5/10/11: The Swedish Crises of 1910s & 1990s: The Lessons Never Learned

Here is an interesting piece of evidence on the nature of real estate bubbles and financial crises these create. One of the largest fallouts from property-driven financial crises in modern European history relates to the early 1991-1992 blowout in Sweden that saw massive collapse in property prices triggering a systemic contagion to financial institutions, The resolution process and the recovery that followed were long. Just about 10 years - the time it took the real property prices to regain their pre-crisis peak.

Source: Zerohedge

But the bigger story is a hundred-years-long bust to recovery cycle that took Stockholm's property prices from 1910 peak until 2007.

What is, however, most telling is the fact that Stockholm's markets show conclusively and without any doubt that all the lessons supposedly 'learned' in the past crises have been un-learned in the aftermath of the 2007-2008 Global Financial Bust. Despite the painful recovery from the 1991-1992, and despite huge efforts put by the successive Governments into highlighting regulatory and market structure reforms that followed it, Swedish property markets have gone into another, this time completely unprecedented in the country history, craze. 

Stockholm is a city that has been so reformed post the 1990s, it makes more sense to live in a hotel, at least in some cases (http://www.businessinsider.com/stockholm-rents-are-so-high-its-often-cheaper-to-live-in-a-hotel-2017-8). It is, of course, worth remembering that Stockholm is the equivalent of 'warm dream' for all rent control enthusiasts worldwide and for all 'moar regulation will save us from ourselves' crowds.

3/10/17: Ambiguity Fun: Perceptions of Rationality?

Here is a very insightful and worth studying set of plots showing the perceived range of probabilities under subjective measure scenarios. Source: https://github.com/zonination/perceptions

The charts above speak volumes about both, our (human) behavioural biases in assessing probabilities of events and the nature of subjective distributions.

First on the former. As our students (in all of my courses, from Introductory Statistics, to Business Economics, to advanced courses of Behavioural Finance and Economics, Investment Analysis and Risk & Resilience) would have learned (to a varying degree of insight and complexity), the world of Rational expectations relies (amongst other assumptions) on the assumption that we, as decision-makers, are capable of perfectly assessing true probabilities of uncertain outcomes. And as we all have learned in these classes, we are not capable of doing this, in part due to informational asymmetries, in part due to behavioural biases and so on. 

The charts above clearly show this. There is a general trend in people assigning increasingly lower probabilities to less likely events, and increasingly larger probabilities to more likely ones. So far, good news for rationality. The range (spread) of assignments also becomes narrower as we move to the tails (lower and higher probabilities assigned), so the degree of confidence in assessment increases. Which is also good news for rationality. 

But at that, evidence of rationality falls. 

Firstly, note the S-shaped nature of distributions from higher assigned probabilities to lower. Clearly, our perceptions of probability are non-linear, with decline in the rate of likelihoods assignments being steeper in the middle of perceptions of probabilities than in the extremes. This is inconsistent with rationality, which implies linear trend. 

Secondly, there is a notable kick-back in the Assigned Probability distribution for Highly Unlikely and Chances Are Slight types of perceptions. This can be due to ambiguity in wording of these perceptions (order can be viewed differently, with Highly Unlikely being precedent to Almost No Chance ordering and Chances Are Slight being precedent to Highly Unlikely. Still, there is a lot of oscillations in other ordering pairs (e.g. Unlikely —> Probably Not —> Little Chance; and We Believe —> Probably. This also consistent with ambiguity - which is a violation of rationality.

Thirdly, not a single distribution of assigned probabilities by perception follows a bell-shaped ‘normal’ curve. Not for a single category of perceptions. All distributions are skewed, almost all have extreme value ‘bubbles’, majority have multiple local modes etc. This is yet another piece of evidence against rational expectations.

