18/4/16: Leverage Risk, the Burden of Debt & the Real Economy

Risk of leverage has been a cornerstone of our recent lectures concerning the corporate capital structure decisions in the MBAG 8679A: Risk & Resilience:Applications in Risk Management class at MIIS. However, as noted on a number of occasions in both MBAG 8679A and other courses I teach at MIIS, from macroeconomic point of view, corporate leverage risks are just one component of the overall economic leveraging equation. The other three components are: household debt, government debt, and the set of interactions between the burden of all three debt sources and the financial system at large.

An interesting research paper by Mikael Juselius and Mathias Drehmann, titled “Leverage Dynamics and the Burden of Debt” (2016, Bank of Finland Research Discussion Paper No. 3/2016: http://ssrn.com/abstract=2759779) looks that both leverage risk arising from the U.S. corporate side and household side.

Per authors, “in addition to leverage, the debt service burden of households and firms is an important link between financial and real developments at the aggregate level. Using US data from 1985 to 2013, we find that the debt service burden has sizeable negative effects on expenditure.” This, in turn, translates into lower economy-wide investment and consumption - two key components of the aggregate demand. Debt “interplay with leverage also explains several data puzzles, such as the lack of above-trend output growth during credit booms and the depth and length of ensuing recessions, without appealing to large shocks or non-linearities. Using data up to 2005, our model predicts paths for credit and expenditure that closely match actual developments before and during the Great Recession.”

With slightly more details: the authors found that “the credit-to-GDP ratio is cointegrated with real asset prices, on the one hand, and with lending rates, on the other. This implies that the trend increase in the credit-to-GDP ratio over the last 30 years can be attributed to falling lending rates and rising real asset prices. The latter two variables are, moreover, inversely related in the long-run.”

In addition and “more importantly, we find that the deviations from the two long-run relationships - the leverage gap and the debt service gap henceforth - have sizeable effects on credit and output. …real credit growth increases when the leverage gap is negative, for instance due to high asset prices. And higher credit growth in turn boosts output growth. Going beyond the existing evidence, we find that the debt service gap plays an additional important role at the aggregate level that has generally been overlooked: it has a strong negative impact on consumption and investment. In addition, it negatively affects credit and real asset price growth.”

The link between leverage gap and debt service gap:

In summary, “The leverage and debt service gaps hold the key for explaining the divergence of credit and output in recent decades. For instance, in the late 1980s and mid 2000s both gaps were negative boosting credit and asset price growth. This had a positive effect on output, but not one-to-one with credit, which caused the credit-to-GDP ratio to rise. This in turn pushed the debt service gap to positive values, at which point it started to offset the output effects from high credit growth so that output growth returned to trend. Yet, as the leverage gap remained negative, credit growth was still high, ie we observed a “growthless” credit boom. This continued to increase the debt-service gap, which had a growing negative effect on asset prices and expenditure, driving the leverage gap into positive territory. And once both gaps became positive they worked in the same direction, generating a sharp decline in output even without additional
large shocks or crises-related non-linearities. The subsequent downturns were deep and protracted, as the per-period reduction in credit had to be faster than the per-period decline in output in order to lower the credit-to-GDP ratio and thereby close the two gaps. This also implied that the recovery was “creditless”.”

Highly intuitive and yet rather novel results linking leverage risk to debt financing costs.

18/4/16: Rollover Risk, Competitive Pressures & Capital Structure of the Firm

Capital structure of the firm, as we discussed in our MBAG 8679A: Risk & Resilience:Applications in Risk Management class in recent weeks, is about counter-balancing equity (higher cost capital with greater safety cushion for the firm) against debt (lower cost capital with higher risk associated with leverage risk). As we noted in some extensions to traditional models of leverage risk, decision to take on new debt as opposed to issue new equity can also involve considerations of timing and be linked to future expected funding demands by the firm.

