Kling On Mankiw On Banks And Modigliani-Miller

A comment I posted on EconLog, "Banks and Modigliani-Miller" by Arnold Kling:

The Fisher separation theorem says that the investors (shareholders, depositors) are not concerned with the investment choice opportunities (the fruit trees) of the bank, as long as the bank invests in positive NPV (net present value) projects. Investors choose their own positive NPV investment opportunities for their own funds separate from the bank's investment opportunities.

MM [Modigliani-Miller] says that the value of the firm, and consequently, the NPV (net present value) of the projects, is independent of the way that the projects and the firm (bank) are financed.

To the extent that a firm can take a tax deduction for interest payments, the deduction is a government subsidy to firms. It allows borrowers to pay, and the lenders to demand, a higher interest rate due to the government subsidy, which by itself should offset the benefit of the tax deduction. If the lender is also taxed on the interest income, then the two taxes will offset each other. If the taxes are equal, then it will be as if there were no interest deduction and if the two taxes are different amounts, a new equilibrium supply and demand point (interest rate cost of borrowing) will occur depending on which tax is higher and by how much. If the two taxes are equal, as they most likely are, the interest deduction will have no effect on leverage. Likewise, if there is only a tax deduction there will be no effect on leverage due to the higher interest rate. It is only when there are different income and deduction tax rates, that there will be some minor leverage effect.

Deposit insurance is a put option (all insurance is a put option) given to the depositor through the bank by the FDIC. Because deposit rates do not risk adjust due to the put, the bank can invest in a greater number of projects with apparent positive NPVs due to low cost deposits. Some of these projects would have a negative NPV if the deposit interest rate adjusted for the riskiness of the project and the bank. The market, however will risk adjust the rate and treat some apparent positive NPV projects as negative NPV projects and decrease the value of the publicly trade stock of the bank.

Deposit insurance fools management, not depositors, as to their available investment projects.

The deposit insurance will have little or no value to the depositor as long as the market value of the assets of the bank is greater than the value of the deposits. The put option will be out of the money. As the market value of the assets declines, due to bad investments, and no longer covers the amount of the deposits, the put option (the FDIC insurance) becomes in the money and increases substantially in value.

Since the bank transfers its assets to the FDIC for the insurance (put) payment of the deposits to the depositors, the FDIC bears all the risk and monetary loss. The FDIC insurance is only paid when deposits exceeds assets. The FDIC pays the full amount of the deposits and loses the excess amount of the deposits over the value of the assets it receives, deposits minus assets.

The essential transparency that is lacking is the value of the FDIC insurance put by institution. However, the publicly traded equity of the bank reflects both the true NPV of the projects on a risk-adjusted cost of financing and reflects the decrease value of the bank due to the value of the put due to the probability of the exercise of the FDIC put and takeover of the bank by the FDIC.

In effect, tax deductions do not increase leverage because it will increase the cost of borrowing and are probability probably completely offset by the tax on interest income.

Deposit insurance allows banks to invest in otherwise negative risk adjusted NPV projects. While deposit insurance allows banks to invest in unprofitable and negative NPV endeavors, the market price of the asset will be independent of deposit costs or deposit insurance. This is the liquidity funding problem. Banks can have enough funds to invest in a positive NPV valued asset that does not have enough market value to roll over as collateral to fund the asset.

Long-term rates are just the (geometric) average of expected short term rates except for the short-term liquidity premium, and banks will on average just make a small liquidity premium spread. Since long-term rates are just expected averages of short-term rates, half the time the short-term rates will be less then the long-term rates and half the time more than the long-term rate [after adjusting for the short-term liquidity premium]. Half the time, the bank will have a positive interest rate spread and half the time it will have a negative interest rate spread.

The New Health Care Law Until The Reconciliation Bill Passes

HR 3590, "The Patient Protection and Affordable Care Act" will be the law of the land and the current version of health care law when signed by the President as expected on Tuesday.

The House also passed a subsequent Reconciliation Bill, HR 4872, "Reconciliation Act of 2010" to amend the health care bill they just passed.

The Reconciliation Bill requires a Senate vote to become law and will not become an amendment to the new health care law until the Senate and the House pass, and the President signs, the same reconciliation amendment.

CBO Scoring Convention Assumes GDP Unchanged By Health Care Reform And Other Laws

When they [CBO] estimate the budget impact of a bill like this [Health Care and Education Affordability Reconciliation Act of 2010], they assume the path of GDP is unchanged....it is just one of the conventions of budget scoring.

