Sweden has been the ‘outlier’ in terms of handling the global Covid-19 pandemic as the country’s health authorities have relied on a more laissez faire approach which have relied on the common sense of the Swedish population rather than on draconian government measures such as lockdowns and mask mandates.

In that sense Sweden has been different than basically every other country in Europe and Northern America.

Consequently, Sweden has also become the benchmark case to compare other countries to.

Unfortunately from day one of this pandemic it has all been about counting the number of people who have died from or with Covid-19. The countries with the least Covid-deaths are the “winners” – at least according to the media, commentators and politicians.

I must say I have long ago come to the conclusion that it makes very little sense making such comparisons without taking what I have termed ‘health fundamentals’ into account.

We for example now well know that the elderly and the obese are much more at risk from dying of Covid-19 than the young and healthy. Therefore, it makes little sense for example to compare a country with a lot of old people like Italy or the UK with a country with a young population like Pakistan. Or an obese nation like the US with a much more fit nation like Japan.

Hence, in my view the outcome in terms of Covid-deaths is mostly explained by these health fundamentals rather than by policies, behaviour or culture. These later factors may have an impact in the very short-term (weeks or months) but over months they are much less important than health fundamentals.

But one thing is to look at Covid-deaths and compare them across countries, but what about total mortality? After all the important thing really isn’t Covid-19. The important thing is total mortality (and age-adjusted mortality).

Thinking about this got me to look at Swedish mortality over the last couple of years. In this blog post I will share my main conclusions from looking at the numbers.

I have looked at daily deaths in Sweden from 2015 and until today.

Daily deaths spiked in April-May 2020

Lets start with the clean numbers for daily deaths for each of the years since 2015.

The years from 2015-19 are different shades of grey while 2020 is is red.

The first thing we notice obviously is that starting from around mid-March 2020 daily death numbers started to rise fairly sharply. In the same periode in the previous years the ‘normal’ seasonal pattern had been a gradual decline in daily deaths.

So there is no doubt that the Covid-19 pandemic clearly is visible in the numbers. Furthermore, this period of “excess deaths” lasted until around the beginning of June.

However, what we also see if we take a closer look is that prior to the pandemic had hit in mid-March the number of deaths had actually been rather low compared the previous years and similarly from around mid-May deaths have again dropped below the average number of deaths in prior years.

This is an indication that there was a significant amount of fragile elders who had survived longer than normally would had expected.

Therefore, some of the excess deaths during the March-May period might therefore be explained by “too few” deaths during January and February compared to what we would have expected.

In fact if we look at 2019 we see that year had somewhat lower general mortality in Sweden normally – further supporting what my fellow Danish economist friends Christian Bjørnskov and Jonas Herby have called the ‘dry tinder’-effect.

In the graph below we see this fairly clearly. Looking at the last decade we see a pretty strong ‘dry tinder’-effect – if the number of deaths is high one year (eg 2012) then change in the number of deaths will likely be negative the following year (eg 2013).

Based on this simple historical relationship we should expect thee dry tinder-effect to have had around 2,300 deaths to the total number of deaths in 2020 due to the ‘low base’ in 2019.

However, even if we ignore the ‘dry tinder’-effect the mortality rate in Sweden during 2020 has been a lot less dramatic than some pundits would have you believe.

We can see that by simply looking at the total number of people who has died in Sweden so far this year.

We see that during March-May there was a considerable excess mortality so by the end of May total deaths was more than 10% above normal levels.

However, since then we have see a gradual return towards ‘normal’ and presently the total number of deaths if around 4% above normal.

In total numbers this means around 3,000 more Swedes have died in 2020 than ‘normally’, which is less than half of the number of people who has officially died with/from Covid-19.

This to me is a strong indication that the Covid-19 pandemic more than anything has moved forward deaths by weeks or months rather than by years and it is an indication that Covid-19 to a considerable extent has ‘replaced’ other ‘normal’ causes of dead among the old such the flu or
pneumonia.

In fact if the trend from recent months continue during the next couple of months we might we the entire excess mortality for the ‘pandemic year March 2020-March 2021’ disappear.

So yes, a deadly pandemic hit Sweden in 2020, but if one steps back a bit and look at the total number of deaths for the entire year it to see the pandemic.

A way to illustrate that is to forecast how many deaths in total we will see in 2020.

I have done that by assuming that we will see the numbers of deaths in the reminder of the year as normal then we are likely to see around 94,000 deaths in total for all of 2020.