An interesting corollary to our discussions is what happens when risk of debt roll-over at maturity enters the decision making tree.

A recent paper by Gianpaolo Parise, titled “Threat of Entry and Debt Maturity: Evidence from Airlines” (April 2016, BIS Working Paper No. 556: http://ssrn.com/abstract=2758708) tries to address this question.

In the presence of low-cost competition airlines, traditional, large airlines tend to alter their debt structure. This effect, according to Parise, is pronounced in the case of legacy airlines forced to defend their strategically important routes from new entrants. Per Parise, “…the main findings suggest that airlines respond to entry threats trading off financial flexibility for lower rollover risk.”

More specifically, Parise found that “…a one standard deviation increase in the threat of entry triggers an increase of 4.5 percentage points in the proportion of long-term debt held by incumbent airlines (a 7.4% increase relative to the baseline of 60%). This effect is particularly strong for airlines whose debt is rated as “speculative” and that are financially constrained, i.e., airlines that have in general a more difficult access to credit.”

On the other hand, “the threat of entry has no significant effect on the leverage ratio.”

Overall, “threatened airlines issue debt instruments with longer maturity and with covenants” and that debt issuance aiming to increase maturity comes via intermediated lending (loans) rather than via bond markets (direct market).

“The results are consistent with models in which firms set their optimal debt structure in the presence of costly rollover failure As Parise notes, “Longer debt maturity allows firms to reduce
rollover (or liquidity) risk, i.e., the risk that lenders are unwilling to refinance when bad news
arrives. Rollover risk enhances credit risk…, magnifies the debt overhang problem…, weakens investment,… and exposes the firm to costly debt restructuring…”

A very interesting study showing dynamic and complex interactions between capital structure of the firm and exogenous pressures from competitive environments, in the presence of systemic roll-over risks in the financial system.

18/4/16: Demographics, Ageing & Inflation

In my Investment Theory & ESG Risk course, a week ago, we were looking at Asset Price Models extensions to incorporate inflation risks. One discussion we had was about the possible correlation between inflation and investor behaviour / choices, linked to behavioural anomalies.

A recent Bank of Finland working paper by Mikael Juselius and Elod Takats, titled “The Age-Structure – Inflation Puzzle” (2016, Bank of Finland Research Discussion Paper No. 4/2016: http://ssrn.com/abstract=2759780) sheds some light on this link via demographic side of investor / economic agent impact on inflationary expectations.

Specifically, the authors uncovered “a puzzling link between low-frequency inflation and the population age-structure”.

This link is pretty simple: due to asymmetric relationship between consumption, savings and investment across the life cycle, “the young and old (dependents) are inflationary whereas the working age population is disinflationary”.

In other words, risks of higher inflation are demographically tilted against markets / economies with either high young age dependencies, old age dependencies or both.

According to authors, “the relationship is not spurious and holds for different specifications and controls in data from 22 advanced economies from 1955 to 2014.”

And effects are large: “The age-structure effect is economically sizable, accounting e.g. for about 6.5 percentage points of U.S. disinflation from 1975 to today’s low inflation environment. It also accounts for much of inflation persistence, which challenges traditional narratives of trend inflation.”

Crucially, “the age-structure effect is forecastable” in so far as we can see pretty accurately long term demographic trends, “and will increase inflationary pressures over the coming decades”. In other words, deflationary environment today is expected to become inflationary environment tomorrow:

Hence, the rising demand for real assets and structural support for new levels of gold prices.

It’s all in the long run game.

17/4/16: Start Ups, Manufacturing Jobs and Structural Changes in the U.S. Economy

In the forthcoming issue of the Cayman Financial Review I am focusing on the topic of the declining labour productivity in the advanced economies - a worrying trend that has been established since just prior to the onset of the Global Financial Crisis. Another trend, not highlighted by me previously in any detail, but related to the productivity slowdown is the ongoing secular relocation of employment from manufacturing to services. However, the plight of this shift in the U.S. workforce has been centre stage in the U.S. Presidential debates recently (see http://fivethirtyeight.com/features/manufacturing-jobs-are-never-coming-back/).

An interesting recent paper on the topic, titled “The Role of Start-Ups in Structural Transformation” by Robert C. Dent, Fatih Karahan, Benjamin Pugsley, and Ayşegül Şahin (Federal Reserve Bank of New York Staff Reports, no. 762, January 2016) sheds some light on the ongoing employment shift.

Per authors, “The U.S. economy has been going through a striking structural transformation—the secular reallocation of employment across sectors—over the past several decades. Most notably, the employment share of manufacturing has declined substantially, matched by an increase in the share of services. Despite a large literature studying the causes and consequences of structural transformation, little is known about the dynamics of reallocation of labor from one sector to the other.”

“There are several margins through which a sector could grow and shrink relative to the rest of the economy”:

1. “…Differences in growth and survival rates of firms across sectors could cause sectoral reallocation of employment”
2. “…differences in sectors' firm age distribution could affect reallocation since firm age is an important determinant of growth or survival behavior” 
3. “…the allocation of employment at the entry stage which we refer to as the entry margin could contribute to the gradual shift of employment from one sector to the other.”
4. “…because the speed at which differences in entry patterns are reflected in employment shares depends on the aggregate entry rate, changes in the latter could affect the extent of structural transformation.”

Factors (1) and (2) above are referenced as “life cycle margins”.

The study “dynamically decomposed the joint evolution of employment across firm age and sector”, focusing on three sectors: manufacturing, retail trade, and services.

Based on data from the Longitudinal Business Database (LBD) and Business Dynamic Statistics (BDS), the authors found that “…at least 50 percent of employment reallocation since 1987 has occurred along the entry margin.” In other words, most of changes in manufacturing jobs ratio to total jobs ratio in the U.S. economy can be accounted for by new firms creation being concentrated outside manufacturing sectors.

Furthermore, “85 percent of the decline in manufacturing employment share is predictable from the average life cycle dynamics and the early 1980s distribution of startup employment across sectors. Further changes over time in the distribution of startup employment away from manufacturing, while having a relatively small effect on manufacturing where entry is less important, explain almost one-third of the increase in the services employment share.”

Again, changed nature of entrepreneurship, as well as in the survival rate of new firms created in the services sector, act as the main determinants of the jobs re-allocation across sectors.

Interestingly, the authors found “…little role for the year-to-year variation in incumbent behavior conditional on firm age in explaining long-term sectoral reallocation.” So legacy firms have little impact on decline in manufacturing sector jobs share, which is not consistent with the commonly advanced thesis that outsourcing of American jobs abroad is the main cause of losses of manufacturing sector jobs share in the economy.

Lastly, the study found that “…a 30-year decline in overall entry (which we refer to as the \startup deficit) has a small but growing effect of dampening sectoral reallocation through the entry margin.”

These are pretty striking results.

The idea that the U.S. manufacturing (in terms of the sector importance in the economy and employment) is either in a decline or on a rebound is not as straight forward as some political debates in the U.S. suggest.

Reality is: in order to reverse or at least arrest the decades-long decline of manufacturing jobs fortunes in America, the U.S. needs to boost dramatically capex in the sector, as well as shift the sector toward greater reliance on human capital-complementary technologies. It is a process that combines automation with more design- and specialist/on-specification manufacturing-centric trends, a process that is likely to see accelerated decline in lower skills manufacturing jobs before establishing (hopefully) a rising trend for highly skilled manufacturing jobs.

17/4/16: Human Capital, Management & Value-Added

The value of management to a given firm rests not only in more efficient use of physical resources and financial capital, as well as corporate / business strategy, but also in the ability of the firm to identify, hire, retain and enable high quality human capital. This is a rather common sense conclusion that might be drawn by any analyst of management systems and any business student.

However, the question always remains as to how much of the firm value-added arises from managerial inputs, as opposed to actual human capital inputs.

Stefan Bender, Nicholas Bloom, David Card, John Van Reenen, and Stephanie Wolter decided to attempt to quantify these differences. In their paper “Management Practices, Workforce Selection and Productivity” (March 2016, NBER Working Paper No. w22101: http://ssrn.com/abstract=2752306) they note that “recent research suggests that much of the cross-firm variation in measured productivity is due to differences in use of advanced management practices.”

“Many of these practices – including monitoring, goal setting, and the use of incentives – are mediated through employee decision-making and effort. To the extent that these practices are complementary with workers’ skills, better-managed firms will tend to recruit higher-ability workers and adopt pay practices to retain these employees.”

The authors then use a survey data on the management practices of German manufacturing firms, as well as data on earnings records for their employees “to study the relationship between productivity, management, worker ability, and pay”.

Per authors: “As documented by Bloom and Van Reenen (2007) there is a strong partial correlation between management practice scores and firm-level productivity in Germany. In our preferred TFP [total factor productivity] estimates only a small fraction of this correlation is explained by the higher human capital of the average employee at better-managed firms. A larger share (about 13%) is attributable to the human capital of the highest-paid workers, a group we interpret as representing the managers of the firm. And a similar amount is mediated through the pay premiums offered by better-managed firms.”

Human capital value-added is neither uniform across types of employees, nor is it independent of the management systems, which means that increasing the value of human capital in the economy requires more emphasis on the structure of the overall utilisation of talent, not just acquisition of talent. This is exactly consistent with the C.A.R.E. framework for human capital-centric economy that I outlined some years ago, here http://trueeconomics.blogspot.com/2013/11/14112013-human-capital-age-of-change.html, the framework of Creating, Attracting, Retaining and Enabling human capital.

The study also confirms that “looking at employee inflows and outflows, … better-managed firms systematically recruit and retain workers with higher average human capital.”

Overall, the authors concluded that “workforce selection and positive pay premiums explain just under 30% of the measured impact of management practices on productivity in German manufacturing.”

These results should add to questions about the ability of the Gig-economy firms, e.g. online platforms providers for labour utilisation, such as Uber, to significantly improve productivity in the economy. The reason for this is simple: contingent workforce talent pool is at least one step further removed from management than in the case of traditional employees. As the result, it is quite possible that contingent workforce productivity does not benefit directly from management quality. If so, that sizeable, ‘just under 30% of the measured impact’ in terms of improved productivity, arising from better management practices, workforce selection and pay premiums can be out of reach for Gig-economy firms and their contingent workers.

Again, as I noted repeatedly, including in my recent presentation at the CXC Global “Future of Work” Summit (see here: http://trueeconomics.blogspot.com/2016/04/7416-globalization-and-future-of-work.html), the key to developing a productive and sustainable Gig-economy will be in our ability to develop institutional, regulatory and strategic frameworks for improving management of human capital held by contingent workforce.

17/4/16: Peer Effects in Classroom: The Value of Better Discipline?

In workplace, as well as in education, peer-pressure and competition, peer-linked cooperation and collaboration and other peer-linked effects of have been important contributors to work- and learning-related outcomes. Ditto for entrepreneurship, as collaborated by the effects of clusters, such as the Silicon Valley. However, we tend to think of peer effects as arising from more mature, adult-level interactions in either third level education, or career-linked workplaces.

As noted by Scott Carrell, Mark Hoekstra and Elira Kuka in their paper “The Long-Run Effects of Disruptive Peers” (February 2016 as NBER WP No. w22042: http://ssrn.com/abstract=2739567), “there is relatively little evidence on the long-run educational and labor market consequences of childhood peers.”

So the authors examined “administrative data on elementary school students” and students’ “subsequent test scores, college attendance and completion, and earnings” to identify any potential effects of childhood peers on educational outcomes.

