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The Demand For Protection and the Persistently High Rates of Gun Violence Among Young Black Males

William Evans National Bureau of Economic Research

Date Posted:: April 25, 2022
Is Database:: Database

Young black males carry guns primarily for protection, creating a high-gun carry equilibrium that is difficult to reverse.

The murder rates for young black males are approximately 10 times higher than those for white males, with 97% of these murders involving guns. Surveys over four decades indicate that young black males carry guns primarily for protection against others who are armed, creating a high-gun carry equilibrium that is difficult to reverse. This situation is exacerbated by the fact that large reductions in the perceived benefits of carrying a gun are necessary to shift back to a low-gun equilibrium. The murder rate for black males aged 15-24 increased by 39.7% from 2019 to 2020, driven largely by gun violence, which rose by 34%. The persistence of this high-gun equilibrium suggests that policy interventions must be substantial and targeted to effectively reduce gun violence in this demographic.

why is the level of violence in the young black male population so high…The murder rates for black men are roughly 10 times higher than the rate for white men in most years…. and how has this level of violence persisted for so long?..The violence in this population is driven by guns. As we outline below, by the end of our sample, 97 percent of murders of young black males are via guns, a rate substantially larger than the rate for the general population. Surveys spanning nearly forty years suggests that young black males carry guns at high rates primarily as protection against others who are also armed...With so many people carrying weapons, disagreements are settled with deadly consequences…To derive specific predictions from our model, we specialize to the case where the two dimensions of a person’s type follow a bivariate normal distribution. If the average instrumental value of carrying a gun is low, gun carry rates are also low. As that value increases, the equilibrium carry rate shifts dramatically. The problem is that returning to a low-gun equilibrium among non-criminals is difficult. The situation can be understood as a coordination failure. Most non-criminals would be better off if everyone stopped carrying guns, but getting there is difficult without a coordinating device. Hence, gun violence persists.The comparative statics are troubling. Once a high gun carry equilibrium is reached, large drops in the benefits of carrying a gun are necessary to revert to a low gun equilibrium. Furthermore, an important asymmetry prevails. The equilibrium gun carry rate, and (by implication in our model) the level of danger and violence, is much more sensitive to changes in the average instrumental value of a gun than its average defensive value, even though the vast majority who arm do so for perceived protection. Our reading of the existing gun policy research suggests these conclusions conflict with real-world policy options in that it has been easier for policy makers to attempt to change the costs of owning guns for non-criminals than criminals. These results suggest the problem may be particularly difficult to solve through legislative means… The homicide rate has ballooned as the COVID-19 pandemic has progressed. In Figure 1, we showed that murder rates increased by 27 percent from 2019 to 2020. Much of this was due to an increase in gun murders, which rose 34 percent compared to 9.4 percent for non-gun murders. Many urban counties have experienced substantially larger increases including Jefferson County, KY, home to Louisville (81.3 percent),Milwaukee County, WI (72.3 percent), Alameda County, CA, home to Oakland (65.2 percent), and Orleans Parish, LA, home to New Orleans (64.2 percent), just to name a few. The groups with the highest murder rates already also had the greatest change in murder rates between 2019 and 2020. Breaking the population into three age groups (15-24, 25-34, 35 and up), four races (white, black, Asian/Pacific Islander, American Indian/Alaskan Native) and 2 genders, there are 24 groups. The three groups that saw the biggest increase in murder rates were white males 15-24 (36.0 percent), black males 25-34 (38.2 percent), and black males 15-24 (39.7 percent). The preliminary data for 2021 looks even worse. Murder counts for the first six months of 2021 are up 13.9 percent over the same time period in 2020.

William Evans and Maciej Kotowski, "The Demand For Protection and the Persistently High Rates of Gun Violence Among Young Black Males,"National Bureau Of Economic Research, April 2022, https://www.nber.org/papers/w29969

“…In Figure 5, the black dashed line reports the fraction of murders of young black males from 1976 to 2019 where an offender is identified in the SHR. This has declined steadily over time from 80 to about 52 percent. In the same graph, the solid line reports the fraction of murders of young black males with known offender where at least one of the offenders is from this same demographic group. This number starts at 44 percent in 1976 rises to 70 percent in 1994 and has been near 60 percent since 2002. When we increase the age range by another decade, the fraction known offenders that are black males ages 15-34 has been hovering around between 77 and 81 percent since 1992…”

