Monday, October 9, 2017

9/10/17: Nature of our reaction to tail events: ‘odds’ framing


Here is an interesting article from Quartz on the Pentagon efforts to fund satellite surveillance of North Korea’s missiles capabilities via Silicon Valley tech companies: https://qz.com/1042673/the-us-is-funding-silicon-valleys-space-industry-to-spot-north-korean-missiles-before-they-fly/. However, the most interesting (from my perspective) bit of the article relates neither to North Korea nor to Pentagon, and not even to the Silicon Valley role in the U.S. efforts to stop nuclear proliferation. Instead, it relates to this passage from the article:



The key here is an example of the link between the our human (behavioral) propensity to take action and the dynamic nature of the tail risks or, put more precisely, deeper uncertainty (as I put in my paper on the de-democratization trend https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2993535, the deeper uncertainty as contrasted by the Knightian uncertainty).

Deeper uncertainty involves a dynamic view of the uncertain environment in which potential tail events evolve before becoming a quantifiable and forecastable risks. This environment is different from the classical Knightian uncertainty in so far as evolution of these events is not predictable and can be set against perceptions or expectations that these events can be prevented, while at the same time providing no historical or empirical basis for assessment of actual underlying probabilities of such events.

In this setting, as opposed to Knightian set up with partially predictable and forecastable uncertainty, behavioral biases (e.g. confirmation bias, overconfidence, herding, framing, base rate neglect, etc) apply. These biases alter our perception of evolutionary dynamics of uncertain events and thus create a referencing point of ‘odds’ of an event taking place. The ‘odds’ view evolves over time as new information arrives, but the ‘odds’ do not become probabilistically defined until very late in the game.

Deeper uncertainty, therefore, is not forecastable and our empirical observations of its evolution are ex ante biased to downplay one, or two, or all dimensions of its dynamics:
- Impact - the potential magnitude of uncertainty when it materializes into risk;
- Proximity - the distance between now and the potential materialization of risk;
- Speed - the speed with which both impact and proximity evolve; and
- Similarity - the extent to which our behavioral biases distort our assessment of the dynamics.

Knightian uncertainty is a simple, one-shot, non-dynamic tail risk. As such, it is similar both in terms of perceived degree of uncertainty (‘odds’) and the actual underlying uncertainty.

Now, materially, the outrun of these dimensions of deeper uncertainty is that in a centralized decision-making setting, e.g. in Pentagon or in a broader setting of the Government agencies, we only take action ex post transition from uncertainty into risk. The bureaucracy’s reliance on ‘expert opinions’ to assess the uncertain environment only acts to reinforce some of the biases listed above. Experts generally do not deal with uncertainty, but are, instead, conditioned to deal with risks. There is zero weight given by experts to uncertainty, until such a moment when the uncertain events become visible on the horizon, or when ‘the odds of an event change’, just as the story told by Andrew Hunter in the Quartz article linked above says. Or in other words, once risk assessment of uncertainty becomes feasible.

The problem with this is that by that time, reacting to the risk can be infeasible or even irrelevant, because the speed and proximity of the shock has been growing along with its impact during the deeper uncertainty stage. And, more fundamentally, because the nature of underlying uncertainty has changed as well.

Take North Korea: current state of uncertainty in North Korea’s evolving path toward fully-developed nuclear and thermonuclear capabilities is about the extent to which North Korea is going to be willing to use its nukes. Yet, the risk assessment framework - including across a range of expert viewpoints - is about the evolution of the nuclear capabilities themselves. The train of uncertainty has left the station. But the ticket holders to policy formation are still standing on the platform, debating how North Korea can be stopped from expanding nuclear arsenal. Yes, the risks of a fully-armed North Korea are now fully visible. They are no longer in the realm of uncertainty as the ‘odds’ of nuclear arsenal have become fully exposed. But dealing with these risks is no longer material to the future, which is shaped by a new level of visible ‘odds’ concerning how far North Korea will be willing to go with its arsenal use in geopolitical positioning. Worse, beyond this, there is a deeper uncertainty that is not yet in the domain of visible ‘odds’ - the uncertainty as to the future of the Korean Peninsula and the broader region that involves much more significant players: China and Russia vs Japan and the U.S.

The lesson here is that a centralized system of analysis and decision-making, e.g. the Deep State, to which we have devolved the power to create ‘true’ models of geopolitical realities is failing. Not because it is populated with non-experts or is under-resourced, but because it is Knightian in nature - dominated by experts and centralized. A decentralized system of risk management is more likely to provide a broader coverage of deeper uncertainty not because its can ‘see deeper’, but because competing for targets or objectives, it can ‘see wider’, or cover more risk and uncertainty sources before the ‘odds’ become significant enough to allow for actual risk modelling.

Take the story told by Andrew Hunter, which relates to the Pentagon procurement of the Joint Light Tactical Vehicle (JLTV) as a replacement for a faulty Humvee, exposed as inadequate by the events in Iraq and Afghanistan. The monopoly contracting nature of Pentagon procurement meant that until Pentagon was publicly shown as being incapable of providing sufficient protection of the U.S. troops, no one in the market was monitoring the uncertainties surrounding the Humvee performance and adequacy in the light of rapidly evolving threats. If Pentagon’s procurement was more distributed, less centralized, alternative vehicles could have been designed and produced - and also shown to be superior to Humvee - under other supply contracts, much earlier, and in fact before the experts-procured Humvees cost thousands of American lives.

There is a basic, fundamental failure in our centralized public decision making bodies - the failure that combines inability to think beyond the confines of quantifiable risks and inability to actively embrace the world of VUCA, the world that requires active engagement of contrarians in not only risk assessment, but in decision making. That this failure is being exposed in the case of North Korea, geopolitics and Pentagon procurement is only the tip of the iceberg. The real bulk of challenges relating to this modus operandi of our decision-making bodies rests in much more prevalent and better distributed threats, e.g. cybersecurity and terrorism.

9/10/17: BRIC Composite PMI 3Q: Failing Global Growth Momentum


Two posts above cover Manufacturing PMIs and Services PMIs for 3Q 2017 for BRIC economies. The following updates Composite PMIs performance.

Global Composite PMI came in at 53.7 in 3Q 2017, matching exactly 1Q and 2Q 2017 readings and basically in line with 53.6 reading in 4Q 2016. In other words, Global Composite activity PMI index has been showing relatively robust growth across the two key sectors for the last 4 quarters running. 

In contrast to Global indicator, BRIC economies posted relatively underwhelming performance with exception of Russia.
  • Brazil Composite PMI index stood at 50.0 (zero growth) in 3Q 2017, which is a marginal gain on 49.8 in 2Q 2017. This marks the first time since 1Q 2014 that Brazil Composite indicator reached above the outright contraction levels, but it is a disappointing reading nonetheless. For one, one quarter does not signal stabilisation in Latin America’s largest economy. Worse, Brazil’s economy has been performing poorly since as far back as 2H 2011. It will take Brazil’s Composite index to hit above 52 mark for 2-3 consecutive quarters to start showing pre-2011 levels of activity again.
  • Russia Composite PMI, on the other hand, remains the bright spark in the BRIC’s dark growth universe. Although falling to 4 quarters low of 54.1 in 3Q 2017, the index remains in strong growth territory. 3Q 2017 marked 6th consecutive quarter of robust post-recession recovery, consistent with 2.5-3 percent growth in GDP, quite ahead of the consensus forecasts from the start of 2017. The last quarter also marks the sixth consecutive quarter of Russian Composite PMIs running above Global Composite PMIs. This means that for the last 18 months, Russia has been the only positive contributor to Global growth from amongst the ranks of the BRIC economies.
  • China Composite PMI firmed up in 3Q 2017, rising to 51.9 from 51.3 in 2Q 2017. 3Q 2017 reading was, however, the second weakest in the last four quarters and suggests relative weakness in the growth environment. 
  • India composite PMI fell below 50.0 mark in 3Q 2017, reaching 48.7 - a level signifying statistically significant contraction in the economy for the first time since 4Q 2013. The robust recovery in 2Q 2017 put India Composite PMI at 52.2, but this now appears to be a blip on the radar which shows anaemic growth in 4Q 2016 and 1Q 2017.



As chart above clearly shows, the growth dynamics as indicated by the Composite PMIs have been weak in the BRIC economies over the last 4 consecutive quarters. This is highly disappointing, considering that 4Q 2016 held a promise of more robust expansion. Russian growth conditions have now outperformed Global growth dynamics in every quarter since 2Q 2016, although the latest reading for PMIs suggests that this momentum has weekend in 3Q 2017. In fact, Russian data is quite surprising overall, showing growth conditions largely in line with pre-2009 levels since 4Q 2016. This is yet to be matched by the GDP figures, suggesting that something might be amiss in the PMI data. 


Finally, the chart above shows sectoral dynamics for BRIC group of economies in terms of PMI indices. Both Services and Manufacturing PMIs for BRIC grouping are now running close to or below statistical significance levels for positive growth. More importantly, on-trend, current performance remains within the bounds of growth consistent with H2 2013-present trend: shallow, close to statistically insignificant expansion, that is distinct from robust growth in pre-2008-2009 period and the short period of post 2009 recovery.

Thus, PMI data still indicates that BRIC economies currently no longer act as the key drivers of global growth.

9/10/17: BRIC Services PMI 3Q 2017: Another Quarter of Weaker Growth


Having covered 3Q 2017 figures for BRIC Manufacturing PMIs in the previous post, let’s update the same for Services sector.

BRIC Services PMI has fallen sharply in 3Q 2017 to 50.8 from 52.1 in 2Q 2017. This is the lowest reading since 2Q 2016 (when it also posted 50.8). The drivers of this poor dynamic are:
  • Brazil Services PMI remained below 50.0 mark for the 12th consecutive quarter, rising marginally to 49.5 in 3Q 2017 from 49.0 in 2Q 2017. Current reading matches 1Q 2015 for the highest levels since 1Q 2014. Statistically, Brazil Services PMI has been at zero or lower growth since 1Q 2014.
  • Russia Services PMI fell to 54.0 in 3Q 2017 from 56.0 in 2Q 2017 and 56.8 in 1Q 2017, indicating some cooling off in otherwise rapid expansion dynamics. The recovery in Russian Services sectors is now 6 quarters long and overall very robust.
  • China Services PMI decline marginally from 52.0 in 2Q 2017 to 51.6 in 3Q 2017. This is consistent with trend established from the local peak performance in 4Q 2016. Overall, Chinese Services are showing signs of persistent weakness, with growth indicator falling below statistically significant reading once again in 3Q 2017.
  • India Services sector has been a major disappointment amongst the BRIC economies, with Services PMI falling from 51.8 in 2Q 2017 to a recessionary 48.0 in 3Q 2017. The Services PMIs for the country have been rather volatile in recent quarters, as the economy has lost any sense of trend since around 4Q 2016.

Table below and the chart illustrate the changes in Services PMIs in 3Q 2017 relative to 2Q 2017 and the trends:





With Global Services PMI remaining virtually unchanged (at 53.9) in 3Q 2017 compared to 2Q 2017 (51.8), with marginal gains on 1Q 2017 (53.6) and 4Q 2016 (53.5), the BRIC Services sectors are showing no signs of leading global growth to the upside since 3Q 2016. For the sixth consecutive quarter, Russia leads BRIC Services PMIs, while Brazil and India compete for being the slowest growth economies in the services sectors within the group.

As with Manufacturing, BRIC Services sectors show no signs of returning to their pre-2009 position of being the engines for global growth.

Stay tuned for Composite PMIs analysis for BRIC economies.

9/10/17: BRIC Manufacturing PMIs 3Q 2017: Lagging Global Growth


With Markit Economics finally releasing China data for Services and Composite PMIs, it is time to update 3Q figures for Manufacturing and Services sectors PMI indicators for BRIC economies.

Summary table:

As shown above, Manufacturing PMIs across the BRIC economies trended lower over 3Q 2017 in Brazil and India, when compared to 2Q 2017, while trending higher in Russia and China.

  • Brazil posted second lowest performance for the sector in the BRIC group, barely managing to stay above the nominal 50.0 mark that defines the boundary between growth and contraction in the sector activity. Statistically, 50.6 reading posted in 3Q 2017 was not statistically different from 50.0 zero growth. And it represents a weakening in the sector recovery compared to 50.9 reading in 2Q 2017. Brazil's Manufacturing sector has now been statistically at zero or negative growth for 18 quarters in a row.
  • Meanwhile, Russian Manufacturing PMI rose from 51.2 in 2Q 2017 to 52.1 in 3Q 2017, marking fifth consecutive quarter of expansion in the sector (nominally) and fourth consecutive quarter of above 50.0 (statistically). With this, Russia is now back at the top of Manufacturing sector growth league amongst the BRIC economies. However, 3Q 2017 reading was weaker than 4Q 2016 and 1Q 2017, suggesting that the post-recession recovery is not gaining speed.
  • China Manufacturing PMI rose in 3Q 2017 to 51.2 from zero growth of 50.1 in 2Q 2017. The dynamics are weaker than in Russia, but similar in pattern, with 3Q growth being anaemic. In general, since moving above 50.0 mark in 3Q 2016, China Manufacturing PMIs never once rose above 51.3 marker, indicating very weak growth conditions in the sector.
  • India's Manufacturing PMI tanked again in 3Q 2017 falling to 50.1 (statistically - zero growth) from 51.7 in 2Q 2017. Most recent peak in Manufacturing activity in India was back in 3Q 2016 and 4Q 2016 at 52.2 and 52.1 and these highs have not been regained since then. India's economy continues to suffer from extremely poor macroeconomic policies adopted by the country in recent years, including botched tax reforms and horrendous experimentation with 'cashless society' ideas. 



Overall, BRIC Manufacturing Index (computed using my methodology on the basis of Markit data) has risen to 51.0 in 3Q 2017 on foot of improved performance in Russia and China, up from 50.6 in 2Q 2017 and virtually matching 51.1 reading in 1Q 2017. At 51.0, the index barely exceed statistical significance bound of 50.9. This runs against the Global Manufacturing PMI of 52.9 in 3Q 2017, 52.6 in 2Q 2017 and 52.9 in 1Q 2017. In simple terms, the last quarter was yet another (18th consecutive) of BRIC Manufacturing PMI falling below Global Manufacturing PMI, highlighting a simple fact that world's largest emerging and middle-income economies are no longer serving as an engine for global growth.

Stay tuned for Services PMIs analysis.

Saturday, October 7, 2017

6/10/17: Life-Cycle Wages and Trends: September US Wage Inflation in Perspective


Last month, I wrote an editorial for @MarketWatch on the declining fortunes of the American wage earners. And this week, the BLS released new data on wage growth in the U.S. economy. The new numbers are 'shiny'.

Per headlines reported in the media, the BLS reported that the annual increase in Average Weekly Earnings was an impressive 2.9%, which is:
  • Well above the 2.5% rate of growth expected in prior estimates, 
  • Well above the 2.5% reported last month, and
  • The highest since the financial crisis
This is a great print. Except, it really is not all that exciting, when one reaches below the surface.

Take the following summary of recent growth rates (H/T @BySamRo): 



September 2017 wage increases are still below 2008-2009 averages for all wage earners, except for low-wage industries. The gains 'break out' drivers are in high-wage industries, where growth has risen 20% compared to much of the 2016-present trend. Overall, growth rate is well below 2008-2009 average of 3.4%.

To see how much more poor the current 'spectacular' print is compared to the past trends, look at longer time series:


Low-wage industries wages inflation is running close to pre-crisis average, since roughly the start of 2017. Good news. High and meddle-wage industries wages inflation is running below the pre-crisis average still. We have had roughly 8 years in the current trends, meaning that a large cohort of current workers have entered the workforce with little past gains in wages under their belt. This means a very brutal and simple arithmetic: many workers in today's economy have never experienced the gains of pre-crisis magnitudes. Wage increases are cumulative or compound in nature. Wage increases slowdown is also cumulative or compound in nature. Hence, workers who entered the workforce from around 2004 onwards have had shallower cumulative gains in wages than workers that preceded them. Guess what else do the former workers have that differentiates them from the latter? Why, yes: 1) higher student debt; 2) higher rent costs; 3) greater risk- and age-adjusted health insurance costs, and so on. In other words, for the later cohorts of workers currently in the workforce, lower wages increases came at a time of rampant increases in non-discretionary spending costs hikes.

To say that today's BLS wage inflation print is great news is to ignore these simple facts of economics: to restore wages to pre-crisis trends - the trends that would allow for the return of the Millennial generation to pre-crisis expectations (or to the cross-generational income and wealth growth patterns of previous decades), we need wages growth rates at 5-percent-plus not in one or two or three months, but in years ahead.  The 2.9% one month blip in data is not the great news. It might be a good news piece, but it is hardly impressive or convincing.

And that figure of 5%-plus hides yet another iceberg, big enough to sink the Titanic: given that the Millennials are carrying huge debts and are delaying household formation in record numbers, 5%-plus wage inflation will also hit them hard through higher interest rates and higher cost of debt carry.

This puts your average news headline relating to 2.9% annual increase in wages September figure into a correct, life-cycle perspective.

Friday, October 6, 2017

6/10/17: Italian Banks Tested EU Banking Reform. It Failed.


My article on the patent failures in the EU Banking Crisis resolution reforms exposed by the 2017 events surrounding Italian banking sector is out via @ManningFinancial http://issuu.com/publicationire/docs/mf_autumn_2017?e=16572344/54030271.






6/10/17: CA&G on Ireland's Tax, Banking Costs & Recovery


Occasionally, the Irish Comptroller and Auditor General (C&AG) office produces some remarkable, in their honesty, and the extent of their disclosures, reports. Last month gave us one of those moment.

There are three key findings by CA&G worth highlighting.

The first one relates to corporate taxation, and the second one to the net cost of banking crisis resolution. The third one comes on foot of tax optimisation-led economy that Ireland has developed since the 1990s, most recently dubbed the Leprechaun Economics by Paul Krugman that resulted in a dramatic increase in Irish contributions to the EU budget (computed as a share of GDP) just as the Irish authorities were forced to admit that MNCs’ chicanery, not real economic activity, accounted for 1/3 of the Irish economy. All three are linked:

  • Irish banking crisis was enabled by the combination of a property bubble that was co-founded by tax optimisation running rampant across Irish economic development model since the 1990s; and by loose money / capital flows within the EU, which was part and parcel of our membership in the euro area. The same membership supported our FDI-focused competitive advantage.
  • Irish recovery from the banking crisis was largely down to non-domestic factors, aka - tax optimisation-driven FDI and foreign companies activities, plus the loose money / capital flows within the EU enabled by the ECB.
  • In a way, as Ireland paid a hefty price for European imbalances and own tax-driven economic development model in 2007-2012, so it is paying a price today for the same imbalances and the same development model-led recovery.



Let’s take the CA&G report through a summary and some comments.


1) Framing CA&G analysis, we had a recent study by World Bank and PwC that estimated Ireland’s effective rate of corporation tax at 12.4%, just 0.1 per cent below the statutory or headline rate of 12.5%. To put this into perspective, if 12.4% effective rate holds, Ireland is not the lowest tax jurisdiction in the OECD, as 12 OECD economies had an effective rate below 12.4% and 21 had an effective rate of corporation tax above 12.4%. For the record, based on 2015 data, France had the 2nd-highest statutory rate at 38% but the lowest effective rate at just 0.4%. I contrast, the U.S. had the highest statutory tax rate at 39% and the second highest effective rate at 28.1%. There is a lot of fog around Irish effective corporate tax rates, but CA&G The C&AG found that the top 100 in taxable income terms companies had a an average effective corporation tax rate at 9.3%, slightly less than the rate applying to all companies (9.8%).

The CA&G findings show some dramatic variation in the effective tax rates paid by the Ireland-based corporations. CA&G report is based on a set of top 100 companies trading from Ireland. Of these, 79 companies paid an effective corporate tax rate of 10-15 percent, and almost 2/3rds paid a rate of 12% and higher. However, 13 companies faced a tax rate of under 1 percent.

Irish corporate tax system is risk-loaded: per CA&G report, 37% of all corporate tax receipts collected by the Irish Exchequer come from just 10 companies, while top 100 firms supply 70% of total corporate tax receipts. This concentration is coincident with rising reliance of the Exchequer on corporate tax collections, as corporation tax contributions to the State rose 49% in 2015 to reach EUR6.9 billion. The Leprechaun Economics that triggered a massive transfer of foreign assets into Ireland in 2015-2016 has pushed corporate tax receipts to account for 15% of the total tax revenues. Worse, 70% of total corporate tax take in Ireland came from only three sectors: finance, manufacturing and ICT. Manufacturing, of course, includes pharma sector and biopharma, while ICT is dominated by services, like Google, Facebook, Airbnb et al. This reliance on corporate tax revenues is the 6th highest in the OECD, based on 2015 figures. Per CA&G report, “Corporation tax receipts are highly concentrated both in terms of sectors and by number of taxpayers”. In other words, the Leprechaun Economics model is wrought with risks of a sudden stop in Exchequer revenues, should global flows of funds and assets into Ireland reverse (e.g. due to EU disruption, such as policy shift or Brexit/geopolitical triggers, or due to the U.S.-led shock, such as radical changes in the U.S. corporate tax regime).

The above is worrying. Leprechaun Economics model - or as I suggested years ago, the Curse of Tax Optimisation model - for economic development, chosen by Ireland is not sustainable and it is open to severe risks of exogenous shocks. Such shocks can be sudden and deep. And were risks to the MNCs domiciling into Ireland to materialise, the Exchequer can see double digit deficits virtually over night.


2) CA&G report also attempts to compute the net expected cost of the banking crisis to the country. Per report, the expected cost of rescuing the banks stands at around EUR 40 billion as of the end of 2016, while on the long run timing, the cost is expected to be EUR56.4 billion. However, accounting for State assets (banks’ shares), Nama ‘surpluses’ and other receipts, the long term net cost falls just below EUR40 billion. At the end of 2016, per CA&G, the value of the State's share in AIB was EUR11.6bn, which was prior to the 29% stake sale in an IPO of the bank. As history tells us, EUR66.8 billion was used to recapitalise the Irish banks with another EUR14.8 billion paid out in debt servicing costs. The debt servicing bill currently runs at around EUR1 billion on average, and that is likely to rise dramatically once the ECB starts unwinding its QE which effectively subsidises Irish Exchequer.

CA&G report accounted for debt servicing costs in its calculation of the total expected cost of banks bailouts, but it failed to account for the fact that these debt costs are perpetual. Ireland does not retire debt when it retires bonds, but predominantly uses new borrowings to roll over debt. hence, debts incurred from banks recapitalisations are perpetual. CA&G report also fails to a account for the opportunity cost of NPRF funds that were used to refinance Irish banks. NPRF funds generated tangible long term returns that were foregone in the bailout. Any economic - as opposed to accounting - analysis of the true costs of Irish banks bailouts must account for opportunity costs and for perpetual debt finance costs.

As a reminder, the State still owns remaining investments in AIB (71% shareholding), Bank of Ireland (14%) and Permanent TSB (75%) which CA&G estimated to be worth EUR13.6 billion. One way this might go is up: if recovery is sustained into the next 3-5 years, the state shares will see appreciation in value. The other way it might turn a decline: these are sizeable shareholdings and disposing off them in the markets will trigger hefty discounts on market share prices. CA&G expects Nama to generate a surplus of EUR3 billion. This is uncertain, to put it mildly, because Nama might not window any time soon, but morph instead into something else, e.g. ’social housing developer’ or into a general “development finance’ vehicle - watch their jostling for a role in ‘resolving’ the housing crisis. If it does, the surplus will be forced, most likely, into some sort of a development finance structure and, although recorded on paper, will be used to pay continued Nama wages and costs.

In simple terms, the CA&G figure is an accounting underestimate of the true net cost of the bailouts and it is also a gross economic underestimate of the same.


3) As noted above, the third aspect of the CA&G report worth mentioning is the rapid acceleration in Ireland’s overpayment to the EU on foot of the rapid superficial GDP expansion of 2015-2016 period. According to CA&G, Ireland’s contributions to the EU rose to EUR2 billion - up 20% y/y - in 2016. This increase was largely driven by the fake growth in GDP that arises from the multinational companies shifting assets into Ireland for tax purposes. CA&G expects this figure to rise to EUR2.4 billion in 2017.

In simple terms, Ireland is overpaying for the EU membership to the tune of EUR1 billion - an overpayment necessitated by the MNCs-induced superficial expansion of the national accounts. This activity has zero impact on the ground, but it induces a real cost on Irish society. Of course, one can as easily make an argument that our beggar-thy-neighbour tax policies are conditional on us being within the EU, so we are paying extra for the privilege of housing all corporate tax optimisers in Ireland.


All in, the CA&G report is a solid attempt at making sense of the Kafkaesque economics of the Irish State. That it deserves some critical comments should not subtract from its value and the quality of effort.

5/10/17: Leverage Risk, Credit Quality & Debt Tax Shield


In our Risk & Resilience class @ MIIS, we cover the impact of various aspects of the VUCA environment on, amongst other things, the Weighted Average Cost of Capital. One key element of this analysis - the one we usually start with - is the leverage risk. In practical terms, we know that the U.S. (bonds --> intermediated bank debt) and Europe (intermediated debt --> bonds) are both addicted to corporate leverage, with lower cost of capital attributable to debt. We also know that this is down not to the recoverability risks or credit risks, but to the asymmetric treatment of debt and equity in tax systems. Specifically, leverage risk is driven predominantly by tax shields (tax deductibility) of debt.

In simple terms, tax system encourages, actively, accumulation of leverage risks on companies capital accounts. Not only that, tax preferences for debt imply distorted U-shaped relationship between credit ratings (credit risk profile of the company) and the cost of capital, whereby top-rated A+, A and A- have higher cost of capital (due to greater exposure to equity) than more risky BBB and BBB- corporates (who have higher share of tax0deductible debt in total capital structure).

Which brings us to one benefit of reducing tax shield value of debt (either by lowering corporate tax rate, which automatically lowers the value of tax shield) or by dropping tax deduction on debt (or both). Here is a chart showing that when tax deductibility of debt is eliminated, companies with lowest risk profile (A+ rated) enjoy lowest cost of capital. As it should be, were risk playing more significant role in determining the cost of company funding, instead of a tax shield.

Simples. com

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.

Tuesday, October 3, 2017

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.

Monday, October 2, 2017

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.


Saturday, September 30, 2017

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.

Friday, September 29, 2017

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. 


Thursday, September 28, 2017

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.

Thursday, September 21, 2017

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.

Tuesday, September 12, 2017

12/9/17: Asymmetric Conflicts and U.S. 'Learning Curve'


'Asymmetric warfare' or more aptly, 'asymmetric conflict' involves a confrontation between two sets of agents in which one set possesses vastly greater resources. In more recent time, the notion of 'asymmetric conflicts' involved the less endowed agents winning against more endowed ones. And the degree of asymmetries has grown significantly over time:

  • In Vietnam War, vastly outgunned Vietnamese forces literally defeated vastly over-equipped French and U.S. military machines;
  • In the Cold War confrontation, significantly less resourced Warsaw Pact managed to sustain relative long-term parity with much more resourced Western counterparts (including Nato);
  • In post-USSR years, vastly under-resourced Russia, compared to vastly over-resourced U.S. has been able to achieve quite a few 'wins' in geopolitical arena; 
  • Isis - with barely any resources, has managed to achieve huge gains against a range of much better equipped counterparties;
  • In Afghanistan, Taliban - with military expenditure of just a few million per annum, is successfully holding the line against both the Afghan state and its backers; and of course,
  • The 'rust-bucket' North Korea has just outplayed the U.S. in its race for nukes as a deterrent.
In summary, thus: spending does not secure reduction of risks in the age of asymmetric conflicts.

Now, consider the two key sources of 'existential' threats to the U.S. geopolitical positioning in the world: Russia and China. Illustrating asymmetric conflict:


And despite this obvious lack of connection between volume of spend and outruns in terms of geopolitical achievements, the prevalent consensus in Washington remains the same: more funds for Pentagon is the only way to assure preservation of the U.S. geopolitical positioning. 

Learning, anyone?

12/9/17: U.S. Median Household Income: The Myths of Recovery

The U.S. Census Bureau published some data on household incomes today. Off the top, the figures are encouraging:


The excitement of some analysts reporting these as a major breakthrough along the trend is understandable, notionally, 2016 U.S. median household income has finally surpassed the previous peak, recorded in 1999. Back then, median household income (adjusted for official inflation) stood at USD58,665 and at the end of 2016 it registered USD59,039. Note: italics denote points of importance, relevant to the analysis below.

As this chart from Marketwatch (http://www.marketwatch.com/story/poverty-rate-drops-as-median-income-climbs-over-3-2017-09-12) clearly illustrates, notionally, we are in the ‘new historical peak’ territory:


Alas, notional is not the same as tangible. And here are the reason why the tangible matters probably more than the notional:

1) Consider the following simple timing observation: real incomes took 17 years to recover from the 2000-2012 collapse. And the Great Recession, officially, accounted for only USD 4,031 in total decline of the total peak-to-trough drop of USD 5,334. Which puts things into a different framework altogether: the stagnation of real incomes from 1999 through today is structural, not cyclical. The ‘good news’ today are really of little consolation for people who endured almost two decades of zero growth in real incomes: their life-cycle incomes, pensions, wealth are permanently damaged and cannot be repaired within their lifetimes.

2) The Census Bureau data shows that bulk of the gains in real income in 2016 has been down to one factor: higher employment. In other words, hours worked rose, but wages did not. American median householders are working harder at more jobs to earn an increase in wages. Which would be ok, were it not down to the fact that working harder means higher expenditure on income-related necessities, such as commuting costs, childcare costs, costs for caring for the dependents, etc. In other words, to earn that extra income, households today have to spend more money than they did back in the 1990s. Now, I don’t know about you, but for my household, if we have to spend more money to earn more money, I would be looking at net increases from that spending, not gross. Census Bureau does not adjust for this. There is an added caveat to this: caring for children and dependents has become excruciatingly more expensive over the years, since 1999. Inflation figures reflect that, but real income deflator takes the average/median basket of consumers in calculating inflation adjustment. However, households gaining new additional jobs are not average/median households to begin with. And most certainly not in 2016, when labour markets were tight. In other words, median household today is more impacted by higher inflation costs pertaining to necessary non-discretionary expenditures than median household in 1999. Without adjusting for this, notional Census Bureau figures misstate (to the upside) current income gains.

3) In 1999, the Census Bureau data on household incomes used different methodology than it does today. The methodology changed in 2013, at which point in time, the Census Bureau estimated that 2013 median income was about USD1,700 higher based on new methodology than under pre-2013 methodology. Since then, we had no updates on this adjustment, so the gap could have actually increased. Today’s number show that median household income at the end of 2016 was only USD374 higher than in 1999. In other words, it was most likely around USD1,330 or so lower not higher, under pre-2013 methodology. Taking a very simplistic (most likely inaccurate, but somewhat indicative) adjustment for 2013-pre-post differences in methodologies, current 2016 reading is roughly 1.6 percent lower than 2007 local peak, and roughly 2.3 percent lower than 1999-2000 level.

4) Costs and taxes do matter, but they do not figure in the Census Bureau statistic. Quite frankly, it is idiotic to assume that gross median income matters to anyone. What matters is after-tax income net of the cost of necessities required to earn that income. Now, consider a simple fact: in 1999, majority of jobs in the U.S. were normal working hours contracts. Today, huge number are zero hours and GIG-economy jobs. The former implied regular and often subsidised demand for transport, childcare, food associated with work etc. The latter implies irregular (including peak hours) transport, childcare, food and other services demand. The former was cheaper. The latter is costlier. To earn the same dollar in traditional employment is not the same as to earn a dollar in the GIG-economy. Worse, taxes are asymmetric across two types of jobs too. GIG-economy adds to this problem yet another dimension. Many GIG-economy earners (e.g. Uber drivers, delivery & messenger services workers, or AirBnB hosts) sue income to purchase assets they use in generating income. These are not reflected in the Census Bureau earnings, as the official figures do not net out cost of employment.

5) Finally, related to the above, there is higher degree of volatility in job-related earnings today than in 1999. And there is longer duration of unemployment spells in today’s economy than in the 1990s. Which means that risk-adjusted dollar earned today requires more unadjusted dollars earned than in 1999. Guess what: Census Bureau statistic shows not-risk-adjusted earnings. You might think of this as an ‘academic’ argument, but we routinely accept (require) risk-adjusted returns in analyzing investment prospects. Why do we ignore tangible risk costs in labor income?

Key point here is that any direct comparison between 1999 and 2016 in terms of median incomes is problematic at best. It is problematic in technical terms (methodological changes and CPI deflator changes), and it is problematic in incidence terms (composition of work earnings, risks, incidences of costs and taxes). My advice: don’t ever do it without thinking about all important caveats.

Materially, U.S. households' disposable risk-adjusted incomes are lower today than they were in 1999. That explains why American households are drowning in debt: the demand for income vastly exceeds the supply of income, even as official median household size shrinks and cost of housing is being deflated by children staying in parents homes for decades after college. The rosy times are not upon us, folks.

12/9/17: Partisan Gap in Consumers' Perception of the U.S. Economy Explodes


A quick post, H/T @profsufi. Here is a chart from the U of Michigan consumer survey showing an explosion in partisan gap between Democrats and Republicans when it comes to self-reported consumer sentiment:

As Sufi stated in his tweet, "Rise in partisan bias in economic expectations according to Michigan Survey of Consumers data". Notably,

  1. Democrats negative perceptions are not at extraordinarily low levels. Similar applied for the Republicans during Obama 1 Administration and Carter Administration, and for Democrats in Carter Administration and Bush W2 Administration. So negative perceptions are not the key driver of the gap dramatic rise.
  2. Republican's optimism during the Trump Administration [short so far] tenure is the main driver of the partisan gap. 
  3. Current partisan gap reflects data that barely touches Trump Administration, with majority of economic performance figures still impacted heavily by the inertia inherent from the Obama Administration days. 
This has to fly in the face of anyone presenting Trump Presidency as the 'minority Republican' thing. Adjusting for the lags in data is impossible without looking at specific monthly series and down weighing observations closer to Obama tenure (I suggest authors do that), but it is clear that the true extent of Trump-specific gap has to reflect also some share of the Republican's perceptions of Obama 2 economic conditions. Which will most likely make the current gap even larger. 

Another point worth making is that the data above clearly shows just how subjective and unreliable (from the point of view of revealing actual quality of underlying economic conditions) the measures of Consumer Confidence are. 

Friday, September 8, 2017

8/9/17: Euro complicates ECB's decision space


My pre-Council meeting analysis of the ECB monetary policy space was published in Sunday Business Post yesterday: https://www.businesspost.ie/opinion/currency-moves-complicate-ecbs-decision-396981.  It turned out to be pretty much on the money, focusing on euro FX rates constraints and QE normalisation path...


Thursday, September 7, 2017

7/9/17: Millennials’ Support for Liberal Democracy is Failing: A Deep Uncertainty Perspective


We just posted three new research papers on SSRN covering a range of research topics.

The third paper is "Millennials’ Support for Liberal Democracy is Failing: A Deep Uncertainty Perspective" and it is available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3033949.

Abstract
Recent data on electoral dynamics and sociopolitical preferences present evidence of declining popular support for the values and institutions of traditional liberal democracy across some western societies. This decrease is more pronounced within the younger cohort of voters, especially the Millennials. Key drivers for the younger generations’ scepticism toward liberal democratic values are domestic intergenerational political and socioeconomic imbalances that engender the environment of deeper uncertainty. Policy and institutional responses to democratic volatility are inconsistent with those necessary to address rising deep uncertainty and may exacerbate and accelerate the negative fallout from the pressures on liberal democratic institutions.

7/9/17: What the Hack: Systematic Risk Contagion from Cyber Events


We just posted three new research papers on SSRN covering a range of research topics.

The second paper is "What the Hack: Systematic Risk Contagion from Cyber Events", available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3033950.

Abstract:

This paper examines the impact of cybercrime and hacking events on equity market volatility across publicly traded corporations. The volatility influence of these cybercrime events is shown to be dependent on the number of clients exposed across all sectors and the type of the cyber security breach event, with significantly large volatility effects presented for companies who find themselves exposed to cybercrime in the form of hacking. Evidence is presented to suggest that corporations with large data breaches are punished substantially in the form of stock market volatility and significantly reduced abnormal stock returns. Companies with lower levels of market capitalisation are found to be most susceptible. In an environment where corporate data protection should be paramount, minor breaches appear to be relatively unpunished by the stock market. We also show that there is a growing importance in the contagion channel from cyber security breaches to markets volatility. Overall, our results support the proposition that acting in a controlled capacity from within a ring-fenced incentives system, hackers may in fact provide the appropriate mechanism for discovery and deterrence of weak corporate cyber security practices. This mechanism can help alleviate the systemic weaknesses in the existent mechanisms for cyber security oversight and enforcement.