock prices in February/March cannot be explained by analysts reducing their earnings forecasts.

If the drop in expected earnings cannot account for the drop in stock prices in February/March, what happened then? Financial economists have a straightforward way of explaining this. Stock prices are discounted cash-flows. To understand stock price movements, we must understand cash-flow and discount rate movements. When the fall in expected earnings is not large enough to account for the drop in stock prices, discount rates must have increased in February/March. In other words, during February/March investors required a higher expected return if they should invest in stocks. This is also the conclusion in Landier & Thesmar and in Gormsen & Koijen (link). Basically, this is the conclusion in most empirical asset-pricing literature: stock prices move too much to be justified by movements in cash-flows. Discount rate variation is the reason, the literature concludes.

When stock prices move, and it cannot be because of cash-flow movements, it must be discount-rate movements. This is fine, but it is also somewhat tautological: If A = B + C, and A moves but B does not, then it must be because C moves.  A more difficult question is what makes discount rates move in the first place? I.e., what is the deeper economic explanation? Perhaps/probably risk aversion spiked, when investors in February suddenly realized the severity of the virus. Perhaps/probably some market participants faced funding constraints. And so on. In other words, I agree that discount rates most likely spiked during March, but I am not 100% sure why and I do not know if the increase in risk aversion is large enough to account for the increase in discount rates, and thus account for the drop in stock prices.

Lingering doubts

So, a potential reason why stock markets have done better than in 2008 is that earnings have not suffered as much as in 2008 and central banks have flooded the market with liquidity (and yields are at zero). The reason why we saw a massive fall in stock prices in February/March, and an unprecedented rebound during April/May/June, then probably is that discount rates increased during the early phase of the crisis, and then stabilized. This is a story that somehow makes sense.

Two things are still strange (to me at least), though.

First, if stock prices are at their right levels now, why did they have to fall so much in March? OK, because risk aversion increased and funding conditions tightened. But, if risk aversion increased in February because investors understood that a recession was looming, why would investors turn less risk averse three weeks later, when economic forecasts just kept on deteriorating? Probably the Fed and the Treasury (via monetary policy and fiscal policy) eliminated the spike in risk aversion via aggressive policy interventions, but it is still not 100% clear how to reconcile these features of the data.

Second, the behavior of earnings has been surprising. During recessions, earnings normally contract much more than economic activity. So, when economic activity in 2020 contracts much more than in, as an example, 2008, a reasonable hypothesis is that earnings in 2020 would contract much more than in 2008. This has not happened.

To some extent, this graph summarizes both the explanation of the relatively mild response of the stock market to this recession and the remaining puzzle:

Percentage changes in US real GDP and earnings of S^P 500 firms from Q3 to Q4 2008 and from Q1 to Q2 2020.

The figure shows how earnings dropped 68% from Q3 to Q4 2008 but seems to drop only 17% from Q1 to Q2 this year. This explains why the stock market has performed considerably better during this recession compared to its performance in 2008, for instance. On the other hand, the figure also shows that GDP dropped by 10% from Q1 to Q2 this year and only by 2% from Q3 to Q4 2008, i.e. the fall in economic activity is five times larger during this recession. It is puzzling that earnings drop so much less during this recession when economic activity contracts so much more.

So, the relatively modest contraction in earnings helps explaining the relatively fine performance of the stock market during this recession, but it is difficult to understand why earnings have behaved reasonably well. Perhaps this is because banks were suffering in 2008, but are able to help firms getting through this recession. Perhaps it is because firms have been able to adapt better this time. We do not really know. From an academic asset-pricing perspective, it is interesting that the stock market has behaved so differently this time around, compared to how it normally behaves. From an investor perspective, we can only hope that the stock market will keep on behaving in a different way than it usually does, as, otherwise, stock prices will fall going forward.

Conclusion

The facts that earnings have done better than in 2008 and that monetary policy has been very aggressive help us understand why the stock market has done well during this recession. Some puzzles still remain, though. For instance, why have earnings done so reasonably well, given the severity of the recession, and why did risk aversion increase so dramatically in February only to normalize few weeks later, in spite of the worsening recession. Perhaps the sensible answer is that this recession has been unusual in many dimensions, and some things will remain difficult to understand.

