“A full-throated defense of economic dynamism.” - The Wall Street Journal
“Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
“Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
“There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts

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Race and Ethnicity of Violent Crime Offenders and Arrestees, 2018

Barbara Oudekerk U.S. Department Of Justice

Date Posted:: March 8, 2021
Is Database:: Database

Blacks overrepresented among offenders in nonfatal violent crimes, 29% of offenders vs 12.5% of population. Whites underrepresented, 52.2% of offenders vs 60.4% of population.

In 2018, black individuals were overrepresented among offenders in nonfatal violent crimes, accounting for 29% of offenders despite comprising only 13% of the U.S. population. This contrasts with white individuals, who were underrepresented, making up 52% of offenders compared to 60% of the population. Specifically, black offenders constituted 51% of those involved in robbery and 34% in aggravated assault. The data, derived from the National Crime Victimization Survey (NCVS) and Uniform Crime Reporting (UCR), highlights disparities in crime involvement and arrest rates, with black individuals representing 35% of offenders in incidents reported to police and 33% of arrests. Meanwhile, Hispanic offenders were overrepresented in arrests (18%) relative to their involvement in violent crimes (14%). These statistics underscore significant racial disparities in crime and arrest patterns, raising questions about systemic factors influencing these outcomes.

I read the DOJ report with the claims made in the WSJ in mind. Bottomline to quote the report,"..White and black people were arrested proportionate to their involvement in serious nonfatal violent crime overall and proportionate to their involvement in serious nonfatal violent crime reported to police…."

Note this report excludes fatal crime, "....Excludes murder, non-negligent manslaughter, and other assault...."

I'm not sure how to think about using arrests as a metric, can't think of a better one, but I suppose somebody could argue that reflect bias against blacks if the police spend more time chasing them in a way they don't whites (though there is no evidence of that) But outside of that the data is relatively straightforward (though they do use the race of criminal as reported by victim which I suppose could be another source of bias)"... Tese UCR data on incidents of nonfatal violent crime can be compared to data from the National Crime Victimization Survey (NCVS) to determine how much offense and arrest differences by race and ethnicity can be attributed to differences in criminal involvement. Te NCVS collects information on victims’ perceptions of offenders' race, ethnicity, and other characteristics in incidents of violent crime..."

Allen Beck, Barbara Oudekerk, Heather Brotsos, Jenna Truman and Alexia Cooper, " Race and Ethnicity of Violent Crime Offenders and Arrestees, 2018," U.S. Department Of Justice, January 2021, https://www.bjs.gov/content/pub/pdf/revcoa18.pdf

Findings on violent crime involvement by race/ethnicity relative to population, “…Relative to their share of the U.S. population (60%), white people were underrepresented among offenders in nonfatal violent crimes overall (52%)(table 8). they accounted for 45% of offenders involved in aggravated assaults and 31% of offenders involved in robbery. They were not underrepresented to a statistically significant degree among offenders involved in rape or sexual assault (56%) or simple assault (59%). Black people were overrepresented among offenders in nonfatal violent crimes overall (29%) relative to their share of the U.S. population (13%).Half of all offenders involved in robbery (51%), a third involved in aggravated assault (34%), and more than a fifth involved in simple assault (23%) and rape or sexual assault (22%) were black….”

Core finding, “…Based on the 2018 NCVS and UCR, black people accounted for 29% of violent-crime offenders and 35% of violent-crime offenders in incidents reported to police, compared to 33% of all persons arrested for violent crimes.... When limited to offenders in incidents reported to police, white people were found to be arrested proportionate to their criminal involvement (48%). Hispanic offenders were overrepresented among persons arrested for nonfatal violent crimes (18%) relative to their representation among violent offenders (14% of all violent offenders and 13% of violent offenders in incidents reported to police)....

An Extra Point for Attendance: The Impact of High School Varsity Athletics on Absenteeism

Nat Malkus and Sam Hollon American Enterprise Institute

Date Posted:: April 16, 2026
Is Database:: Database

The absentee rate of Indiana high school students, ~23% of whom played a varsity sport, was ~20% lower for those who participated in varsity athletics than for non-athletes. The effect was stronger when an athlete’s particular sport was in season.

We find that varsity sports participation is strongly associated with better student attendance, and we argue it is plausible that varsity sports participation causes better attendance. When we control for a number of factors that we know matter for both sports participation and attendance, we continue to find that varsity athletes are absent less often than their peers across the entire year. Across the school year, athletes’ absence rate was 1.37 points lower than non-athletes’. That’s a reduction of almost 20%. The broad pattern shown in Table 1 is that students from more advantaged groups were more likely to participate in varsity sports and less likely to be absent from school. It’s thus no surprise that, in the raw data, there is an association between playing varsity sports and having good attendance (Figure 3). But is that because students who attend school more reliably are more likely to play sports or because playing sports leads to better attendance? One way to tease out the answer is to compare varsity athletes' attendance during their sports seasons with their attendance the rest of the year. Not only do varsity athletes have lower annual absence rates—especially unexcused absences—than non-athletes, but [Figure 3 and Figure 4] show that their absence rates fall further when their sport is in season, [which suggests at least some causal effect].

Takeaways by Macro Roundup^® AI

Varsity athletes’ absence rates drop 1.37 pts below non-athletes’, a ~20% reduction that drives improved school engagement year-round.
In-season absence rates fall further for varsity athletes, suggesting sports participation directly leads to more reliable attendance patterns.
Athletes from advantaged backgrounds show stronger attendance gains, indicating varsity sports participation compounds existing socioeconomic advantages in school engagement.

Sports Betting Across Borders: Spatial Spillovers, Credit Distress, and Fiscal Externalities

Jacob Goss and Daniel Mangrum Federal Reserve Bank of New York

Date Posted:: March 27, 2026
Is Database:: Database

After the legalization of sports betting in 2018, delinquency rates on a wide range of consumer debts rose, increasing .31pp as of 2025. The delinquency rate for the ~3% of the population that were new gamblers increased by ~10pp driven by those under 40.

Exploiting the staggered roll-out of state-level legalization following the 2018 Murphy v. NCAA decision, we use an extended two-way fixed effects (ETWFE) framework that separately estimates direct treatment effects and cross-border spillover effects. Our first-stage estimates establish that legalization dramatically increases betting activity: average quarterly spending per person rises by roughly $46 from a pre-treatment mean of $2.50, and the share of the population with any sportsbook spending in a quarter increases by 3.1 percentage points. The effects on average spending grow continually over time with no clear evidence of saturation, suggesting the market for mobile sports betting continues to mature years after legalization. At the same time, substantial betting activity occurs in counties where sports betting is not legal but which lie near a legal state, with spillover effects on total spending roughly 14% of the direct effect for counties within 15 miles of a legal state, declining monotonically with distance and approaching zero by 60 miles. These spillovers have real consequences for consumer financial health. Three years after legalization, median credit scores are one point lower and overall delinquency rates increase by 0.31 percentage points following legalization. [Under-40 auto loan delinquency increases by half a percentage point and credit card delinquency by one percentage point, driving the overall increase in delinquency.] Since only about 3.1% of the population takes up betting after legalization, these intent-to-treat estimates would imply that those who are induced to bet due to legalization experience delinquency increases of 10 percentage points.

New York City Government Services: Services for the Unsheltered

Thomas DiNapoli New York State Comptroller

Date Posted:: March 16, 2026
Is Database:: Database

In 2025 New York City spent $81,705 per “street” homeless person, up 262% from 2019 whose numbers increased 26% during that period. This does not include spending on “sheltered” homeless, who are ~97% of the homeless population.

New York City’s unsheltered population increased from 3,588 in FY 2019 to 4,504 in FY 2025 — a 26% increase from pre-pandemic levels. In that time, spending on services for this population has more than tripled, growing from $102 million in FY 2019 to nearly $368 million in FY 2025 (a 262% increase). Its share of spending has also increased, from just under 5% to nearly 9% of total Department of Homeless Services (DHS) spending.

Poverty and Dependency in the United States, 1939–2023

Richard Burkhauser and Kevin Corinth National Bureau of Economic Research

Date Posted:: February 3, 2026
Is Database:: Database

Btw 1939 and 1963, the % of Americans below LBJ’s absolute poverty line (3× the cost of a minimal meal plan), fell from 48.5 to 19.5, driven by rising market income. Post-1964, most (for non-blacks, all) drops were the result of transfers, not earnings.

The major innovation of this paper is to extend a comprehensive and consistent measure of poverty back to 1939, exploiting a quarter century of data before the War on Poverty began. From 1939-1963, absolute poverty fell from 48.5% to 19.5%, a 29 percentage point reduction. This pre-war progress provides important context for previously documented success in reducing poverty afterwards, since it occurred before the major expansion of safety net programs like SNAP, Medicaid, and refundable tax credits. During that 1939–1963 period, it was the growth of market income rather than government transfers net of taxes that reduced poverty rates. In fact, poverty fell no faster in the 24 years after the War on Poverty was declared than in the 24 years before, even when applying the same initial poverty rate to both periods. Our results do not imply that poverty would have necessarily continued to fall at the same rate after 1963 in the absence of the War on Poverty. A pre versus post comparison is conflated by contemporaneous macroeconomic and social changes, such as slower economic growth in the post-1963 period. Conversely, any claim that the War on Poverty was necessary for poverty to decline should be accompanied by an attempt to understand why it had already been falling in the quarter century before it was declared.

