18/4/20: Singapore, Korea and Japan: Flattening into Trouble?

New cases are spiking in the 'safe haven' of #COVID19 pandemic: Singapore

And, worse, South Korea is now witnessing re-infection of those who have previously tested positive for coronavirus: 160 people who have been previously confirmed as having recovered from coronavirus have now tested positive again.

In Japan, that 'successfully' flattened the curve in the past, the healthcare system is now running out of ICU beds. So, many "Japanese emergency rooms are even turning away patients suffering from strokes, heart attacks or external injuries" per Axios: https://www.axios.com/japan-singapore-coronavirus-infections-a617efde-3e04-4baf-9a65-377f10454acf.html. Japan has also hit a second peak this week:

While the second peak is lower than the first one, 5 day total new cases around the previous peak was 3,349 against the current peak of 2,706: the difference not as big as would be required not to strain the resources of the healthcare system already carrying previous peak patients.

17/4/20: Error Runs in COVID19 reported data

In my previous post, I referenced some preliminary stats relating to my analysis of significant outliers in the data on the number of cases reported by different countries (see: https://trueeconomics.blogspot.com/2020/04/17420-covid19-updated-charts-and.html). Here are more detailed results:

By country (listing only countries with > 5,000 cases as of April 17, 2020):

And a summary set of statistics (top part is for countries > 5,000 cases and bottom part for countries with > 1,000 cases):

By way of explaining: I have used two methods for detecting observations of 'suspect quality' or 'outliers':

• Firstly, I am only focusing on outliers below the 'normal reporting trend' (potential under-reported observations);
• Secondly, I use two criteria (labeled 1. and 2. in the tables above): 1. relates to the cases where an observation is below the trend and reported day count is < 20 cases; 2. relates to the cases where an observation is below the trend and reported day count is < 50

In all of the above, I am only looking at 'suspect' observations after the date when the country in question reported its first 50 or higher daily count. The reason for this is that it is a commonly accepted view that during the early stages of contagion (small number of cases reported daily), the data does not exhibit a trend.

Final explanation: for trend, I used country-fitted power law trends.

Feel free to draw your own conclusions about different countries, based on this data, but for those interested in my insights:

Highest death rate so far on per capita basis is observed in 

• Belgium at 425.2 persons per 1 million of population, with decent quality of data (potential error range of 0%-9.5%)
• Spain at 409.4 persons per 1 million of population, with very strong data quality (0%-2.3% potential error range)
• Italy at 366.9 persons per 1 million of population, with zero potential error in cases reporting
• France at 267.5 persons per 1 million of population and zero potential error in reported cases
• UK at 206.5 persons per 1 million of population and zero to 2.5% potential error in reported cases.

The above results broadly remain unchanged when one controls for duration of the contagion period (number of days since > 50 cases were reported for the first time).

Highest rates of infection (per 1 million of population) have been recorded in

• Spain - 3,913
• Switzerland - 3,129
• Belgium - 3,048
• Italy - 2,796
• Ireland - 2,743

Adjusting for the days since the onset of contagion, the rates of infection are the highest in:

• Spain - 91 per day in contagion stage
• Ireland - 85.45
• Switzerland - 74.51
• Belgium - 72.56
• Portugal - 53.9

Adjusting for the days since the onset of contagion, the rates of infection are the lowest in:

• India 0.37
• China 0.67
• Indonesia 0.69
• Pakistan 1.03
• Japan 1.72

17/4/20: COVID19 Updated Charts and Outliers

Updating two charts for #COVID19 pandemic today:

First: US vs EU chart:

Second: Russia chart:

Since I included no commentary on Russian data in the chart itself, it is worth noting that data so far indicates no data suppression or mis-reporting. This is confirmed by analysis of 'outliers' in the data. I have looked at all countries with > 1,000 cases reported and considered observations on cases reported that fall out of trend line from the time when the country cumulated cases counts reached > 50 cases. For example, if a country reported 127 cases in day T, followed by 139 cases in day T+1, and suddenly showed 0 cases in T+2, followed by 99 cases in T+3, the date of T+2 was marked as an 'outlier'. I ignored all cases where 'outlier' suspect dates were above 20 cases, even if the number was still outside the range of the trend-defined 'norm'.

Note: these outliers can be a function of tests arrivals dates, availability of tests, hospitals reporting dates and other differences that have nothing to do with 'Government manipulation'. All in, 43 countries out of 77 with more than 1,000 cases have reported at least one outlier.

Russia had 3.45% of days reporting appearing as extreme outliers. 30 out of the total 77 countries on the list had higher percentage of outliers days than Russia. Median for 77 countries was 2.9%, mean was 5.9% and STDEV was 8.6%.

Only two of these countries, namely Russia (3.45% of observations countable as outliers) and China (13.3% of observations being outliers), has been accused in the Western media of releasing politically manipulated data. China, of course, has a very high percentage of observations that can be identified as outliers, while Russia is, basically, middle-of-the-road.

16/4/20: Lessons in Corporate Finance: COVID19

My article summing up some corporate finance lessons from the COVID19 crisis is now available at The Currency: https://www.thecurrency.news/articles/14752/as-we-rebuild-the-economy-we-need-to-escape-the-perilous-spiral-of-corporate-debt.

16/4/20: The BRICS+ challenge to institutional unipolarity and U.S. hegemony 2020 Lecture

My slides from the talk I gave yesterday to the MA in Non-Proliferation and Terrorism Studies students @MIIS on the COVID-updated topic of challenges to Pax-Americana in post-Bretton Woods institutional frameworks (IMF, WB, etc). You can click on each slide to enlarge.

16/4/20: Four Weeks of True Unemployment Numbers: #Covid19

The U.S. has added 5.245 million more unemployment claims in the week ending April 11, 2020, with additional 9,000 claims added to the April 4, 2020 week total. In summary,

• Week ending March 21: official unemployment figures rose 3,307,000
• Week ending March 28: new claims 6,867,000
• Week ending April 4: new claims 6,615,000
• Week ending April 11: new claims 5,245,000

Four weeks total is now 22,034,000. As noted here: https://trueeconomics.blogspot.com/2020/04/1342020-four-weeks-of-unemployment.html last four weeks of increases in unemployment in the U.S. have fully erased all cumulative jobs gained during the 2009-2019 'recovery' period.

This is by a mile not a fully accurate picture of true extent of jobs losses. As noted by the researchers in the https://bfi.uchicago.edu/insight/blog/key-economic-facts-about-covid-19/#unemployment-rate: many unemployed do not seek unemployment benefits, opting to drop out of the labor force instead. Why?

1. Eligibility for unemployment assistance is quite restrictive in the U.S.
2. States' unemployment support systems are both cumbersome and severely overloaded in the present environment.
3. Many unemployed fear Federal retribution against their migrant spouses (including legal migrants) and many are themselves on green cards, making them a potential target for removals.
4. Many unemployed become severely discouraged by the lack of potential jobs to continue job-seeking.

University of Chicago researchers used data from Nielsen survey to estimate the impact of early stage Covid pandemic on labor force participation rates. These numbers imply a drop in labor force participation from the officially-reported 64.2% to 57%. 

The research conducted through April 8th suggested that some 20 million Americans have lost their jobs due to COVID19. Adding to these 3 days to get us through April 11 would have pushed the total number of unemployed to around 3,140,000-3,969,000 more unemployed to the 22,034,000 total reported above. Splitting the difference, we can estimate new claims filed, pending and not filed due to reasons (1)-(4) above at closer to 25,500,000. 

My estimates are roughly in line with those prepared by Alexander Bick of ASU, who estimated (https://azbigmedia.com/business/unemployment-rate-jumps-from-4-5-to-20-2-asu-analysis-shows/) that through the second week of April:

• The employment rate decreased from 72.7% to 60.7%, implying 24 million jobs lost
• The unemployment rate increased from 4.5% to 20.2%
• Hours worked per working age adult declined 25% from the second week of March.

14/4/20: Re-Opening America: A Long Road Ahead

In our Financial Systems class, yesterday, we were discussing the potential trajectories for 'exit' from COVID19 restriction and easing of economic constraints. Handily, yesterday, Morgan Stanley published this analytical timeline of the pandemic evolution:

Their analysis is based on the following assumed timings:

1. They expect U.S. coastal regions to peak in the next 3-5 days (so March 15-17),
2. The rest of the U.S. will lag these by "around 3 weeks", leading to a "second peak" that promises to be not as severe as the first peak.
3. The MS are expecting the second peak to result in the US cases peaking at x4 China and x2 Italy.
4. MS therefore describe the U.S. trajectory as having "a very long tail".
5. Based on comparisons to Korea testing, the MS research suggests the earliest 'reopening' date for the U.S. as mid-to-late May.

Here is MS note on re-opening:

Bleak. 

Key takeaway on the future developments: "only a vaccine will provide a true solution to this pandemic" and that means that we are likely to see - best case scenario - scaled delivery of the vaccine for the 2021 flu season. 

This is a long road ahead...

13/4/20: Four Weeks of Unemployment Spikes: U.S. Jobs Losses in #Covid19

COVID-19 social toll: according to Deutsche Bank Research, since the end of the 2008-2009 Great Recession through mid-March 2020, the U.S. total new jobs creation amounted to ca 22 million jobs. Since then, the economy has lost over 16.8 million jobs over the first three weeks of the pandemic, and according to the DB forecast, the U.S. is now on-track to lose 25 million jobs over the four weeks, once last week numbers come in.

• Week ending March 21: official unemployment figures rose 3.3 million
• Week ending March 28: official unemployment claims rise 6.9 million
• Week ending April 4: additional 6.6 million new unemployment claims
• Week ending April 11: ???

Note: claims filed do not fully reflect actual unemployment levels in the economy. In fact, they underestimate, severely, the true extent of unemployment.

Now, remember, the Millennials entered their careers in the periods of the Global Financial Crisis, the Great Recession and the Eurozone debt crisis. They are now going through career maturation stage (faster growth in income stage) amidst this pandemic. Or as I asked on Twitter a few minutes ago: who is going to buy Boomers' properties inherited by X-ers if the Millennials are skinned?..

11/4/20: Covid19 vs Seasonal Deaths: End of an Argument

A large number of social media pontificators have been making various claims that COVID-19 pandemic is in some ways related to the seasonal flu. One of the arguments made in this context is that the pandemic-related deaths are similar to those produced by a seasonal flu and therefore do not warrant drastic measures deployed by the governments around the world.

Setting this argument to rest, the NY Times have published this analysis: https://twitter.com/sangerkatz/status/1248685404775239680?s=20 with an associated chart:

Others make an argument that people dying from COVID-19 are somehow the same people who would have died from a different condition anyway, without the virus pandemic.

Given the levels of utilization of hospital beds in countries like France, Italy, the UK, and the U.S., and in fact across the entire range of advanced economies, it is hard to imagine how anything about the COVID-19 pandemic can be considered at even remotely related to 'normal' or 'seasonal'.

9/4/20: Updated: US vs EU28 Covid Cases and Deaths

US vs EU28 Covid cases and deaths update:

Note 1: adjusting for the onset of the Covid cases, US is lagging EU by 7 days. 
Note 2: Any comparatives between the U.S. and EU28 across the disease progression time line (with lags as noted in the Note 1 above) is hazardous, due to differences in methodologies of accounting for death rates earlier on in the pandemic as opposed to the current methodologies.

Currently, the U.S. is not on a trajectory/trend to catch up with the EU28 in terms of deaths within the next 10-12 days. Given the uncertainties in the rates of change in both new cases detection and death cases, there is no feasible accuracy in attempting to predict the rates of deaths convergence for the US at this point in time. That said, U.S. deaths have increased at an average rate of 16% daily in the last 5 days, while EU28 deaths increased at an average rate of 7% daily.

9/4/20: Ifo Eurozone Forecast Q1-Q3 2020: Covid19 Impacts

Germany's ifo Institute joint forecasts for Eurozone growth are out today. Bleak reading. The forecasts below assume that Covid-19 restrictions will be gradually lifted over the summer 2020.

Seasonally and working-day adjusted GDP growth:

From ifo forecast: "The economy in the euro area is expected to slide into a deep recession in the first half of 2020:

• GDP growth is forecast to be -2% in Q1 and -10% in Q2, followed by a recovery in Q3 with +8%. 
• Due to the lack of comparable events in the last decades and the unpredictable course of the pandemic, these estimates are subject to substantial uncertainty."
• "Gross fixed capital formation is also certain to decline, with -2% in Q1 and -10% in Q2, due to supply disruptions, planning uncertainty and a preference for liquidity."
• "Foreign demand is likely to contribute negatively to growth, as a result of the euro area’s exposure to recessive international trade and a struggling global economy."

Inflation environment:

Headwinds and risks: 

• "A more unfavorable course of the pandemic would require longer and possibly stricter containment measures...
• "Despite massive liquidity provision by governments and central banks, a prolonged downturn would then lead to liquidity strains in the economy. 
• Increased debt levels associated with low income flows and asset devaluations are likely to lead to solvency issues for thinly capitalized corporations and private households.
• An ensuing rise in loan defaults could in turn lead to problems in the banking sector." 
• "A resurgence of the European debt crisis on a large scale thus constitutes a non-negligible risk to the forecast."

8/4/20: Ifo Institute Germany Forecast for 2020

A surprisingly 'positive' forecast for Germany from ifo Institute this morning:

While GDP contraction for 2020 looks sharp at -4.2 percent y/y, unemployment figures appear rather robust and employment levels seem to be only weakly impacted. Forecast for current account implies subdued global demand shocks. The swing in the fiscal position is roughly 6.5 percent of GDP, reflecting emergency supports measures. This is significant, and underpins shallower expected effects on employment and unemployment, as well as no deflationary dynamics in labour costs.

My view: Germany entered the pandemic crisis with already weak economy. 2019 growth at 0.6 percent was shockingly weak, with the economy skirting recession. Massive strength in the current account was reflective of weak domestic demand and the economy dependent on growth momentum globally. This momentum is now severely disrupted, and I do not expect robust global recovery outside domestic demand. In other words, my view is that worldwide exports are unlikely to rebound robustly in H2 2020, putting severe pressure on net exporting economies, like Germany and Italy.

So, whilst 4+ percent drop in full year GDP might be fine, I would expect closer to 5-5.5 percent decline (reflective of weaker prices), and much more pronounced impact on unemployment and employment levels.