That will mostly likely make it the most deadly year over the last decade but it will none the less be fairly close to the number of deaths in 2012, 2017 and 2018. Sweden was as fairly hard hit like other European countries by influenza pandemics during these years.

Mortality is higher in Denmark than in Sweden

The number of deaths with/from Covid-19 in Sweden has been considerably higher than the other Nordic countries, but what about total mortality.

As a Dane (of Swedish descent) I of course can’t help comparing Swedish and Danish mortality.

The graph below shows the number of daily deaths in Denmark and Sweden adjusted for population size.

It is clear that Sweden was much harder hit by the pandemic in March-May than Denmark.

However, it is also clear that Swedish mortality was considerably lower both period to the pandemic and from May and onwards.

In fact if we look at the total number of deaths in Denmark and Sweden more Danes have died than Swedes adjusted for population size.

The reason for this simply is that the ‘normal’ mortality rate is higher in Denmark than in Sweden. Or said, in another way – a lot more Danes die from cancer than Swedes die from Covid-19.

Mortality has been high, but certainly not catastrophic

Every death is tragic and Sweden has certainly been hard hit by Covid-19. However, when we take a closer look at Swedish overall mortality in 2020 it is also clear that 2020 hardly is the kind of disastor that some pundits would like it into being.

Covid-19 is not “just a flu”. It is certainly more deathly for particularly the elderly. However, in terms of the impact on total Swedish mortality it has more or less been on a comparable level to the ‘bad flu-years’ 2012, 2017 and 2018.

Furthermore, while Sweden has been hard hit by Covid-19 the overall mortality rate is still lower than in neighboring Denmark, where Covid-19 hardly is visible in the mortality rate.

All data in this blog post is from the Swedish statistics office (SCB) and from Statistics Denmark.

Contact:

Mail: lacsen@gmail.com

Phone: +45 52 50 25 06.

This is the number of new daily deaths from/with Covid-19 in Sweden and the Czech Republic.

Source: Here.

The two countries are similar in many ways – the population is just over 10 million in both countries; the average age is around 41 and the number of elderly people as share of the population is also pretty much the same (3-4% of the population is over 80 years old).

Life expectancy in Sweden, however, is 82 years while it is 79 years in the Czech Republic.

The immigrant population in Sweden is much larger as share of the population than is the case in the Czech Republic.

These two factors make it more likely that Sweden will see more Covid-19 deaths than the Czech Republic as we know that the mortality form Covid-19 increases sharply for those older than 70 years old. The average age of the dead from/Covid-19 in Europe is around 80 years.

On the other hand, the Czech Republic is in the top-10 of the most obese countries in Europe and we know that obesity strongly increases the risk of dying from Covid-19. Sweden on the other hand is one of the least obese nations in Europe.

More and more evidence show that vitamin D deficiency is highly correlated with Covid-19 deaths (see here).

Sweden does not have a major problem with vitamin D deficiency, but immigrants in Sweden do have serious problems with vitamin D deficiency as do many residents in nursing homes. The data I have seen on vitamin D deficiency in the Czech Republic indicates the problem is bigger than in Sweden.

These factors indicate that we should expect more Covid-death in the Czech Republic than in Sweden.

When the pandemic started to spread in March the Czech Republic went into a rather draconian lockdown. Sweden as we know did not.

Source: here.

Covid-death rose much more in Sweden initially and the Czech Republic was celebrated by many as an example of how to avoid death – just lockdown the country.

However, now things are changing. New daily deaths in Sweden remain very low, while they are rising fast in the Czech Republic and the country seems to be heading for another lockdown.

Judging from Apple Mobility data economic activity is now again falling fast in the Czech Republic, but not in Sweden.

Source: Here.

That being said we also need to get things into a proper perspective. In 2018 more than 3000 Czechs died from the ‘normal’ flu (around 2000 Swedes died).

Presently 5900 Swedes have died with Covid-19. In the Czech Republic 1200 has died with Covid-19.

Looking ahead it is worth noticing that Sweden in most rankings of the quality of healthcare systems is top-5 in the world – the Czech Republic is way behind. Similarly, Swedish GDP per capita is doble that of the Czech Republic.

In terms of government efficiency and governance Sweden is top in the world. On the Corruption Perception Index Sweden is number 4. The Czech Republic is 44.

These factors would also indicate more Covid-deaths in the Czech Republic than in Sweden.

