Results for “finkelstein” 23 found
Here’s the latest Economists in the Wild video featuring Amy Finkelstein, Tamar Oostrom and Abigail Ostriker discussing some of their research (with Einav and Williams) on breast cancer screening. It’s a good video for illustrating how the tools of economics can be used to study a startling wide variety of problems.
Sorry to be late on this one, but here is the AEA take on her contributions, many of which involve health care economics and the study of health insurance. I am not sure she was considered an obvious front-runner from the beginning, but in my view it is an excellent pick (without intending any slight to the billions who were passed over). She is trying to understand the real world, and she is showing that policy economics should not have lower status in academia. Obviously her major areas of study are topical today.
Dan Drezner has an excellent post, with which I largely agree. I haven’t read the guy’s work (I doubt if I would like it), but my smell test suggests the following. Many non-top universities tenure a large group of faculty members, none of whom really deserve it. They are insiders, they have friends in the department, the replacements wouldn’t really be better, and so the tenure sticks. It is quite easy to argue ex post that a "no" vote is warranted in most of these cases. But if Finkelstein hadn’t done controversial work, he in fact would have received tenure along with many other non-deserving candidates. He didn’t, and in that sense I also suspect the process was unfair.
The benefit of Medicaid coverage received by a newly insured adult is less than half what that coverage costs taxpayers, which is about $5,500 a year.
We have estimated that 60 percent of government spending to expand Medicaid to new recipients ends up paying for care that the nominally uninsured already receive, courtesy of taxpayer dollars and hospital resources. In other words, from the recipient’s perspective the alternatives are $5,500 in cash or only about 40 percent of that — $2,200 — in health insurance benefits, on top of the care they were already receiving.
That is from Amy Finkelstein at the NYT.
2. 1/3 test positive in a semi-random Chelsea, Mass. sample. And “Notably, 43.2% (95% CI 32.2-54.7%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic.” That is from northern Italy. and a further critique of the Santa Clara study.
8. Good and extensive west coast Kaiser data set, and further evidence that R doesn’t fall nearly as much as you might wish for. If you are advocating an extended lockdown, you really need to think this one through and present your reasoning. So far I don’t see enough people doing that, nothing close, including the economists maybe even especially the economists. Right now this is one of the biggest deficiencies in the debate.
9. Countries that have banned alcohol as part of their Covid-19 response. It is striking to me how accepting the American coastal intelligentsia is of a strict lockdown, yet a permanent ban on alcohol is to them an unacceptable idea, curtailing basic liberties and impractical.
10. “…stay-at-home orders caused people to stay at home: county-level measures of mobility declined by between 9% and 13% by the day after the stay-at-home order went into effect.” And: “We show that COVID-19 as a whole reduced consumer spending in a panel of over 1 million small businesses by 40% year-over-year. Conversely, COVID-19 did not affect aggregate consumer spending at 3,600 large businesses.3…Consumer spending at the brick-and mortar stores of large firms fell by 9%, but online transactions at these large firms increased by 56%.”
12. William Hanage and Helen Jenkins at WaPo cover the IHME model with some seriousness. Good piece, but we should have been debating this six weeks ago or more.
13. Andrew Gelman on the Santa Clara study (brutal).
Nationwide’s pet health insurance division has partnered with Purdue University researchers to track trends in pet insurance payouts. The researchers track a “basket” of the most commonly-utilized procedures to see how the typical veterinary visit has changed in price over time. According to their research, these ordinary expenses declined by 6 percent from January 2009 to December 2017 after adjusting for inflation.
This decrease is corroborated by less reliable sources, such as the American Pet Products Association (APPA) annual consumer spending surveys. For virtually every year tracked (accessible via web archive), cat and dog owners reported spending less money on average routine and surgical visits. The data is jumpier than the Nationwide and Purdue rigorous analysis of 30 million insurance claims but confirms an interesting – and counterintuitive – trend. In a system where consumers and patients’ “representatives” have enough skin in the game, healthcare prices behave like they would in most other markets.
That is from Ross Marchand, “Why cats pay a lower price for CAT scans.” Here is earlier work by Einav, Finkelstein, and Gupta about pet health care being about as inefficient as human health care. I don’t consider this a settled issue, but it is interesting to hear a revision on what had been the most common take.
3. Plastic bags designed to embarrass their users (the culture that is Vancouver).
Interesting and substantive throughout, here is one bit:
Syverson: In general, we think companies that do a better job of meeting the needs of their consumers at a low price are going to gain market share, and those that don’t, shrink and eventually go out of business. The null hypothesis seems to be that health care is so hopelessly messed up that there is virtually no responsiveness of demand to quality, however you would like to measure it. The claim is that people don’t observe quality very well — and even if they do, they might not trade off quality and price like we think people do with consumer products, because there is often a third-party payer, so people don’t care about price. Also, there is a lot of government intervention in the health care market, and governments can have priorities that aren’t necessarily about moving market activity in an efficient direction.
Amitabh Chandra, Amy Finkelstein, Adam Sacarny, and I looked at whether demand responds to performance differences using Medicare data. We looked at a number of different ailments, including heart attacks, congestive heart failure, pneumonia, and hip and knee replacements. In every case, you see two patterns. One is that hospitals that are better at treating those ailments treat more patients with those ailments. Now, the causation can go either way with that. However, we also see that being good at treating an ailment today makes the hospital big tomorrow.
Second, responsiveness to quality is larger in instances where patients have more scope for choice. When you’re admitted through the emergency department, there’s still a positive correlation between performance and demand, but it’s even stronger when you’re not admitted through the emergency department — in other words, when you had a greater ability to choose. Half of the people on Medicare in our data do not go to the hospital nearest to where they live when they are having a heart attack. They go to one farther away, and systematically the one they go to is better at treating heart attacks than the one nearer to their house.
What we don’t know is the mechanism that drives that response. We don’t know whether the patients choose a hospital because they have previously heard something from their doctor, or the ambulance drivers are making the choice, or the patient’s family tells the ambulance drivers where to go. Probably all of those things are important.
It’s heartening that the market seems to be responsive to performance differences. But, in addition, these performance differences are coordinated with productivity — not just outcomes but outcomes per unit input. The reallocation of demand across hospitals is making them more efficient overall. It turns out that’s kind of by chance. Patients don’t go to hospitals that get the same survival rate with fewer inputs. They’re not going for productivity per se; they’re going for performance. But performance is correlated with productivity.
All of this is not to say that the health care market is fine and we have nothing to worry about. It just says that the mechanisms here aren’t fundamentally different than they are in other markets that we think “work better.”
2. China’s “Big Hack”: amazing Bloomberg story. One of the best and biggest stories of the year.
It’s well known that a large faction of medical spending occurs in the last 12 months of life but does this mean that the money spent was fruitless? Be careful as there is a big selection effect–we don’t see the people we spent money on who didn’t die. A new paper in Science by Einav, Finkelstein, Mullainathan and Obermeyer finds that most spending is not on people who are predicted to die within the next 12 months.
That one-quarter of Medicare spending in the United States occurs in the last year of life is commonly interpreted as waste. But this interpretation presumes knowledge of who will die and when. Here we analyze how spending is distributed by predicted mortality, based on a machine-learning model of annual mortality risk built using Medicare claims. Death is highly unpredictable. Less than 5% of spending is accounted for by individuals with predicted mortality above 50%. The simple fact that we spend more on the sick—both on those who recover and those who die—accounts for 30 to 50% of the concentration of spending on the dead. Our results suggest that spending on the ex post dead does not necessarily mean that we spend on the ex ante “hopeless.
…”Even if we zoom in further on the subsample of individuals who enter the hospital with metastatic cancer…we find that only 12% of decedents have an annual predicted mortality of more than 80%.
Thus, we aren’t spending on people for whom there is no hope but it doesn’t follow that it’s the spending that creates the hope. What we really want to know is who will live or die conditional on the spending. And to that issue this paper does not speak.
There is a new and very good paper on that question by Amy Finkelstein, Nathaniel Hendren, and Mark Shepard (pdf). In reality, the price elasticity of demand for health insurance is quite high, at least among lower-income groups:
How much are low-income individuals willing to pay for health insurance, and what are the implications for insurance markets? Using administrative data from Massachusetts’ subsidized insurance exchange, we exploit discontinuities in the subsidy schedule to estimate willingness to pay and costs of insurance among low-income adults…For at least 70 percent of the low-income eligible population, we find that willingness to pay for insurance is far below the average cost curve – what it would cost insurers to provide coverage to all who would enroll if the premium were set equal to that WTP. Adverse selection exists, despite the presence of the coverage mandate, but is not the driving force behind low take up. We estimate that willingness to pay is only about one-third of own costs; thus even if insurers could offer actuarially fair, type-specific prices, at least 70 percent of the market would be uncovered.
That is from both the abstract and conclusion. I do understand the ideal of universal coverage, but note this:
For example, we estimate that subsidizing insurer prices by 90% would lead only about three-quarters of potential enrollees to buy insurance.
The somewhat depressing and underexplored implication is that the beneficiaries do not love Obamacare as much as some of you do. In fact you may remember a result from last year, from the research of Mark Pauly, indicating that “close to half” of households covered by the unsubsidized mandate, by the standards of their own preferences, would prefer not to purchase health insurance. And that was before some of the recent rounds of premium increases, and overall these new results seem to imply even lower demands for health insurance relative to cash.
Now, I think it is an open question how much “non-paternalism” is the correct moral stance here. Maybe we should force upon people more health insurance than they would purchase in an adverse selection-free market, because a) they are ill-informed, b) they have children, or c) ex post we still need to take care of them in some way, if indeed their gamble to not purchase insurance turns out badly.
Do, however, note the words of the authors: “We conclude that the size of uncompensated care for low-income populations provides a plausible explanation for their low WTP.” In other words, many of the poor do not value health insurance nearly as much as many planners feel they ought to, in large part because they are already getting some health care.
In any case, consider a political economy point if nothing else. If you institute a policy that forces on people more health insurance than they think they wish to buy, do not be shocked if a huckster comes along offering them a supposedly better deal, and gets away with it.
Along related lines, consider also this result:
From the perspective of social welfare, to justify connecting the 5% least dense areas of North Carolina would require each adopting household value high speed wired broadband access at more than $1519 per month.
For the pointers I thank Peter Metrinko and Kevin Lewis.
In Miami, health care providers spent about $14,423 per Medicare patient in 2010. But in Minneapolis, average spending on Medicare enrollees that year was $7,819, just over half as much. In fact, the U.S. is filled with regional disparities in medical spending. Why is this?
One explanation focuses on providers: In some regions, they may be more likely to use expensive tests or procedures. Another account focuses on patients: If the underlying health or the care preferences of regional populations varies enough, that may cause differences in spending. In recent years, public discussion of this issue has largely highlighted providers, with the implication that reducing apparently excessive treatments could trim overall health care costs.
But now a unique study co-authored by MIT economists provides a new answer to the medical cost mystery: By scrutinizing millions of Medicare patients who have moved from one place to another, the researchers have found that patients and providers account for virtually equal shares of the differences in regional spending.
“We find it is about 50/50, half due to patients and half due to places,” says Heidi Williams, the Class of 1957 Career Development Associate Professor in MIT’s Department of Economics, and a co-author of a new paper detailing the study’s findings.
That’s MIT News ably summarizing the new Finkelstein, Gentzkow, and Williams paper, Sources of Geographic Variation in Health Care: Evidence From Patient Migration (ungated).
If the half of the variation that is due to place is inefficient (which could mean too low or too high but probably means too high given that the medical care curve is flat) then this puts an upper limit on the gains from standardization but still a quite high limit.
By the way, Finkelstein and Gentzkow are both recent John Bates Clark Medal awardees and Williams is a MacArthur “genius award” winner. Perhaps I should have titled this post, assortative co-authoring.
That is the title of the new NBER paper by Liran Einav, Amy Finkelstein, and Atul Gupta, here is the abstract:
We document four similarities between American human healthcare and American pet care: (i) rapid growth in spending as a share of GDP over the last two decades; (ii) strong income-spending gradient; (iii) rapid growth in the employment of healthcare providers; and (iv) similar propensity for high spending at the end of life. We speculate about possible implications of these similar patterns in two sectors that share many common features but differ markedly in institutional features, such as the prevalence of insurance and of public sector involvement.
Note that the number of veterinarians doubled from 1996 to 2013. The authors do not seem to have data on whether cats and dogs live longer in the United States, but I have a surmise…
Here are ungated copies of the paper.
1. Volkswagen and the trade agreements: “In the best of cases, the United States will emerge as the “world super-regulator.”” Bravo.
When I was last living in Chicago, in the spring 2014, a regular visitor to the department of the University of Chicago and the editor of the Journal of Economic Literature, Steven Durlauf, asked me if I would be interested in writing something for the journal. For many years I had promised Gary Becker that I would write something to help clarify the meaning and role of price theory to my generation of economists, especially those with limited exposure to the Chicago environment, which did so much to shape my approach to economics. With Gary’s passing later that spring, I decided to use this opportunity to follow through on that promise. More than a year later I have posted on SSRN the result.
I have an unusual relationship to “price theory”. As far as I know I am the only economist under 40, with the possible exception of my students, who openly identifies myself as focusing my research on price theory. As a result I am constantly asked what the phrase means. Usually colleagues will follow up with their own proposed definitions. My wife even remembers finding me at our wedding reception in a heated debate not about the meaning of marriage, but of price theory.
The most common definition, which emphasizes the connection to Chicago and to models of price-taking in partial equilibrium, doesn’t describe the work of the many prominent economists today who are closely identified with price theory but who are not at Chicago and study a range of different models. It also falls short of describing work by those like Paul Samuelson who were thought of as working on price theory in their time even by rivals like Milton Friedman. Worst of all it consigns price theory to a particular historical period in economic thought and place, making it less relevant to the future of economics.
I therefore have spent many years searching for a definition that I believe works and in the process have drawn on many sources, especially many conversations with Gary Becker and Kevin Murphy on the topic as well as the philosophy of physics and the methodological ideas of Raj Chetty, Peter Diamond and Jim Heckman among others. This process eventually brought me to my own definition of price theory as analysis that reduces rich (e.g. high-dimensional heterogeneity, many individuals) and often incompletely specified models into ‘prices’ sufficient to characterize approximate solutions to simple (e.g. one-dimensional policy) allocative problems. This approach contrasts both with work that tries to completely solve simple models (e.g. game theory) and empirical work that takes measurement of facts as prior to theory. Unlike other definitions, I argue that mine does a good job connecting the use of price theory across a range of fields of microeconomics from international trade to market design, being consistent across history and suggesting productive directions for future research on the topic.
To illustrate my definition I highlight four distinctive characteristics of price theory that follow from this basic philosophy. First, diagrams in price theory are usually used to illustrate simple solutions to rich models, such as the supply and demand diagram, rather than primitives such as indifference curves or statistical relationships. Second, problem sets in price theory tend to ask students to address some allocative or policy question in a loosely-defined model (does the minimum wage always raise employment under monopsony?), rather than solving out completely a simple model or investigating data. Third, measurement in price theory focuses on simple statistics sufficient to answer allocative questions of interest rather than estimating a complete structural model or building inductively from data. Raj Chetty has described these metrics, often prices or elasticities of some sort, as “sufficient statistics”. Finally, price theory tends to have close connections to thermodynamics and sociology, fields that seek simple summaries of complex systems, rather than more deductive (mathematics), individual-focused (psychology) or inductive (clinical epidemiology and history) fields.
I trace the history of price theory from the early nineteenth to the late twentieth when price theory became segregated at Chicago and against the dominant currents in the rest of the profession. For a quarter century following 1980, most of the profession either focused on more complete and fully-solved models (game theory, general equilibrium theory, mechanism design, etc.) or on causal identification. Price theory therefore survived almost exclusively at Chicago, which prided itself on its distinctive approach, even as the rest of the profession migrated away from it.
This situation could not last, however, because price theory is powerfully complementary with the other traditions. One example is work on optimal redistributive taxation. During the 1980’s and 1990’s large empirical literatures developed on the efficiency losses created by income taxation (the elasticity of labor supply) and on wage inequality. At the same time a rich theory literature developed on very simple models of optimal redistributive income taxation. Yet these two literatures were largely disconnected until the work of Emmanuel Saez and other price theorists showed how measurements by empiricists were closely related to the sufficient statistics that characterize some basic properties of optimal income taxation, such as the best linear income tax or the optimal tax rate on top earners.
Yet this was not the end of the story; these price theoretic stimulated empiricists to measure quantities (such as top income inequality and the elasticity of taxable income) more closely connected to the theory and theorists to propose new mechanisms through which taxes impact efficiency which are not summarized correctly by these formulas. This has created a rich and highly productive dialog between price theoretic summaries, empirical measurement of these summaries and more simplistic models that suggest new mechanisms left out of these summaries.
A similar process has occurred in many other fields of microeconomics in the last decade, through the work of, among others, five of the last seven winners of the John Bates Clark medal. Liran Einav and Amy Finkelstein have led this process for the economics of asymmetric information and insurance markets; Raj Chetty for behavioral economics and optimal social insurance; Matt Gentzkow for strategic communication; Costas Arkolakis, Arnaud Costinot and Andrés Rodriguez-Clare in international trade; and Jeremy Bulow and Jon Levin for auction and market design. This important work has shown what a central and complementary tool price theory is in tying together work throughout microeconomics.
Yet the formal tools underlying these price theoretic approximations and summaries have been much less fully developed than have been analytic tools in other areas of economics. When does adding up “consumer surplus” across individuals lead to accurate measurements of social welfare? How much error is created by assumptions of price-taking in the new contexts, like college admissions or voting, to which they are being applied? I highlight some exciting areas for further development of such approximation tools complementary to the burgeoning price theory literature.
Given the broad sweep of this piece, it will likely touch on the interests of many readers of this blog, especially those with a Chicago connection. Your comments are therefore very welcome. If you have any, please email me at [email protected].