Stop And Frisk

“…Third, during the height of SQF use in New York City, murders of young black males fell dramatically. In Figure 15a, we report in solid lines the murder rate for black males 15-24 and 25-34 from New York City while the dotted lines of the same color represent the same numbers for the rest of the country. The police reforms that started in New York City in 1994 occur at a time when the crack epidemic was receding and murder rates for young black males were falling. This makes it difficult to assign how much of the decline is due to SQF or other factors, like mean reversion. That said, the rates for young black males in the rest of the country retreat to their pre-crack levels and do not decline, whereas the decline is dramatic in New York City. In Figure 15b, we report the time series of murder rates in New York City and the rest of the country for everyone who is not a black male 15-34. Here, there is conflicting data on the impact of the SQF program. A result consistent with those favorable to SQF is that New York City had persistently higher murder rates than the rest of the country and starting in 1994, these murder rates drop quickly and are now below the rest of the country. The percent drop in murder rates in New York City for those that are not black males 15-34 is comparable to the drop for younger black males, the primary targets of SQF. This could mean some other policy was impacting murder rates... The model developed in section 3 suggests that once a high-gun carry equilibrium is obtained, it would take a massive reduction in the protective value of guns to return the world to a low gun equilibrium. There may have been no more targeted policing strategy for gun violence among young black males that SQF in New York City. The numbers above suggest it was especially targeted to young black males, but the low yield of arrests, guns and contraband suggest the program was not targeted to likely criminals but to a much larger group. The increased risk of sanction for carrying aweapon along with improved in community safety reduce the attractiveness of guns as a protective means to non-criminals. If we were to make the generous assumption that all of the decline in murders in New York City were attributable to SQF, then this program illustrates the degree to which jurisdictions must police in order to obtain large reduction in the protective value of guns and hence a large reduction in murders. This conclusion is consistent with the relative rigidity of equilibria with respect to changes in… Large and costly interventions along this dimension are necessary to shift outcomes…

“…For completeness, we report in Figure 3 the same graph for white male. The basic time series patterns are quite similar to those of black males. The startling distinction between Figures 2 and 3 is the scale.The murder rates for black men are roughly 10 times higher than the rate for white men in most years. The time series movement in the murder rate for young black males is driven almost exclusively by gun violence. In Figure 4, we report the murder rate, the gun murder rate and the non-gun murder rate for this group since 1968. The non-gun murder rate has fallen steadily since 1968. In contrast, the overall murder rate essentially follows the gun murder rate. Moreover, the fraction of murders attributable to guns is now much higher than 50 years ago, climbing from about three-quarters of murders in 1968 to 98 percent in 2020..”

“…In Figure 2, we report the national time series from 1968 through 2020 for murder rates among black males in three age groups: 15-24, 25-34, and 35-plus. The murder rate for older black men has fallen from 98.3 in 1972 to a low of 21.2 in 2010, a drop of 78 percent. Since 2010, the murder rate in this group has edged up, but is still 63 percent below its peak and 55 percent lower than the 1968 value. The murder rate for black men in the 25-34 age category has been much more volatile, seeing peaks almost every decade. The long term trend is decidedly negative. Between 1968 and 2020, murder rates fell 26 percent. The peak (176.6 in 1972) to trough (67.7 in 2014) changes represents a 62 percent decline. The numbers for young black males follow a completely different series. Between 1978 and 1994 there was a 137 percent increase in murders, then over the next 21 years, murder rates fell by 60 percent. However, the murder rate in 2019 (77) was at about the same as it was in 1968 (81) and the rate and the rate in 2020 (108) is 33 percent higher than in 1968. This is a staggering difference compared to the rest of the country. The rate in 2020 is 17 times what it is for people not in that demographic. Although young black males are about 1 percent of the population, the fraction of murders in this group represented 17 percent of murders in 1994 and 17 percent in 2020…”

Trends in Murder Rates

“…In Figure 1, we graph the national murder rate as reported by the National Vital StatisticsData (NVSD) from 1968 through 2020.The time series was volatile for the first 23 years with peaks in 1974, 1980, and 1992. The national murder rate declined consistently from 1992 through 2015, with a substantial increase after that, especially in 2020 when murder rates for the nation rose by 27 percent, more than twice the second largest annual percent increase in the murder rate in the series. The rate in 2020 is about the same as it was in 1968 and the number for 2019 was 20 percent lower than the value in 1968. In the same graph, we also report the gun and non-gun murder rates. The variation in murders over time is driven mainly by changes in gun murders. Of the increase between 1968 and 1992, 81 percent was attributable to gun violence and of the decline from 1992 to 2015, 65 percent was due to a drop in gun murders. The murder rate for black males differs fundamentally in level and time series than the rest of the country…”

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.

Young black males carry guns primarily for protection, creating a high-gun carry equilibrium that is difficult to reverse.

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