So all in all if we look at what I would call ‘health fundamentals’, which include demographics and socio-economic factors there seem to be little reason to expect less Covid-19 deaths (on a per capita basis) in the Czech Republic than in Sweden.

What is different is the timing – Sweden allowed the virus gradually to spread through society (as we normally do with the flu) and consequently ‘front-loaded’ the deaths.

This would have been a mistake if there was a cure just around the corner, but realistically it is unlikely that we will see widespread Covid-vaccination before well into 2021.

The Czech Republic through draconian lockdown policies ‘postponed’ some Covid-deaths, but now it is coming back. Governments cannot micromanage a virus. The Swedish health authorities realized that. The Czech government did not.

I have many friends in the Czech Republic and dearly hope that death rates will soon stop rising, but we are entering winter and judging from the ‘normal’ seasonal flu pattern we should expect deaths to continue to rise until the spring – whether it is Covid-19 or the flu, but I hope I am wrong.

Since the outbreak of the Covid-19 pandemic I have closely been monitoring the data for the number of deaths and infected across different countries and I have spend considerable time trying to estimate statistical models to explain variations in deaths and infects across different countries.

It quickly became clear to me that relative few factors could explain this variation and back in April I wrote a blog post in which I claimed that ONE factor could explain most of the variation in Covid-19 deaths across countries.

That factor was age or rather the number men older than 80 years as share of the male population.

There really wasn’t anything overly surprising about that as it fast became clear that very few young people or children died from Covid-19 and the average age of the Covid-19 victims was around 80 years old in most countries.

However, I was really never satisfied with this explanation. There had to be more to the story.

The next factor I looked at – but never published my results of – was obesity. Here the results also were pretty clear. The share of the population who are obese seems to be a fairly strong indicator of Covid-19 mortality. This is also confirmed from numerous ‘micro’ studies looking at individual hospitals or cities (see here for an discussion).

But that still isn’t enough to explain the Covid-19 ‘mystery’ as we can also note what we in economics would call ‘stylized facts’ about Covid-19:

• There seems to be a strong – flu-like – seasonality in Covid-19 cases, which seems to be linked to latitude (see here and here).
• There is a significant over-representation of Covid-19 cases and deaths among blacks in the US (see here) and the UK (see here) and among black immigrants (mostly Somalis) in for example Sweden and Denmark (see here), while blacks in the Southern Hemisphere does not seem to be overly hard hit by the Covid-19 pandemic.
• A majority Covid-19 deaths in the developed countries seem to have happened in nursing homes (see here).

I have no medical training and certainly was not familiar with the academic literature on the importance of vitamin D deficiency in general health, but I have been catching up fast and it is now pretty clear to me that if we look at all of these groups – the elderly, particularly those in nursing home who spend a lot of time indoors, blacks living in Northern hemisphere and the obese they all tend to suffer from significant problems with vitamin D deficiency. The same of course is the case with the seasonality – and there is a well-established relationship between the seasonality in flu and seasonal variation in vitamin D (see for example here).

It is for example a well-established fact that particularly the elderly in Spain and Italy suffer from vitamin D deficiency (see here) and numerous studies have shown that African immigrants in Scandinavia also suffer from vitamin D deficiency (see here).

So the only logical thing would be to look at variation in Covid-19 deaths across countries and try to explain that with the share of the population who suffers from vitamin D deficiency.

However, this is where we run into problems – it is very hard to come across comparable data on this across countries. There is some, but there is still too much problems with the data to do a proper statistical study of enough countries (see here for an example nonetheless).

So instead I decided to look at something else – the variation in Covid-19 deaths across US states and the share of the population in each who are African-American.

The reason for this is that numerous studies have shown that as many as 80% of all African-Americans suffer from vitamin D deficiency (see here) so if vitamin D deficiency really is a key explanatory variable in terms of explaining Covid-19 mortality then we should expect that Covid-19 mortality rates should be higher in US states with a larger share of population who are black.

You can judge for yourself by looking at the graph below.

As we see there is a very strong correlation between the share of the African-American population and Covid-19 mortality rates across US states.

In fact it is by far the strongest statistical relationship I have been able to find among all the variables I have been looking at (including age, obesity, population density and longitude).

Obviously this relationship can be due to a number of factors – among them numerous socio-economic factors – but to me at least this is further indication that vitamin D deficiency is an extremely important variable in understanding variation in Covid-19 mortality across different groups of people and across countries.

And this leads me to the conclusion that maybe we should do less testing for Covid-19 and more testing for vitamin D deficiency and a significant part of the public health response to the Covid-19 pandemic should be to focus on protecting groups with vitamin D deficiency and treating it.

The long awaited update of the Federal Reserve’s Monetary Policy Strategy has just been announced.

Here are the key points:

• On maximum employment, the FOMC emphasized that maximum employment is a broad-based and inclusive goal and reports that its policy decision will be informed by its “assessments of the shortfalls of employment from its maximum level.” The original document referred to “deviations from its maximum level.”
• On price stability, the FOMC adjusted its strategy for achieving its longer-run inflation goal of 2 percent by noting that it “seeks to achieve inflation that averages 2 percent over time.” To this end, the revised statement states that “following periods when inflation has been running persistently below 2 percent, appropriate monetary policy will likely aim to achieve inflation moderately above 2 percent for some time.”
• The updates to the strategy statement explicitly acknowledge the challenges for monetary policy posed by a persistently low interest rate environment. Here in the United States and around the world, monetary policy interest rates are more likely to be constrained by their effective lower-bound than in the past.

This is pretty much as expected, but it is nonetheless a significant change relative to the earlier strategy.

Most important clearly is the fact that the Fed has changed its inflation target from a regular inflation target to an ‘average inflation target’.

Under a regular inflation the Fed would let bygones be bygones and if the target has been undershoot or overshoot it would not have implications for the future path of monetary policy. However, under an average inflation target the Fed will try to ‘payback’ if the target has been overshoot or undershot in the previous period.

This obviously is something similar, but not entirely the same as a level target where the Fed would have targeted the price level.

Market monetarists like Scott Sumner, David Beckworth obviously for years have argued that the Fed should implement a NGDP level target. Unfortunately the Fed has not chosen to follow that path, but with an average inflation target we certainly have moved closer so I personally welcome this decision and I believe it will be helpful in securing nominal stability going forward.

The Fed is now de facto targeting 2.5% inflation for the coming years

The Fed has since 2012 had an official 2% inflation target (measured as core PCE inflation). However, the Fed has also consistently failed to hit this target and if we look at 5 and 10 year moving averages of inflation then inflation has been close to 1.5% rather than 2%.

Consequently if we look forward the Fed needs to payback by having inflation above 2% for a sustained period.

The Fed has not said what kind of time interval with will be looking at but i think it would make sense to look at a 5-year moving average.

Over the past year PCE core inflation has average around 1.5% and if we also assume the ‘payback period’ is five years then this would imply a 2.5% de facto inflation for the coming five years.

If we compare this to market expectation then we see that Fed monetary policy is indeed too tight as 5-year market inflation expectations are presently around 1.6% and if we further correct for the fact that market inflation expectations refers to headline CPI inflation rather than core inflation then the difference is likely a further 0.5%.

Said in another way – if the Fed policy change would be 100% credible we should expect market inflation expectations to jump to close 3%. This hasn’t happened…yet, but let see if Fed chief Jerome Powell dare follow through on his announcement today.

No matter what it is hard not to see today’s announcement has a de facto announcement of further monetary easing from the Fed. Not surprisingly global stock markets have risen on the news and the dollar has weakened. If Powell follow-through we should expect a lot more of that going forward.

And yes, in terms of my forecast that US unemployment will drop below 6% by November this certainly helps.

If you are hear about monetary policy or international economics this post is not for you.

Instead this is about ‘sports analytics’ or rather about ‘basketball analytics’.

This morning I was invited to give a presentation on the use of data and analytics at the Filipino basketball network HOOP Coaches International.

You can watch my presentation here:

On July 27 I gave a Webinar-Presentation at Buckingham University’s Institute of International Monetary Research on the Covid-19 crisis and whether this crisis and the particularly the policy response to the crisis will be deflationary or inflationary.

You can watch the presentation here.

Why have epidemiological forecasts been so wrong and what to do about it

If we look at the forecasts, we got from epidemiologists initially in the Covid-19 pandemic it has turned out that they have massively wrong. While tragic the number of people who has died in this pandemic has been much lower than forecasted.

The reason given by epidemiologists then is that that is because of interventions – lockdowns. But then you made the wrong kind of forecast – you forgot to forecast what would happen IF lockdowns were implemented.

