Thursday, September 21, 2017

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


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



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

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

Tuesday, September 12, 2017

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


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

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

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


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

Learning, anyone?

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

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


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

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


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

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

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

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

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

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

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

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

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


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

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

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

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

Friday, September 8, 2017

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


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


Thursday, September 7, 2017

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


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

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

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

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


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

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

Abstract:

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



7/9/17: Long-Term Stock Market Volatility & the Influence of Terrorist Attacks


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

The first paper is "Long-Term Stock Market Volatility and the Influence of Terrorist Attacks in Europe", available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3033951

Abstract:

This paper examines the influence of domestic and international terrorist attacks on the volatility of domestic European stock markets. In the past decade, terrorism fears remained relatively subdued as groups such as Euskadi Ta Askatasuna (ETA) and the Irish Republican Army (IRA) relinquished their arms. However, Europe now faces renewed fear and elevated threats in the form of Middle Eastern and religious extremism sourced in the growth of the Islamic State of Iraq and Levant (ISIL), who remain firmly focused on maximising casualty and collateral damage utilising minimal resources. Our results indicate that acts of domestic terrorism significantly increase domestic stock market volatility, however international acts of terrorism within Europe does not present significant stock market volatility in Ireland and Spain. Secondly, bombings and explosions within Europe present evidence of stock market volatility across all exchanges, whereas infrastructure attacks, hijackings and hostage events do not generate widespread volatility effects. Finally, the growth of ISIL-inspired terror since 2011 is found to be directly influencing stock market volatility in France, Germany, Greece, Italy and the UK.



7/9/17: Deutsche Mark Euro?.. ECB, Taylor rule and monetary policy


In our Economics course @MIIS, we are covering the technological innovation contribution to the break down in the wage inflation, unemployment, and general inflation (Lecture 2). Here is fresh from the press data showing the divergence between actual monetary policy and the Taylor rule in Germany: