Fear, Greed, Stupidity and a Trade for the Ages

Fear, Greed, Stupidity and a Trade for the Ages

April 8, 2013

Wes Chapman

               

 “Three great forces rule the world: stupidity, fear and greed.”

Albert Einstein

Traditional Chinese Medicine recognizes the concept of two great opposing forces – the yin and yang. Not too surprisingly these are captured by opposites: male vs female, light vs dark, sun vs moon.

In modern finance the yin and yang could be considered to be the great two investment motivators: fear and greed. Consider my absolute wonder last Friday when a quick perusal of the day’s headlines finally recognized that both fear and greed have merged into the wonder trade for the ages – borrow short from the Fed, and lend long to the Treasury. According to the headlines in the popular press this is both incredibly lucrative, and absolutely safe.

Better still, this trade has such beneficial macro-economic impact that the Japanese have decided to double down on this bit of financial legerdemain, and have decided to double the profligacy of our own Federal reserve, and create money to buy bonds equal to 1% of GDP per month in the hope of stimulating real economic growth via currency debasement. Good luck with that.

 

“Haven Flows Push Treasury Prices to High for the Year”

WSJ, 4/4/2013

“They babble about a bubble, but it’s not

Treasuries popular because they’re safer”

USA Today, 5/5/2013

“Japan starts monetary revolution,

All but scattering cash from a truck”

Financial Times, 4/5/2013

The minute that fear and greed merge, the great limits on insanity are eliminated – all that remains is the stupidity noted by Einstein. As in the case of the many debt crises of the immediate past, we are accelerating as we approach the edge – and it’s time for the whole world to play. Japan pushes the accelerator of monetary growth, all the while forgetting the hundreds of billions of dollars of worthless 100 year residential mortgages still resting comfortably on their financial institutions balance sheets.

When it comes to the high jinx of the world’s central banks, I think that the Great Emancipator had it right.

“You can fool some of the people all of the time, and all of the people some of the time, but you cannot fool all of the people all of the time.”

Abraham Lincoln, (attributed)

And I’m still mad that I never put on the one-way trade for the ages – remember it will work until it doesn’t.

The Opportunity of Oncology ACOs – Strategic Considerations & Challenges – A Return to the Elusive Promise of Capitation

The Opportunity of Oncology ACOs

Strategic Considerations & Challenges:

A Return to the Elusive Promise of Capitation

 

January 24, 2013

Wes Chapman

The Imperative for Strategic Change

         

Fischer Beats Spassky (again) in their Rematch

 

 

An Oncology ACO

 

Accountable care organizations sprang into the popular parlance in 2006, introduced by Dr. Elliot Fischer of the Dartmouth Institute as a provider driven organization to anchor the push for the “Triple Aim” originally espoused by Dr. Don Berwick;

1. Better patient care,
2. Better population health, and
3. Reduced costs.

ACOs differed from the HMOs from which they were seemingly born by three important characteristics:

1) The organizations were grounded in improved primary care – not just “gatekeepers,”

2) Patient choice was putatively retained, and

3) Continuously improved care – as demonstrated by transparent quality metrics – would drive down costs even as care improved.

 

What was, in fact, clever and demonstrably different about ACOs was the payment mechanism for goods and services. The payment mechanism currently in use allows for a gradual shift: 1) from fee-for-service (FFS) payments, to 2) FFS based payments with risk sharing models and some type of shared savings, and finally to 3) capitated payments based on populations, with significant premiums and penalties for attainment of quality goals. It is important to note that all ACOs models to date use historical costs (provider revenues) – in some fashion – as the baseline for the evaluation of payments in the future; typically for periods of 3-5 years. It is important to note that all ACOs formed to date by Medicare (CMS) are quite idiosyncratic in design, and all are focused on primary care. There have been a few oncology ACOs formed to date – all by private payers and providers.

 

As a result of this payment model, clinical areas which can effectively reduce costs – actual cost from a provider’s perspective, not just utilization – while simultaneously improving care (based on established metrics) can benefit enormously from ACO payment reform. For a variety of reasons, oncology care – particularly medical oncology – is structurally well positioned to benefit financially from the ACO model.

 

There are two major catches in the ACO payment system from a provider perspective: 1) prospective payments always involve some form of a discount from historical levels, and 2) adherence to and attainment of quality metric goals may be difficult or impossible to achieve, and if achieved may not reduce costs or actually improve clinical outcomes.

 

As with any new payment model, ACOs were designed to offer financial incentives for providers to adopt new organization structures and clinical innovations to achieve the Practical Triple Aim: 1) improve patient satisfaction, 2) reduce payer’s outlays, and 3) improve provider financial performance.

 

The high variable cost structure of medical oncology, combined with the care innovation afforded by the emerging areas of palliative care, patient education and informed patient choice (see Palliative Care) offer a unique opportunity for successful ACO formation.

 

Costs, sharing savings, coordinating care, medical homes and dealing with complexity

 

From a practical perspective, oncology care is delivered by numerous clinical specialties – including medical oncology, radiation oncology, surgical oncology, radiology, pathology, primary care and palliation – all too frequently operating without any central care plan or even effective care coordination (see Oncology Care). Based on our work in several different environments, a population of over 250,000 people incurs cancer at a rate of just less than 1%, with a typical cost per patient between $80,000-120,000. Costs for such a population typically are incurred (based on payment) along the following lines:

 

Cost Element	% of Total	Potential Savings
Medical Oncology	35.0%	5-10%
Radiation Oncology	17.5	2.5-5%
Surgical Intervention	22.5	2.5-5%
Radiology and Diagnostic	7.5	2.5%
Other	17.5	5-10%
Total	100.0%	17.5- 32.5%

 

In order to coordinate care and reduce total costs, it is critical to include total patient care in an oncology ACO. As further highlighted below, the cost structure of each of these areas is very different, and simple reduction of utilization may not accomplish actual cost reduction from a provider’s perspective.

 

Cost Element	Description of cost structure
Medical Oncology	Medical   oncology has some of the highest variable costs found in medicine (40-50%).   Capitated payments correspond directly to greater profits because of the   elimination of purchased drugs. The use of clinical pathways and bundles is   becoming widespread – reducing variability and cost. This is also the area of   greatest risk due to high priced medications. This area also has the greatest   level of pathways, process metrics and patient reported outcomes ( Pathways and   metrics,   Patient   reported outcomes)   to ensure quality and best practice adherence.
Radiation Oncology	Radiation   oncology is a very high fixed cost business, and has been under constant   assault from pricing. Extremely expensive equipment and specialized   facilities require high utilization for payback and profit.
Surgical Intervention	Surgical   costs combine the relatively high fixed costs of hospitals, together with the   professional fees, which may be fixed or variable based on employment model.
Radiology and Diagnostic	Radiology   and diagnostic testing is an area of high fixed costs, and dramatic   over-utilization in many circumstances. Over utilization results from poor   care coordination, poor IT systems and patient preference.
Other Costs	Up   to half of other costs are clearly identified as unnecessary care for   therapies which neither extend nor improve life. This is the single easiest   area to target savings, as it does not impact revenue anywhere in the   provider system.
Total	The   ability to translate lower utilization into lower actual incurred cost varies   tremendously by therapy. Lower utilization is necessary, but not sufficient   to achieve cost reduction at the provider level – it will also require   facilities rationalization for capacity requirements.

Another way to consider provider cost rationalization is based on the relative value and efficacy of the care provided – regardless of type of care. A good example is care generally regarded as futile, e.g. any late stage cancer death in the ICU or chemotherapy in the last 24 days of life. Cancer is frequently predictably fatal, and presents cancer patients with certain stark choices regarding tradeoffs of the certain negative impacts of treatment with the possible benefits in terms of marginal extension of life. There are certain operational risks in controlling these costs, as well as a number of key operational considerations as outlined below.

 

Cost Category	Best Payment Model for Cost Control	Risks	Operational Considerations
Overtreatment   Relative to Patient Wishes	ACO	Limited   risk of reduced access	Requires   highly empowered PCP’s, strong medical homes, and excellent data
Pointless   End-of-Life Oncology Care	ACO	Limited   risk of reduced access	Requires   Highly empowered PCP’s, strong medical homes, and excellent data
Pointless   End-of-Life Other Care	ACO	Limited   risk of reduced access	Requires   Highly empowered PCP’s, strong medical homes, and excellent data
High   Variability & “High Price” selection bias in Medical Oncology	ACO/Bundles	Limited   risk of reduced access	Requires   capitation in some form and excellent pathway/bundle definition
Excess   diagnostic testing and radiographic imaging	ACO	Limited   risk of “under-diagnosis”	This   requires excellent IT systems and empowered PCPs

 

The delivery of clinical care in the US is complicated by our fee for service payment system – economics drive care towards a revenue optimization model which maximizes revenue by maximizing the number of touches and the relative value unit (RVU or payment value) per touch. Oncology care further complicates matters by spreading care over three completely separate clinical specialties – medical, surgical and radiation oncology – with little or no coordination between them being the norm. This results in a wildly inconsistent and complex system, operationally opaque to patients, providers and payers alike.

 

An effective medical home – particularly an oncology medical home – with an effective primary care physician is a first and necessary step in providing leadership to untangle the “balls of snakes” that is frequently the flow chart of oncology care delivery. From a patient’s perspective, oncology care is their personal Superbowl – a game with very high stakes. An oncology medical home and oncology PCP affords the patient both a game plan and a quarterback – dramatically improving the odds of victory. From a financial perspective, an oncology medical home and PCP – providing the related planning, palliation and patient education functions – are the only methods to ensure that unnecessary, duplicative and futile care can be identified and eliminated; and the financial benefits of the oncology ACO are realized. The oncology medical home and PCP are absolutely essential elements in achieving the patient satisfaction and financial goals of the Practical Triple Aim.

 

 

Complex oncology care delivery system – uncoordinated care & uncontrolled costs

Planned and coordinated care with rational economic incentives

Critical Management Control Issues in Oncology ACOs

Effective management of a comprehensive oncology ACO requires the integration of 6 fundamental process steps across at least 3 clinical specialties: 1) education of the patient and the determination of patient preferences and goals, 2) planning care for the patient based on best practice pathways, 3) executing the plans with the greatest sharing of resources and diagnostics, 4) integrating palliative care as required, 5) verifying compliance, and 6) updating all of the above as required based on disease condition. There are only a small number of entities in the US capable of managing planned, integrated cancer care in the US, and tiny number capable of effectively managing planned, integrated total patient care including oncology.

 

Most of the 41 NCI designated comprehensive cancer centers are capable of effective care pathway design and selection – development of an effective individual care plan. Most of these are capable of tracking care plan compliance, and a fairly robust suite of process and efficiency metrics. There is one noteworthy for profit player in the area – Cancer Treatment Centers of America – which has really done a terrific job in driving patient satisfaction based on reported diagnostic and care planning, coupled with documented care plan compliance. Finally, there are three noteworthy rural based health systems that stand head and shoulders above the rest in total care planning and documented compliance – Mayo Clinic, Geisinger Health System and Intermountain Healthcare.

 

It is important to note that in virtually every case, the existing operating control systems are integrated into revenue cycle management (RCM) software to a large degree (see Inverted System Requirements), dramatically complicating the ability to move swiftly to a capitated system, rewarding savings.

 

Issues with Shared Savings, Beginnings, Transaction Intensity

 

Oncology ACOs need to be fairly broad to realize their full benefit, but a medical-oncology-only ACO is a good place to start, and really simplifies the ability to identify and capture savings. Most ACOs to date use fee for service billing with a gross up at the end of the year to reflect savings. In any multimodality ACO, this would encourage disparate provider groups to maximize their own billing, while pushing for reduced service levels and savings in other clinical areas. This “best-of-both-worlds” incentive could only be limited by contentious battles refereed by the PCP, and would be destructive and a waste of time. Furthermore, reductions in utilization of high fixed cost operations such as radiation oncology do nothing to reduce actual costs. In these areas, costs can only be reduced by the elimination of capacity – and that requires that somebody take an economic hit.

 

Efficient economic formation of oncology ACOs will benefit from multiple transactions of several types (Transaction Types & Motivations) – targeted at goals including control of operating assets, achieving 340B drug pricing, aligning provider incentives, optimizing pre-ACO reimbursement, forming and engaging provider groups, and controlling assets for rationalization based on projected use. To a very large degree, the operating potential of an oncology ACO depends on factors dependant on well structured and targeted transactions combined with operating management, clinical leadership and IT control systems that allow the economic potential of medical oncology ACOs – potentially reaching 10-30% of margin improvement – to be realized.

Opportunities in Healthcare M&A – a Structural and Data Driven Revolution

Opportunities in Healthcare M&A

The FTC and the Alphabet Soup Antidote –

An Information Driven Structural Revolution

October 15, 2012

Wes Chapman

           

My friend Pete is a senior player in a major regional academic medical center, and a terrific raconteur. He was hilarious in his recounting to a group of pals, the horror of trying to put together a small merger a couple of years ago with another not-for-profit hospital across the state in which he operates. The essence of the problem – the FTC was defining competition in such a fashion that no deal could ever be possible, and after years of work and millions of dollars in expenses, his deal was dead. The story was funny, but the telling was understandably bitter. Pete lived to fight another day and another way – and he just won big.

He did a deep dive into the new alphabet soup of alignment and compensation structures, and put together a data driven, ACO centric series of deals that encompasses 10x the geography and population of the original FDA blocked merger. This is very cool – but particularly so, as he did the whole thing in a matter of months, and the money that he saved on lawyers and accountants is the down payment to build a huge new data center to inform the whole thing. Better still, this should allow his organization to reap cost savings and take advantage of purchasing and operational synergies in a way that the simple merger never would have.

Anti-Trust Considerations

The rate of enforcement actions by the FTC in the healthcare service industry has more than doubled over the last decade – largely targeted at traditional corporate style combinations. As hospitals have responded to increasing costs by seeking cost savings in combination, the FTC, DOJ and state authorities have stepped up vigilance to prevent combinations which could lead to anti-competitive pricing. In local-market M&A transactions in healthcare services pose a dilemma; the potential for anti-competitive pricing, is clearly offset in reality by cost savings potential – savings that the system desperately needs. The traditional corporate transactions and corresponding anti-trust regulations are really not designed to bridge this conundrum.

This anti-trust vigilance has spilled over into the not-for-profit arena following the post-acquisition study of the 1999 Sutter Health acquisition of Summit Hospital in Oakland, California. The California Attorney General sued to block the merger, only to have an injunction overturned by a judicial ruling. A subsequent study – two years later – indicated that the consolidation had resulted in price increases of 72%, and the die was cast – not-for-profit mergers were absolutely fair game – and my friend Pete was an unsuspecting “beneficiary” in his failed merger with another non-profit.

From revenue to cost/information driven solutions

The dominance of fee-for-service pricing mechanisms in recent years has driven revenue model dominated business solutions in healthcare. I know that for at least the last 10-15 years, my friend Pete has fixed all of his budgetary problems with a simple formula – charge more money. Pete’s experience has been standard industry practice for at least the last decade, as illustrated by the chart below.

 

Not too surprisingly, this run up in costs has resulted in a system with a fair amount of fat – particularly around overhead associated with software and systems for “coding enhancement” – estimated to be upwards of 15% of total system costs. Additional overhead crept into the system as combined entities – optimized for an HMO environment in the’80’s and 90’s – disintegrated into individual units offering specialty care solutions. These models were vastly more efficient than the in-hospital services that they replaced – but because they did not reduce hospital capacity, perversely overall systems overheads increased. As an example, the rise of ASC’s and related specialty hospitals has further reduced overall system utilization rates – recently exacerbated by the decline in utilization driven by a weak economy and the widespread adoption of high deductible health insurance.

The insurance industry countered this trend by continuously dropping rates to fractionated specialty care providers – creating yawning gaps between prices being paid to independent providers and those paid to hospitals – routinely as much as 2X, as recently noted in the Wall Street Journal, August 27,2012, Same Doctor Visit, Double the Cost. Hospitals successfully defended their higher reimbursement, based on the somewhat strained logic – “we provide a unique and necessary benefit for society, those specialty shops have stolen our most profitable business, therefore you must subsidize our higher overheads. As you might expect, this pricing differential has provided the impetus for a land-rush of physician practice acquisitions by hospitals.

My friend Pete merged his physician clinic with his hospital years ago for this very reason, and has enjoyed higher rates of billing for the same services ever since. Not too surprisingly, a large group of regulatory and consumer advocacy groups have been screaming bloody murder about this recently, and these deals are getting harder to do without some larger and explicit purpose as articulated and encouraged by the Affordable Care Act (ObamaCare).

ACA and Accountability for Quality

Dr. Elliott Fisher, Director of the Center for Health Policy Research at Dartmouth Medical School – first coined the term Accountable Care Organization in 2006 during a discussion at a public meeting of the Medicare Payment Advisory Commission. The concept is actually quite clever – if exceedingly difficult to translate from concept to reality: 1) ACO’s are  Provider-led organizations with a strong base of primary care that are collectively accountable for quality and total per capita costs across the full continuum of care for a population of patients, 2) Payments linked to quality improvements that also reduce overall costs; and, 3) Reliable and progressively more sophisticated performance measurement, to support improvement and provide confidence that savings are achieved through improvements in care. Most importantly, the success of the ACO model in fostering clinical excellence while simultaneously controlling costs depends on its ability to “incentivize hospitals, physicians, post-acute care facilities, and other providers involved to form linkages and facilitate coordination of care delivery.”

Let’s see, we’ve gone from a policy which specifically discourages, and has the power to block “linkages”, to one which actively promoted them. More importantly, the system went full-throttle in support of these innovations, including Bundled Payments (BPI) Co-management Agreements (CMA’s) and a raft of additional acronyms that would have done FDR proud – this is a revolution being done with prototypes, and they are coming thick and fast. We have an alphabet soup of new structures, and a world of new opportunities.

From the point of view of an old M&A hand, what we have is: 1) The ability to form novel combinations driven from physician organizations – medical practices – where value is created by documented care improvement, and cost reductions driven by documented use of best practices – evidence based pathways and the like, 2) The ability to form “cross-border” arrangements between physicians and hospitals that never existed previously, offering the unusual prospect of lower costs and better care, and 3) The wondrously gentle hand of the DOJ which is not requiring prior approval of these combinations and is offering all forms of safe harbors and the like.

The devil lies in the details in these structures – like all healthcare transactions – but with one additional caveat. These systems need information and quality improvement capabilities in scale, and the more complex the deal, the more specialized the information and quality systems. Doing this job properly requires systems that do not exist today from any vendor, targeted at cost reduction and quality improvement – executed across disparate provider groups with incompatible data and management systems.

These are radically different systems requirements than almost all existing medical management systems, which are targeted at three fundamental characteristics espoused by my old friend Jock – a longtime physician and infomatician: 1) Save time, 2) Make money, and 3) Stay out of jail.

We have selected oncology as perhaps the most appealing clinical target – based on the three key attributes of 1) Clinical and cost benefits from combined disparate clinician groups, 2) Defined clinical pathways and defined best practices to inform clinical activities post combination, and 3) Opportunities to dramatically improve patient experience through combination and advanced information management. The trouble is: 1) These are difficult and time consuming transactions to structure with multiple parties, 2) Payer involvement is critical, and 3) Advanced information systems are a requirement to make this work – and we need to build them.

Is it worth the trouble?

Yes – for three reasons. First, from a financial point of view, we are fairly certain that we can take 10-15% of the cost out of a combined oncology care platform, and do it fairly quickly. There is a fair amount of “secret sauce” in pulling this off – but it can be done.

Second, we can actually improve the patient care experience. This needs to be the central quality objective of the project.

Finally, done right this is both a quality management system and can facilitate rapid learning – regarding care, cost, and satisfaction. Remember the data should be a treasure trove of information and value.

What’s Different this time?

Structured information about cost and quality – the answer is really that simple. There has been an explosion of structured data used in clinical care in the last 5 years – most famously in the electronic medical record (EMR). While these systems are truly atavistic by modern IT system standards – lacking even the most modest of decent data field definition standards – they are vastly better than what existed even 10 years ago. Better yet, the best of these systems are moving to the cloud – bringing with them the promise of continuous improvement and uniform versioning inherent in such systems.

The wild proliferation of incompatible data systems between and within medical systems has resulted in a commensurate explosion in the demand for gigantic data warehouses – both wildly inefficient and grossly over-powered for most of the problems actually faced by medical quality professionals – tantamount to shooting a fly with a cannon. Cloud based solutions are actually very well suited to address these issues, particularly when coupled with rules engines, and fed data from disparate sources.

Like in the pharmacy industry, information in oncology care is changing into a control mechanism – integrating patient, payer and provider. This is a fundamentally different configuration than ever before – and it will drive changes in care delivery and ultimately lead to tremendous industry consolidation. Stay tuned.

Tax Refugees, the Buffett Rule and Emergent Phenomena

September 18, 2012

Wes Chapman

“Capital goes where it’s welcome and stays where it’s well treated”

Walter Wriston

 

I was struck by a recent article (August 29,2012) in the Wall Street Journal highlighting the reincorporation of US firms in various offshore venues to reduce their income tax burden – highlighting such American stalwarts as Eaton Corp, Transocean, Aon and Weatherford. What struck me was that this relocation for tax purposes would qualify as news to anyone. Well run American corporations have used a variety of international tax strategies to their advantage since the founding of the Republic, often forcing wholesale revision of the existing tax code to bring matters back to equilibrium – most spectacularly in 1913 with the passage of the 16^th Amendment and the introduction of the income tax itself.

Why an Income Tax

Prior to 1913, the Federal Government squeaked by on an amazingly complex series of tariffs on imported goods – which averaged 40% pre-1913 and were lowered to 26% post income tax. The high tariffs had their own Laffer curve type impact; reducing trade, lowering tax revenue, increasing domestic corporate and labor power, and infuriating our trading partners. On balance, a top marginal rate of 7% – the top rate in 1913 – looked like a pretty good deal relative to the tariff based alternative.

Interestingly, the original 1913 income tax code made no provisions for capital gains rates, dividend rates, unearned income (remember that concept fellow tax geeks?) and the like. Specifically it provided for taxation of:

“subject only to such exemptions and deductions as are hereinafter allowed, the net income of a taxable person shall include gains, profits, and income derived from salaries, wages, or compensation for personal service of whatever kind and in whatever form paid, or from professions, vocations, businesses, trade, commerce, or sales, or dealings in property, whether real or personal, growing out of the ownership or use of or interest in real or personal property, also from interest, rent, dividends, securities, or the transaction of any lawful business carried on for gain or profit, or gains or profits and income derived from any source whatever”

It seems pretty simple and it was. Within 30 years the top marginal rate for individuals had exploded to over 90%, and did not settle down back out of the more reasonable level of 28% until the Act of 1986 brought a temporary flood of order and sanity to the Tax Code. It stayed at those levels only for two years before the agents of entropy – lobbyists and tax specialists – worked their magic and began the tradeoffs of special treatment (think special deductions and credits) versus marginal rate increases which are the hallmark of our system today.

Chief among these putative inequities is the capital gains tax rate of 15% – the foundation of the simple logic behind the Buffett rule – billionaires should logically pay at least the same marginal rate as their secretaries in any fair tax system – particularly one which bills itself as “progressive”.

International tax codes as competitive Emergent Phenomena

As best noted by Mr. Wriston at the beginning of this paper, capital is free to flow wherever it pleases – typically places with the happy prospects of big returns and low taxes. Tax codes have become terrific methods for countries to attract investment capital and get it to stick around. Capital can flow to new markets in a way that labor cannot. Foreign capital is welcome in markets in a way that immigrant labor is never welcomed.

As a result, it is feasible to tax income on labor in a way that capital would never stand for. Consider the tax rates shown below for some of our trading partners:

Country	Top   Individual Rate	Top   Corporate Rate	Capital   Gains Rate	Value   Added Tax Rate
United   States	35%	39%	15%	0%
Ireland	41	10-25	25	9-23%
United   Kingdom	50	23	28	20
Canada	29	15	22	5
Japan	40	40	20	5
China	45	25	59	17
Mexico	29	28	30	16
Germany	45	30	28	19
India	33	10	15	NA

 

I have highlighted the highest rates in red, and the lowest rates in green. Not too surprisingly, those who can prefer to have capital gains taxed in the US – we have the lowest rates in the group. Ireland, Canada and India are great places to incorporate, but the poor unfortunates living in the UK and Germany are effectively subsidizing low corporate tax rates with very high individual rates and high value added taxes. It is important to note that very low capital gains rates are a recent phenomenon in the US.  As recently as 1989 they were set at the same level as the maximum earned income rate – specifically to address the tax rate disequilibrium that Mr. Buffett finds so distasteful.

Not all tax systems are created equal – They emerge in response to local and international forces

In the US we really hit our corporations and hit high earners fairly hard – in exchange for very low capital gains rates and the unique position of no VAT. The VAT is “regressive” and is considered antithetical to a consumer based economy. In a cynical view, we tax the hell out of high end workers and corporations to subsidize shop-a-holics and billionaires. Not too surprisingly, we have a relative surplus of both of the later, and fairly cranky wage earners and corporations – and the corporations can do something about it; as noted in the WSJ article, they move to a different venue.

Ant Hills and Taxes – Both Emergent Phenomena

Tax codes are really instruments with real competitive policy implications for growth, savings, consumption and investment. Most importantly, no nation’s tax code can be considered in a vacuum – they tend to be self organizing over time to be structured very much alike – but with important differences responsive to local sensibilities. The differences between them have major policy implications – both for internal purposes and external trade.

The classic emergent phenomena are ant hills; through the dedicated work of countless agents – ants – the ant hill emerges consistently – although always without a central plan, design or outside agent. Moreover, the world is full of different types of ants – but all of the successful ones build large hills – protected in their mounds while competing for food with their neighbors. International tax codes are much the same – with tax attorneys and accountants substituting for the ants and countless piles of paper substituting for the anthills – the phenomena are the same – and the metaphor simply compelling. In the case of tax codes the competition is for votes domestically, and discretionary tax revenues internationally.

Emergent phenomena exist at the ragged edge where the entropy promised by the second law of thermodynamics meet systems that make order out of chaos – all without a plan or external agent. The most interesting characteristic about emergent phenomena are that they are almost always best described by the unintended consequences that they create – emergent functionality. Tax systems are ostensibly designed to raise money for governmental activities, but their emergent functionality is entirely trade, investment and consumption related.

As we enter the end game of the silly season of a Presidential election year, let’s not lose sight of the fact that we have surrendered our fiscal policy to a doomsday machine (the fiscal cliff), and substituted a hyper-aggressive monetary policy for any fiscal policy at all – creating a gigantic disequilibrium in the economy. We have frozen all lines of rational discussion about fiscal policy, and locked in place a tax code which is considerably distorted relative to our trade partners, particularly regarding taxes on consumption and the glaring inequities highlighted by Mr. Buffett. We have a bit of a mess on our hands.

We have ceased the natural evolution of the tax code – all emergent phenomena learn and evolve – and created an ossified mess, leaving us at a substantial competitive disadvantage relative to our trading partners. Next year will mark 100 years since the modern tax system began under the Underwood-Simmons Act, and it may be time for a second revolution. The economic impact of the emergent functionality of the tax code is stupendous, and the current tax code is a mess.

In 1913 the US operated under a tariff based tax system that protected certain domestic industries, discouraged investment, hurt consumers, discouraged investment, tremendously distorted trade flows and simply didn’t raise enough money. The folks that ran the US at that time had the courage and wisdom to try something different – which proved responsive and adaptive for nearly a century.

Today, our tax system is at least as bad as the mess in 1913, and has completely ceased to change in response to changing domestic requirements and international competition. The question is – do we have the guts to actually fix it?

Complexity Theory and the 8% Projected Return on Pension Assets

Cry havoc, and let slip the actuaries!

With apologies to William Shakespeare

Cheap money, persistent disequilibria, actuarial follies & the looming pension fiasco

June 2, 2012

                       

Delaying the day of reckoning – assumed pension asset growth

Yesterday the yield on the 10 year bond of the United States slipped under 1.5% for the first time since December of 1941. At the same time the assumed rates of return for most public pensions in the US remains at 7.5-8.0% – a 600-650 BP (basis points) excess return above the 1.5% benchmark risk free asset. By way of comparison, public equities are normally assumed to return around 350 BP above the risk free rate (over the long term) and alternative investments around 500-900 BP to compensate for the additional risk and loss of liquidity associated with these asset classes. I would like to take a look at the reasonableness of the 8% total return assumption and what it may mean vis-à-vis public policy.

There are around $16 T of pension assets in the US, with about 43% or $6.9 T in defined benefit plans – those in which the risk for the returns lies with the plan sponsor – typically states, municipalities and major corporations. This requires around $550 B in annual returns (both yield and realized gains) to produce the minimum return of 8.0%. These returns are earned on assets including bonds (31% of total or $2.1T), public equities (44% or $3.0 T) and alternative investments (25% or $1.7 T) – typically venture capital and private equity.

Three Cases – The Model, The Actual and the Projected with Rate Increases

I thought that it might be interesting to take a minute to look at the impact of ever declining interest rates on the pension assets of the US – particularly in light of the assumption 8% rates of return on assets into perpetuity.

Shown below are three model cases: 1) Case 1 looks at how actuaries are looking at the present and future for returns by major asset classes. This is important because it tests the reasonableness of their assumptions based on historical norms. 2) Case 2 looks at actual returns for the last several years, and highlights the impact that persistent declines in interest rates to historically low levels have had on asset performance. 3) Case 3 looks at the case when interest rates rise even a little – and what happens to the nations accumulated pension assets and obligations.

Case 1 – Model returns on Actual US Defined Benefit Pension Assets and Assumed returns

Assumes 2.5 % Risk free rate

	Bonds	Public Equities	Alternative Investments	Total
Total Assets	$2.1 T	$3.0 T	$1.7 T	$6.9 T
Assumed Returns	3.5%	6%	9.5%	6.0%
Risk Premium above 2.5%	100 BP	350 BP	700 BP
Assumed $ Returns	$73.5 B	$180 B	$161.5 B	$415.0

Model Portfolio Produces Shortfall of $135 B or 2.0%

A review of the available literature indicates that the current shortfall in pension assets is about $1.0 T for states and municipalities, and $400 B for corporations, for a total of $1.4 T. This implies a shortfall of $112 B in yield – which is a reasonable confirmation of the $135 B estimate shown above.

It is important to note that the last decade has produced returns far less than the assumed risk adjusted returns shown in the Table above in public equities and alternative investments, and far in excess of the modeled returns in bonds. The superior performance in bonds has been due entirely to the long term secular decline in interest rates, being led by initiatives sponsored by the Fed, beginning under Chairman Greenspan in 1987.

The Secular decline in interest rates has propelled bond returns

Case 2 – Typical Recent Returns on Actual US Defined Benefit Pension Assets

Assumes 2.5 % Risk free rate

	Bonds	Public Equities	Alternative Investments	Total
Total Assets	$2.1 T	$3.0 T	$1.7 T	$6.9 T
Typical Returns	15.5%	2.5%	5.0%	7.0%
Performance Premium above 2.5%	1300 BP	0 BP	250 BP
Typical $ Returns	$325.5 B	$75 B	$85 B	$485.0

Typical Return Portfolio Produced Shortfall of $65 B or 1.0%

The impact of the bond portfolio on typical returns in the last few years has been overwhelming. Despite limited success in alternative investments, and the virtual stall in public equities, the returns on bonds has vastly outperformed other asset classes (and all reasonable expectations). This has been due entirely to the decline in interest rates, as the overall credit quality has deteriorated markedly in all sectors other than corporate debt. This decline in interest rates is obviously a one-way ticket, as interest rates cannot go below zero, and will under normal conditions return to historical norms. The question is – what happens when interest rates rise to the returns illustrated below?

Case 3 – Model returns on Actual US Defined Benefit Pension Assets and Assuming Interest rate increases – to 7%

(Assumes 7 % Risk free rate)

	Bonds	Public Equities	Alternative Investments	Total
Total Assets	$2.1 T	$3.0 T	$1.7 T	$6.9 T
Projected Returns	(15)%	7%	7.0%	0.2%
Performance Premium above 2.5%	(1750) BP	0 BP	0 BP
Case 3 Model $ Returns	($315 B)	$210 B	$119 B	$14.0

Model (increasing rates) Return Portfolio Produces Shortfall of $536 B or 8.0%

A Persistent Disequilibrium- Strip Mining the Yield Curve

Complexity theory would suggest that any persistent disequilibrium causes complex systems to increasingly consume resources and then degrade into chaos as the disequilibrium ends. The multi-decade decline in interest rates – driven entirely by the Fed – has been intended to stimulate economic activity as the Fed uses its limited tool kit to fulfill its dual mandate. After running out of room to lower rates at the short end of the curve, the Fed switched to targeting the long end – effectively strip mining the yield curve – and leaving a pile of slag and overburden for future generations. As Case 3 above illustrates, even a modest increase in interest rates will create an irreparable hole in the fabric of the American pension system – a future turn of events artfully disguised by the actuarial legerdemain of projecting 8% returns in a 1.5% environment.

It is important to note that the concept of maintaining robust equity and alternative investment yields in Case 3 above is more an of actuarial mercy than a hard eyed view of reality. We have seen the circumstances in which interest rates hit 7% in Europe – and it has a devastating impact on equity values and alternative investments as well. In Case 4 Below, I consider more realistic case in which all asset classes get suitably whacked as interest rates rise – it is not hard to imagine.

Case 4 – Stress Test Recent Returns on Actual US Defined Benefit Pension Assets

Assumes 7.0 % Risk free rate

	Bonds	Public Equities	Alternative Investments	Total
Total Assets	$2.1 T	$3.0 T	$1.7 T	$6.9 T
Typical Returns	(15)%	(20%)	(30)%	(20%)
Performance Premium above 2.5%	(1750) BP	(2250)BP	(3250) BP
Typical $ Returns	($315 B)	$(600) B	$(510) B	$(1.4)T

While Case 4 may be perceived as unnecessarily draconian by the actuarial community – which is considering 8% returns proceeding happily into the future, it is considerably less dire than we saw at the start of the great recession, and considerably better than the situation in much of Europe today.

When the going gets rough – run for the exits

On Friday, GM and Ford both announced plans to exit as many of their defined benefit pension obligations as possible – both through lump sum distributions and annuities purchased through third parties. These are currently profitable companies – currently enjoying a renaissance in domestic auto demand. They are clearly responding to actuarial assumptions which are lagging reality – the assumptions of 8% returns – and the end of the bond market run. They are getting out of the pension business for a very simple reason – because they can.

Very small items – like an assumption of unrealistic returns on pension assets – can have markedly outsized impacts on complex systems – like the world economy. The projected rate of return of 8% is wholly unrealistic based on current interest rates, and wholly unsupportable when considered relative to the only existing comparable – Japan. These seemingly small and innocuous points of actuarial fantasy are precisely the triggers for future chaotic market conditions.

Can you hear the butterfly’s wings flapping?

Chaos Theory, Sub-Prime Mortgages & Positive Feedback Loops

Capitalism at a Cross Roads

Considerations of Persistent Disequilibria and Positive Feedback: Finding the Butterfly

Wes Chapman

April 8, 2012

 

PREFACE

The twin marvels of truly awful weather and systemic market meltdowns have a lot in common. First they feed on persistent disequilibria in their respective systems – weather systems feed on temperature and pressure differentials which can only be resolved through long time frames for adjustment or short term violence – storms. Similarly, economic and financial disequilibrium tend to be founded on regulatory or information impediments, leading to persistent positive feedback loops – first running markets up, and then, inevitably, leading to collapse.

Awful weather – a self-feeding phenomena

Really chaotic behavior in weather systems and financial markets requires that several positive feedback phenomena – think low interest rates, rising housing prices, systematic mispricing of securities, failed regulation, and systemic level fraud – are required to produce a real financial apocalypse. What makes the process interesting is that these factors may exist in the system functioning perfectly for decades, and only when combined a special brew a la the Three Witches of Macbeth do we get the resultant fiasco.

There has been a steady stream of metaphorical comparisons of Sebastian Junger’s book, The Perfect Storm, with the Great Recession in general, and the meltdown in sub-prime mortgages in particular. It is worth taking a look at what actually made the Perfect Storm unique, and what comparisons are meaningful to the sub-prime meltdown vis-à-vis complexity theory.

If they merge – you get the perfect storm

The Great Recession is a rolling disaster that the world economy seemingly stumbled into in the spring of 2008 led by a housing collapse which began in the sub-prime mortgage market.  This rolling economic Verdun was born many years before in a series of ill-conceived and poorly understood policy initiatives championed by consumer advocates and industry groups alike. These reforms – generally characterized as deregulation – were targeted at the seemingly laudable targets of risk mitigation and fairness, and categorically achieved just the opposite. In this paper I take a look at the human faces behind the fiasco, it takes clever and dedicated people to create a mess this big.

A result of negative feedback

Each of these examples is a terrific case study of chaos theory at work. In chaos theory, a small action/change in a complex/dynamic system can have enormously disproportionate impact in the future. The classic example is posited by Lorenzo in his 1972 paper, Predictability: Does the Flap of a Butterfly’s Wings in Brazil set off a Tornado in Texas? What is most important to remember here is that chaos theory is very sensitive to initial conditions, and unpredictable beyond very short periods of time. For those making economic policy this requires a constant vigilance for the undesirable unintended consequences of policy changes – clearly the butterfly did not intend the tornado.

It is to the quest of finding Lorenzo’s butterfly that I dedicate this series of articles.

Considerations of Complexity and Chaos

Complexity is a relatively new area of study, in which the nice equations that we learned in economics and physics are tested against the vagaries of reality. From a practical perspective, it is, at its core a study of the realistic implications of physical and social entropy that we see all around us. To a large degree, complexity theory borrows heavily from the study of biological systems, and applies those lessons to areas as diverse as meteorology to economics. All complex systems share four fundamental characteristics:

1) Autonomous Agents All of the independent actors in any complex system are autonomous agents which produce results in the system. These agents may be storms in a weather system, or stock and bond traders in financial markets. Diversity is a key factor in Autonomous agents – the less diversity, the less complexity and potential variation in outcomes.

2) Connected All Agents in a complex system must be connected – directly or indirectly. Typical examples might include connections via energy sources or communication patterns.

3) Interdependence All Agents in a complex system influence each other through one or more series of connections, and are therefore interdependent, although autonomous.

4) Adaptation Any complex system adapts to external influences in unpredictable ways, and complex social systems are capable of and depend upon learning.

Complex systems are normally open systems like weather, which exist in a thermodynamic gradient and function to dissipate energy in a fundamentally unstable system – a persistent disequilibrium.

Such complex systems frequently produce negative or positive feedback loops, in which actions in the systems in turn impact the system itself – producing more of the original activity. A good example is the self-feeding nature of a hurricane, which continues to grow by deriving energy from heated water, which increases the size and force of the storm, which in turn adds more energy and leads to further growth.

A common positive feedback loop in finance is the positive effect that ample mortgage finance has on real estate prices, feeding more transactions at ever higher values. Such a system is said to be in a persistent disequilibrium until the availability of mortgage financing is curtailed.

Chaotic systems: 1) Are sensitive to initial conditions, 2) Are topologically mixing, and 3) Have dense periodic orbits. Of these three, point one is the object of interest for any amateur historian/scientist – can you figure out where and when the butterfly flapped its wings?

Not too surprisingly, the description of the inputs to complex systems depends – to a large degree – on the academic background and orientation of the party doing the explanation and evaluation. Physicists tend to describe complexity as requiring constant inputs of energy and developing closed feedback loops limiting the dissipation of energy. That might be a pretty good description of a super-charged storm system like a hurricane.

Economists talk of the primacy of information, learning and adaptation and the central role of competition in the adaptive process. In either case, while you are dealing with radically different systems and agents, the same four fundamental characteristics apply.

The following chart gives a pretty good idea of how different branches of study use complexity to explain the same thing – the driving force in each system.

Looking at the simple chart above, it highlights the complexity of a system involving humans; as we are uniquely driven by all of the above factors.

The Perfect Storm as a Metaphor for the Great Recession

Sebastian Junger did a great job touching the mystery and horror associated with the Great Halloween Storm of 1991 in his book, The Perfect Storm. What made the storm particularly noteworthy was its absolutely unique origin – the merger of 1) the remnants of a blown-out hurricane (Grace), 2) an extra-tropical low pressure system, and 3) a vigorous, early season cold front blowing out over the Gulf Stream – which was still unusually warm for relatively late in the season – around 80 degrees.

While the wind speed of the storm was only around 60-75 mph, it took a very unusual track – heading directly back toward shore, and producing some truly gigantic waves. The tides and waves produced some historic damage including the sinking of the Andrea Gail – which was the story line of both the book and movie.

The factors that make the Perfect Storm a good metaphor for the financial wreckage of the Great Recession are: 1) It was born of the merger of a number of small and seemingly normal phenomena into a super storm, 2) It incorporated a number of previously dissipated tempests and reinvigorated them with the infusion of new energy, 3) It brought together common factors – the Gulf Stream and Canadian air masses – in a unique and enormously powerful and destructive manner, and 4) The storm track was very unusual and dramatically amplified the damage from the storm. This sounds like a pretty reasonable group of factors to degrade complexity into destructive chaos.

The Distant Origins of the Sub-Prime Fiasco

Vast amounts have been written about the origins of the Great Recession. Most of it is correct, and all of it (as far as I can tell) is incomplete. The closest that I have found is the work of McLean & Nocera in their book, All the Devils are Here, which begins with the original securitization of mortgages in the early ‘80’s. They focused on the splendid trio of characters Lewis Ranieri of Solomon Brothers, David Maxwell of Fannie Mae, and Larry Fink of First Boston. Of the three, Ranieri was doubtlessly the most colorful – an up-the-hard-way kid from the streets of Brooklyn, who wanted to be an Italian chef, but was chased out of the kitchen by asthma, and into the mailroom at Salomon Brothers, from which he ultimately rose up to be Vice Chairman.

These three guys were simultaneously fierce competitors and iron-bound allies in negotiations and lobbying the Federal Government and Congress for legal and regulatory accommodation to create the securitized mortgage industry. They were tireless, driven and ultimately successful.

Lewis Ranieri – The father of Mortgage Securitization

McLean & Nocera begin their tale at the right point in time, and with the right characters, but fail to correctly identify the fundamental reason that securitization was perceived and sold to the American people and regulators as an absolute necessity. They correctly identify that the Baby Boomers were coming of age and needed mortgages, and the entire S&L industry which would normally provide them was in desperate straits – hemorrhaging cash and on the verge of mass extinction. The fundamental disequilibrium that caused this fiasco – they never addressed; and that is where all the fun was.

In the late 70’s and early 80’s, Paul Volker, dramatically increased interest rates, successfully reversing the pervasive inflation expectations born of the unilateral abrogation of Bretton Woods and resulting currency collapse under the Nixon Administration. There was at the time a little noted regulation – known as Regulation Q – which limited the amount that S&L’s could pay on deposits. The regulators in Washington refused to allow S&L’s to pay market rates, and deposits fled in droves, forcing the S&L’s into the capital markets for liquidity when they could, or to Government funding when they could not. This financing was at rates up to 18%, the vast majority of their assets paid interest at less than 6% – and they were bleeding cash –and lots of it. This was a system in massive disequilibrium caused solely by the Federal Government.

The S&L’s did what they could to try to attract deposits, including giving away appliances as “gifts” to depositors willing to accept below market interest rates. During this period most banks in the US came to resemble hardware/appliance stores – but with armed guards. It was all very strange, and could have been fixed with a little Reagan era deregulation – simply repeal Regulation Q. That, however, would have eliminated the need for mortgage securitization (and money market funds, also born of the same disequilibrium) – the fundamental underpinning that ultimately fed the sub-prime fiasco – and Wall Street profits for 20 years. The combined lobbying forces of Wall Street and the GSE’s (Fannie, Freddie and Ginnie) in Washington simply overwhelmed the local bankers from the S&L’s, the most successful system of home financing in history was tossed into the trash, and the mortgage backed securities industry was born. When historians undertake to total the costs of the bailout for the Great Recession, they must include the $300 billion that was spent to clean up the S&L mess in the late 80’s and early 90’s.

Can you identify the motivations?

Among the Devils – Consider David X. Li

Cry, ‘Havoc!’ and let slip the dogs of war. (3.1.268)

William Shakespeare, Julius Caesar

Much has been written about David X. Li and his pesky little formula that nearly destroyed the world. Li left China in 1987 (a singularly inauspicious start date) to come to the West to study the ways of finance – and apparently he mastered the art of the fomenting uncontrolled market crashes. He spent several years after arriving in Canada studying business and then statistics, ultimately earning a PhD with a focus on actuarial issues. In 2000 he published the seemingly simple paper entitled, “On Default Correlation: A Copula Approach”, and the fuse was lit on the real estate bomb that exploded in full force in 2008. The formula that was the highlight of the paper, relied on an old actuarial principal of correlation – specifically developed around the predictive value of the demise of one marital spouse on the demise of the second. This coupling or copula was the fundamental concept that was extended to bundles of assets – mortgages, auto loans and the like – to the value of credit derivative swaps (CDS’s) used to insure against the failure of the assets in question, or similar securitized assets.

The Formula Credited with the Sub-Prime Crisis

A Mathematical Expression of a Positive Feedback Loop

The Harbinger of Financial Chaos

In Mr. Li’s defense, he did not initially actively promote his formula as a solution for the pricing of portfolios of sub-prime mortgages or other financial dross, but once it started he participated full on. The formula is a dramatic simplification, relying on a constant of correlation to describe the future movement of asset values and performance. Nothing in any complex system is ever correlated by a constant value. The very concept of a concept of a constant of correlation is an oxymoron in a complex system. I guess that for Mr. Li financial markets in junk securities would follow a smooth and even course to maturity – despite all of the evidence to the contrary. In any event, Wall Street bought in hook, line and sinker – and entered into the headlong rush to the apocalypse.

I have only hit the highlights of this story, and would recommend to the reader checking out Felix Salomon’s terrific article in Wired for a more thorough and entirely entertaining read on the subject,  http://www.wired.com/techbiz/it/magazine/17-03/wp_quant?currentPage=all .

 

4.5x Growth following a pesky little equation

A Bolt of Lightning into the Primordial Goo

My high school biology teacher described the origins of life as caused by a bolt of lightning into the primordial goo. I always loved the imagery, and the obvious link to Mary Shelley’s Frankenstein brought the fantastic to life. This was the same effect that David Li’s little equation had on the primordial goo waiting in the sea of mortgage finance. Securitization allowed the direct sale of risk and CDS’s allowed the insuring against them whether or not you even owned the underlying risk. Li’s equation allowed Wall Street to quantify the risk of a portfolio of assets without even knowing what was inside. Better still, the rating agencies bought into all of it, and were rating portfolios sight unseen. The wonder of it all.

This equation led directly to the muscle-bound thugs running around poor communities selling mortgages the same way that they used to run numbers. Like the Canadian cold front teaming up with defunct Hurricane Grace and the energy in the Gulf Stream in the Perfect Storm, David Li’s equation hit the primordial goo of cheap money, dozy regulators, off-exchange CDS’s, compromised rating agencies and securitization machines craving product. In both cases, the positive feedback loop was spectacular, and the results disastrous.

Time for a Regulatory Re-think

Alan Greenspan used to say that he could not recognize a bubble until it popped. While I find this to be nonsensical, I’ll humor the position by suggesting that in each of the articles in this series I have clearly identified that there has been disproportionate growth – or shrinkage – in a major class of financial instruments presaging every financial catastrophe that I’ve examined. In each case there has been some change in the environment which created a fundamentally unstable system – and led directly to either a positive or negative feedback loop. These aren’t hard to identify, even with the use of retrospective data as favored by regulators.

From a practical perspective, the purpose of financial regulation is always two-fold; 1) Isolate the transaction into a singular event equally understood by both parties, and 2) Create the greatest level of information parity between the parties. The purpose of the derivative markets is to confound the first, and gaining an information edge is the second oldest profession. The pace of change, asset concentration and venue selection opportunities make old static regulatory regimes and strategies almost worthless.

Positive and negative feedback loops are more common in finance today than ever before, but they can be identified simply by looking at differential rates of growth of asset classes in the economy. In short, if it is busted – fix it.

 

Can you hear the butterfly wings flapping yet?

 

Reaping the Whirlwind