Furthermore, how do you explain the numbers in South Korea, Taiwan and Japan? There were no lockdowns (until recently) and we haven’t seen a massive death told, which was forecasted by the kind of epidemiological models used for example by the epidemiologists at the Imperial College in the UK.

Similarly, in Sweden with no lockdown, which as the only European country did not have a lockdown. Despite of that the death toll in Sweden has not in general been higher than in other Western European countries. It should of course be mentioned that Sweden’s Covid-death toll has been higher than in the other Nordic countries, but also here government epidemiologists massively overestimated the number of deaths and the need to hospitalizations even after claiming to take the lockdown effects into account.

And the Covid-19 pandemic is not the only pandemic where epidemiologists have been wrong – on the upside.

They were wrong (generally) very wrong on HIV/Aids, Ebola, Swine flu and SARS.

The death toll from these pandemics never reached the levels predicted by leading epidemiologists and there never was the kind of “super spike” in number that standard epidemiological models seem to predict.

We need to take human behavior and technological progress into account

There are probably (at least) two reasons why the standard epidemiological models tend to be wrong in my view.

First, of all as economists have pointed out since the HIV/Aids pandemic standard epidemiological models ignore human behavior. People dislike being sick and hence will change behavior if they know that will reduce the likelihood of being infected with Aids or Covid-19.

The literature on economic-epidemiologic goes back at least to work done by among others University of Chicago economist Tomas Philipson in the 1990s on HIV/Aids and the present pandemic has spurred a lot of new research on this topic. Another example is professor at Cambridge University Flavio Toxsvaerd’s excellent work on what he has termed ‘equilibrium social distancing’.

Furthermore, numerous new studies clearly confirm the thesis that human behavior is very important in terms of mitigating the spread of a virus like Covid-19. American economist William Luther in a recent paper shows that people reacted to the news of the spread of Covid-19 before US States started to implement lockdown.

The same goes for Sweden where there has been no government mandate lockdown and for example school have remained open, but people has nonetheless significantly changed behavior.

The change in behavior before government mandate lockdown has also been shown in a very good blog post by Catarina Midões from the research institution Bruegel. She shows that Google searches for ‘restaurants’ was way down in a number of European countries well before lockdowns were imposed by governments around Europe. The graph below from Midões’ blog post illustrates this well.

A second reason why epidemiological models tend to overestimate the death toll from pandemics is that they ignore technological progress – or rather medical progress. The Aids epidemic of course is a prime example of this, but it is also likely to be the case with Covid-19.

Here we have to see medical progress in a broad sense – it could for example be that we become better at protecting the people most at risk – for example the elderly or the obese – and we get better at treatments. This does not have to be major medical breakthrough but gradually nurses and doctors as they learn small things will adjust their treatment of Covid patients and that on its own will gradual reduce mortality.

This is similar to the critique economists have had for centuries against environmental doomsayers like Thomas Malthus, Paul Ehrlich and Greta Thunberg. The world is not coming to an end as humans adapt all the time and are highly innovative.

Concluding, one can say that epidemiological forecasting today is done like weather forecasting, but it should be done a lot more like economic forecasting – you can’t change the weather by carrying an umbrella, but you can change the course of a pandemic by practicing social distancing.

If there are a pandemic people will react to that – during the present pandemic people are practicing social distancing and extra hand washing without government intervention. We just all want to reduce risk – at the lowest cost.

However, there likely is a more fundamental problem – economists would call it a Public Choice problem or a principle-agent problem

Epidemiologists don’t necessarily have the incentives to be right

Most epidemiologists are government employees – either working for the health authorities or government-funded research institutions.

They are generally not paid to be right. They are mostly paid to do reporting and research – not accurate forecasting.

Furthermore, a government-funded epidemiologist will not be rewarded for making a too optimistic forecast, but will likely receive a lot more funding and attention if they are making doomsday forecasts.

I am not claiming this is done on purpose, but incentives work – also in research and economists would make the exact same mistakes if they worked in the same ‘reward-system’.

However, if we compare epidemiological forecasting to macroeconomic forecasting there is one crucial difference and that is competition.

There are not one or two economists making forecasts on the US or Euro zone economies – there are a many. That means that forecasts can be compared.

Furthermore, we have the financial markets to tell a story. In February the global equity markets started telling the story that the global economy would take a major hit.

If macroeconomic forecasters had ignored that information then they would have been too optimistic. Similarly, now – markets are telling us that the recovery will be quite fast.

That is challenging macroeconomic forecasters making very gloomy forecasts – they have to explain their model assumptions and why they believe markets are wrong.

Markets might indeed be wrong from time to time, but they are unbiased and we also know that it is very hard to find anybody who consistently can beat makes – so if you are a professional macroeconomic forecaster forecasting something very different from what markets are “predicting” then your clients and others will surely question whether your forecast is off.

Furthermore, economists argue in public all the time about their forecasts, which means that policy makers and investors get a very good impression of different scenarios for the outlook for the economy. I haven’t seen a lot of debate among epidemiologists – at least not in public – about how we should expect the Covid-19 pandemic to develop.

It is, however, also well-known that government institutions such as Finance Ministries and the IMF make fairly bad forecasts as they often are politicized (see here and here). For that reason, these forecasts are mostly ignored by market participants.

To me it seems like most epidemiological forecasts are quite similar to economic forecasts made by Finance Ministries – and even worse because Finance Ministries’ forecasts will always be compared by the media to independent forecasts.

We don’t see this to nearly the same degree in epidemiological forecasting as there really isn’t a private market for pandemic forecast – at least not yet.

So to repeat:

1) epidemiological forecasting is not done in an institutional framework where precision is rewarded enough and where doomsday forecasts will get more attention and ‘middle-of-the-road’ forecasts.

2) There isn’t enough competition – there are simply too few epidemiological forecasters and too little competition.

If Covid-19 and other pandemics stay with us and continue to shock major parts of the global economic system going forward then this will change as it will become profitable to do good epidemiological forecasting. (In fact, there might be a business idea here and if you are interested in this drop me a mail: LC@mamoadvisory.com)

However, at the present good epidemiological forecasting isn’t especially rewarding for epidemiologist. Alarmist forecasts on the other hand are.

Please note that I am not claiming economists make good forecasts or that macroeconomic forecasting isn’t often very wrong. It is.

However, macroeconomic forecasting continues to develop and adjust in the market place and being right will yield great economic rewards, which pushes forecasters to do a better job.

We need a market for forecasting pandemics

However, we have something a lot better than economists at doing forecasting – and that is markets.

Financial markets being the ‘wisdom of crowds’ is unbiased and generally (weakly) efficient. That means they are a quite good guide for the direction the economy will take.

This is also why I for years have argued that policy makers should utilize so-called prediction markets to make decisions and why I for example have advocated that monetary policy should be focused on market inflation expectations rather than model-based forecasts.

Generally, we need prediction markets to help policy makers make the right decisions based on unbiased market forecasts.

That mean there would be great public benefit from having ‘global warming’ markets and a ‘pandemic market’

This of course also goes for economic policy – we need prediction markets for unemployment and real and nominal GDP. We already have ‘inflation markets’ given the existence of inflation-linked bonds. I have long argued this – see for example here.

Returning to epidemiological forecasting my point is not that ‘epidemiologists are bad” and “economists are good”. My point is that they operate in different incentive structures.

That said, forecasting economic growth over the coming 2-3 years is something “we” are used to and macroeconomic forecasting has been around forever. Each new shock is different, but not completely different. We have a lot of experience in forecasting macroeconomics.

On the other hand, forecasting the development in a pandemic means you start from scratch every time. That of course is very different and much harder than observing the same kind of shock over and over again.

But the incentive structures do help. Furthermore, the fact that we have seen a lot of “black box models” during this crisis doesn’t help. We need openness and transparency regarding model assumptions. And we need competition rather than ‘forecasting monopolies’

This is not a critique of epidemiologists, but a critique of the overall way forecasting is done and mostly how it is used to shape policies and it is a critique very similar to things I have said about economic forecasting for years.

Concluding, the world more than ever needs good epidemiologists, but more than that we need good epidemiological forecasts and that means that we as societies need to ensure that we have ‘markets’ for epidemiological forecasting rather than forecasting monopolies.

——

Contacts:

Lars Christensen, LC@mamoadvisory.com, +45 52 50 25 06.

See my profile at my Danish speaker agency here.

Warning – this is in Danish.

Her til eftermiddag har jeg haft fornøjelsen for første gang at optræde på SpeakerBee. Temaet var markederne og økonomien – primært i USA.

Jeg taler blandt andet om udsigterne for væksten og arbejdsmarkedet i USA – jeg er meget optimistisk – og for det amerikanske aktiemarkeder, hvor jeg er knap så optimistisk. Hør og se, hvordan det hænger sammen her.

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