There are severe outliers in all perceptions categories. Some (e.g. in the case of ‘Probably Not’ category appear to be largely due to errors that can be induced by ambiguous ranking of the category or due to judgement errors. Others, e.g. in the case of “We Doubt” category appear to be systemic and influential. Dispersion of assignments seems to be following the ambiguity pattern, with higher ambiguity (tails) categories inducing greater dispersion. But, interestingly, there also appears to be stronger ambiguity in the lower range of perceptions (from “We Doubt” to “Highly Unlikely”) than in the upper range. This can be ‘natural’ or ‘rational’ if we think that less likely event signifier is more ambiguous. But the same holds for more likely events too (see range from “We Believe” to “Likely” and “Highly Likely”).

There are many more points worth discussing in the context of this exercise. But on the net, the data suggests that the rational expectations view of our ability to assess true probabilities of uncertain outcomes is faulty not only at the level of the tail events that are patently identifiable as ‘unlikely’, but also in the range of tail events that should be ‘nearly certain’. In other words, ambiguity is tangible in our decision making. 

Note: it is also worth noting that the above evidence suggests that we tend to treat inversely certainty (tails) and uncertainty (centre of perceptions and assignment choices) to what can be expected under rational expectations:

In rational setting, perceptions that carry indeterminate outruns should have greater dispersion of values for assigned probabilities: if something is is "almost evenly" distributed, it should be harder for us to form a consistent judgement as to how probable such an outrun can be. Especially compared to something that is either "highly unlikely" (aka, quite certain not to occur) and something that is "highly likely" (aka, quite certain to occur). The data above suggests the opposite.

1/10/17: The Old, The Young and Resources Leveraging

In our Economics class at MIIS, we have discussed last week - briefly - the dynamics of demographic change (ageing population and cohorts dominance) around the world, with a side-road to the twin secular stagnations theses. We mostly talked about the supply side of the secular stagnation and mentioned the context of long-term technological cycles. Here is an intelligent take on one of the multiple aspects of the issue, the different angle to technological cycles: https://www.bloomberg.com/view/articles/2017-06-13/the-old-are-eating-the-young. The connection between financial debt and environmental/resource capacity leveraging is a rich vein to explore.

30/9/17: Technological Revolution is Fizzling Out, as Ideas Get Harder to Find

Nicholas Bloom, Charles Jones, John Van Reenen, and Michael Webb’s latest paper has just landed in my mailbox and it is an interesting one. Titled “Are Ideas Getting Harder to Find?” (September 2017, NBER Working Paper No. w23782. http://www.nber.org/papers/w23782.pdf) the paper asks a hugely important question related to the supply side of the secular stagnation thesis that I have been writing about for some years now (see explainer here: http://trueeconomics.blogspot.com/2015/07/7615-secular-stagnation-double-threat.html and you can search my blog for key words “secular stagnation” to see a large number of papers and data points on the matter). Specifically, the new paper addresses the question of whether technological innovations are becoming more efficient - or put differently, if there is any evidence of productivity growth in innovation.

The reason this topic is important is two-fold. Firstly, as authors note: “In many growth models, economic growth arises from people creating ideas, and the long-run growth rate is the product of two terms: the effective number of researchers and their research productivity.” But, secondly, the issue is important because we have been talking in recent years about self-perpetuating virtuous cycles of innovation:

• Clusters of innovation engendering more innovation;
• Growth in ‘knowledge capital’ or ‘knowledge economies’ becoming self-sustaining; and
• Expansion of AI and other ‘learning’ fields leading to exponential growth in knowledge (remember, even the Big Data was supposed to trigger this).

So what do the authors find?

“We present a wide range of evidence from various industries, products, and firms showing that research effort is rising substantially while research productivity is declining sharply.” In other words, there is no evidence of self-sustained improvements in research productivity or in the knowledge economies.

Worse, there is a diminishing marginal returns in technology, just as there is the same for every industry or sector of the economy: “A good example is Moore's Law. The number of researchers required today to achieve the famous doubling every two years of the density of computer chips is more than 18 times larger than the number required in the early 1970s. Across a broad range of case studies at various levels of (dis)aggregation, we find that ideas — and in particular the exponential growth they imply — are getting harder and harder to find. Exponential growth results from the large increases in research effort that offset its declining productivity.”

We are on the extensive margin when it comes to knowledge creation and innovation, which - to put it differently - makes ‘innovation-based economies’ equivalent to ‘coal mining’ ones: to achieve the next unit of growth these economies require an ever increasing input of resources.

Computers are not the only sector where the authors find this bleak reality. “We consider detailed microeconomic evidence on idea production functions, focusing on places where we can get the best measures of both the output of ideas and the inputs used to produce them. In addition to Moore’s Law, our case studies include agricultural productivity (corn, soybeans, cotton, and wheat) and medical innovations. Research productivity for seed yields declines at about 5% per year. We find a similar rate of decline when studying the mortality improvements associated with cancer and heart disease.” And more: “We find substantial heterogeneity across firms, but research productivity is declining in more than 85% of our sample. Averaging across firms, research productivity declines at a rate of around 10% per year.”

This is really bad news. In recent years, we have seen declines in labor productivity and capital productivity, and TFP (the residual measuring technological productivity). Now, knowledge productivity is falling too. There is literally no input into production function one can think of that can be measured and is not showing a decline in productivity.

The ugly facts presented in the paper reach across the entire U.S. economy: “Perhaps research productivity is declining sharply within every particular case that we look at and yet not declining for the economy as a whole. While existing varieties run into diminishing returns, perhaps new varieties are always being invented to stave this off. We consider this possibility by taking it to the extreme. Suppose each variety has a productivity that cannot be improved at all, and instead aggregate growth proceeds entirely by inventing new varieties. To examine this case, we consider research productivity for the economy as a whole. We once again find that it is declining sharply: aggregate growth rates are relatively stable over time, while the number of researchers has risen enormously. In fact, this is simply another way of looking at the original point of Jones (1995), and for this reason, we present this application first to illustrate our methodology. We find that research productivity for the aggregate U.S. economy has declined by a factor of 41 since the 1930s, an average decrease of more than 5% per year.”

This evidence further confirms the supply side of the secular stagnation thesis. Technological revolution has been slowing down over recent decades (not recent years) and we are clearly past the peak of the TFP growth of the 1940s, and the local peak of the 1990s (the ‘fourth wave’ of technological revolution).

Update June 7, 2018: A new version of the paper is available at https://web.stanford.edu/~chadj/IdeaPF.pdf.

29/9/17: Eurocoin: Eurozone growth is still on the upside trend

The latest data from Eurocoin - an early growth indicator published by Banca d’Italia and CEPR - shows robust continued growth dynamics for the common currency GDP through August-September 2017. Rising from 0.67 in August to 0.71 in September, Eurocoin posted the highest reading since March 2017 and matched the 3Q 2017 GDP growth projection of 0,67.

The charts below show both the trends in Eurocoin and underlying GDP growth, as well as key policy constraints for the monetary policy forward.

The last chart above shows significant gains in both growth and inflation over the last 12 months, with the euro area economy moving closer to the ECB target zone for higher rates. In fact, current state of unemployment and growth suggests policy rates at around 2.4-3 percent, while inflation is implying ECB rate in the regions of 1.25-1.5 percent.

In summary, euro area recovery continues at relative strength, with growth trending above the post-crisis period average since January 2017, and rising. Inflationary expectations are starting to edge toward the ECB target / tolerance zone, so October ECB meeting should be critical. Signals so far suggests that the ECB will outline core modalities of monetary policy normalisation, which will be further expanded upon before the end of 2017, setting the stage for QE unwinding and some cautious policy rates uplift from the start of 2018.

28/9/17: Pimco on Russian Economy: My Take

An interesting post about the Russian economy, quite neatly summarising both the top-line challenges faced and the resilience exhibited to-date via Pimco: https://blog.pimco.com/en/2017/09/Russia%20Growth%20Up%20Inflation%20Down. Worth a read.

My view: couple of points are over- and under-played somewhat.

Sanctions: these are a thorny issue in Moscow and are putting pressure on Russian banks operations and strategic plans worldwide. While they do take secondary seat after other considerations in public eye, Moscow insiders are quite discomforted by the effective shutting down of the large swathes of European markets (energy and finance), and North American markets (finance, technology and personal safe havens). On the latter, it is worth noting that a number of high profile Russian figures, including in pro-Kremlin media, have in recent years been forced to shut down shell companies previously operating in the U.S. and divest out of real estate assets. Sanctions are also geopolitical thorns in terms of limiting Moscow's ability to navigate the European policy space.

Banks: this issue is overplayed. Bailouts and shutting down of banks are imposing low cost on the Russian economy and are bearable, as long as inflationary pressures remain subdued. Moscow can recapitalise the banks it wants to recapitalise, so all and any banks that do end up going to the wall, e.g. B&N and Otkrytie - cited in the post - are going to the wall for a different reason. That reason is consolidation of the banking sector in the hands of state-owned TBTF banks that fits both the Central Bank agenda and the Kremlin agenda. The CBR has been on an active campaign to clear out medium- and medium-large banks out of the way both from macroprudential point of view (these institutions have been woefully undercapitalised and exposed to serious risks on assets side), and the financial system stability point of view (majority of these banks are parts of conglomerates with inter-linked and networked systems of loans, funds transfers etc).

Yurga, another bank that was stripped of its license in late July - is the case in point, it was part of a real estate and oil empire. B&N is another example: the bank was a part of the Safmar group with $34 billion worth of assets, from oil and coal to pension funds.

The CBR knowingly tightened the screws on these types of banks back in January:

• The new rules placed a strict limit on bank’s exposure to its own shareholders - maximum of 20% of its capital, forcing the de-centralisation of equity holdings in banking sector; and
• Restricted loans to any single borrower or group of connected borrowers to no more than 25% of total lending.

I cannot imagine that analysts covering Russian markets did not understand back in January that these rules will spell the end of many so-called 'pocket' banks linked to oligarchs and their business empires.

The balance of the banking sector is feeling the pain, but this pain is largely contained within the sector. Investment in Russian economy, usually heavily dependent on the banks loans, has been sluggish for a number of years now, but the key catalyst to lifting investment will be VBR's monetary policy and not the state of the banking sector. 

Here is a chart from Reuters summarising movements in interbank debt levels across the top 20 banks:

The chart suggests that net borrowing is rising amongst the top-tier banks, alongside deposits gains (noted by Pimco), so the core of the system is picking up strength off the weaker banks and is providing liquidity. Per NYU's v-lab data, both Sberbank and VTB saw declines in systemic risk exposures in August, compared to July. So overall, the banking system is a problem, but the problem is largely contained within the mid-tier banks and the CBR is likely to have enough fire power to sustain more banks going through a resolution. 

28/7/17: Climbing the Deficit Mountains: Advanced Economies in the Age of Austerity

Just a stat: between 2001-2006 period, cumulative Government deficits across the Advanced Economies rose by SUD 5.135 trillion. Over the subsequent 6 years period (2007-2012) the same deficits clocked up USD 14.299 trillion and over the period 2013-2018 (using IMF forecasts for 2017 and 2018), the cumulated deficits will add up to USD 8.197 trillion. On an average annual basis, deficits across the Advanced Economies run at an annual rate of USD0.86 trillion over 2001-2006, USD 2.375 trillion over 2007-2012 and USD 1.385 trillion over 2013-2017 (excluding forecast year of 2018).

As a percentage of GDP, 2001-2006 saw Government deficits for the Advanced economies averaging 2.68% of GDP annually in pre-crisis era, rising to 5.42% of GDP in peak crisis years of 2007-2012, and running at 2.98% of GDP in 2013-2017 period. Looking at the post-crisis period, return to pre-crisis levels of Government spending would require

In simple terms, there is a mountain of deficits out there that has been sustained by cheap - Central Banks’ subsidised - funding, the cost of which is starting to go North. The cost of debt financing is a material risk consideration.

28/9/17: Schauble: A Requiem For Austerity Finance

My comment for yesterday’s NY Times on Wolfgang Schäuble’s departure from the Finance Ministry post: https://nyti.ms/2k5N2Er 

28/9/17: Irish Migration: Some Good News in 2017

While headline figures for net migration to Ieland paint an overall positive picture in the annual data (provided on April-April basis) for 2017, there are some creases on the canvas, both good and bad.

Top line numbers are good: net inward migration posted a print of 19,800 in 2017, up on 16,200 in 2016 and 5,900 in 2015. This marks the third year of positive inflows. However, on a cumulative basis, the last three years are still falling short of offsetting massive outflows recorded in 2010-2014. Cumulatively, between 2010 and 2017, the overall net migration stands at -65,900. Taking last two years’ average net inward immigration, it will take Ireland almost 4 years to cover the shortfall. Worse, on pre-crisis trend (omitting peak inward migration years of 2005-2007), we should be seeing inward net migration of around 27,100, well above the current rate. And on a cumulative basis, were the pre-crisis trends to remain unbroken, we would have added 487,600 residents between 2000 and 2017, instead of the actual addition of 394,500 over the same period. 

So things are improving and getting toward healthy, but we are not quite there, yet.

And there are other points of concern. Primary one is the fact that net inward migration remains negative for Irish nationals: in 2017, net outflow of Irish nationals fell to 3,400 from 8,700 in 2016. However, the figures continue to record net outflows for 8th year in a row. Over the period of 2010-2017, Ireland lost net 139,800 nationals.

On a positive side, there is net inflow of all other nationalities into Ireland, with non-EU nationals inflows jumping (net basis) to 15,7000 in 2017, the highest levels on record (albeit records only start from 2006). It is impossible to tell from CSO figures which nationalities are driving these numbers - a crucial point when it comes to assessing the nature of inflows.

Final point worth making is a positive one: in 2017, Ireland recorded another year or growth in - already strong - net inflows of skills and human capital as reflected both in age demographics and educational attainment. By educational attainment, third level graduates and higher category of net inflows posted another historical record in 2017 at 23,600, topping 2016 record of 20,800. Since 2009, including the years of the acute crisis of 2010-2012, Ireland added net 61,000 new immigrants and returned migrants with third level and higher education. This is consistent with continued recovery in human capital-intensive sectors of the economy and is a huge net positive for Ireland.

Hence, overall, the figures for migration are on the balance positive, although some pockets of weaknesses continue to remain and pose a challenge to the arguments about the breadth and depth of the recovery to-date.

21/9/17: Another reminder: Financial Crises are becoming more frequent & more disruptive

As recently noted by Holger Zschaepitz @Schuldensuehner, new research from Deutsche Bank shows that "Post Bretton Woods (1971-) system vulnerable to crises. Frequency of Financial Crises increased since then. Growth of finance encouraged trend".

Of course, readers of this blog would have known as much by now.  Almost 2.5 years ago I wrote about research by Claudio Borio of BIS on the same topic (see http://trueeconomics.blogspot.com/2015/05/8515-bis-on-build-up-of-financial.html) and Borio's findings are linked to his own earlier work on excess financial elasticity hypothesis (see http://trueeconomics.blogspot.com/2011/11/07112011-dont-blame-johnny-foreigner.html).

So while the DB 'research' simply replicates the findings of others who paved the way, it does present a nice picture of the amplified nature of financial crises in recent decades, both in terms of timing/frequency and in terms of impact.

14/91/17: Risk, Uncertainty, Political Risks and Markets

My article on the links between political risks, financial returns and economic growth in the MFTimes: http://issuu.com/publicationire/docs/mf_august_2017?e=16572344/51951043 pages 5-7.

14/9/17: MarketWatch Op-Ed: U.S. Economy

My op-ed on the state of the U.S. Household Incomes is available on MarketWatch: http://www.marketwatch.com/story/the-myths-of-recovery-why-american-households-arent-better-off-2017-09-13.