The Biggest Fraud in Welfare

Phil Gramm and John Early Wall Street Journal

Date Posted:: December 18, 2025
Is Database:: Database

Counting non-cash benefits as income would reduce the 19.8mm US households defined as poor by 90%. If the $1.4T in annual Federal poverty spending, including non-cash benefits, were distributed in cash to those households, each would receive $70,000.

The government’s failure to count its largess as recipients’ income allows welfare households to blow past the income level above which a working family no longer qualifies for government help. Take a single parent with two school-age children who earns $11,000 annually from part-time work. The government considers this household in poverty because its income is below $25,273. But this family would qualify for benefits worth $53,128. It would receive Treasury checks of $3,400 in refundable child tax credits and $4,400 in refundable earned-income tax credits. The family would also receive Food Stamp debit cards worth $9,216 a year, $9,476 in housing subsidies, $877 of government payments for utility bills, $16,033 to fund Medicaid, $3,102 in free meals at school and $6,624 in Temporary Assistance for Needy Families. All this puts the family’s income at $64,128, or 254% of the poverty level. A hardworking family earning anything like $64,128 in salary wouldn’t be eligible for any of these welfare benefits in four-fifths of the states. Meanwhile, the welfare family would be eligible for another 90 small federal benefits and sundry state and local welfare programs.

Explaining the Widening Divides in US Midlife Mortality: Is There a Smoking Gun?

Christopher Foote, Ellen Meara, Jonathan Skinner, and Luke Stewart National Bureau of Economic Research

Date Posted:: December 17, 2025
Is Database:: Database
Is Important:: Important

The college/non-college life expectancy gap widened from 2.6–6.3 years btw 1992 and 2019, while county mortality inequality jumped 30% to the detriment of rural areas. Smoking by state predicts ~300 extra deaths per 100k for non-college grads, 0 for grads.

The education-mortality gradient has increased sharply in the last three decades, with the life expectancy gap btw people with and without a college degree widening from 2.6 years in 1992 to 6.3 years in 2019. During the same period, mortality inequality across counties rose 30%, accompanied by an increasing rural health penalty. Using county- and state-level data from the 1992–2019 period, we demonstrate that these three trends arose due to a fundamental shift in the geographic patterns of mortality among college and non-college populations. First, we find a sharp decline in both mortality rates and geographic inequality for college graduates. Second, the reverse was true for people without a college degree; spatial inequality became amplified. Third, we find that rates of smoking play a key role in explaining all three empirical puzzles, with secondary roles attributed to income, other health behaviors, and state policies. [An objection is that] the non-college smoking rate declined by somewhat more than the college rate from 1992 to 2019. [The resolution is that] college populations gave up smoking decades before non-college populations did. [The key] college/non-college comparison [is] among 55–64 year-olds, the age group for which the smoking mortality penalty is greatest.

Blacks overrepresented among offenders in nonfatal violent crimes, 29% of offenders vs 12.5% of population. Whites underrepresented, 52.2% of offenders vs 60.4% of population.

The absentee rate of Indiana high school students, ~23% of whom played a varsity sport, was ~20% lower for those who participated in varsity athletics than for non-athletes. The effect was stronger when an athlete’s particular sport was in season.

Does participation in high school sports significantly reduce student absenteeism?

Takeaways by Macro Roundup® AI

Related Articles:

After the legalization of sports betting in 2018, delinquency rates on a wide range of consumer debts rose, increasing .31pp as of 2025. The delinquency rate for the ~3% of the population that were new gamblers increased by ~10pp driven by those under 40.

Related Articles:

In 2025 New York City spent $81,705 per “street” homeless person, up 262% from 2019 whose numbers increased 26% during that period. This does not include spending on “sheltered” homeless, who are ~97% of the homeless population.

Related Articles:

Btw 1939 and 1963, the % of Americans below LBJ’s absolute poverty line (3× the cost of a minimal meal plan), fell from 48.5 to 19.5, driven by rising market income. Post-1964, most (for non-blacks, all) drops were the result of transfers, not earnings.

Related Articles:

Counting non-cash benefits as income would reduce the 19.8mm US households defined as poor by 90%. If the $1.4T in annual Federal poverty spending, including non-cash benefits, were distributed in cash to those households, each would receive $70,000.

Related Articles:

The college/non-college life expectancy gap widened from 2.6–6.3 years btw 1992 and 2019, while county mortality inequality jumped 30% to the detriment of rural areas. Smoking by state predicts ~300 extra deaths per 100k for non-college grads, 0 for grads.

Related Articles:

Takeaways by Macro Roundup^® AI