The weird stock market. Part I: Facts and wrong explanations

The behavior of the stock market during this recession has been perplexingly. To understand it, we need to answer three main questions: (i) why did stock markets fall so spectacularly during February/March, (ii) why did stocks rebound so spectacularly during April/May, and (iii) why is the stock market currently at its pre-crisis level? This blog post explains why these stylized facts are so difficult to understand jointly. In my next blog post (link), I will offer my interpretation of the evens.

Observing the stock market during this recession has been a like watching a roller coaster. The fall in late-February/early-March was the fastest bear market in history, the rebound has been historically fast, too, and – in spite of the worst recession ever – the stock market is currently back at pre-recession levels. Somebody leaving for the moon in January and returning now would not be able to see any trace in the stock market of the worst recession ever. This is in stark contrast to normal recessions. People interested in financial markets and the economy should be puzzled.

The problem – in a nutshell – is that if you claim that you understand why stocks are currently at pre-recession levels, then you face a challenge explaining why we needed to go through the fastest bear market ever during February/March. On the other hand, if you claim that the fast fall and rise in markets was just a short-lived technical blip (perhaps due to funding squeezes and fear), then you face a challenge explaining why that technical blip should result in a loss to the tune of USD 20 trillion (link). Finally, if you claim that you understand why markets fell so fast in February/March (perhaps because we were facing the worst recession ever – which, by the way, is a good explanation), then you face a challenge explaining why markets recovered so strongly in April/May/June, as the recovery cannot be explained by a brighter economic outlook. In fact, we have seen continuous downgrades of the economic outlook. E.g., the IMF WEO in June lowered its April forecasts for global economic output to –4.9%, from –3.0%. A huge downgrade. Strange that stocks recover in spite of this.

In this post, I describe the facts. I also review a couple of suggested, but wrong, explanations. In my next post (that I will publish next week), I will offer my view on what has been going on.

The facts

Here is an updated version of a graph that I have presented earlier. It shows the Danish, US, emerging market, and world stock markets (MSCI), normalized to one on January 1, 2020:

Stock markets since January 1, 2020. MSCI indices.
Data source: Thomson Reuter Datastream via Eikon.

Stock markets reached a temporary peak on February 19, after which they tanked dramatically. As mentioned here (link), it was the fastest US bear market in history.

The rebound has been equally spectacular. The US stock market is already back at its January 1 level. World and emerging markets are still a few percentages behind, but, basically, they have also recovered from the crisis.

In the US, it was the fastest bear market ever, as mentioned. In this graph, I document that it has also been one of the fastest recoveries. I calculate rolling 11-week gains/losses in the SP500 during the last 50 years.

S&P 500, 11-week percentage changes.
Data source: Fed St. Louis Database

As you can see from the encircled peak on the right-hand-side of the graph, from its bottom on March 23, the SP500 gained app. 45% until June 8. The graphs shows that no other 11-week period since 1970 has witnessed such a large gain (I cherry-pick the 11-week period, but the main message is that the rebound has been spectacular, and this message is robust).

Wrong explanations

You hear/read many explanations. Some of them are just not correct.

It all boils down to FAANG

Some claim that it is not the overall stock market (typically these people refer to the SP500) that has recovered. Instead, some argue, it is all due to FAANG (Facebook, Apple, Amazon, Netflix, and Alphabet’s Google). It is true that the behavior of FAANG has been impressive and has driven a significant part of the SP500’s recovery, but this is not the whole story. As you see from the first graph above, emerging markets have recovered, too. This is obviously not due to FAANG. Also, some markets, such as the Danish, have recovered even more spectacularly than the US market. Not FAANG either. Even US small-cap stock have recovered. Not fully, but significantly. The Wilshire US Small-Cap Index gained an astonishing 57% during the March 23 through June 6 period. True, small-cap stocks are still (early August) 12% below their January 1 level, but when small-cap stocks have rebounded spectacularly, too, it emphasizes that this is not all about all FAANG, even when FAANG stocks have done very well.

Markets also recovered after the 2008 financial crisis

This is a no-brainer: Markets always recover. The point here is that this rebound has just been amazingly strong. In this graph, I compare the behavior of the SP500 during autumn 2008 and the corona crisis. “0” in the figure is September 19, 2008, respectively February 21, 2020:

S&P 500, daily closing prices. Normalized to “1” 25 days before September 19, 2008, respectively February 21, 2020. September 19, 2008 and February 21, 2020 marked by vertical line.
Data source: Fed St. Louis Database

During the first couple of weeks of this spring’s crash, it looked like autumn 2008. The pain was short-lived, though. Stock markets fell for a couple of weeks and then rebounded. In 2008, stocks just continued falling.

It has taken a couple of months to recover this time around. After the financial crisis of 2008, it took more than two years. This figure shows that the US stock market was back at its summer-2008 level in early 2011 only, and the world stock market later still.

Stock markets since January 1, 2020. MSCI indices.
Data source: Thomson Reuter Datastream via Eikon.

This recession is not as bad as 2008

It should be obvious by now that this argument is very wrong indeed. I have argued myself that there is hope that, when we get a vaccine and economic activity picks up again, the economic rebound will be stronger than in 2008, the reason being that we entered this recession with a more “balanced” economy than in 2008 (in 2008, we had a housing bubble, a weak financial sector, etc.). Nevertheless, the short-run loss this time around is just so much larger than in 2008.

Last week, we got figures for GDP in the US and Europe. This graph compares the cumulative falls in real GDP in the Eurozone and the US in Q3+Q4 2008 with the cumulative drops during the first two quarters of this year.

Cumulative change in real GDP in the US and the Eurozone. “2008” is Q3+Q4 2008 and “2020” is Q1+Q2 2020.
Data source: Fed St. Louis Database

US real GDP fell by more than three percent in Q3 and Q4 2008, whereas Eurozone real GDP dropped by five percent in autumn 2008. It was a severe recession in 2008. Nevertheless, it pales compared to this recession. This time around, US GDP has fallen by more than ten percent already and Eurozone GDP is down by a staggering 15% during the first two quarters of 2020.

What about the length of the recovery? After 2008, it took around two years before economic activity had reached its pre-crisis level. This figure shows for, e.g., the Eurozone that it will last more or less equally long this time (expectations for 2020 and 2021 are from the EU Commission, Spring 2020).

Development in real GDP for the Eurozone as of Q2 2008 and as of Q4 2019. Developments after Q2 2020, i.e. after 2 quarters in 2020, are expectations from the EU commission.
Data source: EU commission.

The figure shows that Eurozone GDP was 5% lower in Q4 2008 compared to Q2 2008 whereas it is 15% down in Q2 2020 compared with Q4 2019. After eight quarters, GDP is basically back at its pre-crisis level. This means that the recovery is expected to be stronger, but this recession is just very deep.

In other words, this recession is much deeper – one can multiply the drop in 2008 by a factor of three or so to get the drop this time – and it will take several years before economic activity is back at pre-crisis levels. This means that the short-run cost to society is bigger this time around (a deeper fall stretched over the same period).

And, in spite of this very strong recession, stocks are doing fine. That is perplexing.

Above, I have presented stories that cannot explain what has been going on. In my next post (link), I will offer my view on this.

How stable is the Nordic financial sector?

In 2008, banks were too fragile given the risks on and off their balance sheets. Many banks failed, others were rescued by governments/taxpayers. The societal costs were enormous. In a new publication, I evaluate the robustness of the Nordic financial sector today. I conclude that the Nordic financial sector is more robust than in 2008. This is important because we are currently going through a severe recession. If banks today were as weak as in 2008, this recession would have been even worse.

Once a year, Nordregio publishes the Nordic Economic Policy Review. The theme of this year’s publication is “Financial Regulation and Macroeconomic Stability in the Nordics”. Because of my experience from analyzing the financial crisis in Denmark in 2008 (I chaired the government-appointed committee that investigated the causes and consequences of the financial crisis in Denmark, the Rangvid-committee, link), I was asked to write the first paper in the publication (link), assessing the robustness of the Nordic financial sector today.

It is a policy paper. No fancy equations and regressions, but straight-to-the-point analyses and conclusions. The Review was published Tuesday, June 16. At its launch, I participated in a panel debate with, among others, two former deputy-governors at Riksbanken (the Swedish central bank), a former governor at Riksbanken, and myself. In this post, I review my main conclusions and relate them to this crisis.

An ironic incident
I start my paper emphasizing that it is difficult too foresee financial crises.

