We describe research on the impact of health insurance on healthcare spending (“moral hazard”), and use this context to illustrate the value of and important complementarities between different empirical approaches. One common approach is to emphasize a credible research design; we review results from two randomized experiments, as well as some quasi-experimental studies. This work has produced compelling evidence that moral hazard in health insurance exists – that is, individuals, on average, consume less healthcare when they are required to pay more for it out of pocket – as well as qualitative evidence about its nature. These studies alone, however, provide little guidance for forecasting healthcare spending under contracts not directly observed in the data. Therefore, a second and complementary approach is to develop an economic model that can be used out of sample. We note that modeling choices can be consequential: different economic models may fit the reduced form but deliver different counterfactual predictions. An additional role of the more descriptive analyses is therefore to provide guidance regarding model choice.
Drug Channels: Follow the Dollar Math: How Much Do Pharmacies, Wholesalers, and PBMs Make From a Prescription?August 8, 2017
Yesterday,The Wall Street Journal published an intriguing article by Jonathan Rockoff titled Behind the Push to Keep Higher-Priced EpiPen in Consumers’ Hands.
The article includes a graphic attributed to me (cited as Pembroke Consulting). It shows that the drug channel—pharmacy benefit managers (PBMs), wholesalers, and pharmacies—receive more than $37 in gross profit for a brand-name drug with a $300 list price. PBMs capture about half of this amount.The WSJ article doesn’t describe how I arrived at the figures. But now you, Drug Channels reader, will get the inside scoop.
The combined effect means that mortality rates of whites with no more than a high school degree, which were around 30 percent lower than mortality rates of blacks in 1999, grew to be 30 percent higher than blacks by 2015.
Experienced Inequality and Preferences for Redistribution by Christopher Roth, Johannes Wohlfart :: SSRNFebruary 12, 2017
We examine in how far people’s experiences of income inequality affect their preferences for redistribution. We use several large nationally representative datasets to provide evidence that people who have experienced more inequality while growing up are less in favor of redistribution, after controlling for income, demographics, unemployment experiences and current macro-economic conditions. They are also less likely to consider the prevailing distribution of incomes to be unfair, suggesting that inequality experiences affect the reference point about what is a fair division of overall income. Finally, we conduct an experiment to show that individuals randomly exposed to environments promoting inequality in the experience stage of the experiment redistribute less in a subsequent behavioral measure.
Savings Medicare Beneficiaries Need for Health Expenses: Some Couples Could Need as Much as $350,000 by Paul Fronstin, Jack VanDerhei :: SSRNFebruary 9, 2017
This paper examines the amount of savings Medicare beneficiaries are projected to need to cover program deductibles, premiums and other health expenses in retirement. For the purposes of this study, health expenses include premiums for Medicare Parts B and D, premiums for Medigap Plan F, and out-of-pocket spending for outpatient prescription drugs. Data come from a variety of sources and are used in a Monte Carlo simulation model that simulates 100,000 observations, allowing for the uncertainty related to individual mortality and rates of return on assets in retirement.
- In 2016, a 65-year-old man would need $72,000 in savings and a 65-year-old woman would need $93,000 if each had a goal of having a 50 percent chance of having enough savings to cover health care expenses in retirement.
- If they wanted a 90 percent chance of having enough savings, the man would need $127,000 and the woman would need $143,000.
- A couple with median prescription drug expenses would need $165,000 if they had a goal of having a 50 percent chance of having enough savings to cover health care expenses in retirement. If they wanted a 90 percent chance of having enough savings, they would need $265,000.
- For a couple with drug expenses at the 90th percentile throughout retirement who wanted a 90 percent chance of having enough money saved for health care expenses in retirement by age 65, targeted savings would be $349,000 in 2016.
- From 2015 to 2016, projected savings targets increased between 0 percent and 6 percent. In contrast, savings targets declined between 2011 and 2014, but then they increased from 2014 to 2015 as well. Despite the increase in savings targets since 2014, the 2016 savings targets continue to be lower than they were in 2012 almost across the board. It is important to note that many individuals are likely to need more than the amounts cited in this report.
This analysis does not factor in the savings needed to cover long-term care expenses and other expenses not covered by Medicare, nor does it take into account the fact that many individuals retire prior to becoming eligible for Medicare. However, some workers will need to save less than what is reported if they choose to work past age 65, thereby postponing enrollment in Medicare Parts B and D if they receive health benefits as active workers.
Longitudinal Evidence for a Midlife Nadir in Human Well‐Being: Results from Four Data Sets by Terence Chai Cheng, Andrew J. Oswald :: SSRNFebruary 8, 2017
There is a large amount of cross‐sectional evidence for a midlife low in the life cycle of human happiness and well‐being (a ‘U shape’). Yet no genuinely longitudinal inquiry has uncovered evidence for a U‐shaped pattern. Thus, some researchers believe the U is a statistical artefact. We re‐examine this fundamental cross‐disciplinary question. We suggest a new test. Drawing on four data sets, and only within‐person changes in well‐being, we document powerful support for a U shape in longitudinal data (without the need for formal regression equations). The article’s methodological contribution is to use the first‐derivative properties of a well‐being equation.