5/2/17: European Patents and Ireland's 'Knowledge Economy' Myths

Irish policymakers are keen on promoting Ireland as a technology and R&D centre of excellence, often claiming the country is a ‘Knowledge Economy’, a ‘Data Island’, a ‘Europe’s Tech Capital’ and so on. While catchy, these tag lines are far from reality, and, in fact, represent an empirically dubious proposition. 

To establish this claim, consider the European Patent Office data on patent filings and approvals, with the latest data set covering the period of 2006-2015. 

As chart below clearly shows, Ireland is far from being a significant source of patent filing in Europe, despite the fact that many patents from Ireland are filed by the U.S. and other multinationals, including a score of foreign companies that choose to tax-invert into Ireland. The EPO data, in fact, fails to control for this distortion. Still, even with those companies filings counted as ‘Irish’ by origin, Ireland ranks 14th in a key metric of the rate of European Patent Applications per million of inhabitants. 

Worse, Irish rate of patent applications (119 per 1 million of inhabitants) is below the mean for the sub-sample of European states (including EU28 states and other countries within the EEA). Statistically, Irish rate of patent applications per inhabitant is not distinguishable from the rates filed by Italy and Slovenia, and is well below the rate recorded for France, Belgium, Austria, Germany, Denmark, Finland, Sweden and the Netherlands. Irish numbers are also statistically indistinguishable from the global average - the average that includes non-European states’ filings. It is worth noting that the data set includes other countries, that similar to Ireland serve as major tax optimnization locations for R&D and IP, e.g. Luxembourg and the Netherlands. However, even controlling for these states, Irish data does not shine beyond being average.

In absolute terms, Irish patent filings and applications with the EPO have trended up in 2006-2010 period, but have since flat-lined (on trend) for filings and declined (on trend) for applications. 

In addition to the chart above, combined filings and applications for EPO patents by Irish-origination stood at 1,325 in 2015, down on 1,364 in 2014 and down on 1,356 average for 2008-2011 period. While data can be interpreted in a number of ways, there is clearly no indication of an improving trend in either filings or applications over the recent years. This comes on foot of aggressive acceleration in tax inversions into Ireland in previous years - an acceleration that brought into Ireland a range of large R&D-intensive companies.

Consistent with the above, Ireland’s share of all European Patent Office filings and applications has declined, on trend, in recent years, as evidenced by data presented in the chart below:

As the chart above shows, Ireland accounts of just 0.266% of all EPO patent filings and 0.364% of all EPO patent applications. Separately reported data for patents approvals shows Irish share of all patents granted by EPO to be just 0.395%. The number is laughably negligible by Europe-wide standards and is massively out of line with Irish share of European GDP. However, these numbers are consistent with the simple fact, also highlighted by EPO data, that Ireland fails to register in the top tier of generators of patents in any of the sectors tracked by EPO. 

In summary, Ireland is far from being a powerhouse for R&D and knowledge economy activities as measured by a key research output measured by European authorities. 

3/2/17: Global Composite PMI signals improving growth in January

Over the last four months, I have been suggesting that markets participants pay close attention to Global PMIs, and in particular to the emerging signals of firming global economic growth. January 2017 figures did not disappoint on this front.

I covered Manufacturing PMI yesterday in a post available here.

Today, we got the reading for Services and Composite data. Both printed 53.9, which marks statistically significant expansion and a rise on 4Q 2016 figures, suggesting that global growth is still accelerating. Crucially, new orders are continuing to rise as well.

Per Markit: “The J.P.Morgan Global All-Industry Output Index… posted 53.9 in January, its best reading since March 2015 and up from 53.6 in December. The index has now signalled expansion for 52 consecutive months.”

One caveat is that China data is not included in both Manufacturing and Services PMI readings. But, As shown here: China Manufacturing PMI posted lacklustre performance in January, barely staying above 50.0 level.

Again, quitting Markit, “growth of global service sector business activity improved to a 17-month high in January, offsetting a minor easing in the rate of expansion of manufacturing production.”

Geographically, “the acceleration in the rate of increase in all-industry output was led by the US and Russia. US growth was the sharpest since November 2015, while Russia registered its quickest expansion of economic activity for over eight-and-a-half years. The euro area saw output growth steady at December’s 67-month record, while rates of increase slowed in Japan and the UK. India and Brazil both saw all-industry activity decline at the start of 2017.”

“Global employment rose again in January, with the pace of job creation matching December’s 19-month record.” Again, geographically, employment “…increased in the US, the eurozone, Japan, the UK, Russia and India, but fell further in Brazil.”

Crucially for monetary policy forward, inflation ticked up as well.

Overall, Global Manufacturing PMI remained at rather robust levels of 52.7 in January 2017, comparable to those attained at the end of 4Q 2016 and well above the 51.4 average for the last 4 years. Global Services PMI ended January 2017 at 53.9, which is above already robust 53.5 recorded in 4Q 2016 and above the 4-year average of 53.4. At 53.9, Global Composite PMI is slightly ahead of 4Q 2016 levels (53.6) and is well above 53.0 average for the last 5 years. Thus, across both sectors, the global economic expansion appears to be improving to the upside at the start of 1Q 2017.

Analysis of BRIC Services and Composite PMIs coming up as soon as we have China data.

2/2/17: BRIC Manufacturing PMIs: Russia Leads, Brazil Drags

Quick run through the Manufacturing PMIs for January for BRIC economies:

Brazil's Manufacturing PMI slumped to 44.0 in January 2017, down from 45.2 in December, marking 24th consecutive month of sub-50 readings. Worse, rate of contraction in the sector fell to 46.3 in October 2016, prompting some analysts to declare a possible turnaround in Latin America's largest economy. This has now been fully erased, with month-after-month drops through January. January reading is so dire, it marks the lowest reading in seven months and the fourth lowest reading since April 2009 and ninth lowest on record. Three-month average through January sits at 45.1, which is worse than 46.0 3mo average previously and 45.6 3mo average reading through January 2016. In simple terms, economic contraction is accelerating in the case of Brazil, despite the fact that the country has been in a crisis since mid-2013.

Russian Manufacturing PMI continued to surge in January, rising from 53.7 in December 2016 to 54.7. This marks 6th consecutive above-50 reading and, more importantly, marks the highest rate of growth in 70 months (since March 2011). Another important marker, the index has posted increasing rates of growth every month since July 2016, and has now broke away from the resistance at 53.6-53.7. Index's 3mo average though January 2017 is at 54.0, marking a huge reversal of fortunes compared to 3mo average through January 2016 (49.5). All of this is consistent with rapid recovery from the 2014-2016 crisis and we can date the start of this recovery back to May-June 2016, based on Manufacturing data.

India's Manufacturing PMI regained 50.0 territory rising to statistically insignificant 50.4 in January 2017 from 49.6 in December 2016. 3mo average through January 2071 is at 50.8, which is slightly better than 50.2 3mo average a year ago. The rate of Manufacturing expansion is the second slowest in 13 months, implying that the recovery in the Indian economy is still very fragile. As I noted in 4Q analysis of BRIC PMIs last month, India is suffering from the economic crisis brought about by botched de-monetisation of its economy. This crisis appears to be easing, but is not over, yet.

China's Manufacturing PMI failed to gain faster momentum compared to December 2016 (51.9), falling back to 51.0 in January 2017. 51.0 is not a statistically significant reading for growth in China's case, although the index reading in January was still third highest since August 2014. Chinese Manufacturing PMIs have now been notionally (but not statistically) above 50.0 in five consecutive months. Current 3mo average is at 51.3, which is a sizeable improvement on 3mo average through January 2016 (49.5). Still, current PMI reading continues to signal substantial weakness in Chinese Manufacturing and is a reason to worry.

Charts below plot the trends in Manufacturing PMIs and tabulate more recent changes:

Chart below contextualises January PMI readings into quarterly data set and includes comparative for the Global Manufacturing PMI:

Overall, Russia continues to lead BRIC economies in Manufacturing PMI readings for the third month in a row. China comes in second after Russia for the second month in a row. India is effectively posting stagnant economic performance, while Brazil is showing accelerated rate of contraction.

2/2/17: FactSet on Five 'Notable' 2016 Corporate Data Breaches

In our recent working paper on the systemic effects of cyber risks expressed via financial markets, we have shown the first empirical evidence of systemic (cross exchanges and cross companies) contagion from cyber risks to share prices of the world’s largest corporates, starting with 2014. You can read the full paper here: http://trueeconomics.blogspot.com/2017/01/23117-regulating-for-cybercrime-hacking.html.

Some new evidence on the effects of cyber crime on corporate performance is now also presented in a recent FactSet analysis here.

In this article, FactSet look at the corporate performance effects arising from five “notable” 2016 data breaches, specifically focusing on the stock performance. The methodology in this analysis, unfortunately, is weak and does not lend itself to establishing any specific hypotheses, including those claimed.

Still, an interesting collection of factoids and illustrations of the shorter term impacts (or lags in such).

2/2/17: Global Manufacturing PMI Continues to Signal Potential Growth Recovery in January

Market published Global Manufacturing PMI (Purchasing Managers Index) for January, showing that growth conditions in global manufacturing at the start of 2017 have matched those prevailing in December 2016, with both months posting a PMI reading of 52.7, which is:

1. Statistically above 50.0 (signalling statistically significant expansion in the sector);
2. Statistically above 51.4 - the long run average; and
3. Current reading ties December 2016 reading for a 34-month high and 51st consecutive month of above 50.0 readings.

Some important details from Markit release are:

• “The improvement in business conditions was led by the investment goods sector, where the PMI rose to its highest level in over five-and-a-half years.” This suggests that the globally depressed capex cycle might be turning to the upside, finally, after years of subdued capita investment by companies;
• “The improvement at consumer goods producers was slightly better than that seen in December, while growth in the intermediate goods category lost some momentum.” This suggests that current outlook is for improved short run consumer demand, but a moderation in previous expectations about future growth in demand might be afoot. 
• Growth was concentrated in the US, the euro area and the UK, but slowed in Japan. South Korea, Brazil, Turkey and Greece were “the only nations to register contractions.”
• “…the rate of growth in new business intakes accelerated to a two-and-a-half year high. Part of the increase in demand reflected stronger international trade flows, as new export orders rose at the quickest pace since September 2014.” This fed into “a further increase in outstanding business during January. Backlogs of work expanded for the eighth consecutive month, with growth registered across the consumer, intermediate and investment goods categories.” This is consistent with my view - expressed earlier - that going forward, expectations of future growth in final demand might be moderating.

Additionally, “the latest release sees the launch of a new index tracking business sentiment – the Future Output Index – that is based on a question asking companies if they expect output to be higher, the same or lower in 12 months’ time. The start of 2017 saw positive sentiment climb to a 19- month high, with improvements seen in the US, the euro area, Japan, the UK, India, Brazil and Russia.” I would not hold my breath for the robustness of this indicator for quite some time, as we need to see more historical data building up to assess just what exactly does it tell us about the sector activity.

As the chart above clearly shows, we are only inching toward late-2009-mid 2011 levels of activity, although we have now breached 2015-mid-2016 doldrums trend.

Overall, the data is a welcome news for the global growth, but we will have to wait and see for China and Indonesia Manufacturing PMIs to come out to see more robust picture of what is happening in global trade and manufacturing trends. We also need to see if the current levels of growth can be successfully breached to the upside in February-March. January is, overall, a challenging month to base one’s assessment for broader 1Q economic performance signals due to shorter range of working days and lags from December feeding into January numbers.

2/2/17: What Euro Health Index 2016 Tells Us about Ireland's Health System?

Some pretty harsh ratings of the Irish Health system have been released by the Euro Health Consumer Index back at the end of January. Overall, based on data across 35 countries, including European Union member states, Norway, Iceland, Switzerland and the Balkan states (Montenegro, Albania, Serbia and FYR Macedonia), Irish health system ranks miserly 21st, scoring 689 points across 6 key macro-categories of assessment (or sub-disciplines).

The sub-disciplines on which assessments were based are:

1) Patient Rights and Information

2) Accessibility (waiting times of treatment)

3) Outcomes

4) Range and reach of services

5) Prevention

6) Pharmaceuticals

Ireland’s total score is statistically indistinguishable with a higher-ranked FYR of Macedonia (20th place), not exactly a known powerhouse of social or public services and Italy (ranked 22nd). With exception of Italy, Ireland’s ranking is the weakest amongst all high income countries present in the EU and in the sample overall. 

The issue of income and relationship between amounts spent on healthcare and the system performance is a complex one. And the report does attempt some analysis of this. However, it might be an interesting exercise to see, just how much better would Ireland’s system perform were we to adapt the best practices found across each sub-discipline amongst two subsets of the countries, both with vastly lower incomes than here. 

I undertake this exercise below under two scenarios. For each sub-discipline:

1) Scenario IRL “Peripheral” assumes that Ireland adopts the best practice found in the group of the euro ‘peripherals’ states (Greece, Ireland, Italy, Portugal and Spain); and 

2) Scenario IRL “Emerging” assumes that Ireland adopts the best practice found in the group of the sampled states that comprise emerging economies of East-Central Europe (Slovenia, Estonia, Croatia, FYR Macedonia, Slovakia, Serbia, Lithuania, Latvia, Hungary, Poland, Albania, Bulgaria, Montenegro and Romania).

Note: these are not exactly scientific exercises, so treat them as an indicative analysts, rather than an in-depth and conclusive. However, I did perform some simple statistical robustness checks on these findings and they do not appear to be complete ad hoc.

The two scenarios are co-plotted in the following charts alongside the actual Euro Health Consumer Index scores:

As shown in the last chart above, adopting best practices from the countries with vastly lower incomes (and, thus, lower per capita expenditures on healthcare - controlling for the argument that the issue with Irish system is lack of money) would have resulted in a vastly better performance of the system across the board. That is because with exception of just one sub-discipline (Pharmaceuticals), Ireland’s performance is substantially sub-par when compared to the lower income countries best practice experiences. 

The truth is: the Euro Health Consumer Index suggests that the real problem with Irish health system's abysmal performance is not necessarily solely down to the lack of money (although that too might be the case) but may be significantly down to the lack of will to adapt some of the better practices that are, apparently, available and accessible for lower income economies. Yet, despite this pretty simple to grasp observation, majority of Irish analysts and media continue to insist that improving Irish health system requires only one thing: more cash from the taxpayers. What's the margin of error on this argument, given Macedonia scores better on Health Index than Ireland? I would say it is huge.

28/1/17: Trust in Core Social Institutions Has Collapsed

The latest Edelman Trust Barometer for 2017 shows comprehensive collapse in trust around the world in 4 key institutions of any society: the Government (aka, the State), the NGOs (including international organizations), the Media (predominantly, the so-called mainstream media, or established print, TV and radio networks) and the Businesses (heavily dominated by the multinational and larger private and public corporates).

Here are 8 key slides containing Edelman's own insights and my analysis of these.

Let's start with the trend:

In simple terms, world-wide, both trust in Governments and trust in Media are co-trending and are now below the 50 percent public approval levels. For the media, the wide-spread scepticism over the media institutions capacity to deliver on its core trust-related objectives is now below 50 percent for the second year in a row. even at its peak, media managed to command sub-60 percent trust support from the general public, globally. This coincided with the peak for the Governments' trust ratings back in 2013. Four years in a row now, Governments enjoy trust ratings sub-50 percent and in 2017, mistrust in Governments rose, despite the evidence in favour of the on-going global economic recovery.

In 2017, compared to 2015-2016, Media experienced a wholesale collapse in trust ratings. In only three countries of all surveyed by Edelman did trust in media improve: Sweden, Turkey and the U.S. Ironically, the data covering full 2016, does not yet fully reflect the impact of the U.S. Presidential election, during which trust in media (especially the mainstream media) has suffered a series of heavy blows.

 In 2016, 12 out of 29 countries surveyed had trust in Media at 50 percent or higher. In 2017, the number fell to 5.

Similar dynamics are impacting trust in NGOs:

 Of 29 countries surveyed by Edelman, 21 had trust in NGOs in excess of 50 percent in 2017, down from 23 in 2016. Although overall levels of trust in NGOs remains much higher than that for the Media institutions, the trend is for declining trust in NGOs since 2014 and this trend remans on track in 2017 data.

As per trust in Government, changes in 2017 compared to 2015-2016 show only 7 countries with improving Government ratings our of 29 surveyed. This might sound like an improvement, unless you consider the already low levels of trust in Governments.

In 2017, as in 2016 survey, only 7 countries posted trust in Government in excess of 50 percent. This is the lowest proportion of majority trust in Government for any survey on record.

Based on Edelman analysis, the gap between 'experts' (or informed public) view of institutions and that of the wider population is growing.

 And as the above slide from Edelman presentation shows, the gap between informed and general public is substantively the same in culturally (and institutionally) different countries, e.g. the U.S., UK and France. All three countries lead the sample by the size of the differences between their informed public trust in institutions and the general public trust. All of these countries have well-established, historically stable institutions and robust checks and balances underpinning their democracies. Yet, the elites (including intellectual elites) detachment from general public is not only massive, but growing.

These trends are also present in other countries:

As Edelman researchers conclude: the public in general is now driven to reject the status quo.

All of the above suggests that political opportunism, ideological populism and rising nationalism are neither new phenomena, nor un-reflected in historical data, nor fleeting. Instead, we are witnessing organic decline in trust of the institutions that continue to sustain the status quo.

27/1/17: Eurocoin Signals Accelerating Growth in January

Eurocoin, leading growth indicator for euro area growth published by Banca d'Italia and CEPR has risen to 0.69 in January 2017 from 0.59 in December 2016, signalling stronger growth conditions in the common currency block. This is the strongest reading for the indicator since March 2010 and comes on foot of some firming up in inflation.

Two charts to illustrate the trends:

Eurocoin has been signalling statistically positive growth since March 2015 and has been exhibiting strong upward trend since the start of 2Q 2016. The latest rise in the indicator was down to improved consumer and business confidence, as well as higher inflationary pressures. Although un-mentioned by CEPR, higher stock markets valuations also helped.

27/1/17: Sovereign Debt Junkies Can't Get Negative Enough in 4Q 16

There’s less euphoria in sovereign borrowers camps of recent, but plenty of happiness still.

Per latest data from FitchRatings, “global negative-yielding sovereign debt declined slightly to $9.1 trillion outstanding as of Dec. 29, 2016, from $9.3 trillion as of Nov. 28, 2016… The decline came from the strengthening of the US dollar and little net change in European and Japanese sovereign long-term bond yields.” In other words, currency movements are pinching valuations.

Notably, “there was $5.5 trillion in Japanese government bonds yielding less than 0%, down about $2.4 trillion since the end of June 2016. Slight increases in Japanese yields and a weaker yen contributed to the ongoing decline in the amount of negative-yielding debt outstanding in Japan.” Never mind: world’s third largest economy accounts for 60.5 percent of all negative yielding sovereign debt. That’s just to tell you how swimmingly everything is going in Japan.

27/1/17: U.S. GDP Growth is Down, Not Quite Out...

So President Trump wants U.S. economy growing at 4 percent per annum. And he wants a trade tussle with Mexico and China, and possibly much of the rest of the world, or may be a trade war, not a tussle. And he wants tariffs on imports from Mexico to pay for the Wall. And all of this is as likely to support his 4 percent growth target, as a crutch is to support a two-legged sheep.

Take the latest U.S. GDP figures. The latest preliminary estimates for the 4Q 2016 U.S. GDP growth came out today. It is pretty ugly. The markets expected 4Q GDP print to come in up 2.2 percent, with some forecasters being on a much more optimistic side of this figure. Instead, q/q growth (preliminary estimate) came in at 1.9 percent. This puts full year 2016 growth estimate at 1.6 percent which, if confirmed in subsequent revisions, will be the one of the two lowest rates of growth over 2010-2016 period. In 2015, FY growth was 2.6 percent.

The key reason for the drop in growth that everyone is talking about is net exports. In 4Q 2016, net exports subtracted 1.7 percentage points from the U.S. GDP, which is the largest negative impact for net trade figures since 2Q 2010. This was ugly. But less-talked about was a rather not-pretty 1 percentage point positive contribution to GDP from inventories which was the largest positive contribution since 1Q 2015. And more: inventories overall contribution to 2016 FY growth was higher than in both 2014 and 2015.

Quarterly GDP Growth and Contributions to Growth

Source: ZeroHedge

Good news: business investment rose, adding 0.67 percentage points to overall growth, and private sector equipment purchases rose 3.1 percent. Good-ish news: (after-tax) disposable personal income rose 1.5 percent in real terms on an annualised basis, but this marked the lowest growth rate in income over 3 years. Slower rate of growth in personal income over 4Q 2016 was down to “deceleration in wages and salaries”. Structurally, this suggests we might see some capex growth in 2017, while wages and salaries growth slowdown is likely to give way to more labour costs inflation, consistent with headline unemployment figures. If so, 1.6 percent annual growth can shift to 2-2.2 percent range.

Adding a summary to the above, BEA report notes:  “The increase in real GDP in 2016 reflected positive contributions from PCE [private consumption], residential fixed investment, state and local government spending, exports, and federal government spending that were partly offset by negative contributions from private inventory investment and nonresidential fixed investment. Imports, which are a subtraction in the calculation of GDP, increased.” In other words: borrowed money-based personal spending, plus borrowed money-based government spending, borrowed money-based property ‘investments’ were up. Capacity investments were down.

So, about that 4% target figure, Mr. President... time to hire some Chinese 'state statisticians' to get the figures right?..


In a final caveat: this is the first print of GDP growth and it is subject to future revisions.

27/1/17: Eurogroup has ignored Brexit risks to Ireland

My article for the Sunday Business Post on the latest Eurogroup meeting:  https://www.businesspost.ie/opinion/constantin-gurdgiev-eurogroup-ignored-brexit-risks-irish-economy-376645.

27/1/17: Some News Links

Some recent news links that reference the site or carry my comments:

Global Capital article by Jeremy Weltman looking at key country risks for 2016-2017: http://www.globalcapital.com/article/b1157nr86h8byh/country-risk-review-2016-populism-is-risky.

Il Foglio (Italian) looking at the failures of policymakers around the world to address the issues of demographics, citing one of the analysis pieces published on this blog: http://www.ilfoglio.it/list/2017/01/04/news/cona-cie-demografia-dimenticata-113573/?refresh_ce.

23/1/17: Regulating for Cybersecurity: A Hacking-Based Mechanism

Our second paper on systemic nature (and regulatory response to) cyber security risks is now available in a working paper format here: Corbet, Shaen and Gurdgiev, Constantin, Regulatory Cybercrime: A Hacking-Based Mechanism to Regulate and Supervise Corporate Cyber Governance? (January 23, 2017): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2904749.

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.

20/1/17: Obama Legacy: Debt

Great chart via @Schuldensuehner showing that Trump presidency is off to a cracking start, courtesy of Obama legacy: debt overhang

Now, keep in mind: the entire legislative legacy of Obama's administration (amounting pretty much to Obamacare) can be undone by Congress and the new President. What cannot be undone is the debt mountain accumulated by the U.S. That mountain is here to stay. For generations to come.

Oh, and the above chart does not even begin to describe the mountain of unfunded liabilities that keeps expanding from President to President.

18/1/17: Bitcoin Demand: It's a Chinese Tale

Bitcoin demand by geographic location of trading activity:

H/T for the chart to Dave Lauer @dlauer

It shows exactly what it says: Bitcoin is currently driven by safe haven instrument (and not as a hedge) against capital controls. Which implies massive expected price and volumes volatility in the future, wider cost margins and artificial support for demand in the near term.

17/1/17: Government Debt in the Age of Austerity

The fact that the world is awash with debt is hard to dispute (see data here and here), but it is quite commonly argued that the aggressive re-leveraging happening in the corporate and household sectors runs contrary to the austerity trends in the public debt segment of the total economic debt. The paradox of the austerity arguments is, of course, that whilst debt is rising, public investment is falling and public consumption remains either stagnant of rising slowly. This should see public debt either declining or remaining static. Of course, banks bailouts in a number of advanced economies would have resulted in an uplift in public debt during the early years of the Global Financial Crisis and the Great Recession, but these years behind us, we should have witnessed the austerity translating into moderating debt levels in the global economy when it comes to public debt.

Alas, this is not the case, as illustrated in the chart below:

Here's a tricky bit:

• In the 5 years 2012-2016 (post-onset of the recovery) Government debt around the world rose 11.4% in level terms (USD), and 14.51 percentage points as a share of GDP per capita. During the crisis years of 2007-2011, Government debt rose 72.7% in dollar terms and was down 4.39 percentage points as a share of GDP.
• In the advanced economies, Government debt rose 67.6% in dollar terms in 2007-2011 period, up 4.7 percentage points, before rising 5.44% in dollar terms over subsequent 5 years (up 26.65 percentage points in terms of debt to GDP ratio). 
• In the euro area, Government debt was up 57.4% in dollar terms and up 0.51 percentage points in GDP ratio terms over the period of 2007-2011, before falling 6.9 percent in dollar terms but rising 24.8 percentage points relative to GDP in 2012-2016 period.
• And so on...

As the above chart shows, globally, total volume of Government debt was estimated to be USD63.2 trillion at the end of 2016, up USD6.46 trillion on the end of 2011. That is almost 84.1% of the world GDP today, as opposed to 78% of GDP at the end of 2011. More than half of this increase (USD3.91 trillion) came from the Emerging and Developing Economies, and USD2.3 trillion came from G7 economies. Meanwhile, euro area Government Debt levels declined USD815 billion, all of which was due solely to changes in the exchange rate and the rollover of some debt into multinational organisations' (e.g. ESM) and quasi-governmental (e.g. promissory notes) debt. Worse, over the said period of time, only one euro area country saw reduction in the levels of debt: Greece (down EUR34.46 billion due to restructuring of debt). In fact, in Euro terms, total euro area government debt rose some EUR1.36 trillion over the span of the 2011-2016 period.

All in, global pile of Government debt is now USD27.84 trillion (or 78.7%) up on where it was at the end of 2007 and the start of the Global Financial Crisis.

So may be, just may be, the real economy woe is that most of the new debt accumulated by the Governments in recent years has flown into waste (supporting banks, financial markets valuations, doling out subsidies to politically favoured sectors etc), instead of going to fund productive public investments, including education, skills training, apprenticeships and so on. Who knows?..

17/1/17: Economics of Blockchain

One of the first systemic papers on economic of blockchain, via NBER (http://www.nber.org/papers/w22952) by Christian Catalini and Joshua S. Gans, NBER Working Paper No. 22952 (December 2016).

In basic terms, the authors see blockchain technology and cryptocurrencies influencing the rate and direction of innovation through two channels:

1. Reducing the cost of verification; and 
2. Reducing the cost of networking.

Per authors, for any "exchange to be executed, key attributes of a transaction need to be verified by the parties involved at multiple points in time. Blockchain technology, by allowing market participants to perform costless verification, lowers the costs of auditing transaction information, and allows new marketplaces to emerge. Furthermore, when a distributed ledger is combined with a native cryptographic token (as in Bitcoin), marketplaces can be bootstrapped without the need of
traditional trusted intermediaries, lowering the cost of networking. This challenges existing
revenue models and incumbents's market power, and opens opportunities for novel approaches to
regulation, auctions and the provision of public goods, software, identity and reputation systems."

A bit more granularly, per authors,

• "Because of how it provides incentives for maintaining a ledger in a fully decentralized way, Bitcoin is also the first example of how an open protocol can be used to implement a marketplace without the need of a central actor." In other words, key feature of cryptocurrencies and blockchain is that it removes the need to create a central verification authority / intermediary / regulator or repository of data. The result is more than the cost reduction (focus of the Catalini and Gans paper), but the redistribution of market power away from intermediaries to the agents of supply and demand. In other words, a direct streamlining of the market away from third parties power toward the direct power for economic agents.
• "Furthermore, as the core protocol is extended (e.g. by adding the ability to store documents through a distributed ledger-storage system), as we will see the market enabled by a cryptocurrency becomes a  flexible, permission-less development platform for novel applications." Agin, while one might focus on reductions in the direct costs of innovation in that context, one cannot ignore the simple fact that blockchain is resulting in reduced non-cost barriers to innovation, further reducing monopolistic market power (especially of intermediaries and regulators) and diffusing that power to innovators.

So what are the implications of this view of economics of blockchain? "Whereas the utopian view has argued that blockchain technology will affect every market by reducing the need for intermediation, we argue that it is more likely to change the scope of intermediation both on the intensive margin of transactions (e.g., by reducing costs and possibly influencing market structure) as well as on the extensive one (e.g., by allowing for new types of marketplaces)." So far, reasonable. Intermediation will not disappear as such - there will always be need for some analytics, pricing, management etc of data, contracts and so on, even with blockchain ledgers in place. However, the authors are missing a major point: blockchain ledgers are opening possibility to fully automated direct data analytics and AI deployment on the transactions ledgers. In other words, traditional forms of intermediation (for example in the context of insurance contract transactions, those involving data collection, data preparation, risk underwriting, contract pricing, contract enforcement, contract payments across premia and payouts, etc) all can be automated and supported by live data-based analytics engine(s) operating on blockchain ledgers. If so, the argument that the utopian view won't materialise is questionable.

The paper is worth reading, for it is one of the early attempts to create some theoretical framework around blockchain systems. Alas, my gut feeling is that the authors are failing to fully understand the depth of the blockchain technology. 

17/1/17: Russian Economic Policy Uncertainty 2016

In the previous post (link here), I covered 2016 full year spike in economic policy uncertainty in Europe on foot of amplification of systemic risks. Here is the analysis of Russian index.

As shown in the chart above, 2016 continued the trend for downward correction in Russian economic policy uncertainty that took the index from its all-time high in 2014 (at 180.4) to 160 in 2015 and 142.5 in 2016. All data is rebased to 1994 - the first year for which Russian data is available. However, at 142.5, the index is still well above its historical average of 94.1 and stands at the fifth highest reading in history.

Much of the reduction in economic policy uncertainty over 2016 came over the fist seven months of the year, with index readings rising into the second half of 2016 and peaking at 251.1 in December.

In simple terms, while the peak of 2014 crisis has now passed, questions about economic policies in Russia remain, in line with concerns about the sustainability of the nascent economic recovery. Moderation in economic policy uncertainty over the course of 2016 appears to be closely aligned with:

1. Variations in oil prices outlook; and
2. External geopolitical shocks (including the election of Donald Trump, with raw index data spiking in August and September 2016 and November and December 2016, while falling in October, in line with Mr. Trump's electoral prospect).

In other words, relative moderation in the index appears to reflect mostly exogenous factors, rather than internal structural reforms or policies changes.

15/1/17: 2016 was a year of records-breaking policy uncertainty in Europe

When it comes to economic policy uncertainty, 2016 was a bad year for the Big 4 European states, except for one: Italy.

Consider the above chart showing indices of Economic Policy Uncertainty across Europe's Big Four states, as represented by period averages across four main periods, plus 2016.

German economic policy uncertainty rose from 87.9 average for the period of 2002-2007 to 144.5 for the period of 2008-2011 and 152.1 over 2012-2015. In 2016, the index averaged 230.5. While not in itself indicative of a crisis, the trajectory is consistent with systemic rise in uncertainty, especially since 2016 was not a political outlier year (there were no major elections or external shocks, other than shocks related to German policy itself, such as the refugees crisis). That German index increase took place during one of the strongest years for growth and employment is, in itself, quite revealing.

Like Germany, France also experienced increases in uncertainty index over the recent years, with index rising from 109.7 in 2002-2007 period to 189.2 average over the period of 2008-2011 and to 235.6 over the years 2012-2015. In 2016, the index averaged 309.6. Once again, as in the Germany's case, there were no external or political catalysts to this, other than the dynamics of internal / domestic policies. And, as in the German case, economic cycles cannot explain this rise either. Thus, it is quite reasonable to conclude that systemic uncertainty is rising within the French society at large.

Perhaps surprisingly - given the outrun of the Italian Constitutional Referendum and the dire state of the Italian economy - Italy's Economic Policy Uncertainty Index has managed to eek out a small (statistically insignificant) reduction in 2016, falling to 129.3 in 2016 from 2012-2015 average of 130.9. However, December 2016 referendum is not fully factored in the 2016 average, yet (there are lags in Index adjustments and revisions that are yet to show up in the data), and both 2016 average and 2012-2015 average are well above 2008-2011 average of 113.7 and 2002-2007 average of 94.3.

Perhaps the only European country where index readings in 2016 can be clearly linked to internal structural shocks is the UK, where 2016 average index reading reached 528.8, compared to 2012-2015 average of 228.5. Chart below clearly shows that the increase in uncertainty started around the date of the Brexit referendum.

Overall, taken over longer term horizon, and smoothing out some occasionally impressive volatility, index averages across all four European economies shows structural increases in uncertainty relating to economic policy since the start of the Global Financial Crisis. These structural increases are not abating since the onset of economic recoveries and, as the result, suggest that the improvement in the European economies sustained since 2011 onward is not seen as being well anchored (or structurally sustainable) on the ground and amongst the newsmakers.

14/1/17: Country Risks survey results for 2016

+Euromoney have published their @CountryRisks survey results for 2016: available here quoting, amongst other analysts, myself.

13/1/17: AID:Tech in Global Top 10 at IBM SmartCamp 2016

Another brilliant win for the AID:Tech https://aid.technology/ team placing into Global Top 10 Startups for IBM SmartCamp http://smartcamp2016.com/.

12/1/17: Betrayal Aversion, Populism and Donald Trump Election

In their 2003 paper, Koehler and Gershoff provide a definition of a specific behavioural phenomenon, known as betrayal aversion. Specifically, the authors state that “A form of betrayal occurs when agents of protection cause the very harm that they are entrusted to guard against. Examples include the military leader who commits treason and the exploding automobile air bag.” The duo showed - across five studies - that people respond differently “to criminal betrayals, safety product betrayals, and the risk of future betrayal by safety products” depending on who acts as an agent of betrayal. Specifically, the authors “found that people reacted more strongly (in terms of punishment assigned and negative emotions felt) to acts of betrayal than to identical bad acts that do not violate a duty or promise to protect. We also found that, when faced with a choice among pairs of safety devices (air
bags, smoke alarms, and vaccines), most people preferred inferior options (in terms of risk exposure) to options that included a slim (0.01%) risk of betrayal. However, when the betrayal risk was replaced by an equivalent non-betrayal risk, the choice pattern was reversed. Apparently, people are willing to incur greater risks of the very harm they seek protection from to avoid the mere possibility of betrayal.”

Put into different context, we opt for suboptimal degree of protection against harm in order to avoid being betrayed.

Now, consider the case of political betrayal. Suppose voters vest their trust in a candidate for office on the basis of the candidate’s claims (call these policy platform, for example) to deliver protection of the voters’ interests. One, the relationship between the voters and the candidate is emotionally-framed (this is important). Two, the relationship of trust induces the acute feeling of betrayal if the candidate does not deliver on his/her promises. Three, past experience of betrayal, quite rationally, induces betrayal aversion: in the next round of voting, voters will prefer a candidate who offers less in terms of his/her platform feasibility (aka: the candidate less equipped or qualified to run the office).

In other words, betrayal aversion will drive voters to prefer a poorer quality candidate.

Sounds plausible? Ok. Sounds like something we’ve seen recently? You bet. Let’s go over the above steps in the context of the recent U.S. presidential contest.

One: emotional basis for selection (vesting trust). The U.S. voters had eight years of ‘hope’ from President Obama. Hope based on emotional context of his campaigns, not on hard delivery of his policies. In fact, the entire U.S. electoral space has become nothing more than a battlefield of carefully orchestrated emotional contests.

Two: an acute feeling of betrayal is clearly afoot in the case of the U.S. electorate. Whether or not the voters today blame Mr. Obama for their feeling of betrayal, or they blame the proverbial Washington ’swamp’ that includes the entire lot of elected politicians (including Mrs. Clinton and others) is immaterial. What is material is that many voters do feel betrayed by the elites (both the Burn effect and the Trump campaign were based on capturing this sentiment).

Three: of the two candidates that did capture the minds of swing voters and marginalised voters (the types of voters who matter in election outrun in the end) were both campaigning on razor-thin policies proposals and more on general sentiment basis. Whether you consider these platforms feasible or not, they were not articulated with the same degree of precision and competency as, say, Mrs Clinton’s highly elaborate platform.

Which means the election of Mr Trump fits (from pre-conditions through to outcome) the pattern of betrayal aversion phenomena: fleeing the chance of being betrayed by the agent they trust, American voters opted for a populist, less competent (in traditional Washington’s sense) choice.

Now, enter two brainiacs from Harvard. Rafael Di Tella and Julio Rotemberg were quick on their feet recognising the above emergence of betrayal avoidance or aversion in voting decisions. In their December 2016 NBER paper, linked below, the authors argue that voters preference for populism is the form of “rejection of “disloyal” leaders.” To do this, the authors add an “assumption that people are worse off when they experience low income as a result of leader betrayal”, than when such a loss of income “is the result of bad luck”. In other words, they explicitly assume betrayal aversion in their model of a simple voter choice. The end result is that their model “yields a [voter] preference for incompetent leaders. These deliver worse material outcomes in general, but they reduce the feelings of betrayal during bad times.”

More to the point, just as I narrated the logical empirical hypothesis (steps one through three) above, Di Tella and Rotemberg “find some evidence consistent with our model in a survey carried out on the eve of the recent U.S. presidential election. Priming survey participants with questions about the importance of competence in policymaking usually reduced their support for the candidate who was perceived as less competent; this effect was reversed for rural, and less educated white, survey participants.”

Here you have it: classical behavioural bias of betrayal aversion explains why Mrs Clinton simply could not connect with the swing or marginalised voters. It wasn’t hope that they sought, but avoidance of putting hope/trust in someone like her. Done. Not ‘deplorables’ but those betrayed in the past have swung the vote in favour of a populist, not because he emotionally won their trust, but because he was the less competent of the two standing candidates.



Jonathan J. Koehler, and Andrew D. Gershof, “Betrayal aversion: When agents of protection become agents of harm”, Organizational Behavior and Human Decision Processes 90 (2003) 244–261: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.11.1841&rep=rep1&type=pdf

Di Tella, Rafael and Rotemberg, Julio J., Populism and the Return of the 'Paranoid Style': Some Evidence and a Simple Model of Demand for Incompetence as Insurance Against Elite Betrayal (December 2016). NBER Working Paper No. w22975: https://ssrn.com/abstract=2890079

12/1/17: Breaking EU Rules? Often and Freely

EU's Fiscal Discipline in one table: here is a summary of the EU member states' performance when it comes to 3% deficit ceiling set out as a core fiscal criteria:

Yes, even after a large scale fiscal 'retrenching' of 2016, on average, EU member states have been outside satisfying fiscal deficit ceiling criteria 41 percent of the time, with EA12 average being worse - at 43 percent.

Six EU states are more than just serial violators of the rule, with their respective frequencies of falling outside the rule constraints being in excess of 2/3rds. It is worth noting that in this group, all states are violating rules predominantly during the years of economic expansion.

Another 11 states are frequent violators, breaking the rule more than 1/3rd of the time but less than 2/3rds. Here too, with exception of Cyprus and Slovenia, more violations took place during the times of expanding economies than during the periods of recessions. All in, 17 states of the EU are breaking the EU fiscal rule on deficit ceilings more than 1/3rd of the time. Only 7 states break the rule less than 25 percent of the time and only 5 break the rule less than 10 percent of the time.

Surely, nothing to worry about.

12/1/17: NIRP: Central Banks Monetary Easing Fireworks

Major central banks of the advanced economies have ended 2016 on another bang of fireworks of NIRP (Negative Interest Rates Policies).

Across the six major advanced economies (G6), namely the U.S., the UK, Euro area, Japan, Canada and Australia, average policy rates ended 2016 at 0.46 percent, just 0.04 percentage points up on November 2016 and 0.13 basis points down on December 2015. For G3 economies (U.S., Euro area and Japan, December 2016 average policy rate was at 0.18 percent, identical to 0.18 percent reading for December 2015.

For ECB, current rates environment is historically unprecedented. Based on the data from January 1999, current episode of low interest rates is now into 100th month in duration (measured as the number of months the rates have deviated from their historical mean) and the scale of downward deviation from the historical ‘norms’ is now at 4.29 percentage points, up on 4.24 percentage points in December 2015.

Since January 2016, the euribor rate for 12 month lending contracts in the euro interbank markets has been running below the ECB rate, the longest period of negative spread between interbank rates and policy rates on record.

Currently, mean-reversion (to pre-2008 crisis mean rates) for the euro area implies an uplift in policy rates of some 3.1 percentage points, implying a euribor rate at around 3.6-3.7 percent. Which would imply euro area average corporate borrowing rates at around 4.8-5.1 percent compared to current average rates of around 1.4 percent.

11/1/17: Mr. Trump's Plan for Addressing Conflicts of Interest is a Fig Leaf of Corporate Governance

Why PEOTUS Donal Trump’s plan to donate hotels profits earned from foreign government payments to the U.S. Treasury is a fig leaf of corporate governance measures?

Photo credit: GettyImages

There are several reasons why a commitment to donate profits arising from foreign governments' payments to his hotels will not reduce, nor even alleviate, business incentives for potential conflict of interest that may arise in the future.

Firstly, donating profits from such activities requires that profits are declared on these activities in the first place. Since profits are declared across the entire business, not on the basis of individual transactions, Mr. Trump can use full extent of tax laws and accounting procedures, including cumulated losses deductions and tax shields on investment, to effectively reduce such denotable profits to nil over the next 4-8 years. 

Secondly, profits are not the most important financial line on which Mr. Trump operates. Mr. Trump operates on the basis of business (net) worth (value of his business) which reflects not so much the declared profits, but rather the earnings generated by his businesses (cash flow basis, e.g. EBITDA) and also reflects earnings over the longer term time horizon (timing factor). 

Now, consider the following hypothetical scenario: suppose Mr. Trump’s hotels receive USD1 million in foreign government’s bookings in 2017. Suppose he earns 10 percent profit margin on these earnings (so we neglect the issue raised in the first argument above). The profit is declared and Mr. Trump donates USD100K to the U.S. Treasury in 2017. The problem is that the 10% profit margin is across the entire group of hotels, not across the individual rooms and services supplied in exchange for the USD1 million foreign Governments' payments. As the result, 10% margin reflects costs and investments undertaken by the whole group. Foreign earnings, therefore, can be used to fund internal investment activities, ammortization and capital replacement costs, hiring costs, new services deployments etc. All of which will increase the value of Mr. Trump's hotels, including hotels that did not collect foreign payments.

In the mean time, Mr. Trump's business earnings did increase in 2017 by USD1 million as the result of the assumed foreign governments' payments. If this increase is viewed as organic or permanent, rather than a one-off windfall, his business value will increase as the result of these 2017 earnings even independent of the aforementioned investment. Why? Because companies are valued on the basis of their cash flow. Not on the basis of declared profits.

Furthermore, foreign governments' paid earnings will increase Mr. Triump's businesses capacity to borrow and raise equity. These increased borrowings and equity raises can further be used to invest in new business capital. This too will enhance business valuations for Mr. Trump.

In simple terms, even after donating his profits, Mr. Trump will be able to still gain substantially from increased revenues paid for by foreign governments. 

Thirdly, there is a host of other implications relating to Mr. Trump’s plan. 

1. It will be hard to account for all payments by ‘foreign governments’ because many such payments can come via private foreign and even domestic companies, foreign organisations and foreign individuals, or for that matter, via domestic agents and agencies acting on behalf of these foreign governments. 
2. How will the donations to Treasury be treated under the U.S. tax laws is material as well. If these are treated as charitable donations, they can be tax deductible, creating a tax shield for Mr. Trump. This tax shield can be extremely valuable, especially if his businesses use foreign-funded earnings to borrow for investment (effectively transferring these payments into future interest-related tax benefits). 
3. Mr. Trump announced today that his companies will not be permitted to make any new foreign deals during his presidency tenure. However, domestic deals will be allowed. The problem is that this does not preclude use of foreign governments’ payments/earnings for the purpose of reinvestment in the U.S. Which cycles us back to the argument that these payments can still be used to enhance Mr. Trump’s business valuations.

In simple terms, Mr. Trump’s plan to prevent conflicts of interest arising does not add up to reducing incentives for conflict of interest. It is a fig leaf of corporate governance.

10/1/17: For Love or Money: Gender Gap in Online Labor Markets

The issue of a gender gap in the workplace, relating to gender differences in terms of occupations, is a highly contentious, politically charged and, despite a wealth of research on the subject, not fully explained to-date. One thing that economists generally agree on is that it is not one caused by a single factor or even a confluence of factors stemming from a single origin (e.g. access to education, time taken for maternity leave or concerted discrimination against women in the workplace, or any other set of closely linked factors). Instead, a range of exogenous, endogenous, personal, institutional, social etc factors determine the size of the gap, its existence and its evolution over time.

Hence, any new research identifying new factors is both - confusing (especially to those of us, who would stress the social equality dimension of the labour market outcomes) and important (especially to those of us, who prefer evidence-based policy and institutional responses to the issue). Note: the two sets of ‘us’ identified above are not mutually exclusive. In fact, I would suggest that majority of us - researchers, policymakers, analysts, and generally-speaking people, belong to both groupings, being concerned simultaneously with the social justice dimension of the labor market gender gaps and the need for well-designed policy responses to the problem.

With this preamble, here is a new piece of research on the subject. In their paper, titled “For Love or Money? Gender Differences in How One Approaches Getting a Job”, UC Berkeley researchers, Ng, Weiyi and Leung, Ming D (March 22, 2015: https://ssrn.com/abstract=2583592)note that current theories of the labor markets “conclude that women and men apply to different jobs”. However, these theories fail “to explain differences in how [men and women] may behave when applying to the same job.”

The authors “correct this discrepancy by considering gendered approaches to the hiring process. We propose that applicants can emphasize either the relational or the transactional aspects of the job and that this affects getting hired.”

What do these two approaches mean?

• “Relational job seekers focus on developing a social connection with their employer.”
• “Transactional job seekers focus on quantitative and pecuniary aspects of the job.”

The authors “hypothesize that the approach women take in applying for a job will differ from men. In particular, we believe that women, enacting their gender will focus on the relational aspects of the exchange: they emphasize the social, emotional aspects of the employment relationship and focus on mutually beneficial interests. On the other hand, men will be more transactional in nature: they focus more on the task at hand, their own qualifications and achievements, and highlight the quantifiable, observable and tangible aspects of the job.”

The evidence in support of these hypotheses is presented in the paper (for example, see Chart below).

Crucially, the authors note that “while both these approaches have their merits, this difference should result in variation in a person’s likelihood of being hired.”

The study then applies this theoretical hypothesis to see if it can account for “the hiring gap
between male and female job applicants we observe [in the actual data], net of controls for underlying ability, in an online market for contract labor, Elance.com.”

The reason the authors chose the online labor market data is that

1. “The online setting provides a richness and granularity of data which allows us to further unpack the nuances in the strategies employed by job seekers. The transparency of the setting provides a glimpse into the black box of the hiring process. For example, the data provides insight and access to the details of every job posting, the applicant pool, background work histories of each applicant, their photographs, how much they were willing to work for, the text of their job proposal, and the eventual winner of the job.”
2. Secondly, there is an “increasing trend towards self-employment whereby labor market participants eschew the long-term role as a corporate employee and instead participate on a contract basis, moving from job to job and working for different employers” which further validates the use of online labor market data. 

Based on the data and a barrage of econometric tests, the authors concluded that “women are more likely to be hired than men by about 5.2% [in the Elance.com type of the labor market]. Quantitative linguistic analysis on the unstructured text of job proposals reveals that women (men) adopt more relational (transactional) language in their applications. These different approaches affect a job seeker’s likelihood of being hired and attenuate the gender gap we identified.”

Besides own interesting insights and conclusions, the paper is well-worth reading for the quality of discussion it presents relating to existent social and economic literature on the subject of gender gaps. If anything, this discussion itself is worth paying close attention to, for it highlights the wealth of our knowledge on the subject as well as posits some serious questions about the future of gender gap research.