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Joe SabiaThe Center for Health Economics & Policy Studies (CHEPS) is an interdisciplinary research center that supports impactful, policy relevant scholarship in the areas of health economics and social policy analysis. Housed in the College of Arts & Letters, CHEPS brings together faculty and graduate students engaged in complementary research in the areas of national defense policy, economic demography, the economics of crime and punishment, and the economics of risky health behaviors.  Read more>>

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CHEPS 2021 Pioneering Research

 


Featured Research

city in Texas with covid symbol overlayDid the Statewide Reopening of the Texas Economy Lead to Economic Growth or a Surge of COVID-19?

In the midst of mass COVID-19 vaccination distribution efforts in the U.S., Texas became the first state to abolish its mask mandate and fully lift capacity constraints for all businesses, taking effect on March 10, 2021. The policy announcement elicited immediate, passionate reaction. Proponents claimed that the reopening would generate short-run employment growth and signal a return to normal while opponents argued that it would cause a resurgence of COVID-19 and kill Texans.

A new National Bureau of Economic Research Working Paper, released in June 2021, finds that each side was largely incorrect. This study, written by Dhaval Dave, Samuel Safford, and Joseph Sabia documents several important findings. First, using daily anonymized smartphone data — and synthetic control and difference-in-differences approaches — the study finds no evidence that the Texas reopening led to substantial changes in mobility, including foot traffic at a wide set of business establishments. Second, there is no evidence that the Texas reopening affected the rate of new COVID-19 cases during the five weeks following the reopening. The null results persist across more urbanized and less urbanized counties, as well as across counties that supported Donald Trump and Joe Biden in the 2020 presidential election. Finally, there is no evidence that the Texas reopening impacted short-run employment, including in industries most affected by the reopening. 

"With the medical advancements of vaccines and antibody therapeutic drugs, Texas now has the tools to protect Texans from the virus…. Too many Texans have been sidelined from employment opportunities. Too many small business owners have struggled to pay their bills. This must end. It is now time to open Texas 100%.”
- Texas Governor Greg Abbott, March 3, 2021

" I think it's a big mistake…The last thing -- the last thing we need is Neanderthal thinking that in the meantime, everything's fine, take off your mask, forget it. It still matters.”
- U.S. President Joseph R. Biden, March 3, 2021

 

Will a Higher Minimum Wage Reduce Poverty?Minimum Wage

During the 85 years since the U.S. Supreme Court ruled in favor of the constitutionality of minimum wage laws (West Coast Hotel Co. v. Parrish, 300 U.S. 379 (1937)), advocates of minimum wage increases have consistently touted their potential to reduce poverty. The potential of ever-higher minimum wages to reduce poverty has taken center stage in the recent federal debate over the Raise the Wage Act of 2021. This new legislation, advocated by President Joe
Biden, would more than double the Federal minimum wage from $7.25 to $15 per hour by June 2025, raise the “tipped” minimum wage from $2.13 to $15 per hour by June 2026, and eliminate subminimum wages for younger teenagers and workers with disabilities. According to a February 2021 Congressional Budget Office (CBO) analysis, a $15 minimum wage would directly impact approximately 17 million U.S. workers earning hourly wages below $15, indirectly affect 10 million more who earn wages slightly above $15.

If minimum wage increases boost hourly wages paid to near-poor workers — without causing substantial adverse labor demand effects — such hikes could raise family incomes and lift workers above the poverty line. Moreover, if minimum wage increases boost spending among workers with a higher marginal propensity to consume, they could induce longer-run economic growth that lifts poor workers out of poverty. On the other hand, if minimum wage increases increase labor costs to firms, and low-skilled labor markets are competitive, such hikes could reduce employment and work hours among low-skilled workers. If these employment losses are felt by some poor and near-poor workers, their family incomes could fall, thereby plunging some low-skilled workers into (deeper) poverty. Thus, the impacts of minimum wage increases may resemble income redistribution among poor and near-poor families. Therefore, the net impact of minimum wage increases on poverty rates depends on (i) wage, employment, and hours elasticities with respect to the minimum wage, (ii) the distribution of earnings gains and losses for workers with household incomes near the poverty threshold, and (iii) spillover effects of the minimum wage on output prices and longer-run economic growth.

This study will make three contributions to the minimum wage-poverty literature. First, it will provide new evidence on the impacts of recent, large increases in state minimum increases. While larger increases bring with them the possibility of larger family income gains and poverty rate reductions, such increases may also be accompanied by larger adverse labor demand effects that plunge some families into poverty. Second, we will attempt to reconcile our findings with recent evidence that minimum wage increases enacted prior to the Great Recession were associated with declines in poverty. Finally, to address the current policy discussion over a federal minimum wage increase, we will explore the effectiveness of $15 (and $11) per hour minimum wage in delivering income to the working poor.

“No one should work 40 hours a week and live below the poverty wage. And if you’re making less than $15 an hour, you’re living below the poverty wage.”
- President Joseph R. Biden (2020)


Is Recreational Marijuana a Gateway to Harder Drug Use and Crime?cannibas in glass jar in front of money

Recreational marijuana laws (RMLs), which legalize the possession, sale, and consumption of marijuana for recreational purposes, have been adopted by 18 states and the District of Columbia. RMLs are a relatively recent phenomenon. In November of 2012, Colorado and Washington became the first states to adopt RMLs, but it was not until 2014 that recreational dispensaries, or “pot shops,” opened in these states. More than 6 years later, researchers are just beginning to gauge the public health consequences of legalizing recreational, as opposed to medical marijuana.

Unlike most medical marijuana laws (MMLs), RMLs, do not require a doctor’s recommendation, nor do they require registration. Under RMLs, possession of a limited amount of marijuana (e.g., one or two ounces) by anyone 21 years of age or older is legal, and purchases of marijuana can be made at recreational dispensaries simply by showing proof of age. Most RML states allow marijuana plants to be grown at home. However, in Washington D.C., home cultivation is allowed, but its RML prohibits the exchange of money, goods, or services for marijuana; transfers of up to an ounce of marijuana, are, however, legal.

While support for legalization has increased markedly in the last decade, some policymakers and public health experts have expressed concern that legalization for recreational purposes will, through a gateway effect, encourage the use of “harder” substances such as cocaine, heroin, fentanyl, and methamphetamines, generating substantial public health costs, including drug- related overdoses.

While many of the costs of hard drug use are privately borne to the extent that addiction to hard drugs is rational, there are a number of reasons to expect that some of the costs of hard drug use will not be internalized. For instance, if preferences are time-inconsistent and reflect hyperbolic discounting of future wellbeing, addictive drug use may exceed that which is socially optimal. Moreover, for some younger hard drug users, decision-making over consuming addictive substances may not be rational due to underdevelopment of the prefrontal cortex. Finally, addiction may lead to more crime — i.e., income-generating crime to finance one’s addiction or violent offenses as a result of one’s altered state of mind — thereby imposing costs of hard drug use on to third parties. Together, these external costs of legalization should be weighed against the utility gains from consumption, as well as the cost savings from reduced incarceration, to judge the efficacy of legalization from a social welfare perspective.

This study will be the first to comprehensively examine the impacts of state recreational marijuana laws (RMLs) on a wide set of outcomes related to hard drug use, including illicit non-marijuana related consumption, drug-related arrests, property and violent offenses, substance use disorders, admissions for treatment for hard drug addiction, and mortality due to drug-related overdoses.

Using state-level panel data from 2000- 2019 from a variety of national datasets — the National Survey of Drug Use and Health (NSDUH), the Uniform Crime Reports (UCR), the Treatment Episode Data Set (TEDS), and the Vital Statistics Multiple- Cause-of-Death Mortality Files (MCDMF) — and a difference-in-differences identification strategy, a new research team, including Claremont Graduate University Doctoral Students Abdullah Alswelh and Fawaz Alotaibi (who are from CGU’s Computational Justice Lab) will examine the impact of RMLs on marijuana use, “hard” drug use, substance use disorder, admissions for drug treatment, property and violent crime arrests, and drug-related overdose deaths.

Assessing the effects of RMLs on the use of harder drugs, drug-related overdose deaths, and criminal behavior is critically important. From a social welfare perspective, addiction, crime, and treatment costs may not be taken into account by private actors. Documenting the existence and magnitude of these “external” costs is the first step in assessing the net benefits of RMLs. The findings from this project will provide important information to state and federal policymakers considering the adoption of RMLs as well as those who wish to liberalize access to marijuana while minimizing their negative spillovers.

“There's not nearly enough evidence as to whether or not marijuana is a gateway drug.”
- President Joseph Biden (2021)

“Let's be clear: marijuana isn't a gateway drug and should be legalized.”
- Vice President Kamala Harris (2021)


Are Tobacco-21 Laws Effective?no smoking sign

Tobacco use is the leading cause of preventable death in the United States, responsible for over 480,000 deaths each year. Its consumption has been linked to increased risk of heart disease, cancers of the lung, liver, head, and colon, diminished respiratory function, and stroke (U.S. Department of Health and Human Services 2014). The social costs of tobacco consumption are substantial, with estimates of the annual health care costs of treating tobacco-related illnesses totaling nearly $200 billion. Estimates of the external costs of smoking — driven by exposure to secondhand, or even thirdhand, tobacco smoke — exceed $7 billion.

The vast majority of adult smokers initiate tobacco use as minors, with a mean age of smoking initiation of 15.3. Given that youth smokers (i) are more likely than adults to have time-inconsistent preferences that give insufficient weight to future costs of addiction, (ii) often fail to account for the external costs of smoking when choosing current consumption, and (iii) typically obtain tobacco products via the informal social market, policymakers have often targeted anti-smoking campaigns at youths.

A new National Bureau of Economic Research Working Paper, released in December 2020 by Benjamin Hansen, Drew McNichols, Calvin Bryan, and Joseph Sabia studies the impact of Tobacco-21 laws. Tobacco 21 (T-21) laws prohibit the sale of tobacco products to individuals under age 21. Using data from the 2009-2019 Behavioral Risk Factor Surveillance Survey (BRFSS), the authors find that the enactment of a statewide T-21 law was associated with a 2.5 to 3.9 percentage-point decline in smoking participation among 18-to-20-year-olds. Next, using data from the 2009-2019 State Youth Risky Behavior Surveys (YRBS), they find that statewide T- 21 laws reduced tobacco cigarette and electronic cigarette (e-cigarette) consumption among 18- year-old high school students. Finally, we find that T-21 laws generate important spillovers including (i) a reduction in tobacco cigarette use among 16-to-17-year-olds, a group that relies heavily on the “social market” — including 18-year-old peers — to access tobacco, and (ii) reductions in both marijuana use and frequency of alcohol consumption among older teenagers.

“We should do everything we can to prevent young people from smoking and save lives. Increasing the tobacco age to 21 will help achieve these goals… Increasing the tobacco age to 21 [will also] reduce the likelihood that a high school student will be able to legally purchase tobacco products for other students and underage friends.”
- Campaign for Tobacco-Free Kids (2020)

More Research

capital riotOn January 6, 2020, the U.S. Capitol was sieged by rioters protesting certification of Joseph R. Biden’s election as the 46th president of the United States. The Director of the Centers for Disease Control and Prevention (CDC) quickly predicted that the Riot would be a COVID-19 “surge event.”

In a National Bureau of Economic Research working paper released in February 2021, Dhaval Dave, Drew McNichols, and Joseph Sabia examine the impact of the Capitol Riot on risk-averting behavior and community-level spread of the novel coronavirus. They use anonymized smartphone data from SafeGraph, Inc. and an event-study approach to document that on January 6th there was a substantial increase in non-resident smartphone pings in the census block groups including the Ellipse, the National Mall, and the U.S. Capitol Building, consistent with a large protest that day. Next, using data from the same source and a synthetic control approach, they find that the Capitol Riot increased stay-at-home behavior among District of Columbia residents, indicative of risk averting behaviors in response to violence and health risks.

They find no evidence that the Capitol Riot substantially increased community spread of COVID- 19 in the District of Columbia in the month-long period following the event. This may be due to increases in social distancing and a “virtual lockdown” of the Capitol prior to the inauguration of the new president. Finally, exploiting variation in non-resident smartphone inflows into the January 6 Capitol protest, they find that counties with the highest protester inflows experienced a significant increase in the rate of daily cumulative COVID-19 case growth in the month following the protest. Together, the results of this study suggest important public health costs of the U.S. Capitol Riot. These findings add to our understanding of the large social costs of this insurrection event to the health and wellbeing of the Republic. 

Minimum WageGiving birth as a teenager is associated with increases in the risk of dropping out of high school and living in poverty, while children born to teenage mothers clearly struggle cognitively and economically as compared to children born to older mothers. Although the U.S. adolescent fertility rate has declined substantially since 2007, it is still higher than in any other developed country, and many other policy interventions aimed at reducing childbearing rates have had little effect. CHEPS researchers have begun their investigation of the minimum wage as a potential policy tool for curbing teen pregnancy rates, but there is theoretical possibility to both sides of the argument. By raising the minimum wage, there is the possibility that teenagers may respond to better labor market opportunities by working harder and delaying childbearing. Taken at face value, this hypothesis suggests that raising the minimum wage could substantially reduce the public costs of teenage childbearing, which are estimated to be $9.4 billion per year. 

The current study undertaken by CHEPS researchers employs the most recent years of data which include frequent, large minimum wage increases, in addition to cutting-edge empirical methods that allow for dynamic fertility effects over time that may differ across states that increase their minimum wage, and a thorough exploration the mechanisms through which the minimum wage could have an impact on teen fertility such as the minimum wage’s impacts on the teen marriage rate, abortion rate, and sexual behavior.

In theory, the relationship between minimum wages and teenage childbearing depends upon the employment effect and its magnitude. Teenagers who are laid off (or work fewer hours) after an increase in the minimum wage may find that condoms and other forms of contraception have become unaffordable; those who retain their minimum-wage job and experience an increase in earnings may be more likely to use contraception, purposely postponing becoming a parent. However, it is also possible that teenagers who experience a minimum wage increase may become more financially stable, and thus may be more likely to be interested in settling down and starting a family, thus increasing the teen fertility rate. CHEPS researchers have taken pleasure in thoroughly evaluating what would otherwise be an ostensibly ambiguous conclusion and look forward to contributing their insights to this important policy debate at the intersection of minimum wages and public health outcomes.

E-cigarette and vaping devicesSince first entering American markets in 2006 as an advertised “healthier” version of traditional cigarettes, e-cigarette use has grown dramatically, especially among teens and young adults. The use of electronic nicotine products among high school students has risen from one in four teenagers in 2011 to one in three by 2019. Over this same period, tobacco cigarette use fell by over 50 percent, starkly following an increase between 2003 and 2011. This trend suggests that vaping could be pushing current smokers toward a middle ground between traditional cigarettes and the complete cessation of smoking.

Some policymakers have argued that e- cigarettes might foster safer nicotine addictions than traditional cigarettes since carcinogen exposure is lower for both the smoker and second-hand exposure, though this claim has fallen under scrutiny by public health and medical researchers. Despite the trend suggesting that rising e-cigarette use coincides with declines in tobacco cigarette smoking, public health officials have continued to raise concerns that e- cigarette products might instead be inducing a return to the use of cigarettes, leading policymakers to enact minimum legal purchasing age (MLPA) laws and institute taxes on e-cigarette cartridges.

In order to examine the complicated relationship between taxes, e-cigarette use, and potential substitution to traditional combustible tobacco products, CHEPS has joined forces with leading tobacco-use researchers Catherine Maclean, Michael Pesko, Rahi Abouk, Charles Courtemanche, Abigail Friedman, Bo Feng, and Dhaval Dave to study the impact of electronic cigarette taxes on youth e-cigarette use and “traditional” cigarette consumption.

