Why we have the Affordable Care Act  (ACA)

Insurance or the pooling of risk should shield people from the financial risk of disease.  Unlike, other types of insurance, the healthcare marketplace has some unique problems including moral hazard and adverse selection.    With  asymmetric information, healthy people tend to round their low risk estimation to zero and drop out of the insured pool, which raises the average cost to insure everyone left to a level above that which low risk people will pay.   On the other hand, when insurance companies assess applicant risk and underwrite in order to price profitably, 1 in 7 applicants prior to the ACA were  rejected for individual health insurance. 

 Like electricity, phone, and cable markets the healthcare marketplace is not competitive but consist of local monopolies.   Other problems include that people can not assess their utility (probability of loss times the amount) , they aren’t aware of taxes, and that the interest of future generations is not reflected in the market.

Most people get insurance from their employer sine the insurance benefit is not taxed and employers generally have a healthier risk pool.  Most large companies self -insure their risk.   The risk is that employees who get sick loose their jobs and then their insurance. 

One original health insurance model was that insurance companies would offer pairs of insurance policies.  The healthy would buy the less expensive and less generous plan, which the sick would avoid.  That is how the market would segment.   Experience showed many comprehensive plans were not profitable due to adverse selection.  

If the average cost is higher than the demand curve the market brakes down

The ACA has been implemented and there is a lot of complaining by some.  So why do we have this.  It was the reaction to a problem.  15% of us didn’t have healthcare insurance and 13% of us were underinsured.     Healthcare costs were increasing at an unsustainable rate and expected to grow to 35% of GDP.  

            In 1963, the economist Kenneth Arrow predicted medical insurance would increase the demand for medical care.   The Rand experiment and Oregon experiment showed that providing health insurance increases annual spending by 25%.   Rand showed people spend less up to their stop loss limit.  However the amount is 25% less than the  predicted amount because people foresee that at the end of the year their marginal cost of healthcare is zero.  High deductible plans often have a self-pay to $3000 and then the insurance pays.   

The provision of healthcare insurance increases moral hazard and the price and quantity used but the lack of healthcare insurance leads to under utilization and a lower quality of life.   Leaving Medicaid to the states leaves areas of third world healthcare access with third world healthcare outcomes in poor areas of the US. This contrasts with Rwanda which is able to provide a uniform level of basic healthcare throughout the country.

            The growth in healthcare spending led to to an increase in investment and development of new technology.   The demand increase was led by these improved technologies with their low cost to patients and the moral hazard of providers who are rewarded for their use.   Provider side moral hazard is demonstrated by the 15% drop in Medicare hospital length of stay with the introduction of DRG financing which paid a fixed amount for each hospital admission.  ACA does try to reduce cost buy encouraging Accountable Care Organizations, which would provide care at a fixed cost and by taxing luxury health plans. 

            Thus we have multiple problems including the rising cost of healthcare, unequal access and distribution and lack of social services which lowers US healthcare statistics to that of Cuba, and that without an individual mandate that makes everyone pay into the system people won’t buy healthcare insurance until they are ill.   The ACA is one improvement step but not the final answer.   

           

I recommend  Andrew W. Lo’s Mit Finance course on I tunes U. Lecture 19

Behavioral Finance :   Watch the one on efficient markets 2

Are markets efficient?  Buffett says clearly no. They are subject to animal spirits.    Market efficiency requires rationality which comes and goes in waves.  Behavioral finance says people suffer from loss aversion, overconfidence, overreaction, herding, and mental accounting.

Daniel Ellsberg,  most famous for releasing the Pentagon Papers in 1969 came up with the Ellsberg paradox.    People will pay less for a gamble with less clear odds.   When there is uncertainty about risk people shy away. We are hard wired to avoid things we don’t understand because these could kill you, to avoid hidden crocodiles.  That is why when markets get scary people shy away although the expected return is increased.

Frank Knight looked at why entrepreneurs are paid so much.  He decided that it is because they take on uncertainty and not just risk.   Uncertainty is the risk that no one can quantify e.g. Nanotechnology. 

Lastly, people tend to see only what they are looking for. 

Since people are unable to assess odds, they are susceptible to be Dutch Booked.

It is though that his provides a limit to irrationality.  Smart people will take advantage and the market will correct.   An example is arbitrage. 

Efficient market folks feel that market forces will force people to be rational if there are enough rational people around.

However Keynes said the market can stay irrational longer then you can stay solvent. 

Antonio Damasio, a neurosurgeon, wrote a book DescartesError in which he argued that rationality stems from emotion.   He describes a patient who had a brain tumor removed.  Although he tested normally in math or logic he was unable to function in the world and quickly lost his job.  After the surgery he had no emotion reactions as shown by eye blink tests.   You have to be able to feel to act rational.

This relates to the triune brain.    The reptile brain regulates heart rate and vital functions. The mammalian brain sits over this and it regulates fear, greed, love, and emotion.   The hominid brain or neocortex is responsible for language, math and logical deliberation.    Under the stress  of shock such as loss of blood the reptile brain shuts last.   People faint but keep breathing.   In fact you can be brain dead and continue breathing.  Of the remaining brains the hominid brain shuts down first when under stress.   Evolution favors running from thetiger.   Experiments have shown under stress or pain the neocortex does not resume normal function for hours after an insult.  Under stress, body shunts blood away from the cortex.   When stressed people cannot use the cortex and don’t think. 

That is why love makes you stupid.

Emotion is necessary for rationality but too much emotion impairs rationality.

Best advice:  Be clear about your goals.  Decide what you want to achieve and ask will my current actions help or hinder the objectives. 

Lo developed the Adaptive Market Hypothesis

He says that prices in the market reflect available information and the number of species in the economy.  Species means professionals, pension managers, hedge fund managers, and individual investors.    When people are stressed either positive or negative, they are not rational. 

This theory takes a biological view of markets.  We are both creatures of our rational brains and emotional brains.

Adaptive market theory properties are that:

Individuals act in their self-interest

They make mistakes

They learn and adapt

Competition drives adaptation and innovation

Natural selection shapes the market ecology

Evolution determines market dynamics

It takes negative feedback to cause us to learn and develop adaptive heuristics or thought process shortcuts . 

The implications of the Adaptive Market Hypothesis are that:

Risk reward is not stable because individual preferences are not stable

Risk premiums are time varying. 2007 is different from 2008

Limited arbitrage (free lunches) exist from time to time 

Strategies wax and wane

Adaptation and innovation are key to survival

Survival is all that matters

Market efficiency goes in cycles that depend on the population of investors that are interacting with each other.   These cycles can be anticipated and perhaps  some profit can be made.

Vegas -

I played some Slots.  Actually I put a dollar in the machine, bet a penny, and won $4.25.  At this point I quit and collected by $5.25 thinking my return could never be higher.  

The Gamblers Ruin problem goes back to the 1600s.   If 2 gamblers bet back and forth a dollar you can calculate the probability that one will go bankrupt.   I listened to Joe Blitzstein's lecture on this on his Harvard stats course at Itunes U

The important parameters are that gambler A has i amount of money and gambler B has N-i

The probability of A winning a round is p and of B winning is q which = 1 - p

If p = q, fair odds,   then the odds of A winning = i/N or what fraction of the wealth A has.

The Probability of A winning = 1-(q/p)^i/1-(q/p)^N with unfair odds. 

if p = .49 and i=N-i that is A and B have equal amounts of money.
then if N = 20   the chance of A winning is .4
           N =  100 the chance of  A winning is .12
           N = 200  the chance of  A winning is .02

In Las Vegas the casino has more money and games are more unfair

Since the probability of A winning + the probability of B winning is 1 there is no chance the game goes on forever.



In slots it is hard to figure out the odds of winning a hand as you can read below.

From Wikipedia
The return to player is not the only statistic that is of interest. The probabilities of every payout on the pay table is also critical. For example, consider a hypothetical slot machine with a dozen different values on the pay table. However, the probabilities of getting all the payouts are zero except the largest one. If the payout is 4,000 times the input amount, and it happens every 4,000 times on average, the return to player is exactly 100%, but the game would be dull to play. Also, most people would not win anything, and having entries on the paytable that have a return of zero would be deceptive. As these individual probabilities are closely guarded secrets, it is possible that the advertised machines with high return to player simply increase the probabilities of these jackpots. The casino could legally place machines of a similar style payout and advertise that some machines have 100% return to player. The added advantage is that these large jackpots increase the excitement of the other players.
The table of probabilities for a specific machine is called the Paytable and Reel Strips sheet, or PARS. The Wizard of Odds revealed the PARS for one commercial slot machine, an original International Gaming Technology Red White and Blue machine. This game, in its original form, is obsolete, so these specific probabilities do not apply. He only published the odds after a fan of his sent him some information provided on a slot machine that was posted on a machine in the Netherlands. The psychology of the machine design is quickly revealed. There are 13 possible payouts ranging from 1:1 to 2,400:1. The 1:1 payout comes every 8 plays. The 5:1 payout comes every 33 plays, whereas the 2:1 payout comes every 600 plays. Most players assume the likelihood increases proportionate to the payout. The one midsize payout that is designed to give the player a thrill is the 80:1 payout. It is programmed to occur an average of once every 219 plays. The 80:1 payout is high enough to create excitement, but not high enough that it makes it likely that the player will take his winnings and abandon the game. More than likely the player began the game with at least 80 times his bet (for instance there are 80 quarters in $20). In contrast the 150:1 payout occurs only on average of once every 6,241 plays. The highest payout of 2,400:1 occurs only on average of once every 64³=262,144 plays since the machine has 64 virtual stops. The player who continues to feed the machine is likely to have several midsize payouts, but unlikely to have a large payout. He quits after he is bored or has exhausted his bankroll.^[21]

The Value of Everything

The Federal Reserve calculates the value of Assets in the USA  (Table B – 100 )

Assets

Real-estate                 18   trillion

Pensions                     13   trillion

Family businesses      6.2 trillion

Deposits in banks      7.9 trillion

Corporate Equity       8.5 trillion

Mutual Funds                        4.7 trillion

Durables                    4.6 trillion

Treasury bonds         1   trillion

Corporate bonds       1.9 trillion

Life insurance            1.3 trillion

Other                          2 trillion

Total                           70 trillion

Liabilities

Mortgages                  10 trillion

Credit                                      2.5 trillion

Loans                          1.4 trillion

Total                           13 trillion

Net worth                  56 trillion

Federal debt              14 trillion

State debt                  3 trillion

Human Capital  = national income(gdp) / (int- growth rate) 

                               = 13 trillion / (.05/.03)

                               = 260 trillion

Conclusion -  Suzy Orman is right.  People should come first, money second. Increasing the value of human capital through education, a social safety net, healthcare, a higher minimum wage will increase wealth more than investing in things.

Stats in Risk   

Probabilities were invented in 1600s.  Kahneman showed that people round off their probabilities to: won’t happen, will happen, or maybe.  We are not good a judging how much insurance we need.  Robert Shiller points out that with stats we are like the cultures that count one, two, and, many.  They are able to remember hundreds of different plants but they do not count. 

In emergent theory outcomes are dependent on millions of little things, independent events, that accumulate.   Think of humans from DNA.

Unexpected events are often caused by a failure of the independence of these events.   For example changes in the stock market indices should be random since market changes are based on news, which is random and the indices cancel out individual stock risk.  Are stock returns independent variables?  They are until group think sets in. 

Fat tail events complicate this model.   In Finance, low probability shocks that shouldn’t happen occur.This is why geometric returns are more useful.  Outliers exist .  Random shocks to the economy are normally distributed. In nature the normal distribution is not the only distribution that occurs and some

other distributions have fatter tails.   -  Kurtosis

The Central limit theorem is probably the most important theory of statistics.  if you have independent identically distributed random variables and they have a finite variance  then the distribution of an average of these variables converges to a normal distribution as the number is increased.  The normal curve is so common because so many things we observe are averages of separate events.   Note that he normal distribution does not have fat tails.   This is why things work most of the time.

One reason that the normal distribution is so common because most events we observe are an average of independent events.   In a normal distribution the tails drop off.   It assumes the underlying variables have a finite variance. 

Other stat concepts include

Variance – is the sum of weighted probabilities of deviation from the mean

And standard deviation = square root of the variance

Covariance - how two different random variables move together?

 Can be positive, negative, or zero if unrelated

Correlation -  is scaled  -1  to +1

P = cov(x,y) /(s1,s2)

 

Low covariance is important in reducing risk.  We may not get expected return if the observations are not independent.

In the Law of large numbers, which is another stat concept– although there are a lot of independent shocks if they are independent, there is not much risk.   Variance goes to zero as n goes to infinity.   Insurance relies on this.

Value at Risk  VaR  was invented in 1987 to measure corporate risk.  Companies would calculate that there is a 5% probability   of loosing a million dollars.  It was found not to work well in 2008.

CoVar  was invented by  Brunnermier at Princeton.  It is  Value at risk of financial institutions conditional on other institutions being under distress.  This is supposed to be a newer more accurate model

Majority rule can be a good way to decide the better of two options.  Intrinsic justifications do not concern themselves with the quality of the decisions.  Voting outcomes can track truth if three conditions hold.  The voters are better choosers than random, are independent, and they vote sincerely.    One problem is that people  have preexisting cultural mindsets which determine how they look at information or even what new information they consider.   Only ten percent of people can explain what nano-technology is but 80% have an opinion on how safe it is.  Page argues that good decisions depend on sufficient cognitive diversity of the group or having people use different models to arrive at a solution.   A  smart diverse group of people is needed to get to the right answer.      

I am not sure how this ties to religion or even political parties, which encourage uniformity of thought.   Most people do not choose their political party or religion.  

 Shiller Finance Lecture

 wisdom of crowds

Scott Page wisdom of crowds

Eggspression APP

Our free App came out this week.  If you have an I Phone, try it

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Travels

More travels.  Went to Krakow and Prague.  In the 19th century most of the worlds Jews lived in this part of the world.  Now it is a museum.  My grandparents and father came to America from a small village near Gorlice, Poland.  There is a plaque in the town square in memory of the Jews who used to live there.   The town still looks similar to they way it was in the 1800s.   The land where his father had a farm is still farm country but there are no remnants of any Jewish community.   Countries change.  

  Wooden bridge near Owczary near Gorlice

Gorlice

Trip to a town near Owczary