Category: Data Source

How well did Medicare pay-for-performance work?

For pain management, and pain management, only, it seems it worked just fine:

Medicare uses a pay-for-performance program to reimburse hospitals. One of the key input measures in the performance formula is patient satisfaction with their hospital care. Physicians and hospitals, however, have raised concerns regarding questions related to patient satisfaction with pain management during hospitalization. They report feeling pressured to prescribe opioids to alleviate pain and boost satisfaction survey scores for higher reimbursements. This overprescription of opioids has been cited as a cause of current opioid crisis in the United States. Due to these concerns, Medicare stopped using pain management questions as inputs in its payment formula. The authors collected multiyear data from six diverse data sources, employed propensity score matching to obtain comparable groups, and estimated difference-in-difference models to show that, in fact, pain management was the only measure to improve in response to the pay-for-performance system. No other input measure showed significant improvement. Thus, removing pain management from the formula may weaken the effectiveness of the Hospital Value-Based Purchasing Program at improving patient satisfaction, which is one of the key goals of the program. The authors suggest two divergent paths for Medicare to make the program more effective.

That is from a new paper by Lu Liu, Dinesh K. Gauri, and Rupinder P. Jindal.  Overall, why did incentives fail us so badly?

Via the excellent Kevin Lewis.

Newark fact of the day

Newark Police officers did not fire a single shot during the calendar year 2020, and the city didn’t pay a single dime to settle police brutality cases. That’s never happened, at least in the city’s modern history.

At the same time, crime is dropping, and police recovered almost 500 illegal guns from the street during the year.

Here is the longer story.

Do career disruptions matter for the top five percent?

How resilient are high-skilled, white collar workers? We exploit a uniquely comprehensive dataset of individual-level resumes of bank employees and the setting of the Lehman Brothers bankruptcy to estimate the effect of an unanticipated shock on the career paths of mobile and high skilled labor. We find evidence of short-term effects that largely dissipate over the course of the decade and that touch only the senior-most employees. We match each employee of Lehman Brothers in January 2008 to the most similar employees at Goldman Sachs, Morgan Stanley, Deutsche Bank, and UBS based on job positions, skills, education, and demographics. By 2019, the former Lehman Brothers employees are 2% more likely to have experienced at least a six-months-long break from reported employment and 3% more likely to have left the financial services industry. However, these effects concentrate among the senior individuals such as vice presidents and managing directors and are absent for junior employees such as analysts and associates. Furthermore, in terms of subsequent career growth, junior employees of Lehman Brothers fare no worse than their counterparts at the other banks. Analysts and associates employed at Lehman Brothers in January 2008 have equal or greater likelihoods of achieving senior roles such as managing director in existing enterprises by January 2019 and are more likely to found their own businesses.

That is from a new paper by Anastassia Fedyk and James Hodson.  Via the excellent Kevin Lewis.

When doctors stay in their lane

Here is the paper, showing massive overdiagnosis, even following testing.  If you don’t wish to click through, here is a nice summary:


Ideology and performance in public organizations

We combine personnel records of the United States federal bureaucracy from 1997-2019 with administrative voter registration data to study how ideological alignment between politicians and bureaucrats affects the personnel policies and performance of public organizations. We present four results. (i) Consistent with the use of the spoils system to align ideology at the highest levels of government, we document significant partisan cycles and substantial turnover among political appointees. (ii) By contrast, we find virtually no political cycles in the civil service. The lower levels of the federal government resemble a “Weberian” bureaucracy that appears to be largely protected from political interference. (iii) Democrats make up the plurality of civil servants. Overrepresentation of Democrats increases with seniority, with the difference in career progression being largely explained by positive selection on observables. (iv) Political misalignment carries a sizeable performance penalty. Exploiting presidential transitions as a source of “within-bureaucrat” variation in the political alignment of procurement officers over time, we find that contracts overseen by a misaligned officer exhibit cost overruns that are, on average, 8% higher than the mean overrun. We provide evidence that is consistent with a general “morale effect,” whereby misaligned bureaucrats are less motivated.

They seem to be saying (among other things) that government is worse under Republican administrations because Democrats in the bureaucracy are not as loyal to their missions?  That is a new NBER working paper by Jorg L. Spenkuch, Edoardo Teso, and Guo Xu.

How to extract information from on-line reviews, or why Star Wars is still a thing

Online reviews promise to provide people with immediate access to the wisdom of the crowds. Yet, half of all reviews on Amazon and Yelp provide the most positive rating possible, despite human behaviour being substantially more varied in nature. We term the challenge of discerning success within this sea of positive ratings the ‘positivity problem’. Positivity, however, is only one facet of individuals’ opinions. We propose that one solution to the positivity problem lies with the emotionality of people’s opinions. Using computational linguistics, we predict the box office revenue of nearly 2,400 movies, sales of 1.6 million books, new brand followers across two years of Super Bowl commercials, and real-world reservations at over 1,000 restaurants. Whereas star ratings are an unreliable predictor of success, emotionality from the very same reviews offers a consistent diagnostic signal. More emotional language was associated with more subsequent success.

Here is more from Matthew D. Rocklage, Derek D. Rucker, and Loran F. Nordgren, via the excellent Kevin Lewis.

Facts about Nigerian-Americans

Second-generation black Americans have been inadequately studied in prior quantitative research. The authors seek to ameliorate this research gap by using the Current Population Survey to investigate education and wages among second-generation black Americans with a focus on Nigerian Americans. The latter group has been identified in some qualitative studies as having particularly notable socioeconomic attainments. The results indicate that the educational attainment of second-generation Nigerian Americans exceeds other second-generation black Americans, third- and higher generation African Americans, third- and higher generation whites, second-generation whites, and second-generation Asian Americans. Controlling for age, education, and disability, the wages of second-generation Nigerian Americans have reached parity with those of third- and higher generation whites. The educational attainment of other second-generation black Americans exceeds that of third- and higher generation African Americans but has reached parity with that of third- and higher generation whites only among women. These results indicate significant socioeconomic variation within the African American/black category by gender, ethnicity, and generational status that merits further research.

Here is the full paper by Sakomoto,

Further estimates on the cost of climate change and global warming

Sea level rise will cause spatial shifts in economic activity over the next 200 years. Using a spatially disaggregated, dynamic model of the world economy, this paper estimates the consequences of probabilistic projections of local sea level changes. Under an intermediate scenario of greenhouse gas emissions, permanent flooding is projected to reduce global real GDP by 0.19 percent in present value terms. By the year 2200, a projected 1.46 percent of the population will be displaced. Losses in coastal localities are much larger. When ignoring the dynamic response of investment and migration, the loss in real GDP in 2200 increases from 0.11 percent to 4.5 percent.

That newly published paper is from Klaus Desmet, Robert E. Kopp, Scott A. Kulp, Dávid Krisztián Nagy, Michael Oppenheimer, Esteban Rossi-Hansberg and Benjamin H. Strauss in American Economic Journal: Macroeconomics.  Am I wrong to feel a little…underwhelmed by those estimates?  Here is an earlier recent paper on other cost estimates.

The mortality of scholars

After recovering from a severe mortality crisis in the seventeenth century, life expectancy among scholars started to increase as early as in the eighteenth century, well before the Industrial Revolution. Our finding that members of scientific academies—an elite group among scholars—were the first to experience mortality improvements suggests that 300 years ago, individuals with higher social status already enjoyed lower mortality. We also show, however, that the onset of mortality improvements among scholars in medicine was delayed, possibly because these scholars were exposed to pathogens and did not have germ theory knowledge that might have protected them. The disadvantage among medical professionals decreased toward the end of the nineteenth century.

Here is more from Robert Stelter, David de la Croix, and Mikko Myrskylä.  Via the excellent Kevin Lewis.

The influence of hidden researcher decisions in applied microeconomics

Another one from the Department of Uh-Oh:

Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many‐analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect’s sign varied as well. The standard deviation of estimates across replications was 3–4 times the mean reported standard error.

Here is the paper by numerous authors, via Scott Cunningham.

Are Americans getting worse?

Maybe so:

Morbidity and mortality have been increasing among middle-aged and young-old Americans since the turn of the century. We investigate whether these unfavorable trends extend to younger cohorts and their underlying physiological, psychological, and behavioral mechanisms. Applying generalized linear mixed effects models to 62,833 adults from the National Health and Nutrition Examination Surveys (1988-2016) and 625,221 adults from the National Health Interview Surveys (1997-2018), we find that for all gender and racial groups, physiological dysregulation has increased continuously from Baby Boomers through late-Gen X and Gen Y. The magnitude of the increase is higher for White men than other groups, while Black men have a steepest increase in low urinary albumin (a marker of chronic inflammation). In addition, Whites undergo distinctive increases in anxiety, depression, and heavy drinking, and have a higher level than Blacks and Hispanics of smoking and drug use in recent cohorts. Smoking is not responsible for the increasing physiological dysregulation across cohorts. The obesity epidemic contributes to the increase in metabolic syndrome, but not in low urinary albumin. The worsening physiological and mental health profiles among younger generations imply a challenging morbidity and mortality prospect for the United States, one that may be particularly inauspicious for Whites.

Here is the full article, via an excellent loyal MR reader.

Testing Todd

Emmanuel Todd, that is.  Here is a recent paper from Jerg Gutmann and Stefan Voigt:

Many years ago, Emmanuel Todd came up with a classification of family types and argued that the historically prevalent family types in a society have important consequences for its economic, political, and social development. Here, we evaluate Todd’s most important predictions empirically. Relying on a parsimonious model with exogenous covariates, we find mixed results. On the one hand, authoritarian family types are, in stark contrast to Todd’s predictions, associated with increased levels of the rule of law and innovation. On the other hand, and in line with Todd’s expectations, communitarian family types are linked to racism, low levels of the rule of law, and late industrialization. Countries in which endogamy is frequently practiced also display an expectedly high level of state fragility and weak civil society organizations.

Via the excellent Kevin Lewis.

Socioeconomic roots of academic faculty

Using a survey of 7218 professors in PhD-granting departments in the United States across eight disciplines in STEM, social sciences, and the humanities, we find that the estimated median childhood household income among faculty is 23.7% higher than the general public, and faculty are 25 times more likely to have a parent with a PhD. Moreover, the proportion of faculty with PhD parents nearly doubles at more prestigious universities and is stable across the past 50 years.

Here is the full paper, via all over Twitter.

On the GDP-Temperature relationship and its relevance for climate damages

I have worried about related issues for some while, and now that someone has done the hard work I find the results disturbing and possibly significant:

Econometric models of temperature impacts on GDP are increasingly used to inform global warming damage assessments. But theory does not prescribe estimable forms of this relationship. By estimating 800 plausible specifications of the temperature-GDP relationship, we demonstrate that a wide variety of models are statistically indistinguishable in their out-of-sample performance, including models that exclude any temperature effect. This full set of models, however, implies a wide range of climate change impacts by 2100, yielding considerable model uncertainty. The uncertainty is greatest for models that specify effects of temperature on GDP growth that accumulate over time; the 95% confidence interval that accounts for both sampling and model uncertainty across the best-performing models ranges from 84% GDP losses to 359% gains. Models of GDP levels effects yield a much narrower distribution of GDP impacts centered around 1–3% losses, consistent with damage functions of major integrated assessment models. Further, models that incorporate lagged temperature effects are indicative of impacts on GDP levels rather than GDP growth. We identify statistically significant marginal effects of temperature on poor country GDP and agricultural production, but not rich country GDP, non-agricultural production, or GDP growth.

That is from Richard G Newell, Brian C. Prest, and Steven E. Sexton.  Via the excellent Kevin Lewis.

When Did Growth Begin?

The subtitle of the paper is “New Estimates of Productivity Growth in England from 1250 to 1870” and it is by Paul Bouscasse, Emi Nakamura, and Jon Steinsson:

We provide new estimates of the evolution of productivity in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. We develop and implement a new methodology for estimating productivity that accounts for these Malthusian dynamics. In the early part of our sample, we find that productivity growth was zero. Productivity growth began in 1600—almost a century before the Glorious Revolution. Post-1600 productivity growth had two phases: an initial phase of modest growth of 4% per decade between 1600 and 1810, followed by a rapid acceleration at the time of the Industrial Revolution to 18% per decade. Our evidence helps distinguish between theories of why growth began. In particular, our findings support the idea that broad-based economic change preceded the bourgeois institutional reforms of 17th century England and may have contributed to causing them. We also estimate the strength of Malthusian population forces on real wages. We find that these forces were sufficiently weak to be easily overwhelmed by post-1800 productivity growth.

Via Anton Howes.  Here is a related tweet storm from Steinsson.