From Greg Mankiw's Blog, "A Warning about CBO Scoring."

Did A M3 Decline Blindside The Fed And Cause The Economic Crisis

wondering how M3 has behaved compared to M2 or M1 during this crisis. Based on [Gary] Gorton's discussion it would seem that M3 would better reveal the impact of the crisis.

From "The Correct Money Supply Measure for This Crisis" by David Beckworth on the Macro and Other Market Musings blog.

FYI: Money Supply Definitions from Wikipedia:

• M3: M2 + all other CDs (large time deposits, institutional money market mutual fund balances), deposits of eurodollars and repurchase agreements.
  
• M2: M1 + most savings accounts, money market accounts, retail money market mutual funds,and small denomination time deposits (certificates of deposit of under $100,000).
  
• M1: The total of all physical currency part of bank reserves + the amount in demand accounts ("checking" or "current" accounts).

Gary Gorton's paper mentioned by Beckworth with thanks to Mark Thoma is well worth a read. It is an excellent explanation of the mechanism that turned a housing crisis into a banking crisis and an economic recession. The upshot is that the Fed was not watching the repo market as it collapsed and failed to take timely corrective action to replenish this loss of liquidity.

[Addendum: regulation2point0 blog mentioned Gorton's paper on March 6, 11 days before Thoma.]

Large And Small Financial Bubbles Are Similar

Statistically speaking, size doesn’t matter when a financial bubble bursts.

The big crashes may hurt a lot more, but new analyses of “microbubbles” presented March 15 at a meeting of the American Physical Society find that the same mathematical laws underlying massive economic crises are also at work in tiny fluctuations that occur on the order of milliseconds.

The new understanding of economic fluctuations both big and small doesn’t predict when the next economic meltdown will wreak havoc on retirement accounts, said study coauthor H. Eugene Stanley of Boston University. But the results help describe complex financial fluctuations and reinforce the idea that governments ought to have a contingency plan in place for the calamitous collapses that his research describes as inevitable, Stanley said.

From "Big or small, financial bubbles burst alike: Even when they inflate and collapse in milliseconds, the same rules" apply By Laura Sanders in ScienceNews. [Article link updated.]

Intrade Obamacare Security Collapses Overnight: Loses 50% Value

The Intrade prediction market security that tracks Obamacare lost 50 percent of its value overnight as Bloomberg reported "Health-Care Bill Faces Delay as Democrats Struggle With CBO."

The contract closed on Tuesday at 70.3 and last traded this morning as of 3 AM ET at 35.1.

The security terms require 'Obamacare' health care reform to become law before midnight ET 30 Jun 2010.

Users Rationally Reject Security Advice

It is often suggested that users are hopelessly lazy and unmotivated on security questions. They chose weak passwords, ignore security warnings, and are oblivious to certificates errors. We argue that users' rejection of the security advice they receive is entirely rational from an economic perspective. The advice offers to shield them from the direct costs of attacks, but burdens them with far greater indirect costs in the form of effort. Looking at various examples of security advice we find that the advice is complex and growing, but the benefit is largely speculative or moot.

From "So Long, And No Thanks for the Externalities: The Rational Rejection of Security Advice by Users" by Cormac Herley, Microsoft Research. (HT:Slashdot)

Madoff Is A Case Of SEC Dysfunction

Below is a comment I posted on "Regulators are from Mars, Investors are from Venus?" by Lisa Fairfax on the Conglomerate Blog.

Madoff is a case of SEC dysfunction.

Madoff's crime is a simple form of affinity fraud. A gullible group with some cohesion, similarities and member trust is targeted, such as church groups, religious groups, ethnic groups, immigrant groups, country club members, etc. The fraudster relies on members of the group to introduce other members to the fraud. The referral and implicit trust among members of the group makes the job of the fraudster easier than if he targeted strangers.

The SEC has prosecuted affinity frauds for years. Yet, it does not ask questions during an exam to determine if the investors have any commonality that would suggest the possibility of an affinity fraud. A simple question such as how did you find the investor would have indicated to the SEC that most of Madoff's investors were referrals from a few small social circles and indicated the extremely high likelihood of affinity fraud.

Similarly, standard audit procedures include selectively confirming transactions with third parties, such as vendors, banks, customers, etc. Only in the last year, after Madoff, has the SEC adopted these well-established audit procedures. A true audit process would have found that the assets did not exist. The SEC at the time of Madoff's fraud did not even have standards for outside audit firms or standards to determine if there were possibilities of conflict and collusion between the auditors and the firms.

Furthermore, Madoff's reported long run of positive returns to investors should have been a signal to the SEC. The returns were too good to be true and unlike the returns of other investment managers. Several banks and brokerage firms did not do business with Madoff because his returns were suspicious. Why is the SEC isolated from the information available to other investment firms on the street?

We have an SEC that does not incorporate its own knowledge of fraud into its examinations, does not use standard business practices and audit procedures and has isolated itself from common industry knowledge. It is not due to a lack of staff or funding. It is an SEC internal cultural problem. The SEC had enough funds to investigate and examine Madoff. The SEC did a poor job and did not find any problems.

The Madoff case shows that the SEC is ill prepared to protect investors. The Commission needs to develop heuristics based on its history with investor fraud and act more wisely with the funds and tools it has. It needs to improve communication between itself and firms on the street. It needs to rid itself of most of its lawyers and remove the adversarial process that is part and parcel of its culture.

If one actually reviewed the SEC's ability to prevent investor fraud since its founding, I think one would probably find that the SEC does a poor job of preventing investor fraud.

GDP Bond Addition To My February 18 Post "Limits Of Econometric Models ..."

The following is an addendum to my February 18, 2010 post, "Limits Of Econometric Models Of The Macro-Economy". It is reprint of a comment I wrote in early 2009 about using GDP bonds to reveal investor expectations of future US GDP growth.

Why not try a different approach to forecast the economy directly based on rational expectations and the securities markets. Along the lines of TIPS securities, the US Treasury (at the insistence and lobbying of economists) could issue securities whose prices are transparently dependent on future GDP. Different, acceptable forms of securities based on future GDP are possible.

One form could be a US Treasury bond that had a semi-annual interest payment that was a single, fixed percentage (determined at issuance time by a Treasury auction process) of published US nominal GDPs (nominal since cash flows are discounted by nominal interest rates) at the time of the scheduled semi-annual interest payments. Issuance of securities with differing maturities and with the aging of seasoned securities would allow computation of a GDP forward rate yield curve and computation of expected future real GDP growth for different periods. Of course, some might want to make corrections for tax effects, risk premiums, and other possibly distorting and biasing effects.

Another possible form of the security could be a discounted single principal payment at maturity bond that paid a fixed percentage (also determined at issuance through an auction) of US published GDP at time of maturity. Obviously, this percentage would be cumulative for the missed interest payments during the life of the bond, similar to principal only US Treasuries.

Whatever final forms this type of security took, as long as it is transparently dependent on future GDP, it would allow the computation of future real GDP expectations for different future periods. Additionally, other securities based on different macro-economic values can be developed.

A GDP security would also allow for event studies of the US economy and for studies of real time price movements due to government, geo-political, Fed and other actions. The volatility of these securities' prices will reflect a measure of the uncertainty of future GDP growth faced by businesses and others that must make decisions in anticipation of future economic growth. The securities could be used to determine a risk premium of the US economy and to see if it is time varying. It would also allow event studies of the effects of governmental actions on different future period GDPs.

Businesses could use options, futures and other derivatives on these securities to cheaply hedge against future GDP slowdowns and downturns. For example, while the auto industry, and other manufacturing industries, can hedge many raw material and commodity input costs, the new security would allow for a hedge for an unexpected economic slowdown that would cause an excessive inventory buildup.

Therefore, if macro-economic modeling has shortcomings, possibly some of them can be overcome by the use of the expectations embedded in a GDP dependent US bond. Of course, the assistance of the US Treasury Department in issuing a bond of this type is essential.

The above is a reprint of a comment I originally published over a year ago, February 13, 2009, on "Why Macro-Econometric Models Don't Work" on the EclectEcon blog.

Full Lehman Bankruptcy Examiner Report Publicly Available

The law firm of Jenner & Block is providing links to the 2200 page Lehman bankruptcy examiner report in nine PDF parts. The chairman of Jenner & Block, Anton R. Valukas, is the Examiner.

The Lehman Examiner's report is available here.

Scientists, Social Scientists, Economists Do Not Understand Statistics

Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.”

****

“Replication is vital,” says statistician Juliet Shaffer, a lecturer emeritus at the University of California, Berkeley. And in medicine, she says, the need for replication is widely recognized. “But in the social sciences and behavioral sciences, replication is not common,” she noted in San Diego in February at the annual meeting of the American Association for the Advancement of Science. “This is a sad situation.”

From the excellent article, "Odds are, it's wrong: Science fails to face the shortcomings of statistics" by Tom Siegfried, ScienceNews, March 27th, 2010; Vol.177 #7 (p. 26).

Also see my previous blog, "Limits Of Econometric Models Of The Macro-Economy."

Why New Drug Prices Are So High

Recently, Pfizer abandoned the development of a new drug after spending a billion dollars. Finding new drugs and navigating the FDA regulatory process is a risky endeavor. As Pfizer and other drug companies know, there are few successes, many failures and the cost of searching for and finding effective new medicines is high.

Despite the high costs of developing new drugs, the actual production cost of an effective and approved drug can be low. Companies that make generic versions of useful drugs can take advantage of low production costs and sell the medicines at a reduced price, once the original patents lapse. These generic drug companies do not have to recoup the funds they paid for finding, developing, proving effectiveness and marketing. They know the chemical formulas for the approved medicines, which work and have a market.

Let's make up an example to see how a generic drug company can sell a drug for a significantly lower price than a developing drug company can.

Let's say only 1 in 10 drug prospects is effective, gets regulatory approval and has a consumer market. If pharmaceutical companies spend a billion dollars on each of these prospective drugs, for each $1 billion spent on a successful drug, they spend $9 billion on unsuccessful drug efforts.

To attract funds to invest in new drug research, companies and investors expect a fair return for their money. Companies however do not know beforehand which drugs will be successful and which will be failures, which will pay them a return and which will lead to investment losses.

Let's say for this example a realized 5 percent return on the invested funds is a fair return. Since there is only a 1 in 10 chance of a successful drug and getting the fair return, an investor in all the drugs would like to see a 50 percent expected return from each project. Since there is a 1 in 10 chance of success, a 50 percent expected return from a project is a 5 percent expected value.

For a $1 billion investment, the investor wants a return of $50,000,000 but to get that $50,000,000 return, on average, $10,000,000,000 is invested. The $10,000,000,000 must have an expected 5 percent fair return and profit of $500,000,000. Only 1 in the 10 investments will succeed and the successful $1 billion investment must pay $500,000,000 to have a fair 5 percent return on the total $10 billion invested, which is a 50 percent return on the one successful drug's investment of $1 billion.

Suppose, a generic company can sell a drug to make a 5 percent return, but a research and development drug company must make a 50 percent return. The research drug company must make a profit that is ten times the amount of the generic company.

Let's say a generic drug company can make a pill for 60 cents and sells it at 70 cents (10 cents profit) to make a fair after tax profit. The developing drug company must sell the same drug at $1.60 to make a fair return ($1.00 profit).

When politicians and consumers look at a drug's selling price and costs, they look at only that drug's production costs and investments. They only look at the successful drugs in the marketplace. They ignore all the false starts and costs associated with those failed efforts. To stay in business and attract new investment funds, a pharmaceutical company must be able to recoup its lost funds on unsuccessful efforts in the profit it makes on successful drugs.

New drugs are expensive and cost more than the later generic version because the cost of finding and proving the effectiveness of new medicines is high. The generic drug companies do not bear the cost of finding new medicines and can set drug prices based solely on production costs, which are a small part of the cost of most drugs.

The price of a new drug represents more than the cost of its development and production. It also represents a fair return on all the funds invested, including the investments on the failures without which the drug company could not find and bring to market successful medicines.

Capital Is The Fool's Gold Of Banking

Is capital important for the health and safety of the banking industry? Was a shortage of capital the reason there was a financial crisis and would higher capital levels prevent another crisis? Wasn't liquidity the real cause of the recent banking problems?

One of the proposed solutions to prevent another banking industry crisis is to require banks to hold more capital. However, the banks that needed bailing out or failed in the recent crisis all satisfied the existing capital requirements. Capital is just a naive and confused patent medicine approach to a complex problem.

Bear Stearns and Lehman failed because they had a liquidity crunch and Citibank needed government help because it was experiencing a run on the bank, a liquidity shortfall.

Capital is a balance sheet approach to bank supervision and control. It is a regulatory concept computed by a regulatory formula. It does not represent the residual liquidation value of the bank after its debts are paid. It does not represent the bank's net worth, the accounting or market value of the bank's assets less its liabilities. It does not represent the future earnings capacity of the financial institution. It does not measure the liquidity health of a financial institution.

Regulators establish guidelines for bank capital levels and monitor the capital levels of banks. Governments, and their agencies, such as the banking industry regulators, cannot act arbitrarily. Capital levels are the way that the government banking regulators justify their actions. When capital levels are threatened or below regulatory requirements, federal banking supervisors act to preserve deposits, and the deposit insurance fund. They close banks, merge unhealthy banks with healthy banks, or put banks under protective orders with restrictive requirements. They act with a consistent, predefined purpose and as such are not easily subject to judicial review to overturn the regulators' actions and interventions. Capital levels are just trigger points that allow the government to act in a consistent manner.

Suggested proposals to prevent another crisis are mere refinements to the current capital requirements. The arguments for change are that the risk adjustments were inadequate, incentives were wrong; the levels were too low, or inconsistent, etc. However, any set of capital rules will not cover all situations, will create a new set of economic incentives and will always be too low for some catastrophe, just as a dike cannot restrain all levels of water.

Often a banking crisis is a liquidity crisis. Customers notice bank problems when banks are having a liquidity problem, a run on a bank, because the bank does not have the funds to pay depositors' withdrawals or the funds to make loans.

Regulators like high capital amounts because it allows them to delay classifying a bank as a troubled bank and delay government intervention. It does not guarantee an improvement in the deposit insurance fund or a positive net worth at a bank. It does not measure or help a bank's liquidity needs.

Capital does nothing to prevent liquidity problems at banks. When a bank is experiencing a shortfall of funds, the institution must borrow funds to pay depositors, and fund new loans and meet daily cash needs. To borrow funds, a bank must often put up collateral, assets it has on its books. Usually, the liquidity lender to a bank wants the collateral amount, in market value, to exceed the amount of funds lent. Bear Stearns failed because as it needed more liquidity, the value of its collateral was decreasing due to the declining value of real estate and the increasing default rates on mortgage loans. Some of its mortgage backed securities it was using as collateral declined in value by as much as 70 percent. Eventually, Bear ran out of collateral and could not fund it daily operational needs.

Capital is nice to talk about because the regulators find it easy to measure, not subject to dispute or interpretation under the regulations and consistently applied to all banks. It is easy to explain when a bank is above or below required capital levels and requires government involvement.

Liquidity is a much more difficult concept to use because the liquidity needs of each bank are different and can vary within an individual bank over a short time. It is more difficult to monitor, more difficult for the public to see when a bank is short of funds and more difficult to explain to politicians and the general press. Furthermore, publicly disclosing a liquidity shortfall at one bank can create a panic and run on another bank. Using liquidity as a guideline for bank troubles can cause a broader financial problem and make it much more difficult for regulators to contain a problem to a sole bank.

The contagion in the recent crisis was, in effect, a run on the banks. Everyone feared that the financial institutions were running out of liquid assets and that the collateral was declining in value in excess of the liquidity needs of the institutions. There was a wide spread fear that the banks did not have enough cash for their daily operational needs.

Capital is easy to understand and for regulators to measure. It is a convenient and acceptable trigger for regulatory intervention. Capital, however, does little to minimize future banking problems. It does nothing to promote the best practices for preventing future banking crises. Capital does not promote good banking, which must include asset diversification, sound business strategies and decisions, quality management, expense control and strong, sustainable earnings.

Reform, instead of focusing on capital levels, should instead focus on promoting sound banking practices as previously mentioned. Best business practices are the best way to prevent another crisis. Raising capital requirements by itself does not promote best practices. It just makes the regulators feels happy and allows them to offer patent medicine to those in search of a tonic.

Capital is a fool's gold that has little value, if any, in a severe financial crisis. The real gold is asset diversification, sound business strategies and decisions, quality management, expense control and strong, sustainable earnings.

More Funding And Staffing At The SEC Will Not Reduce Fraud

The following is a comment I posted on the Conglomerate Blog, "Funding the SEC: Dependent on the Kindness of the Regulated?" by Erik Gerding.

What indications are there that more funding and staffing at the SEC will reduce fraud? The failure to stop Madoff was not due to a shortage of staff or inadequate funding. Dysfunction at the SEC is the core issue. For example, the IRS has statistical profiles of IRS returns to identify likely tax evaders. In all its existence, the SEC has failed to develop a manageable, efficient system to identify fraud at the corporate level, at the investment level, or to evaluate the likelihood that an investor complaint to the SEC is true.

SEC staff investigated Madoff and fundamental procedures that have been in existence in auditing for decades, such as verifying payments, receipts and funds at other institutions, were not part of SEC investigations until after Madoff.

Madoff is a form of affinity fraud, which is a type of fraud the SEC has known about for years. It is based on investor commonalities to form referrals based on unfounded trust. Immigration groups based on country of origin, religious groups, country club membership, etc and other forms of referrals allow affinity fraud to succeed. Does the SEC even attempt to determine if the investors are part of an affinity group that would alert the SEC that there is a high likelihood of affinity fraud? It did not at Madoff. Does anyone remember ever seeing an ad or other outreach informing the public of this kind of fraud? The SEC has a 2009 pamphlet (after Madoff) and a 2006 press release, but what is the best preventative measure at the investor level and at the SEC to limit affinity fraud?

Option backdating was discovered because a professor published a statistical study showing its likely existence. Shouldn't a SEC priority be finding and funding research in important areas of potential fraud to help it efficiently identify corporate fraud? More staff would not have found backdating.

The SEC today is like a ship lost at sea that keeps asking for more stargazers to help identify its position instead of asking for a GPS navigation system. It is a 1930s organization with a 1930s culture that does not know how to function in the modern world. It is heavily staffed with lawyers whose culture is to avenge a fraud instead of prevent a fraud.

More money and staff are not the answer. A complete rethinking and restructuring is in order.

Furthermore, contractual legal rights are a powerful mechanism for protecting the rights of parties to commercial transactions. In fact, most transactions are based on contractual protections as opposed to regulatory protections. Shareholders and other interested private parties, and not the SEC, often sue to enforce their legal rights in securities transactions, when courts have recognized their right to sue to protect themselves.

While the counterfactual of life without 75 years of an SEC is difficult to envision, the existence of the SEC did not prevent major securities and investor fraud. Additionally, the SEC is always requesting more funding and staffing to investigate and litigate fraud. It is unclear that the 33 and 34 Acts have decreased fraudulent activities.

Forget CSI: DNA Matching Putting The Innocent In Jail

...increasingly DNA is being used for a new purpose: to target the culprits in cold cases, where other investigative options have been exhausted. All told, U.S. law enforcement agencies have conducted more than 100,000 so-called cold-hit investigations using the federal DNA database and its state-level counterparts, which hold upward of 7.6 million offender profiles. In these instances, where the DNA is often incomplete or degraded and there are few other clues to go on, the reliability of DNA evidence plummets—a fact that jurors weighing such cases are almost never told. As a result, DNA, a tool renowned for exonerating the innocent, may actually be putting a growing number of them behind bars.

***

When analyzing DNA, scientists ideally focus on thirteen markers, known as loci. The odds of finding two people who share all thirteen is roughly on par with those of being hit by an asteroid—about one in a quadrillion in many cases. But the fewer the markers, the higher the probability that more than one person will match the same profile, since relatives often share a number of markers and even perfect strangers usually share two or three.

***

In 2006, for instance, a Chicago judge ordered a search of the Illinois database, which contained 233,000 profiles. It turned up 903 pairs with nine or more matching DNA markers. Among geneticists and statisticians, these findings have eroded faith in the FBI’s DNA rarity statistics, which were based on data from just 200 or 300 people and are used by crime labs across the country.

From "DNA’s Dirty Little Secret: A forensic tool renowned for exonerating the innocent may actually be putting them in prison" by Michael Bobelian in Washington Monthly.

Reconciling Lower Doctor Pay With Rising Health Care Costs

As reported on Bloomberg, "Doctors’ Hours Fall for a Decade, Adding to a U.S. Shortage" by Pat Wechsler:

Feb. 23 (Bloomberg) -- Work hours for U.S. doctors dropped steadily for more than a decade, mirroring a decline in inflation-adjusted fees and worsening a nationwide physician shortage, a study said.

Doctors’ hours per week fell to an average of 51 in 2008 from 55 in 1996, after two decades of being almost unchanged, according to research published today in the Journal of the American Medical Association. The report showed the slide was linked to a falloff in fees paid to physicians. The charges declined 25 percent after inflation from 1995 to 2006, according to an index measure of fees going to doctors.

Physicians are working less and are being paid less. Health insurance companies and hospitals are not making exorbitant amounts of money. For example, see Mark Perry's Carpe Diem blog, "Profit Margin: Health Insurance Industry Ranks #86."

Health costs have been growing faster than the US economy and faster than inflation. If not from doctors and hospitals, where are the costs increases in medical care coming from? It is highly unlikely, the pharmaceutical industry can account for the enormous growth in health care spending.

As more of the costs of health care are shifted from our out of pocket costs to health insurance, it makes sense the cost of health insurance will rise. The problem is discovering why the costs of total medical care have also risen so much faster than the economy and inflation.

Is it simply just a change in consumer preference? Do we just use more medical services, which include doctors, nurses, medical and lab technicians, medical equipment, lab tests, drugs, etc., but no one cost item is overpriced. Do doctors make less because we are spending more on medical services other than physicians?

The open question is how much of the shift in consumer preferences for more medical services are related to the reduction in the consumers' out of pocket expense? If the shift is due to third party payers than the answer to controlling our medical spending is to shift more of the costs sharing to the consumer. It can be accomplished by removing the tax deduction for employer health care benefit and by shifting Medicare and Medicaid more towards a voucher system similar to food stamps with a backstop for catastrophic illness and injury.

If third party payers do not exaggerate the shift to more medical care, than there is not any reason to control our medical costs. The issue then becomes government affordability of government programs and vouchers probably could best control government medical costs. Under a voucher system, the government's yearly costs are limited but individuals are free to seek as much health care as they wish.

It is obvious, that we are seeking to "fix" our medical system and reduce health care costs without a clear understanding of the drivers of health care spending. Without detailed knowledge of the problem, it is highly likely any "fix" will create more problems than solutions.

Making Health Care Worse

Despite the rampant inefficiencies and extremely high costs of health care in the United States, it is still possible to make the American health care system even more inefficient and more costly. Regrettably, the health care bills passed by the House and Senate would do precisely that by saddling an already burdened system with more mandates, higher taxes, and less flexibility.

From the comprehensive Wall Street Journal article, "Bending the Curve": What Really Drives Health Care Spending" by Jason Fodeman, M.D. and Robert A. Book, Ph.D.

Limits Of Econometric Models Of The Macro-Economy

The following is a comment I posted On Econlog, "Macroeconometrics and Science" by Arnold Kling about the limits of econometric models of the macro-economy.

There is also the "Lucas Critique". Lucas said that economic models derived from historical data could not be used to recommend effective changes to government policies because the past relationships in the data are dependent on the effects of policies in place at the time of the data. Predictions based on past data will miss the effects of new policies and produce incorrect predictions unless the relationships in the model are calibrated for the new policy. One needs to build a model where the internal relationships (coefficients) vary depending upon policy recommendations. It requires an understanding (or at least an assumption) on how policy affects economic outcomes. It can become a tautology. The model predicts what it is set to predict. If a model is calibrated to predict that policies A, B and C will move the economy to long term trend, then a recommendation to use policies A, B and C will show in the model that the economy is moving towards its long term trend. The model will become the basis for a recommendation that was assumed as part of the model in building the model.

Additionally, when models are not validated against out of sample data, there is the problem of data mining and spurious results. When a 100 economists run a 100 different, independent models on historical data looking for economic and theoretical explanatory relationships, even at a 90 percent statistical significance level, there will result 1000 (100x100x.1), different models that meet model acceptance criteria.

Out of sample data tests would drastically reduce the number of acceptable models from 1000 to a much lower amount. Those that survive may again be spurious, because at the 90 percent significance level, the probability is that 100 out of the 1000 will survive and look meaningful. These 100 models exist based on luck without any need for there to be any economic meaning to their internal relationships. They can even be inconsistent with each other and known economic theories.

Economists then derive explanations to match the model results instead of vice versa. Data mining and spurious models can lead to inconsistent policy recommendations among economists.

It is like a gambler's hot streak at the roulette table, where the bettor develops superstitions about why he is winning, such as color of his shirt, etc. Economic policies based on the surviving models are equivalent to a gambler's idiosyncratic behavior that he thinks changes the odds at the roulette table and enables him to win. Each gambler has a different reason for the winning streak. Like different schools of economists.

The scientific method is based on the concepts of hypothesis testing against data and reproducible results. Model building is the reverse. The data is used to derive the hypothesis and it is not tested against new data (out of sample) to see if it is reproducible.

Both the Ptolemy (Earth centric) and Copernican (Sun centric) views of planetary motion were internally consistent with the data on planetary motion known at the time. Both were accurate in predicting future planetary position (actually, Ptolemy's method, revolving around the Earth, initially was more accurate than the Copernican method).

However, it is extremely unlikely that Sir Isaac Newton could have developed his theory of gravity under the Ptolemy system. Newton's gravity requires rotation around the larger mass body, the Sun, and not the Earth. While an equivalent gravitational system could probably have been mathematically built in a Ptolemy system, it would not be as simple to comprehend or visualize as the Newtonian system.

Expectation theory is in many ways equivalent to Copernican theory, but that is another long and controversial discussion. Suffice it to say, many economic models are inconsistent with expectation theory.

The above is a comment I posted On Econlog, "Macroeconometrics and Science" by Arnold Kling.

[See my March 16, 2010 addendum post: "GDP Bond Addition To My February 18 Post 'Limits Of Econometric Models ...'"]

States Short $1 Trillion For Public Employee Retiree Benefits

State governments face a trillion-dollar gap between the pension, health-care and other retirement benefits promised to public employees and the money set aside to pay for them, according to a new report from the Pew Center on the States.

From "States Sink in Benefits Hole" by Amy Merrick in The Wall St. Journal.

The Multiple Solvency Goals Of Regulatory Reform

Everyone most likely agrees that the proposals for regulatory reform of the banking industry are attempts to lower the insolvency risk of financial institutions. The various regulatory reform mechanisms place prohibitions on bank activities and assets, increase a bank's required capital, or increase regulatory powers and oversight of the banks.

Solvency (Insolvency) is a single word with several meanings, but each definition requires different protective measures to protect solvency and prevent insolvency. The individual connotations are often unidentified in proposals or discussions and much of the debate about banking reform is really confusion over which form of insolvency the new rules are trying to avoid. Discussions of the ineffectiveness of a proposal often result from confusion over which form of solvency the rule is protecting as much as it is about the effectiveness of the proposal.

A sensible banking reform package first requires clear articulation of its goals and a determination that the industry modifications will achieve their desired results of protecting the banking institutions and the payment system from the many forms of insolvency.

To help with the process, I am republishing some definitions of insolvency that I first blogged about, "Understanding The Different Meanings Of Insolvency" from almost a year ago.

Solvency can take various forms:

Regulatory

There is regulatory solvency, which wants banks to have adequate and sufficient capital to meet regulatory and legal solvency tests. These tests determine if there will be a regulatory takeover or shutdown of the institution. When one speaks of too big to fail, one generally means that an institution failed the regulatory solvency test, but the regulators are too timid to take it over or shut it down.

Net Worth

There is GAAP (Generally Accepted Accounting Principals) positive net worth, which requires banks to have a positive net worth, more assets than liabilities, on their accounting statements, using the appropriate applicable accounting rules even if they require market value or other measures of the accounting value of the assets and liabilities on the bank's balance sheet.

Economic Value

There is the positive economic value of the bank as an operating entity, which requires an assessment that the bank will be able to pay back its debt and replace its capital if regulators allow it to continue to stay in business, despite its failure to meet other solvency tests.

Liquidation Value

There is positive liquidation value, which looks for a positive value after liquidation of the bank at today's market prices. Personally, I believe that most of the media and the public mistakenly believe that regulatory solvency and capital is equivalent to having positive liquidation value. It is not in most cases. In many cases, due to high leverage and due to many balance sheet assets not valued at current market prices, a bank's liquidation will fail to produce enough value from the assets to payoff the liabilities.

Liquidity

Finally, there is liquidity, which attempts to insure that bank has sufficient cash for its daily operation by holding cash, readily marketable securities and other assets that can easily become cash without a significant loss of value. Many banking crises begin as liquidity crises because as an institution starts to face operating difficulties other institutions are reluctant to lend it money or do business with it without additional assurances, such as more collateral.

Each of these five definitions of solvency behaves differently under different economic scenarios, risk taking and market conditions. Specific regulatory mechanisms to protect each form of solvency are therefore different. A scheme to protect one form of solvency is often inadequate by itself to protect another. Additionally, some schemes may overprotect and unnecessarily burden another form of solvency.

The ultimate goal is to protect the financial institutions and therefore regulatory proposals for reform need to deal with each type of insolvency. To guard each form of solvency, there will be overlapping requirements, over protection of some forms of solvency and unnecessary rules to shield against other forms of insolvency. A perfect regulatory reform package will prevent all forms of potential insolvency. In the end, an excellent regulatory reform package will significantly lower the insolvency risks in the banking industry.