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. 

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...

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:

23/8/17: Ireland: A Haven for SPVs?

Ireland scored another ‘first’ in the league tables relating to tax optimisation and avoidance, staying at the top of the Euro area rankings as a Special Purpose Vehicles (SPVs) destination: http://uk.reuters.com/article/uk-ireland-funds-idUKKCN1AY1AK (featuring my comment, amongst others).

As my comment in the article linked above alludes, there is a combination of factors that is driving Ireland’s ‘competitiveness’ in this area. Some are positive for the economy and non-zero-game in relation to our trading partners, e.g. 

- Ireland providing a functional access to the European markets via regulatory and markets infrastructure arrangements that facilitate trading from Dublin into the rest of the EEC;

- Ireland offering a strong platform for on-shoring human capital, a much more functional platform than any other EU nation, due to greater openness to skills-based migration, English language, common law and open culture;

- Ireland serves as a clustering centre for a range of financial services functions, making it more attractive than traditional tax havens for conducting real business.

Over the recent decades, Irish Governments and business organisations have been aggressive (or better said - active) in positioning the country as a platform for inward investment. The first waves of this strategy involved emphasis on pure tax optimisation (e.g. during the 1990s), with subsequent efforts (often less successful and slower to develop) involving building specialist niches of financial services activities in Ireland (e.g. funds management in the 2000s and focus on specialist listings, such as debt and SPVs, in the 2000s-2010s).

On the other hand, aggressive positioning achieved by Ireland in tax optimisation-driven FDI and tax-focused corporate inversions has become a significant drag on the country’s reputation as a functional (as opposed to post-box) business centre. In addition, the Financial Crisis has introduced new dimensions to this reputational erosion: in addition to the G20-initiated push for greater tax transparency and harmonisation, Ireland also - mistakenly - pursued tax-based incentives for vulture funds acquiring distressed Irish properties from the likes of Nama and IBRC. A combination of growing tax inversions, BEPS reviews and reforms, vulture funds aggressive use of the tax structures has resulted in a more recent tightening of the SPVs regulations and oversight. 

Striking a balance between real economic incentives and egregious tax optimisation is a hard target to hit for a small open economy that, like Ireland, faces very tangible and aggressive international competition. The bad news is that we are yet to find a ‘golden ratio’ for proper regulation and supervision regimes that can allow us to retain a competitive edge, while rebuilding positive reputation with our trading partners and investors as a place for doing functional/tangible business. The good news is that we are becoming more aware of the need to strike such a balance.

22/8/17: Focus Economics on Refugees Integration Challenge

Focus Economics posted a neat and timely blog post on the topic of potential economic impacts of mass forced migration that has been sweeping across Europe in recent years, driven by the civil war in Syria and botched 'democratization' efforts in Iraq and Afghanistan, as well as the less-discussed dismantling of Libya.

The link to the post is here: http://www.focus-economics.com/blog/impact-of-refugees-on-european-economies.

In my opinion, the key here is the following issues:

"In the longer term, the picture becomes far murkier. This isn’t just because little is known about the current cohort of refugees, such as their average level of education or how long they will remain in their host countries. It is also because the long-term economic impact of refugees rests largely on how successful countries are at weaving them into the economic fabric of their societies."

Yes, long term viability of all positive assessments of the current migration crisis is questionable. And the problem rests on both sides, the migrants' quality of human capital, and the host countries quality of labor markets.

End result, so far, is that history offers only ominous assessments of the success rates that can be achieved in integrating refugees into active members in the host societies. "If past experience is anything to go by, the full economic integration of refugees will prove an arduous task. Studies from many developed countries have repeatedly shown that refugees tend to earn less, have worse employment prospects and hold lower occupational status than native workers or economic migrants. Even in Sweden, a country with a relatively strong track record of integrating refugees, a study of those arriving between 1997 and 2010 found that fewer than 20% had found employment after one year. Ten years down the line, only between 50% and 60% were working, significantly below the corresponding figure for Swedish natives."

This is not to say that attempts to integrate refugees are a waste of scarce resources. Quite to the contrary, both humanitarian and socio-economic dimensions of the current crisis suggest that we should be doing more (and doing it better) to develop policies and institutions to provide refugees with more open and more efficient access to work-related training, language skills acquisition and general education, including avenues to complete unfinished degrees and pursue higher degrees. As the  Focus Economics post stresses, positive incentives and pro-active systems for engagement should be put forward. One question, however, remains unasked and unanswered, as is common with this analysis: what should be done to identify early and correct any negative choices that some of the refugees might make following their arrival in the host societies. While we have an idea as to how we can help those who want to integrate (note: having an idea is yet to translate into deploying actual policies), we don't really have a good understanding as to how we can prevent adverse choices.

16/8/17: Year Eight of the Great American Recovery: Household Debt

U.S. data for household debt for 2Q 2017 is out at last, and the likes of Reuters and there best of the official business media are shouting over each other about the ‘record debt levels’ warnings. As if the ‘record debt levels’ is something so refreshingly new, that no one noticed them in 1Q 2017.

So with that much hoopla in your favourite media pages, what’s the data really telling us?

Quite a bit, folks. Quite a bit.

Let’s start from the top:

Debt levels are up. Almost +4.5% y/y. All debt categories are up, save for HE Revolving debt (down 5.44% y/y). Increases are led by Auto Loans (+7.89% y/y) and Credit Cards (+7.54%). High growth is also in Student Loans (+6.75%). Mortgages debt is rising much slower, as consistent with lack of purchasing power amongst the younger generation of buyers.

As you know, I look at this debt from another perspective, slightly different from the rest of the media pack. That is, I am interested in what is happening with assets-backed debt and asset-free debt. So here it is:

Yes, debt is up again. Mortgages debt share of total household debt has shrunk (it is now at 67.7%) and unsecured debt share is up (32.3%). Unsecured debt was $3.925 trillion in 2016 Q2 and it is now $4.148 trillion. Why this matters? Because although cars can be repossessed and student loans are non-defaultable even in bankruptcy, in reality, good luck collecting many quarters on that debt. Housing debt is different, because with recent lending being a little less mad than in 2004-2007, there is more equity in the system so repossessions can at least recover meaningful amounts of loans. So here’s the thing: low recovery debt is booming. While mortgages debt is still some $600 billion odd below the pre-crisis peak levels.

On the surface, mortgages originations are improving in terms of credit scores. In practice, of course, credit scores are superficially being inflated by all the debt being taken out. Yes, that’s the perverse nature of the American credit ratings system: if you have zero debt, your credit rating is shit, if you are drowning in debt, you are rocking…

Still, here is the kicker: mortgages credit ratings at origination are getting slightly stronger. Total debt written to those with a credit score <660 2016.="" 2016="" 2017="" 2q.="" 2q="" also="" auto="" billion="" buyers="" class="Apple-converted-space" credit="" down="" fell="" from="" good="" improving:="" in="" is="" issuance="" loans="" news.="" origination="" quality="" score="" span="" sub-660="" to="" which=""> 

Bad news:

Severely Derogatory and 120+ delinquent loans are still accounting for 3% of total loans, same as in 2Q 2016 and well above the pre-crisis average of 2.1%. Total share of delinquent loans is at 4.77%, slightly below 1Q 2017 (4.83%) and on par with 4.79% a year ago. So little change in delinquencies as a result of improving credit standards at origination, thus. Which suggests that improving standards are at least in part… err… superficial.

And things are not getting better across majority of categories of delinquent loans:

As the above clearly shows, transition from lesser delinquency to serious delinquency is up for Credit Cards, Student Loans and Auto Loans. And confirming that the problem of reading Credit Scores as improvement in quality of borrowers are the figures for foreclosures and bankruptcies. These stood at 308,840 households in 2Q 2017, up on 294,100 in 1Q 2017 and on 307,260 in 2Q 2016. Now, give it a thought: over the crisis period, many new mortgages issued went to households with better credit ratings, against properties with lower prices that appreciated since issuance, and under the covenants involving lower LTVs. In other words, we should not be seeing rising foreclosures, because voluntary sales should have been more sufficient to cover the outstanding amounts on loans. And that would be especially true, were credit quality of borrowing households improving. In other words, how does one get better credit scores of the borrowers, rising property prices, stricter lending controls AND simultaneously rising foreclosures?

Reinforcing this is the data on third party debt collections: in 2Q 2017, 12.5% of all consumers had outstanding debt collection action against them, virtually flat on 2Q 2016 figure of 12.6%. 

In simple terms, in this Great Recovery Year Eight, one in eight Americans are so far into debt, they are getting debt collectors visits and phone calls. And as a proportion of consumers facing debt collection action stagnates, their cumulative debts subject to collection are rising. 

Things are really going MAGA all around American households, just in time for the Fed to hike cost of credit (and thus tank credit affordability) some more. 

15/8/17: A Great Recovery or a Great Stagnation?

Value-added is one measure of economic activity that links the production side to consumption/ demand side (using inputs of say $X value to produce a good that sells for $Y generates $Y-$X in Gross Value Added). Adjusted for inflation, this returns Real Gross Value Added (RGVA) in the economy. Taken across two key sectors that comprise the private sector economy: households & institutions serving the households, and private businesses (including or excluding farming sector), these provide a measure of the economic activity in the private economy (i.e. excluding Government).

Since the end of WW2, negative q/q growth rates in the private sectors RGVA have pretty accurately tracked evolution of economic growth (as measured, usually, by growth rates in GDP). Only in the mid-1950s did the private sector RGVA growth turn negative without triggering associated official recession on two occasions, and even then the negative growth rates signalled upcoming late-1950s recession.

Which brings us to the current period of Great Recovery.

Consider the chart below, computed based on the data from the Fred database:

The first thing that jumps out in the above data is that since the end of the Great Recession, the period of the Great Recovery has been associated with two episodes of sub-zero growth in the private sector RGVA. This is unprecedented for any period of recovery post-recession, except for the period between two closely-spaced 1950s recessions: July 1953-April 1954 and August 1957-March 1958.

The second thing that stands out in the data is the average growth rate in RGVA during the current recovery. At 0.579% q/q, this rate is the lowest on the record for any recovery period since the end of WW2. Worse, it is not statistically within 95% confidence interval bands for average growth rate in post-recovery periods for the entire history of the U.S. economy between January 1948 and October 2007. In other words, the Great Recovery is, statistically, not a recovery at all.

The third matter worth noting is that current non-recovery Great Recovery period is the third consecutive period of post-recession growth with declining average growth rates.

The fourth point that becomes apparent when looking at the data is that the current Great Recovery produced only two quarters with RGVA growth statistically above the average rate of growth for a 'normal' or average recovery. This is another historical record low (on per-annum-of-recovery basis) when compared across all other periods of economic recoveries.

All of the above observations combine to define one really dire aftermath of the Great Recession: despite all the talk about the Great Recovery sloshing around, the U.S. economy has never recovered from the crisis of 2007-2009. Omitting the years of the official recession from the data, the chart below shows two trends in the RGVA for the private sector economy in the U.S.

Based on quadratic trends for January 1948-June 2007 (pre-crisis trend) and for July 2009 - present (post-crisis trend), current recovery period growth is not sufficient to return the U.S. to its pre-crisis long term trend path. This is yet another historical first produced by the data. And worse, looking at the slopes of the two trend lines, the current recovery is failing to catch up with pre-crisis trend not because of the sharp decline in real economic activity during the peak recession years, but because the rate of growth post-Great Recession has been so anaemic. In other words, the current trend is drawing real value added in the U.S. economy further away from the pre-crisis trend.

The Great Recovery, folks, is really a Great (near) Stagnation.

12/8/17: Some growth optimism from the Russian regional data

An interesting note on the latest data updates for the Russian economy via Bofit.

Per Bofit: "Industrial output in Russian regions rises, while consumption gradually recovers." This is important, because regional recovery has been quite spotty and overall economic recovery has been dominated by a handful of regions and bigger urban centres.

"Industrial output growth continued in the first half of this year in all of Russia’s eight federal districts," with production up 1.5–2% y/y in the Northwest, Central and Volga Federal Districts, as well as in the Moscow city and region. St. Petersburg regional output rose 3-4% y/y.

An interesting observation is that during the recent recession, there has been no contraction in manufacturing and industrial output. Per Bofit: "Over the past couple of years, neither industrial output overall nor manufacturing overall has not contracted in any of Russia’s federal districts. Industrial output has even increased briskly in 2015–16 and this year in the Southern Federal
District due to high growth in manufacturing and in the Far East Federal District driven by growth in the mineral extraction industries."

This is striking, until you consider the nature of the 2014-2016 crisis: a negative shock of collapsing oil and raw materials prices was mitigated by rapid devaluation of the ruble. This cushioned domestic production costs and shifted more demand into imports substitutes. While investment drop off was sharp and negative on demand side for industrial equipment and machinery, it was offset by cost mitigation and improved price competitiveness in the domestic and exports markets.

Another aspect of this week's report is that Russian retail sales continue to slowly inch upward. Retail sales have been lagging industrial production during the first 12 months of the recovery. This is a latent factor that still offers significant upside to future growth in the later stages of the recovery, with investment lagging behind consumer demand.

Now, "retail sales have turned to growth, albeit slowly, in six [out of eight] federal districts."

Here is why these news matter. As I noted above, the recovery in Russian economy has three phases (coincident with three key areas of potential economic activity): industrial production, consumption and investment. The first stage - the industrial production growth stage - is on-going at a moderate pace. The 0.4-0.6 percent annual growth rate contribution to GDP from industrial production and manufacturing can be sustained without a major boom in investment. The second stage - delayed due to ruble devaluation taking a bite from the household real incomes - is just starting. This can add 0.5-1 percent in annual growth, implying that second stage of recovery can see growth of around 2 percent per annum. The next stage of recovery will involve investment re-start (and this requires first and foremost Central Bank support). Investment re-start can add another 0.2-0.3 percentage points to industrial production and a whole 1 percent or so to GDP growth on its own. Which means that with a shift toward monetary accommodation and some moderate reforms and incentives, Russian economy's growth potential should be closer to 3.3 percent per annum once the third stage of recovery kicks in and assuming the other two stages continue running at sustainable capacity levels.

However, until that happens, the economy will be stuck at around the rates of growth below 2 percent.