As an example, the first-page headline – typed in large bold letters – in the 2008 Financial Stability Report of Nationalbanken (the Danish central bank) was: ‘Robust Financial Sector in Denmark’. The Financial Stability Report analyzed the robustness of the Danish financial sector. It was published in May 2008, i.e. only a few months prior to the outbreak of the worst financial crisis since the 1930s. Half of Danish banks disappeared following the financial crisis of 2008.

Even if this headline probably still haunts Nationalbanken, Nationalbanken was not alone in not foreseeing the financial crisis. On the contrary. Financial crises are almost per definition unpredictable. If it was generally accepted that a financial crisis was in the making, action would surely be taken to prevent it. In this sense, we tend to become surprised each time.

The first version of my analysis was written in autumn last year. The final version was submitted in January this year. Right before the corona crisis.

I had not seen the corona crisis coming. In particular, I had not seen how severe it would be. Clearly, I was not alone either. Financial markets, for instance, had not seen it, and financial markets summarize the average views of all investors. Stock markets, credit spreads, stress indicators, etc. did not react before the crisis was in fact happening. So, was my assessment of the financial sector in January – that I present below – “robust” in light of the events that have happened? I will return to this in the end.

Why an important question?

If financial crises, and more generally stress in financial systems, are so hard to predict, why do we bother? There is one main reason: The societal costs associated with financial crises are enormous.

In the paper, I present new calculations of the societal losses resulting from financial crises in the Nordics. I do as follows. Societal losses are calculated as forgone economic activity due to financial crises. And this, forgone economic activity, I calculate by projecting economic activity, from the start of a financial crisis, by the growth rate of economic activity. The result is a path of economic activity in the hypothetical event that there had been no crisis. I contrast this with actual economic activity during the crisis. The difference is the cost of the financial crisis.

In the paper, I present results from such calculations for Denmark, Finland, Norway, and Sweden for the crises in the early 1990s and the crises in 2008. Let me present just one of the calculations here. This figure shows the result for Denmark for the 2008 crisis:

GDP and hypothetical non-crisis GDP for Denmark.
Data source : St. Louis FRED database.

The blue line shows developments in real per capita GDP (in USD to allow for a comparison across the Nordics) whereas the red line shows hypothetical GDP assuming no crisis. Before the crisis, real GDP per capita was developing steadily around the growth trend. The crisis changed this dramatically. GDP fell 5% during the crisis, itself a huge drop in GDP. On top of this, however, the recovery was slow. In 2018, ten years after the crisis, GDP had not recovered to the level that could have prevailed had there been no crisis. In fact, ten years after the crisis, the accumulated difference between hypothetical no-crisis GDP and actual GDP amounts to 91% of GDP in 2008. One year of GDP was lost due to the crisis.

I present these calculations for the other Nordic countries and other crises. The editors of the publication, Lars Calmfors and Peter Englund, in their introduction, summarize the results as follows: “Losses accumulate to a staggering one or two years of economic output”. This is why it is important to deal with financial crises.

In the paper, I describe the underlying causes behind the crises in the Nordics, as well as similarities and differences across countries. I skip this here. Read the paper to get it.

Risks assessment

As the next step, I venture into a kind of risk assessment.

Literature on financial crises concludes that even when it is difficult to foresee crises, some variables tend to be more informative about risks to financial stability than others are. I mainly discuss credit growth, house price growth, and household leverage. I conclude that lights are not flashing red.

Credit growth is the indicator to which most attention is typically paid. For instance, credit growth is the most important indicator when the counter-cyclical capital buffer is determined in the new Basle capital-regulation regime. Credit growth has been low during recent years.

House prices and household leverage are other important indicators. In the Nordics, they have been growing for almost three decades. House prices are currently high, as are levels of household debt.

At the same time, it is difficult to use an indicator that has been increasing for almost three decades as a predictor of the timing of a turnaround. The literature typically uses a three-year window for house-price growth when predicting crises. House-price growth has not been particularly strong during the recent couple of years.

So, house prices and household debt levels are high today. But twenty years ago, they were higher than they were thirty years ago. And, ten years ago, they were higher than they were twenty years ago. Today, they are higher than they were ten years ago. It is very difficult to say when the level is “too high”, in particular when interest rates have been fallen throughout the last thirty years, too (I return to this below). Had there been an explosion in house prices during the last couple of years, like prior to the 2008 crisis, it would have been a different matter. But this is not the case.

I conclude that house prices and levels of household debt are high but their developments are not particular useful to predict the timing of a crisis, and thus not supporting a conclusion that “a crisis is around the corner”

Robustness of the financial sector

Traditional indicators of risks to financial stability are not flashing red in the Nordics, but my introductory point was that crises tend to arise in unforeseen ways. The financial system should thus be robust to withstand unforeseen shocks. Prior to the 2008 financial crisis, the financial system was clearly not resilient enough. Banks “too large to fall” had to be rescued by governments and taxpayers. As a consequence, increasing the resilience of the financial system has been high on the agenda since the financial crisis.

Capital and liquidity requirements have been tightened, stress tests are conducted more systematically now, assuming even more severe stresses than assumed in stress tests conducted before 2008, restructuring and resolution regime have been introduced, macroprudential instruments employed, etc. I conclude that the financial system in the Nordics is more resilient today. This graph is just one way of illustrating this:

Capital ratios of selected large Nordic banks, before and after the 2008 financial crisis.
Data source: Eikon.

The graph shows capital ratios of selected large Nordic banks before (2006) and after (2018) the financial crisis. Prior to the financial crisis, large banks financed around 8-10% of their risk-weighted assets with equity. Today, the ratio is between 18-20%. In other words, capitalization of banks has been basically doubled since the financial crisis.

Causes for concern

Does all this (no lights flashing red and a more resilient financial sector) mean that there is no cause for concern? That would be going too far.

I am concerned by the current low-interest rate environment. Or, rather, I am concerned about the consequences if interest rates at some point start rising.

Today, interest rates are very low in an historical content. I use this graph to illustrate:

Monetary policy rates in the Nordics.
Data source: Datastream via Eikon.

The figure shows monetary policy rates in the Nordics since the early 1990s. Rates have been constantly falling, reaching negative territory in Denmark and Sweden (Sweden now back at zero again).

As mentioned above, house prices and debt levels have been increasing for app. 30 years in the Nordics, most likely driven by the fall in interest rates. Higher house prices and levels of debt might be justifiable when interest rates are low, but should interest rates rise, they might not be sustainable any more. Furthermore, asset prices are even more sensitive to the interest rate when interest rates are low. This means that it takes less of an interest rate increase to cause drops in assets prices (such as house prices) at low levels of the interest rate. Interest-rate risk is important to monitor, in my opinion.

On the other hand, if interest rates stay low, this might squeeze bank profits, if banks are unwilling to pass on low or negative interest rates to customers. This seems to be the case. In spite of negative policy rates since 2012 in Denmark, it was only in 2019 that Danish banks started charging negative deposit rates towards retail customers, and still only on large deposits (typically above EUR 100,000). An incomplete pass through of negative rates hurts bank profits, squeezing their resilience.

Finally, in the paper, I discuss briefly the possibility that the next crisis might arise in nontraditional banking areas, such as the emergence of credit extension by non-regulated financial institutions or cyber risks.

Discussion

The publication (Nordic Economic Policy Review) also includes great comments from two discussants of my paper: Anneli Tuomenin, CEO of the Finnish Financial Supervisory Authority and Peter Englund, Professor at the Stockholm School of Economics. Both largely agree with my assessment that the Nordic financial system is more robust today. Anneli is, though, perhaps even more worried than I am about the current low interest rate environment and outlines an additional number of non-traditional risks, such as climate risk and cyberrisk. Peter discusses whether banks really are that much better capitalized today (has capitalization gone up or risk weights down?) as well as additional risks associated with low interest rates. Read their comments. The main point is, I believe, that all of us share the view that we are particularly concerned about risks associated with low levels of interest rates.

The publication also contains additional interesting articles on the banking union, on macro prudential regulation, on monetary policy and household debt, on bail-in instruments, and other interesting topics. If you are interested in financial stability, the publication should be a must-read.

Lessons in light of the corona crisis

As mentioned, I wrote this paper in January 2020, right before the outbreak of the corona crisis. In the paper, I conclude as mentioned that the financial sector is more resilient today than in 2008. Now, we are in the midst of a recession that will cause a considerably larger fall in economic activity (on the short run) than during the financial crisis in autumn 2008. In autumn 2008, banks went belly-up and many had to be rescued. What has happened this time around? No bank has gone bankrupt, no banks have been saved, spreads are up on financial markets but not as much as in autumn 2008 (they were briefly in March, but came down quickly again). In autumn 2008, banks cut lending dramatically. Today, banks are helping customers getting through the crisis. I think this is important to emphasize, as you can still find people who argue that banks are not much more robust than they were in 2008. I judge that they are.

I am not saying that all banks will survive this, and I am not saying that we will not face any threats to financial stability. But I am saying that, given the fact that this recession is even deeper (on the short run) than the 2008 recession, and the fact that we are not witnessing the problems we did in 2008, this indicates – at least until now – that the financial system is more resilient today. Of course, should the situation turn to the worse, e.g. with a new wave of the virus, things will look different.

Webinar

The paper was presented at a webinar on June 16, 2020. The presentation was followed by a panel discussion on “Will the corona crisis also trigger a financial crisis?”. Panelists included Karolina Ekholm, Stockholm University and former deputy-governor at Riksbanken, Lars Heikensten, the Nobel Foundation and former governor of Riksbanken, Kerstin Hessius, CEO of the Third Swedish National Pension Fund and former deputy-governor at Riksbanken, and myself. The panel was moderated by Peter Englund. It was an interesting debate.

Interventions that pay off. And, interventions that do not

In many European countries, lock-downs have been comprehensive. Now that we have more data, it is time to ask the question whether all types of interventions are equally effective. New research indicates that restricting large gatherings and public events is effective. Restricting international and internal travel is not.

Given the fact that the number of new cases continues to fall in Europe, even when more and more is opened up (link), I cannot help wondering whether all types of lock-downs are equally effective. It must so that some measures are more effective than others are. And, if some measures are not effective, they should be applied with greater caution if we will face a second wave of the Covid-19 virus.

It is understandable that lock-downs were comprehensive early on, as data and studies on the effectiveness of different non-pharmaceutical interventions were lacking. Now we have more data. A new study is interesting in this regard.

Nikos Askitas, Konstantinos Tatsiramos, and Bertrand Verheyden (link) use data from 135 countries to study the effectiveness of different types of non-pharmaceutical interventions. By studying such comprehensive data, Askitas et al. are able to exploit variation in the timing, type, and effectiveness of interventions within and across countries in order to identify the effects of different types of interventions. The data also allow the authors to control for the contemporaneous influence of multiple non-pharmaceutical interventions, i.e. they can do their best to isolate the effect of each type of intervention.

Askitas et al. classify interventions into eight different categories: (i) international travel controls, (ii) public transport closures, (iii) cancelation of public events, (iv) restrictions on private gatherings, (v) school closures, (vi) workplace closures, (vii) stay-at-home requirements, and (viii) internal mobility restrictions (across cities and regions). Their main results are here:

Source : Askitas, Tatsiramos, and Verheyden (2020)

The figure reveals how the number of daily new infections develop prior and subsequent to the introduction of different types of interventions. The figure shows that the most effective interventions are cancellations of public events and restrictions on gatherings. For instance, 35 days after the introduction of interventions that cancel public events, the number of new infections has fallen by 25%, compared to the number of new infections at the event time, i.e. at the time of introducing the intervention, on average across the 135 countries in the study. The figure also shows that the effect becomes significant only after app. 20 days, i.e. it takes time before the interventions work.

On the other hand, international travel controls, public transport closure, and restrictions on internal (within country) movements seem to have basically no effect on the number of new cases. In fact, these types of interventions do not seem to have any statistically significant effect on the number of new infections.

School closures seem to have some effect, although it is barely significant.

Other authors have studied the effectiveness of non-pharmaceutical interventions, even when these studies do not look as carefully as the Askitas et al. study on the effectiveness of different types of interventions. Robert Barro (link), for instance, studies data from the 1918 Spanish flu, exploiting variation in the intensity and duration of interventions across US state. Barro finds only little effect of interventions. Barro also reports, however, that this no-effect result is most likely due to the short duration of the interventions implemented during the Spanish flu. Most of the interventions back then had a duration of around one month. The figure above shows that interventions only start being really effective after one month or so. In this light, it is perhaps not surprising that Barro finds only little effect of non-pharmaceutical interventions.