“To distinguish the effect of peers from confounding factors, we exploit the population variation in the proportion of children from families linked to domestic violence, who were shown by Carrell and Hoekstra (2010, 2012) to disrupt contemporaneous behavior and learning.”

The end results show that “exposure to a disruptive peer in classes of 25 during elementary school reduces earnings at age 26 by 3 to 4 percent. We estimate that differential exposure to children linked to domestic violence explains 5 to 6 percent of the rich-poor earnings gap in our data, and that removing one disruptive peer from a classroom for one year would raise the present discounted value of classmates' future earnings by $100,000.”

These are striking numbers. Accumulated over life-cycle of employment, gains from reducing classroom-level disruptive behaviour of peers can lead to a significant uplift in both, economic welfare and individual financial wellbeing. It can also, potentially, help closing the income inequality gaps. The question, however, is how does one achieve such an outcome in the real world, where even disruptive students have a right to education.

15/4/16: Tech Sector Finance: Gravity of Gravy

Previously, having posted on disconnection between S&P500 market valuations and basic corporate finance (earnings and distributions) - see that post here: http://trueeconomics.blogspot.com/2016/04/15416-corporate-finance-s-and-bubble.html - it is time to remind us all what a popping bubble looks like.

Earlier this month, I was in San Francisco, the epicentre of the corporate finance-free world of tech. Not surprisingly, few smoke breaks and few chats over a glass of wine with some tech folks revealed a very interesting insight: every single one tech CEO/CFO/COO (but not CTO) I spoke to was concerned with evaporating funding in the markets for non-public equity financing around the Silicon Valley.

Need confirmation? Here is a chart through 1Q 2016 on Tech IPOs trends:

Source: https://www.theatlas.com/charts/Nkk4jHLCe

And a note from the WSJ: http://www.wsj.com/articles/startup-investors-hit-the-brakes-1460676478 on same with a handy graph:

And the numbers of deals? Why, off the cliff too:

Source: https://www.theatlas.com/charts/Vk8_bYUAl

There is not panic, yet, but there is panic already in works: techies are retrenching on new hiring and there are rumours of some layoffs in younger companies. Meanwhile, states-sponsored agencies seeking to lock start ups and existent players into relocating to their countries or landing in the countries with regional HQs are still shopping around, as if money will always be there to rent plush offices and the case-styled furniture for those whiz kids who make up apps with little cash flow behind them...

It all might be temporary. Or it might be the beginning of the real thing. But one thing is certain: on a long enough timeline, one can defy gravity of basic corporate finance only as long as the interest rates defy gravity of risk pricing.

15/4/16: Corporate Finance, S&P500 and Bubble Trouble...

Classical corporate finance tells us that companies should be valued on their earnings with past earnings being indicative of future earnings (predictive component). Which is tosh. In today's world that is.

Q4 2016 saw highest payouts to shareholders (combined cash dividends and share repurchases) in over 10 years (couple of slides from my course presentation):

And yet... yet... earnings have hit the brick wall back in Q3 2014 and have been trending down ever since:

You really can't call S&P500 anything but a sail-in-the-Fed-wind. There are no fundamentals sustaining it above 1600-1650 range. At least, not corporate fundamentals.

Unless, of course, one expects the recent extraordinary payout performance to remain indefinitely present in the future. Which only a sell-side analyst or a lunatic can...

15/4/16: Slovakia v France: Risk Divergence

I love it when the good guys lead: "Slovakia leaps ahead of France, reveals country risk survey

Full article available here: http://www.euromoney.com/Article/3545875/Slovakia-leaps-ahead-of-France-reveals-country-risk-survey.html?copyrightInfo=true

My full comment on the matter:

"From macroeconomic perspective the two economies appear to be heading in the opposite direction.

While France is experiencing weakening growth momentum with forecast real GDP growth rates for 2016-2017 at around 1.55 percent on average and declining (1H 2015 compared to current, a forecast swing of around 0.05 percentage points), Slovakian economy is gaining speed, with current forecast growth rate at around 3.57 percent for 2016-2017, representing an upgrade of around 0.3 percentage points.

Much of this is accounted for by differences in investment (rising in Slovakia, as a share of GDP, while relatively stagnant in France), as well as growth in exports of goods and services (with Slovakia expected to outperform France in terms of growth in exports in both 2016 and 2017 - a reversal on 2015 outrun).

In fiscal policy terms, both countries are expected to post modest reduction in total burden of Government in the economy, reflected in the declining ratio of Government revenues to GDP over 2016-2017. However, in France, this forecast is less certain due to political cycle and ongoing lack of progress on both structural reforms and fiscal targets. In contrast, Slovakia already runs relatively lean, strongly value-for-money focused public spending policies. As the result, even under relatively rosy projections, France will continue to post greater Government deficits than Slovakia through 2017. Crucially, even with negative Government yields on French debt, France is currently running deeper primary deficits than Slovakia, which suggests that the French fiscal space is much thinner than headline difference between the two countries suggest.

The above dynamics also point to continued divergence between the two countries' paths in terms of external balances. Slovakia's current account surplus in 2016-2017 is likely to average at around 0.15 percent of GDP. In contrast, France's current account deficit is expected to be around 0.37 percent of GDP.

In simple terms, diverging macroeconomic and political risks paths do warrant risk repricing in the case of both Slovakia (to the downside of risks) and France (to the upside in terms of risks assessment) into 2016, and possibly into 2017."

The risk trends are indeed showing counter-movement:

15/4/16: Of Breakeven Price of Oil: Russia v ROW

There has been much confusion in recent months as to the 'break-even' price of oil for Russian and other producers. In particular, some analysts have, in the past, claimed that Russian production is bust at oil prices below USD40pb, USD30pb and so on.

This ignores the effects of Ruble valuations on oil production costs. Devalued Ruble results in lower U.S. Dollar break-even pricing of oil production for Russian producers.

It also ignores the capital cost of production (which is not only denominated in Rubles, with exception of smaller share of Dollar and Euro-denominated debt, but is also partially offset by the cross-holdings of Russian corporate debt by affiliated banks and investment funds). It generally ignores capital structuring of various producers, including the values of tax shields and leverage ratios involved.

Third factor driving oil break-even price for Russian (and other) producers is ability to switch some of production across the fields, pursuing lower cost, less mature fields where extraction costs might be lower. This is independent of type of field referenced (conventional vs unconventional oils).

Russian Energy Ministry recently stated that Russian oil production break-even price of Brent for Russian producers is around USD 2 pb, which reflects (more likely than not) top quality fields for conventional oil. Russian shale reserves break-even at USD20 pb. In contrast, Rosneft estimates break-even at USD2.7 pb (February 2016 estimate) down from USD4.0 pb (September 2015 estimate).

Here is a chart mapping international comparatives in terms of break-even prices that more closely resembles the above statements:

Here is another chart (from November 2015) showing more crude averaging, with breakdown between notional capital costs (not separating capital costs that are soft leverage - cross-owned - from hard leverage - carrying hard claims on EBIT):

Another point of contention with the above figures is that they use Brent grade pricing as a benchmark, whereby Russian oil is priced at Urals grade, while U.S. prices oil at WTI (see here: http://oilprice.com/Energy/Crude-Oil/Will-Russian-Urals-Overtake-Brent-As-The-Worlds-Oil-Benchmark.html). All three benchmarks are moving targets relative to each other, but adjusting for two factors:

• Historical Brent-Urals spread at around 3.5-4 USD pb and
• Ongoing increase in Urals-like supply of Iranian oil

we can relatively safely say that Russian break-even production point is probably closer to USD7.5-10 pb Brent benchmark than to USD20pb or USD30pb.

