Panic-driven austerity in the Eurozone and its implications

By Don Alexander, MBA
Associate, RSD Solutions Inc.
Mr. Alexander also lectures at NYU and SunySB

Eurozone policy seems driven by market sentiment. This Paul De Grauwe and Yuemei Ji argue, in a recent VOXEU communique (Feb. 21^st), that fear and panic led to excessive, and possibly self-defeating, austerity in the south while failing to induce offsetting stimulus in the north. The resulting deflation bias produced the double-dip recession and perhaps more dire consequences. As it becomes obvious that austerity produces unnecessary suffering, millions may seek liberation from ‘euro shackles’.

There is a strong perception that countries that introduced austerity programs in the Eurozone were somehow forced to do so by the financial markets. Financial markets exerted different degrees of pressure on countries. By raising the spreads they forced some countries to engage in severe austerity programs. Other countries did not experience increases in spreads and as a result did not feel much urge to apply the austerity medicine.

The next question that arises is whether the judgment of the market (measured by the spreads) about how much austerity each country should apply was the correct one. There are essentially two theories that can be invoked to answer this question. According to the first theory, the surging spreads observed from 2010 to the middle of 2012 were the result of deteriorating fundamentals.

Another theory, while accepting that fundamentals matter, recognizes that collective movements of fear and panic can have dramatic effects on spreads. These movements can drive the spreads away from underlying fundamentals, very much like in the stock markets prices can be gripped by a bubble pushing them far away from underlying fundamentals.

The decision by the ECB in 2012 to commit itself to unlimited support of the government bond markets was a game changer in the Eurozone. It had dramatic effects. By taking away the intense existential fears that the collapse of the Eurozone was imminent the ECB’s lender of last resort commitment pacified government bond markets and led to a strong decline in the spreads of the Eurozone countries.

This decision of the ECB provides us with an interesting experiment to test these two theories about how spreads are formed.   Thus it appears that the only variable that matters to explain the size of the decline in the spreads since the ECB announced its determination to be the lender of last resort is the initial level of the spread. Countries whose spread had climbed the most prior to the ECB announcement experienced the strongest decline in their spreads – a remarkable feature. 

A large component of the movements of the spreads since 2010 was driven by market sentiments. These market sentiments of fear and panic first drove the spreads away from their fundamentals. Later as the market sentiments improved thanks to the ECB, these spreads declined.

Three conclusions can be drawn:  the debt crisis financial markets have provided wrong signals; led by fear and panic, they pushing spreads artificially high and forced cash-strapped nations into intense austerity; Panic and fear are not good guides for economic policies as the quick and intense austerity  led to deep recessions, but did not help to restore sustainability of public finances; and financial markets did not signal northern countries to stimulate their economies, thus introducing a deflationary bias that lead to the double-dip recession.

The intense austerity programs that have been dictated by financial markets create new risks for the Eurozone. While the ECB 2012 decision to be a lender of last resort in the government bond markets eliminated the existential fears about the future of the Eurozone, the new risks for the future of the Eurozone now have shifted into the social and political sphere. As it becomes obvious that the austerity programs produce unnecessary sufferings especially for the people who have been thrown into unemployment and poverty, resistance against these programs associated with the euro is likely to increase.

www.voxeu.org/article/panic-driven-austerity-eurozone

Sports and Risk Management

by Rick Nason, PhD, CFA
Partner, RSD Solutions Inc.

It seems as if there is no end of sports talk shows.  There are many reasons for this – in part because sports fans like to talk about, and hear about, and discuss their favorite teams.  Another reason is that there is no end of sports experts / pundits.  A third reason is the sheer quantity of data to analyze and discuss.  Particularly for the major team sports like baseball, football and basketball, it seems like there is an endless stream of statistics that allow one to analyze every angle of the game.  With all of this analysis, and all of these experts, you would think that the outcome of virtually every game ought to be completely predictable.  However, we still tune in to watch the "big game".

Sports are complex, and thus despite all of the analysis, there is great variability in the outcome.  This is despite the volume of data and analysis that is available to coaches.  (Has anyone read Moneyball by Michael Lewis?)  Players perform in unpredictable ways to pressure referees make unexpected calls, the ball bounces in strange ways, the wind blows etc. etc. (the Bud Light Fans do not align their bottles correctly http://adsoftheworld.com/media/tv/bud_light_very_superstitious ….)

Risk management is also complex.  Despite all of the analysis, we still have to watch the game unfold, and just as a coach is limited in what they can do to affect the results of a game, as risk managers we are also limited in how we can affect outcomes.  Data, analysis, talk, debating, etc. etc. all help, but they do not make outcomes predictable.  Gotta go – game is starting.

Overfitting

By Rick Nason, PhD, CFA
Partner, RSD Solutions Inc.

In academic finance we tend to research questions where there is data, rather than where there are important questions that need some answers.  One of the problems this raises (there are many) is that of the problem of “overfitting”.  In other words, with enough data you can make almost any hypothesis have statistical significance.  In turn we tend to think of statistical significance (and correlation) as the same as causation.  Overfitting means that you can explain almost anything with enough data.  It is not knowledge.  Important difference.

Culture

By Rick Nason, PhD, CFA
Partner, RSD Solutions Inc.

In biology class you may have grown a culture of some organism in a petri dish.  With the right ingredients and conditions, the culture could be reliably formed.  There is a “recipe” if you will, of growing a bacterial culture in a biology lab.

In risk management we also talk about culture, and the need to form a specific risk culture in order to achieve the risk management objectives of the organization.  Growing a risk culture is not the same as growing a bacterial culture.  There is not a “recipe” for growing a risk culture.  There are not a set of conditions or nutrients that will guarantee success.  Stop thinking that there is.

John Karlin

By Rick Nason, PhD, CFA
Partner, RSD Solutions Inc.

Unless you read the business obituaries lately it is quite likely that you have never heard of John Karlin.  I have to admit that I had never heard of him.  However you see his work virtually every day – and many many times a day if you are like most people.  You see John Karlin was the “father of human factors engineering”.  (I am sure that statement makes it all very clear for now – right?!)

John Karlin worked at Bell Labs as an industrial psychologist.  Basically he designed products for how they would be most effectively used by humans.  That is the essence of what we mean by human factors engineering.  It is a field that is often woefully lacking in Enterprise Risk Management, and as I often argue, a reason that so much risk management in corporations is so ineffective.  If systems (protocols, tools, etc.) are not designed in a way that is easy and intuitive for employees to effectively use, then those same systems (protocols, tools, etc.) will not be used, or if used will only be used grudgingly, or ineffectively.

A very readable book on human factor engineering is called “The Human Factor: Revolutionizing the Way We Live with Technology”, by Kim Vicente www.amazon.com/The-Human-Factor-Revolutionizing-Technology/dp/0415978912/ref=sr_1_5?ie=UTF8&qid=1360433770&sr=8-5&keywords=the+human+factor

I believe that if human factor engineering (and social factor engineering) was a part of risk management design and implementation, then ERM would be much more effective than it currently is.

By the way, John Karlin determined that the layout of phone numbers, with square numbers laid out as 123 on the first row, was the most efficient and effective way to go from rotary dial phones to push button phones.  Take a look at your phone and know that it is because of Karlin’s analysis in the 1950’s that your phone has the layout it has today.