Other studies, for instance link and link, also report a positive effect of non-pharmaceutical interventions but do not estimate as clearly the effect of different types of interventions.

So, the conclusion, at least to me, is that:

  1. Non-pharmaceutical interventions can be effective, in particular if their duration is not too short.
  2. Some interventions are more useful than others are.
  3. In particular, restrictions of large gatherings and public events seem to be rather effective.
  4. Restricting international travel and public transportation does not seem to be effective.

Hopefully, results like these will be read carefully by politicians. If we will face a second wave of Covid-19, activities that do not influence how the virus spreads should not be shut down. On the other hand, we should be fast in implementing interventions that are effective, and their duration should not be too short. In particular, there is no need to uncritically just shut down “everything”. It is perhaps understandable that this was the approach taken in many European countries in March when evidence on the effectiveness of different types of interventions was missing. Today, we know more. Research indicates that it pays off to restrict gatherings of large groups of people, while restricting international travel and public transportation does not seem to pay off.

The price of a lockdown

Has the lockdown been too strict and have we paid too high a price (in terms of forgone economic activity) as a result? Evidence from Denmark and Sweden helps answering this important question.

The fact that the number of deaths associated with Covid-19 falls in many European countries is unbelievably good news. As a result, European economies are opening up again. This is also good news. What is perhaps somewhat surprising, though, is that the number of deaths and new cases has not started climbing after opening up. This raises the question whether too many sectors were shut down and we, consequently, paid too high a price to contain the virus. Evidence from Denmark and Sweden suggests that the price was probably not as high as one might intuitively have expected.

Covid-19 in Denmark

The Danish prime minister announced the lockdown of Denmark on March 11. Death numbers kept climbing until early April, but has fallen steadily since then, as this figure shows

Number of new deaths in Denmark. Rolling 5-days average. Vertical lines indicate April 15 (primary schools opened), April 20 (dentists etc. opened), May 11 (retail shops opened), and May 18 (restaurants opened).
Data source: Statens Serum Institute. https://en.ssi.dk/

The fact that Covid-19 seems to be under control in Denmark is obviously very good news.

The lockdown has been costly, though. Jobs have been lost, firms have closed down, incomes have fallen, etc. Public debt levels will increase significantly.

Denmark started opening up again in mid-April. On April 14, private corporations that had been asked to encourage people to work from home were now encouraged to let workers return to their offices, subject to suitable safety measures. On April 15, kindergartens and lower primary schools opened up, and on April 20, hairdressers, dentists, etc. were allowed to open. If the lockdown helped contain the virus, one would have expected to see a rise in deaths and new cases after easing the lockdown. This has not happened.

On May 11, retail shops opened. On May 18, restaurants. Again, if the lockdown was the primary reason why the virus stopped spreading, we should have seen the number of new cases increase after opening up. This we have (luckily) not.

Given that the number of deaths and new cases has been constantly falling since opening up, one may wonder whether the lockdown was too strict. It seems that voluntary social distancing, avoiding large crowds, and the washing of hands have been perhaps even more important. Doctors and scientists wonder whether the virus has mutated and turned less infectious, or warmer weather in April and May has caused a slowdown in new cases, but if I understand what they are saying, they believe that hand washing (and related precautions) is a main reason why numbers fall.

If this is true, we need to ask the question whether it was necessary to keep children and workers at home and close down as much as we did. Whether the economic costs have been too high. This is a sensitive and difficult question, though, because it requires that we evaluate how much economic activity would have fallen had we not shut down as much as we did. Surely, people would have cut consumption anyhow, as people would have been afraid of the virus itself and its consequences. So, what was the extra price we paid because of the lockdown?

Evidence from a clever study

A clever study (Link) by University of Copenhagen researchers Asger Andersen, Emil Hansen, Niels Johannesen, and Adam Sheridan helps us answering this question.

Asger, Emil, Niels, and Adam compare spending by Danes and Swedes. Denmark and Sweden are similar along many dimensions, but have followed different strategies when it comes to Covid-19. Denmark enforced a strict lockdown, as mentioned, whereas Sweden has kept primary schools, restaurants, bars, etc. open (though did close universities and encouraged working from home). If the lockdown was the main cause of the recession, economic activity should have suffered more in Denmark than in Sweden. Andersen et al. use individual bank-account data from a large Danish bank that operates in both Denmark and Sweden (Danske Bank) to address this question. They track spending of 860,000 individuals before and during the lockdown, studying their use of cards, cash withdrawals, mobile wallets, etc. They compare spending of Danes and Sweden from mid-March (when Denmark shut down) through early April. This figure contains their most important result:

Data source: Andersen, Hansen, Johannesen, and Sheridan (2020).

The figure shows that spending of Danes fell 29% compared to a hypothetical spending path without the Covid-19 pandemic. A 29% contraction is enormous. But, and this is the main point, spending by Swedes fell by almost as much, 25%. This means that Danes cut spending by “only” 4%-points more than Swedes. Swedes could continue visiting restaurants, schools, etc., but Swedes cut spending dramatically nevertheless. The causal effect on spending, resulting from the extra lockdown in Denmark, is 4%-points and considerably smaller than the effect of the virus itself.

One may debate whether 4% is a small or a large number. In normal times, we would say that a 4% drop in aggregate spending is large. The main cause of this recession, at least according to this study, was not the lockdown, though, but the virus. In other words, even if economies had not been shut down as much as they were, the contraction in economic activity would still have been very large.

The broader picture

The paper by Andersen et al. weighs in on an important debate about the underlying cause of this recession. Is it due to a reduction in supply or demand? Their results indicate that the demand effect is the important one. Spending drops even when supply is less constrained.

But the strict lockdown in Denmark did cause an extra 4%-point drop in spending. Was it worth it? Nobody knows, but research from the MIT (Link) on the 1918 pandemic indicates that areas in the US that took more drastic measures early on, in terms of social-distancing measures and other public health interventions, had stronger recoveries after the measures were eased. There is debate how strong this result is, though (Link).

If all this is true, i.e. that the lockdown was not the main cause of the recession, but the main cause was the virus itself and the fear it created, and that the recovery is stronger afterwards in countries that imposed stronger interventions, we should see forward-looking measures indicating this. Early data from the Danish and Swedish stock market seem to point in this direction, even if the evidence is admittedly very tentative and a fuller analysis is obviously needed. This figure shows the Danish and the Swedish stock markets surrounding the date of the lockdown.

Danish (OMX Copenhagen 25) and Swedish (OMX Stockholm 30) stock market indices. Vertical line indicates March 12, when Denmark was shut down.
Data source: www.nasdaqomxnordic.com

I have normalized the two stock-market indices to “1” on March 12, the day after the lockdown was announced in Denmark. The Danish and the Swedish stock markets followed more or less similar paths during March, but, since then, the Danish stock market has gained 29% whereas the Swedish market has gained “only” 20%. Again, one needs a more detailed analysis (the Danish stock market is heavily influenced by pharmaceuticals and other defensive stocks that do relatively well in downturns), but this early evidence indicates that stock market investors are more positive on the Danish stock market.

Furthermore, the number of deaths is currently much lower in Denmark than in Sweden (also on a per capita basis), which is of course also something to remember:

Denmark and Sweden vs. other countries

The idea of using credit-card and other payment-type information is great and has been used by a number of economists to obtain real-time information on the economic impact of Covid-19. Microdata indicate that consumer spending in France fell by 50% as a result of the virus (Link), in Spain by 50% (Link), and in the US by something like 50%, too (Link). It thus seems that the contraction in spending is somewhat smaller in Denmark and Sweden compared to other countries. The comments above should be viewed in this light.

In any case, a 30% or 50% drop in spending is a huge drop. But, a 50% drop in spending does not mean that overall economic activity drops by 50%. Overall economic activity includes public spending, exports/imports, etc. So, credit card transactions provide useful information about consumer spending, but cannot stand alone when judging overall economic activity.

Conclusion

At some stage, we need to evaluate carefully whether too much was shut down. Not to blame somebody, but to learn. It is important that we analyze thoroughly whether it is better to be very aggressive early on in a pandemic or whether less aggressive measures are enough. Currently, it seems that we shut down a little too much (and we are now too slow in opening up e.g. borders again), but that the price of doing so was not as high as one might have expected intuitively.