Another interesting aspect of the charts above is related to the first chart, which shows clearly that Russian state extracts more in revenues, relative to production costs, from each barrel of oil than the U.S. unconventional oil rate of revenue extraction. Now, you might think that higher burden of taxation (extraction) is bad, except, of course, when it comes to the economic effects of the curse of oil. In normal economic setting, a country producing natural resources should aim to capture more of natural resources revenues into reserve funds to reduce its economic concentration on the extractive sectors. So Russia appears to be doing this. Which, assuming (a tall assumption, of course) Russia can increase efficiency of its fiscal spending, means that Russia can more effectively divert oil-related cash flows toward internal investment and development.

During the boom years, it failed to do so (see here: http://trueeconomics.blogspot.com/2016/02/10216-was-resource-boom-boom-for.html) although it was not unique amongst oil producers in its failure. 

Note: WSJ just published some figures on the same topic, which largely align with my analysis above: http://graphics.wsj.com/oil-barrel-breakdown/?mod=e2tw.

Update: Bloomberg summarises impact of low oil prices on U.S. banks' balancesheets: http://www.bloomberg.com/news/articles/2016-04-15/wall-street-s-oil-crash-a-story-told-in-charts.

Update 2: Meanwhile, Daily Reckoning posted this handy chart showing the futility of forecasting oil prices with 'expert' models

15/4/16: Banking Union, Competition and Banking Sector Concentration

One of the key changes in recent years across the entire U.S. economy has been growth in market concentration (lower competition) and regulatory burden increases in a number of sector, including banking. A good summary of the matter is provided here: http://www.americanactionforum.org/research/market-concentration-grew-obama-administration/ .

However, an interesting chart based on the U.S. Fed data, shows that even with these changes U.S. banking sector remains relatively more competitive than in other advanced economies:

Source: @HPSInsight

Interestingly, European banks are also becoming more regional, as opposed to global, players as discussed here: http://www.nakedcapitalism.com/2016/03/the-us-is-beginning-to-dominate-global-investment-banking-implications-for-europe.html

Chart next shows market shares of the European Investment Banking markets accruing to banks originating in the following jurisdictions:

Source: @NakedCapitalism

As an argument goes: “Deutsche Bank and Barclays are the only Europeans left in the top seven for the EMEA market. But they are likely to lose their positions because Deutsche Bank is currently undergoing a major reorganisation and Barclays is in the process of executing the Vickers split. In the investment banking field, the only pan-European banks will all soon be American. This has the corollary, for good or bad, that European national and EU-level authorities, such as the European Commission, will have rather less direct control over them. A key part of the European financial system is slipping out of the grasp of the European authorities.”

Which begs two questions:

Does Europe need more regulation-induced consolidation in the sector, aiming to make TBTF European banking giants even bigger and even less diversified globally, as the European Banking Union and European Capital Markets Union, coupled with increasing push toward greater regulatory constraints on Fintech sector are likely to do?

Or does Europe need more disruptive and more agile, as well as risk-diversified, smaller banking systems and more open innovation culture in banking and financial services?


Note: you can see my analysis of the European Capital Markets Union here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2592918

12/4/16: Look, Ma... It's [not] Working: IMF & the R-word

A handy chart from the IMF highlighting changes over the last 12 months in forecast probability of recession 12mo forward across the global economy

Yes, things are getting boomier... as every major region, save Asia and ROW are experiencing higher probability of recession today than in both October 2015 and April 2015, and as probability of a recession in 2016 is now above 30 percent for the Euro area and above 40 percent for Japan.

In that 'repaired' world of Central Banks' activism (described here: http://trueeconomics.blogspot.com/2016/04/12416-imf-rip-growth-update-risks.html) we can only dream of more assets purchases and more government debt monetizing, and more public investment on things we all can't live without...

Because, look, it's working: