Maxine Udall (girl economist)

A Technical Note on Empirical Modeling of Self-Chosen Behavior

The following is technical and possibly of interest only (and just barely) to those conducting applied economics research. You have been warned.

I have been thinking about the common support problem. Specifically, I’ve been thinking that economists conducting applied research on self-chosen behaviors or objectives do not pay enough attention to it. I have always suspected this, but two recent seminars I attended have caused me to be a bit more certain that my suspicions are correct. One seminar involved estimation of hospitals’ decisions to simultaneously acquire both diagnostic and therapeutic radiology technology. The other (which I have also written about here) involved estimation of individuals’ decisions about calorie consumption and optimal body mass index (BMI).

What is the common support problem? It arises in observational data where assignment to or participation in an intervention or program  is self-chosen (D=1 for those who choose assignment; D=0 for those who do not choose assignment). [1, 2, 3] When modeling self-chosen assignment or participation based on observed covariates (p(Di =1)|Xi), observations located in the central portion of the probability of assignment distribution are more likely to be “close” to each other in covariate space, regardless of their assignment status, i.e., to be similar to each other on observables. Those at the extremes of the assignment choice probability distribution (i.e., those observations with very high or very low probabilities of choosing assignment are often observed not to have counterparts with opposite assignment but with similar covariates. In extreme cases, there may be no overlap in covariate space between those who choose assignment and those who do not, i.e., they are very different on observables and therefore have no similar counterpart with the opposite assignment choice.  

Here are examples of a sample with and without common support. The box plots are of assignment propensity scores  (p(D=1|X) [4, 5, 6] stratified by observed assignment (D=1 or D=0).

Notice that the graph on the left indicates that for every observation with D=1 (on the X axis), there is likely to be a matching observation with similar covariates and similar propensity for assignment among those with D=0. In the graph on the right, there are no matching observations for D=0 or for D=1, i.e., no common support, no similarities on covariates, no positive probability of assignment for persons with similar covariates. 

There are two practical implications from the above. One is that when assignment is self-chosen, individuals at the extremes of the probability of assignment distribution may be very different (in terms of observables) from those whose covariates have positive probability of being in either assignment category. The second is that whatever is different about the observables of those at the extreme of the assignment distribution may predict assignment perfectly and therefore may be uninformative for the research question under consideration [7].

In empirical investigations using observed data from surveys, one usually observes some overlap in propensities for assignment (and covariates). The less overlap, the more reason for concern. This is because comparing outcomes when there is little or no common support in assignment is an important source of bias in observational studies [1].

Readers familiar with matching methods, including propensity score matching, may already know about this [1, 2, 3, 4, 5, 6]. Matching is frequently used to remove bias on observables from observational data when a number of rather stringent criteria are met, for example, that the data matrix is very rich in covariates that are relevant to assignment; pre-assignment outcomes can be conditioned on to partially control for selection on unobservables; the groups being compared are similar in regulatory, social and economic context (i.e., from similar geographic areas); and participants answer similar survey questions. [4, 5, 6, 8, 9, 10, 11]

What many readers may not be familiar with is the use of the propensity score as a diagnostic tool for gaining insight into potential sources of bias in observational data or data where self-selection is of interest and as a tool for removing the bias that results from failure of the common support assumption [2, 10, 12, 14]. 

In the two seminars I recently attended, both presenters seemed to have a sense that the extremes of the technology adoption distribution and the obesity distribution might be somehow qualitatively or behaviorally different from observations in the center of the those distributions.However, neither appeared to have investigated this empirically (other than some simple comparisons of selected covariates, like caloric intake or BMI preferences, between those with D=1 and D=0).

One advantage of the propensity score as a diagnostic tool is that it provides a mapping of all covariates to a single score. It may, therefore, pick up important differences on observables between those who choose assignment and those who do not that could not be detected by simply stratifying on or comparing means of variables believed to correlate with tech adoption or obesity and decisions about food consumption.

In the case of tech adoption, which was being modeled as a simultaneous decision that depended on the tech adoption decisions of other players in the market, one can easily imagine that the range of the propensity to adopt includes what can be thought of as “always takers” (high p(D=1|X)) ~ 1) and “never takers” (low p(D=1|X)) ~ 0) [12, p. 158]. Always adopters might be Stackleberg leaders or they may simply have objective functions that are very different from those of other hospitals in the area. For example, always takers could be large, high bed-count, tertiary care medical centers with affiliated medical schools, where the teaching objective and the need to attract and retain high quality faculty imposes minimum constraints on available technology.  Never takers may be small hospitals, which for historical or other reasons have tended not to acquire cutting edge technology that serves relatively small portions of total market patient mix. 

A simple diagnostic that might shed light on this would be to estimate the probability of joint adoption of diagnostic and therapeutic technology. Then simply compare box plots of the resulting propensity scores between those who adopt and those who don’t. If I’m right, the extremes will have few matches (overlaps in covariate space or propensity to adopt).  Then the issue for the researcher would be to investigate whether or not the presence in a market of what might be an always taker produces Stackleberg-like behavior among the other market players or are the always takers so different that they don’t really enter into the competitive decisions made by the remaining market players. Similarly, effort could be devoted to empirically investigating the lower extreme of the distribution to determine if they respond to the behavior of other firms in the market.  If the data support the conjectures that the two groups’ behaviors are relatively independent of market characteristics and other market players, then elimination of observations with no common support should result in a sample that would allow investigation of hospital behavior among the hospitals that are most likely to be making  the hypothesized trade offs about investment in new technologies given other market players’ adoption decisions at the margin.

In the case of the obese, I would expect that a similar diagnostic exercise might provide information that would allow the investigator to determine whether or not the very obese and the very overweight are very different in their covariates from individuals in the center of the obesity propensity distribution. As above, if they are, then the observations of policy interest may well be those who are more alike on covariates even though they differ in weight.  Restriction of the sample to those who may be amenable to policies aimed at reducing caloric intake or increasing energy output may yield results with greater policy relevance.

Please note that I am NOT recommending mindless adoption of a rule like “get rid of all the observations with no common support” (See [12, 13, 14] for more nuanced and intelligent approaches. I have nightmares that “enforcing common support” will become the next “p-values are all that matter” statistical lunacy.) Rather, I’m suggesting that the use of propensity scores as a diagnostic tool may offer important insights, may in certain circumstances result in a more correctly specified sample,  and may aid in conceptualizing the underlying behavioral structure from which the empirical model is derived.  

What little evidence there is seems to suggest that estimation of average treatment effects on the treated without correction for failure of common support is an important source of bias [1] or that it doesn’t matter very much in some cases and matters somewhat in others [12, p. 86-91, 13] or that it matters but in more nuanced ways [14]. I'm suggesting that even in the absence of interest in a treatment effect per se, determination of common support is an easy diagnostic that may help clarify the conceptualization of the underlying self-chosen behavior that is being modeled by economists. At a minimum, it may point to previously undetected behavioral heterogeneity when assignment is self-chosen, which could have implications for the hypothesized underlying structure and for the policy question of interest. Behavioral heterogeneity could also have implications for that darling of applied econometrics, instrumental variables regression [15].

IMHO, all of these would be good things for applied economists to think about more rigorously.

References

1. Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. Review of Economic Studies, 64: 605-54.

2. Heckman, J. J., Ichimura, H., Smith, J., & Todd, P. (1998). Characterizing selection bias using  experimental data. Econometrica, 66: 1017-1098.

3. Heckman, JJ, Smith, JA (1995) Assessing the Case for Social Experiments, J Econ Perspectives, 9(2): 85-110.

4. Rosenbaum, P. R. & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1): 41-55.

5. Rosenbaum, P. R. & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387): 516-24.

6. Rubin, D. B. (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology. 66(3):688-701.

7. Chamberlain, G. (1980), “Analysis of Covariance with Qualitative Data,” Review of Economic Statistics, 48, 225-238.

8. Dehejia, R. H. and Wahba, S. (1999) Causal Effects in Non-experimental Studies: Reevaluating the Evaluation of Training Programs. Journal of the American Statistics Association. 94(448): 1053-1062.

9. Smith, J, Todd, (2001) Reconciling conflicting evidence on the performance of propensity- score matching methods. Amer. Econ. Rev. 91: 112-118.

10. Dehejia, R. (2005) Practical propensity score matching: A reply to Smith and Todd. J. Econ. 125: 355-364.

11. Diaz, J.J., Handa, S. (2006) An assessment of propensity score matching as a nonexperimental impact estimator. J. Human Resour. 41: 319-345.

12. Angrist, JD, Pischke, J-S (2009) Mostly Harmless Econometrics: An Empiricist’s Companion, Princeton, NJ: Princeton University Press, pp. 69-94.

13. Crump, RK, Hotz, VJ, Imbens, GW, Mitnik, OA (2009) “Dealing with Limited Overlap in the Estimation of Average Treatment Effects. Biometrika, http://biomet.oxfordjournals.org/cgi/content/abstract/asn055v1

14. Lechner, Michael, A Note on the Common Support Problem in Applied Evaluation Studies (November 2000). Univ. of St. Gallen Economics, Disc. Paper 2001-01. Available at SSRN: http://ssrn.com/abstract=259239  or doi:10.2139/ssrn.259239

15. Heckman, J. J. (1997). Instrumental variables: A study of implicit behavioral assumptions underlying one widely used estimator for program evaluations. Journal of Human Resources. 32: 441-61

The Socrates Parameter

A few days ago, I attended a seminar on the economics of obesity and overeating that left me thinking, not about obesity and metabolic syndrome, which are epidemic in the US and important contributors to both national health care costs and declining national health indicators, and not about medicine’s inability at present to provide satisfactory preventive remedies. It left me thinking about the “split” between our presumably rational, self-interested, fully-informed or near fully-informed deliberative selves and our primitive, acquisitive, also self-interested (if a trifle myopic), less than rational selves.

The seminar speaker motivated his analysis of overeating and obesity by providing a nice, albeit simplistic, overview of human brain areas and function. The limbic system, the primitive part of our brains, gives rise to impulsive behavior and affective (emotional) responses to stimuli that may have had and may still have value in promoting at least short-term survival of the individual, for example, fight or flight, “eat this now it will lay down fat for winter”, “mate now for tomorrow we may die.” Our deliberative functions, the thought, the marshaling and integration of cues, stimuli, signals, previous experience, and conjectures about future states of the world and our place in them that temper the primitive impulses emanating from our limbic system to form more complex and rational behavioral responses, resides in the frontal lobe.

The seminar provided a simplistic framework for thinking about what I think is a key metaphysical question that we economists are only recently starting to wrestle with: what really determines the behavior of homo economicus? Or perhaps more correctly, is there such a being as homo economicus, at least as economists have tended to conceptualize him?

As I listened to the seminar speaker, I kept thinking of John Stuart Mill’s famous quote from Utilitarianism:

It is better to be a human being dissatisfied than a pig satisfied; better to be Socrates dissatisfied than a fool satisfied. And if the fool, or the pig, are a different opinion, it is because they only know their own side of the question. The other party to the comparison knows both sides.

It seems to fit exactly the dilemma we face in understanding and in modeling human behavior.  (Note: use of this quote is in no way meant to imply that the obese and overweight are “pigs” or “fools.” This same model fits people making choices about saving for retirement or taking preventive measures against (bad) future health or income states. It also fits investment bankers making decisions about whether or not to continue to invest in mortgage backed securities even after being warned that they are on a collision course with disaster. It fits economists and bank regulators who were warned a decade ago that derivatives markets should be regulated.  We are all pigs and fools at some times in our lives, some more so than others.)

But there was another stark question raised by the seminar that economists in particular must come to grips with: are consumers really utility maximizers or are they, at best, preference satisfiers? It matters because our theory takes as given that consumers are utility maximizers. Implicit in this are the essential requirements of rationality, self-interest (presumably long-term and broad enough to encompass family, friends, and community), and full-information.  If we are primarily preference satisfiers and those preferences do not correspond to some approximation of “utility” where utility comprises more than immediate, uninformed happiness or satisfaction, we are at the heart of an epistemological conundrum: are consumers the best judges of what is best for them? We take as given in economics that they are and much of welfare economics rests on this assumption. We often take it as given regardless of uncertainties and information asymmetries that clearly compromise the assumption.

What then is it within us or without us that forms the bridge between affect and deliberation? What are the determinants and what are the public and health policies that would strengthen that bridge in ways that benefit the utility of both individuals and society?

One seminar participant suggested that the relationship between the ideal or utility maximizing state of the world (as judged by the individual, for example, their optimal body mass index  (BMI)) and the actual state of the world (in this case a person’s actual BMI) be modeled as a weighted average of the empirically observed or inferred desiderata of the two portions of the brain. A simplistic equation may help here:

B=θD + (1-θ)A

Let  B be the “bridge” between the two parts of the brain or between our primitive selves and our rationally self-interested, fully-informed selves. D is the empirically observed output or state of the world that results from the deliberative portion of reason. A is the empirically observed output or state of the world that results from the affective or primitive portion of reason, and 0 ≤ θ ≤ 1 is a weight.   (My words and interpretation, not his.)

What I liked about this suggestion is that it provides a nice conceptualization of what I like to think of as the “Socrates parameter, “ θ. The parameter that determines how deliberative, how reasoned, how fully-informed, how forward thinking we really are. A high value implies high deliberation, but it can also imply better information or better use of available information, or even openness to new, information that conflicts with preconceived ideas or ideology. A high value may also imply lower rates of time preference or a longer time horizon to a quasi-hyperbolic  “cliff.” Low values imply low deliberation and are consistent with poor information or poor use of available information, higher rates of time preference and/or very short time horizons, or an inability or unwillingness to consider novel information and perspectives.

(For those not used to thinking in equations, it may help to notice that θ can only take values between 0 and 1.  When θ = 1 (the highest value it can take),  (1- θ)=0, so a person with the highest possible value of θ had B=D, i.e., they are pure deliberative with no influence from the limbic portion of their brain. Conversely, a person with θ = 0, the lowest value it can take, has (1- θ) = 1. That person is pure limbic, affective with no deliberative influence on choices. A person with θ = ½ will have (1- θ) = ½  implying a 50/50 split between deliberative and affective influences on his/her decision making. Thus, varying values of θ describe the degree to which a person or group of people temper emotion and impulse with deliberation.)

Behavioral economics and neurological economics are now helping us to understand the Socrates parameter; the dimensions of being, belief, and behavior that serve to bridge and temper affect with deliberation as well as the aspects of being, belief, and behavior grounded in emotion that serve as barriers between the good that we will to do and our actual behavior.

This is important stuff to understand. Right now, A in the equation above usually shows up in our error terms. If it is a genetic component we all share, then it may well generate correlation across individuals and communities as might also D, but in less easily measured and quantified ways.  In the absence of widely disseminated, easily understood information bolstered by regulation, A may well be a major contributor to bank bubbles and bailouts as well as to obesity and overweight, youthful smoking initiation, and unfettered appetites for risk and sweets to name a few.

The seminar speaker made the point that marketers of food and drink (and this could also apply to marketers of subprime mortgages and subprime political ideas) have tended to focus on the emotional, primitive part of our brains rather than the deliberative part. Foods have been engineered to contain more calories and fewer nutrients per portion as portion sizes have increased. To the extent that our limbic systems respond to such engineering by over-riding the judgment of our frontal lobe and to the extent that our frontal lobe is deprived of the information it requires to make a rationally self-interested judgment, we are not only pigs and fools, we are slaves.

Paul Krugman Weighs in on Health Care Reform

You can read his NY Times Op Ed here.

As it happens, Reuters published an investigative report this week that powerfully illustrates the vileness of our current system. The report concerns the insurer Fortis, now part of Assurant Health, which turns out to have had a systematic policy of revoking its clients’ policies when they got sick. In particular, according to the Reuters report, it targeted every single policyholder who contracted H.I.V., looking for any excuse, no matter how flimsy, for cancellation...

...But this is much more than a law enforcement issue. For one thing, it’s an example those who castigate President Obama for “demonizing” insurance companies should consider. The truth, widely documented, is that behavior like Assurant Health’s is widespread for a simple reason: it pays. A House committee estimated that Assurant made $150 million in profits between 2003 and 2007 by canceling coverage of people who thought they had insurance, a sum that dwarfs the fine the court imposed in this particular case. It’s not demonizing insurers to describe what they actually do.

Beyond that, this is a story that could happen only in America. In every other advanced nation, insurance coverage is available to everyone regardless of medical history. Our system is unique in its cruelty...

Can we afford this? Yes, says the Congressional Budget Office, which on Thursday concluded that the proposed legislation would reduce the deficit by $138 billion in its first decade and half of 1 percent of G.D.P., amounting to around $1.2 trillion, in its second decade.

Remind me again, please, why is it we prefer the private sector to the public sector when it comes to health insurance? It can't be that it's more cost efficient. This less than optimal bill will save money. Do we prefer the private sector because it's more efficient at managing risk than the public sector? It does this by failing to provide insurance to those who need it most and dropping beneficiaries when they cost "too much." Is that health insurance we can believe in?

Write or phone your putatively Democratic representative, please.

If not now, when?

Kucinich Does the Right Thing

Dennis Kucinich (D-OH) does the right thing and for the right reasons (IMHO). 

“In the past week, it’s become clear that the vote on the final health care bill will be quite close…. I know I have to make a decision -- not on the bill as I would like to see it, but as it is.”

But we aren't "home" yet. Now would be a good time to write your representative, especially if s/he is a putative Democrat and a potential "no" and you are a firm "yes."

Health Care Reform: Is the expedient the enemy of the best?

In 1994, ABC News aired a report describing the way that tobacco manufacturers recovered nicotine from the pulp of stems and leaf scraps, concentrated it, and added it and the pressed scraps back into tobacco leaf used in cigarettes. The manufacturers knew that nicotine is addictive and they carefully controlled the amount to maintain tobacco demand (aka addiction).  For a variety of reasons, including these revelations, a few years later a majority of state attorneys general brought suit against tobacco manufacturers to recover state health care expenditures (primarily the states’ shares of Medicaid expenditures) attributable to smoking-related disease. As the process that resulted in the Tobacco Master Settlement Agreement evolved, there was an attempt to reach a global settlement at the federal level that allowed the FDA to regulate nicotine. Sponsored by Senator John McCain, it failed to pass.

Efforts to negotiate a global settlement agreement died for a number of reasons. Not least was the inability of the public health community and tobacco control advocates to coalesce to support it. The wedge issue for many was the mere idea of negotiating with the tobacco companies or doing anything that would allow them to stay in business. Particularly galling was tort reform that would have prohibited class action suits, punitive awards, and future state prosecutions against tobacco manufacturers that was included in the bill along with FDA regulation of tobacco. Many public health and tobacco control advocates took positions that were very similar to Senator Dennis Kucinich's principled stance on health reform. Here is a quote by tobacco researcher and committed tobacco control advocate, Stanton Glantz (a researcher and advocate that I very much admire and respect), from Allan Brandt’s book The Cigarette Century (p. 424): “The fundamental reality of tobacco is that the way to beat them is to beat them. I have never found a single instance anywhere, anywhere, where a compromise with the industry served the public health.” Glantz’s objection was mainly to the tort law concessions contained in the proposed global settlement agreement.

One of the most effective tools the tobacco companies had in opposing the global settlement agreement besides money and power was the emotional response of tobacco control advocates. Their righteous anger interfered with their ability to hammer out a second-best solution in a world where first-best (regulation AND beating the tobacco industry) was not an option.  

We waited another 10 years for FDA regulation of tobacco. The good news is that the tobacco manufacturers did not obtain the tort reform concessions that were in the original proposed global settlement agreement. However, they are certainly not “beaten.”  Moreover, many adolescents have become addicted and will die because of the wait. I don’t know if the wait was worth it. I suspect it was now that we know that the tort law concessions were successfully eliminated. We can’t know for sure because there is no counterfactual.

You can read the entire story of tobacco regulation in this book by David Kessler and this book by Allan M. Brandt. I highly recommend both books. You can read about the methods tobacco companies use to avoid regulation here. I also recommend a visit to Campaign for Tobacco Free Kids website. Here is a good online article about the economics of tobacco regulation by Jonathan Gruber. And here is an excellent article by Alan Blinder that provides good insight into the reality of how bills become federal law (although some of you may disagree that economists should have more voice in the process).

So why am I telling you about tobacco regulation?

The Hobson’s choice before us with regard to health care reform is to hold out for something that has fewer sops to Pharma and the health insurance industry or to accept a second-best alternative that would start the US on the road to something that delivers over time universal access to affordable health insurance and health care.  There is no reason to think that the path from this starting position could not lead where we want to go. There are countries that provide universal cover through a combination of public and private insurance with no public option, but with strict regulation of private insurers. Some who oppose the current reform bill rightly worry about the effect of the individual mandate on individuals with low incomes. My understanding (from Kaiser Family Foundation’s Website, click all 3 bills and then check "mandate") is that financial risk is limited to 8% of income above certain cut points with hardship and other exclusions and a relatively low penalty for non-compliance. This is not meant as unequivocal endorsement of the bill. It is simply pointing out that it is not draconian.

Not having a reliable crystal ball, I honestly don’t know what is the right thing to do. But I do know that in the presence of uncertainty, the optimal path is almost always from where you are, not from where you would like to be.

My fear is that a desire to stick it to pharma and private health insurers (and perhaps even Democratic lawmakers who are more center than left no matter what the right says) and the emotions this evokes  on the far left will cloud judgment, leading some to oppose a bill that is not nearly so bad as it is portrayed.  Moreover, it contains many provisions that can and will be fixed over time. There may be short-term windfall profits for Pharma and private insurers, but this is unsustainable and I believe will be remedied. The same forces that would give us a better bill 5-10 years from now will be operating (possibly faster with health care reform enacted now) to shape a more efficient system. Increasing the public share of health care finance, even if initially diverted to private insurers, is the best way to concentrate lawmakers’ attention on restructuring the system.

This doesn’t mean that disappointed voters shouldn’t let BHO and the Democrats know how badly they have failed (so far) to provide “change we can believe in.”  But is joining ranks with the Republicans to defeat the current bill the best way to do this?  I’m pretty sure that if this bill is not enacted, pharma and private health insurers will still be there and no less powerful when the battle is rejoined. Why not take the first step now with something that is “good” by most measures and leverage it to something that is best for all of us, especially the currently or soon-to-be uninsured?

PBS' Judy Woodruff Interviews Progressive Political Economist, David Coates

David Coates, political economist and Worrell Chair in Anglo-American Studies at Wake Forest University, answers questions from PBS newscaster, Judy Woodruff, about his progressive blog, Answering Back.

"Answering Back" was written, and is now maintained, to give sustenance to ordinary party members campaigning for progressive candidates and causes. It is less focused on the leadership of the party than on the movement, because it is at that lower level that so much work needs still to be done, to strengthen the progressive voice in American politics. Good ideas will not win elections unaided, but without good ideas any election won will be valueless.

David also concisely summarizes what I think are the left and right forces that are most likely to torpedo passage of a health reform bill.

The reform the president is fighting for is far from perfect, but it is worth fighting for. If we get it, it will change the architecture of health care provision in the United States, and act as the launching pad for further health care reform down the line. Conservatives know that. They know concessions made now will be hard to pull back later. They know we are in trench warfare and need to fight one trench at a time.

My main worry is that many liberals seem to think that the fight we are in is a tank battle, and that we should go for fast moving total victory and risk total defeat. Center-left forces in democratic politics are often brilliant at snatching defeat from the jaws of victory, and letting the perfect drive out the good. 

Read the entire interview here.

Health Reform: If Not Now, When?

Two recent encounters have gotten me thinking about health reform.  The first was with my hair stylist—hardworking, talented, bright—who had a bad respiratory infection. She had just finished a 7-day course of antibiotics, but still had symptoms of a secondary bacterial sinus infection. Because she has no health insurance, she was thrilled that the antibiotics had only set her back $70. She was dismayed that she was still sick after a 7-day course of antibiotics. She was terrified that it might still land her in hospital. Another stylist at the same salon with the same symptoms had ended up in hospital with pneumonia. The other stylist also did not have health insurance.

The second encounter occurred a few days later when I gave a seminar at a university in another city.  During the cab ride to the train station after the seminar, my 38 year old cab driver revealed that he had recently obtained health insurance for the first time in his life.  He was thrilled, but also concerned that his new insurance was not comprehensive and most likely would not cover a serious illness or injury.

Then he asked me THE QUESTION: What do people do who don’t have insurance?

Many if not most hair stylists and cab drivers are essentially self-employed independent contractors who “rent” the place where they stand in a salon or the cab that they drive. They receive no health insurance benefits, no sick days, no retirement benefits. If they don’t work, they lose income. If they get really sick or injured, they lose everything.

The inequalities in income distribution  that have become greater in the US over the last 30 years are nothing compared to the growing inequalities that will result from an increasingly larger pool of Americans who lack adequate health insurance cover. Each unforeseen, primary care-preventable illness, every serious injury will cause them and their families to fall further behind economically and in the quality of their lives.

Joseph Stiglitz, Amartya Sen, and Jean-Paul Fittousi recently wrote in the Report of the Commission on the Measurement of Economic Performance and Social Progress:

But while the precise list of the features affecting quality of life inevitably rests on value judgments, there is a consensus that quality of life depends on people’s health and education, their everyday activities (which include the right to a decent job and housing), their participation in the political process, the social and natural environment in which they live, and the factors shaping their personal and economic security.

The Gini coefficient captures our growing income inequality. How do we capture the inequality induced by 30 million people and growing who have no health insurance?

More importantly, why, in a nation whose national narrative extols the virtues of entrepreneurship and individual effort, are young entreprenurs who choose jobs like hair styling or cab driving penalized for that choice?  I personally know two hair stylists who started as  independent contractors and worked their way to salon owner and employers of 10 to 20 stylists, manicurists, and estheticians. A major uninsured illness could have stopped them and the contributions they made to our economy dead. Literally.

As I contemplate this, I find myself recalling one of my favorite passages from Adam Smith’s Wealth of Nations (B1, Ch 2 )

The difference of natural talents in different men is, in reality, much less than we are aware of; and the very different genius which appears to distinguish men of different professions, when grown up to maturity, is not upon many occasions so much the cause, as the effect of the division of labour. The difference between the most dissimilar characters, between a philosopher and a common street porter, for example, seems to arise not so much from nature, as from habit, custom, and education. When they came into the world, and for the first six or eight years of their existence, they were perhaps, very much alike, and neither their parents nor playfellows could perceive any remarkable difference. About that age, or soon after, they come to be employed in very different occupations. The difference of talents comes then to be taken notice of, and widens by degrees, till at last the vanity of the philosopher is willing to acknowledge scarce any resemblance. But without the disposition to truck, barter, and exchange, every man must have procured to himself every necessary and conveniency of life which he wanted. All must have had the same duties to perform, and the same work to do, and there could have been no such difference of employment as could alone give occasion to any great difference of talents.

“...till at last the vanity of the philosopher [or banker or politician or school teacher or auto worker or college professor or physician or economist or...fill in your own occupation...] is willing to acknowledge scarce any resemblance.”

The division of labor has allowed us to enjoy the fruits of unfettered productivity and common wealth. Smith’s famous pin factory has over time given us greater output. With an assist from labor unions and the National Labor Relations Act  it has also given us higher wages, and more leisure time. In the US, the pin factory for a variety of reasons, some historical , some economic, some political, provides health insurance to its employees.  Over time, pin factories in the US have closed, replaced by large corporations that provide fewer manufactured goods and more services.  Those who do not work for large companies, including small business owners, independent contractors, and the individuals they employ, are often unable to obtain health insurance either as employer-sponsored groups or as individuals in private markets.  Yet these entrepreneurs are an important source of job creation and economic growth. Moreover, they represent the kinds of businesses we as a society should want to foster: embedded in their communities and therefore responsive to community demand and community welfare; small enough to fail and big enough to foster growth, employment, and innovation from the bottom up.

We in the US have been marginalizing the people who are the heart and soul of commercial enterprise, the small businesses and workers around which most of our communities used to be built. We are in effect segregating them based on employment status and health insurance cover. These are people who embody the values we say lie at the heart of our nation and our economic system: entrepreneurial, hard working, self-starters. By continuing to exclude them and their employees from affordable and adequate health insurance, we are in real danger of relegating them instead to a permanent underclass, a “servant” class that styles our hair, drives our cabs, cooks our food, cares for our children, and manicures our lawns. Until they get sick or have a car accident.

The divide is unsustainable. We cannot maintain economic growth and greatness with a growing proportion of US citizens excluded from one of the most basic requirements for the successful pursuit of life, liberty, and happiness.

I have written elsewhere about the efficiency aspects of a public option, but even without it Paul Krugman,  David Coates and Theda Skocpol are right.  Comprehensive, affordable health insurance must be made available to everyone. Every other developed country has done it. It does not get cheaper or easier to fix as time passes. We must do it now, in a form as close to optimal as can be achieved politically, and worry about the details later.  It’s the right thing to do both economically and morally.

Bring Back the Robber Barons? I Don't Think So.

Before we take Daniel Henninger’s advice over at the WSJ and Bring Back the Robber Barons, let’s consider the proposition more fully by reflecting on an alternative view of corporate “entrepreneurship” offered by Barry C. Lynn and Phillip Longman at Washington Monthly.

And while we're at it, let's perform this thought experiment: imagine all the entrepreneurship that is effectively squelched by locking potentially entrepreneurial people into corporate jobs in order to maintain health insurance cover for themselves and their families.

Yeah...that's the ticket...robber barons.

(Thanks to my friend, Obey, for the link to Lynn & Longman’s piece and my friend, Ecrive, for the link to the wsj piece.)