Wednesday, May 6, 2020

6/5/20: Eurozone Composite PMI: Covid Horror Show


Final Eurozone Composite Output Index came in at 13.6 (Flash: 13.5, against March Final: 29.7). March was bad. April is worse. Final Eurozone Services Business Activity Index was at 12.0 (Flash: 11.7, March Final: 26.4), final Manufacturing PMI covered here: https://trueeconomics.blogspot.com/2020/05/4520-eurozone-manufacturing-pmis-crater.html.


1Q 2020 implied decline in Euro area GDP is at around 3.5%. 2Q 2020 start is now worse than 1Q 2020.


5/5/20: Sweden v Denmark: Covid19 experiences and outruns


For those interested, there's an ongoing debate about the benefits and costs of two different approaches to dealing with the Covid19 pandemic that are being contrasted in the case of Sweden (low level of restrictions) and Denmark (high level of restrictions). The two countries offer a decent 'natural experiment' data, due to their physical, cultural, historical and socio-economic proximities.

Peter Turchin dissects the evidence on the outcomes here: http://peterturchin.com/cliodynamica/a-tale-of-two-countries/ in a very readable and, yet, empirically rigorous analysis.

The chart above is the key, although not the only source of the insights. Lines represent a fitted model, while points represent actual data.

What is notable in the above (some of it is in Peter's post, some is not) are the following features of the data:

  1. Death rates models in Denmark trail below those in Sweden, albeit the two converge into late April and reverse in early May. We do not know why, though Peter identifies one specific potential cause: slower and lower rate of testing in Sweden. Another potential cause can be the duration of treatment differences between the two countries. A third potential one, differences in vintage/strand of the virus. Etc...
  2. Actual death rates uptick in Denmark around May 1 seem to be relative outliers to the Denmark data (we do not know why, nor do we know if these are going to become a 'new normal' or a 'new trend'). These outliers are certainly responsible for the trend lines reversals.
  3. Actual death rates in Sweden are massively more volatile than those in Denmark. This volatility is most evident in April. This should imply serious differences in the accuracy/precision of both models, with Swedish model potentially down-weighing these upward outliers (this depends on the model used, of course).
The rest of conclusions are down to you, folks.

Tuesday, May 5, 2020

5/5/20: A simple view of Globalization: some thoughts


Globalization in  retreat chart via PIIE: https://www.piie.com/blogs/realtime-economic-issues-watch/pandemic-adds-momentum-deglobalization-trend


A neat visual summary of the extent of economic openness and globalization, via trade dimension alone. The caveats here are that this only captures trade in goods & services flows (see https://fredblog.stlouisfed.org/2017/05/are-you-open/), but ignores capital flows and the extent of globalization-induced complexity within modern economic systems.

We tend to think about globalization as a mass-type measurement, where the volume or the value of flows is what matters. Alas, things are more complex. Mass measurements should be properly adjusted for risks inherent in the flows and stocks, including geopolitical risks. Imagine a flow of goods from China to the U.S. as opposed to the same volume flow of the same goods from China to Ecuador. Geopolitical risks and uncertainties, as well as non-monetary costs/values involved in the two flows are distinct. Similarly, consider a set stock of capital from the U.S. domiciled in, say, the Netherlands as opposed to, say, in Russia. Once again, even when nominal values are identical, risk-adjusted values are distinct.

In simple terms, as neat as the above chart might be, it does not even begin to reflect the VUCA/risk-indicative nature and volumes of globalization-related flows and stocks.

5/5/20: A V-Shaped Recovery? Ireland post-Covid


My article for The Currency on the post-Covid19 recovery and labour markets lessons from the pst recessions: https://www.thecurrency.news/articles/16215/the-fiction-of-a-v-shaped-recovery-hides-the-weaknesses-in-irelands-labour-market.


Key takeaways:
"Trends in employment recovery post-major recessions are worrying and point to long-term damage to the life-cycle income of those currently entering the workforce, those experiencing cyclical (as opposed to pandemic-related) unemployment risks, as well as those who are entering the peak of their earnings growth. This means a range of three generations of younger workers are being adversely and permanently impacted.

"All of the millennials, the older sub-cohorts of the GenZ, and the lower-to-middle classes of the GenX are all in trouble. Older millennials and the entire GenX are also likely to face permanently lower pensions savings, especially since both cohorts have now been hit with two systemic crises, the 2008-2014 Great Recession and the 2020 Covid-19 pandemic.

"These generations are the core of modern Ireland’s population pyramid, and their fates represent the likely direction of our society’s and economy’s evolution in decades to come."


Monday, May 4, 2020

4/5/20: Eurozone Manufacturing PMIs Crater to Historic Lows


I do not commonly cover Eurozone PMIs, but April read-out is shocking. Truly, abysmally, shocking.

From Markit release:

  • Final Eurozone Manufacturing PMI at 33.4 in April (Flash: 33.6, March Final: 44.5), so down 11.1 points m/m
  • March was bad - at 44.5 well below the zero growth line of 50.0. April came in woefully bad. 
  • Confidence sinks to record low and job losses mount
  • This was "the lowest ever recorded by the series (which began in June 1997), surpassing readings seen during the depths of the global financial crisis". 





I have covered BRICS and Global Manufacturing PMIs for April here: https://trueeconomics.blogspot.com/2020/05/4520-bric-manufacturing-pmi-april.html

4/5/20: BRIC Manufacturing PMI: April


Coronavirus pandemic has finally bitted deeply into the BRICs economic activity data, with April 2020 manufacturing PMIs coming in sharp down:


Combined, GDP-weighted average Manufacturing PMI for Brazil, Russia, India and China came in at 41.4 in April 2020, down from 49.1 in 1Q 2020 and 51.2 in 4Q 2019. Sharp declines in Brazil Manufacturing PMI (down to 36.0 in April, compared to 50.6 in 1Q 2020), Russia (down from an already-recessionary 47.9 in 1Q 2020 to 31.3 in April), and India (collapsing from 53.9 in 1Q 2020 to 27.4 in April) were also not helped by the continued weakness in China (1Q 2020 PMI was 47.2, albeit March 2020 reading was an encouraging 50.1, down to 49.4 in April). So far, the first month of 2Q 2020 shows no positive indicators for Manufacturing sectors across all BRICs.

However, even with this woeful performance, BRICs managed to post higher PMI (slower decline in the economic activity) than the Global economy. Global Manufacturing PMI in April sunk to 39.8 from 48.4 in 1Q 2020 - a drop of 8.6 points, against BRIC Manufacturing PMI sinking from 49.1 to 41.4 - a drop of 7.8 points.

4/5/20: Updated Covid19 charts


Post-weekend updated charts on COVID19:

First off, global comparatives on incidence rates and death rates:



The above chart shows lack of convincing decline in the rate of detected new cases and deaths worldwide. In the last three days, global case numbers posted another 'local peak' reading of 93.328 cases on May 2, which marks a fifth 'local peak' in the overall time series. 'Local trough' of 65,944 cases on April 28 - much touted in the media as the evidence of the pandemic moderating - has now been followed by four consecutive days of increases through May 2, and the usual declines in cases on May 3 and 4th. May 4th counts were 78,657, which ranks 18th most severe increase in overall time history of the series.

U.S. vs EU27 comparatives:



To better capture the convergence in death rates between the EU and the U.S., here is a summary chart plotting the gap in death rates per 1 million of population between the two:


In simple terms, U.S. deaths rate per 1 million of population trailed the EU27 by 31.4 points back on April 8th. This gap has now closed to 11.6 points on April 27th. Note: we have to compare U.S. and EU27 figures referencing a 7-days gap in the timing of the major pandemic dynamics on-set in the U.S. vs EU27.

Finally, an update on data for Russia and BRICS:


The pattern established in recent weeks persists: Russia continues to post higher numbers (increasing) in the new detected cases, while Russia's death rate per confirmed case remains well below the BRIICS comparatives. Russia's death rate per 1 million population is statistically within the BRIICS range.

Sunday, May 3, 2020

3/5/20: Financial Strength Across Emerging Markets


A somewhat simplified, but nonetheless telling heat map of financial strengths and vulnerabilities across emerging market/middle income economies via the Economist:


I have outlined European economies included (for some strange reason, the Baltics are not in the assessment, neither are Bulgaria, Moldova, etc). The top 9 as well as those ranked 11th, 12th and 15th are economies with no risk category at or below 'moderate'.  The bottom 15 have no risk category within a 'safety' zone.

Have fun with these...

3/5/20: Updated: The Scariest Chart in Economics


Updating one of the two 'Scariest Charts' in economics with the latest data - preliminary, through April 25, 2020:


This goes hand-in-hand with the earlier chart here: https://trueeconomics.blogspot.com/2020/05/3520-updated-shocking-wave-of-jobs.html

The speed and the depth of jobs destruction in the U.S. during the last two months has been beyond precedent. 

3/5/20: Updated: Shocking Wave of Jobs Destruction


Updating my previous post on the subject of jobs losses in the U.S. (https://trueeconomics.blogspot.com/2020/04/230420-shocking-wave-of-jobs.html):


We are now one week away from the unemployment claims filed in March-May 2020 exceeding the grand total of all jobs destroyed during all U.S. recessions between 1945 and 2019. That is, before actually exceeding the number of all jobs destroyed over all recessions over 75 years combined.

Current estimated non-farm payrolls are approximately back to 1997 levels, throwing payroll numbers some 23 years back within the span of just 2 months:


Friday, May 1, 2020

1/5/20: US vs EU COVID19 cases and deaths


Updating my data charts for EU27 comparatives to the U.S. in the number of cases, deaths and death rates:


Thursday, April 30, 2020

30/4/20: No, Healthcare Systems are Not Lean Startups, Mr. Musk


A tweet from @elonmusk yesterday has prompted a brief response from myself:

https://twitter.com/GTCost/status/1255681426445365248?s=20

For two reasons, as follows, it is worth elaborating on my argument a little more:

  1. I have seen similar sentiment toward authorities' over-providing healthcare system capacity in other countries as well, including, for example in Ireland, where the public has raised some concerns with the State contracting private hospitals for surplus capacity; and
  2. Quite a few people have engaged with my response to Musk.
So here are some more thoughts on the subject:

'Lean startups' is an idea that goes hand-in-hand with the notion that a startup needs some organic growth runway. In other words, it needs to ‘nail’ parts of its business model first, before ‘scaling’ the model up. ‘Nailing’ bit is done using highly scarce resources pre-extensive funding (which is a ‘scaling’ phase). It makes perfect sense for a start up, imo, for a startup.

But in the ‘nailing’ stage, when financial resources are scarce, the startup enterprise has another resource is relies upon to execute on a ‘lean’ strategy: time. Why? Because a ‘lean’ startup is a smaller undertaking than a scaling startup. As a result, failure at that stage carries lower costs. In other words, you can be ‘lean’ because you are allowed to fail, because if you do fail in that stage of development, you can re-group and re-launch. You can afford to be reactive to news flows and changes in your environment, which means you do not need to over-provide resources in being predictive or pro-active. Your startup can survive on lean funding.

As you scale startup, you accumulate resources (investment and retained earnings) forward. In other words, you are securing your organization by over-providing capacity. Why? Because failure is more expensive for a scaling startup than for a 'lean' early stage startup. The notion of retained and untilized cash is no longer the idea of waste, but, rather a prudential cushion. Tesla, Mr. Musk's company, carries cash reserves and lines of credit that it is NOT using at the moment in time precisely because not doing so risks smaller shocks to the company immediately escalating into existential shocks. And a failure of Tesla has larger impact than a failure of small 'lean' startup. In other words, Mr. Musk does not run a 'lean startup' for a good reason. Now, in a public health emergency with rapid rates of evolution and high degree of forecast uncertainty, you cannot be reactive. You must allocate resources to be pro-active, or anticipatory. In doing so, you do not have a choice, but to over-supply resources. You cannot be ‘lean’, because the potential (and highly probable) impact of any resource under-provision is a public health threat spinning out of control into a public health emergency and a systemic shock. ‘Lean’ startup methods work, when you are dealing with risk and uncertainty in a de-coupled systems with a limited degree of complexity involved and the range of shocks impact limited by the size of the organization/system being shocked. Public health emergence are the exact opposite of such a environment: we are dealing with severe uncertainty (as opposed to risk) with hugely substantial impacts of these shocks (think thousands of lives here, vs few million dollars in investment in an early stage start up failure). We are also dealing with severe extent of complexity. High speed of evolution of threats and shocks, uncertain and potentially ambiguous pathways for shocks propagation, and highly complex shock contagion pathways that go beyond the already hard-to-model disease contagion pathways. So a proper response to a pandemic, like the one we are witnessing today, is to use an extremely precautionary principle in providing resources and imposing controls. This means: (1) over-providing resources before they become needed (which, by definition, means having excess capacity ex-post shock realization); (2) over-imposing controls to create breaks on shock contagion (which, by definition, means doing too-much-tightening in social and economic environment), (3) doing (1) and (2) earlier in the threat evolution process rather than later (which means overpaying severely for spare capacity and controls, including - by design - at the time when these costs may appear irrational). And (4), relying on the worst-case-scenario parameterization of adverse impact in your probabilistic and forecasting analysis and planning. This basis for a public health threat means that responses to public health threat are the exact opposite to a ‘lean’ start up environment. In fact they are not comparable to the ‘scaling up’ start up environment either. A system that has a huge surplus capacity left in it, not utilized, in a case of a start up is equivalent to waste. Such system’s leadership should be penalized. A system that has a huge surplus capacity left un-utilized, in a case of a pandemic is equivalent to the best possible practice in prudential management of the public health threat. Such system’s leadership should be applauded.

And even more so in the case of COVID pandemic. Mr. Musk implies something being wrong with California secured hospital beds capacity running at more than double the rate of COVID patients arrivals. That's the great news, folks. COVID pandemic carries infection detection rates that double the population of infected individuals every 3-30 days, depending on the stage of contagion evolution. Earlier on, doubling times are closer to 3 days, later on, they are closer to 30 days. But, utilization of hospital beds follows an even more complex dynamic, because in addition to the arrival rates of new patients, you also need to account for the duration of hospital stay for patients arriving at different times in the pandemic. Let's be generous to sceptics, like Mr. Musk, and assume that duration-of-stay adjusted arrivals of new patients into the hospitals has a doubling time of the mid-point of 3-30 days or, close to two weeks. If California Government did NOT secure massively excessive capacity for COVID patients in advance of their arrival, the system would not have been able to add new capacity amidst the pandemic on time to match the doubling of new cases arrivals. This would have meant that some patients would be able to access beds only later in the disease progression period, arriving to hospital beds later in time, with more severe impact from the disease and in the need of longer stays and more aggressive interventions. The result would have been even faster doubling rate in the demand for hospital beds with a lag of few days. You can see how the system shortages would escalate out of control.

Running tight supply chains in a pandemic is the exact opposite to what has to be done. Running supply capacity at more than double the rate of realized demand is exactly what needs to be done. We do not cut corners on basic safety equipment. Boeing did, with 737-Max, and we know where they should be because of this. We most certainly should not treat public health pandemic as the basis for cutting surplus safety capacity in the system.