Using data from both the Monitoring the Future (MTF) and Youth Risk Behavior Surveillance System (YRBS) surveys, the research team seeks to examine both the impact of e-cigarette taxes on different levels of e-cigarette use, as well as the potential spillover effects that vaping has had on current tobacco use.

Follow-up studies involving CHEPS researchers will explore whether the impacts of e-cigarette taxes differ by characteristics of youth — including sexual identity — as well as whether electronic cigarette taxes generate spillovers to other youth risky behaviors, including alcohol use, marijuana use, and harder drug use.

group of teens drinkingContinuing the Center’s interest in examining youth risky behaviors, CHEPS is currently conducting work to assess the efficacy of so-called vertical license laws (VLLs), under which minors (below 21 years of age) are issued vertically oriented drivers licenses or ID cards, before they are eventually given horizontally oriented replacements upon reaching the legal drinking age. Considering the persistent prevalence of youth involvement in alcohol-related traffic fatalities, we believe that this work has real merit for the public well-being. After all, car crashes are the leading cause of death for teens, and, according to the NHTSA, about a quarter of those crashes involve alcohol.

The first VLL was enacted in Colorado in 1994, and by 2009 over 40 states had adopted such policies. The underlying idea of these policies is that the drastic difference in ID appearance between those of legal age and those below should make it easier for alcoholic beverage retailers to quickly determine whether an individual is legally eligible to purchase alcohol.

We seek to analyze this subject by taking advantage of Youth Risky Behavior Surveillance System (YRBS) survey data going back to 1991, employing recent breakthroughs in econometric techniques, and considering data from states that have recently adopted these policies. With current YRBS survey data available to us through 2019, we can test whether VLLs are meeting their policy goals as they become the norm across the country. Additionally, we bring in data from the complementary State-level YRBS, which features a large number of observations across a slightly different collection of states. Combining the State and National YRBS, we can get a better idea of the drinking behavior of teenagers on a national level. Finally, modern statistical techniques (pioneered by Spring CHEPS Seminar speaker Andrew Goodman-Bacon) allow us to more accurately assess the effects of policies enacted with staggered treatment timing. Since VLLS were rolled out gradually by states over the course of 25 years, this project constitutes an ideal opportunity to use some of the new tools available to researchers to shed some light on this policy, which has reasonably broad public safety and health implications.

We plan to push the analysis of these policies past the binary question of whether teens drink alcohol, towards the more relevant questions of binge drinking behavior, drinking and driving, and the channels through which teens obtain their alcohol. Clearly, binge drinking behavior and driving under the influence are important questions as they relate to the broader public health issues associated with alcohol, such as alcoholism, alcohol-related sexual assault, and traffic fatalities. Investigating whether the source of teens’ alcohol is affected by VLLs is similarly important, as the answer to this question allows us to assess whether VLLs have actually changed the underage black market for alcohol, which likely has snowballing effects on these other, larger public health issues.

No Bully signIn 2020, CHEPS Director Joseph Sabia and MA student Alicia Marquez released their paper “Anti- Bullying Laws and Youth Risky Health Behaviors” as a CHEPS working paper. This paper was motivated by the large epidemiological literature suggesting that bullying victimization is causally linked to detrimental behavior among youth. Additionally, the U.S. Department of Health and Human Services has urged districts to adopt a “public health approach” when combating bullying in schools. While bullying is still a large issue in U.S. high schools, with 20 percent of teenagers reporting being victimized by bullying in 2017, the public health implications of bullying victimization led CHEPS researchers to question whether the link between victimization and risky health behaviors was in fact causal or was instead the result of perpetrators’ non-random targeting of vulnerable victims.

Epidemiological studies examining the relationship between bullying victimization and risky health behaviors have treated bullying victimization as exogenous to other unmeasured determinants of behavioral health. This assumption may be problematic for a number of a reasons. While those who are bullied clearly do not choose to be victims, they may be non-randomly targeted by perpetrators. For example, perpetrators may bully those who are more vulnerable, who have fewer social support networks, or who have higher personal discount rates, all of which are characteristics that are difficult-to-observe and also related to risky health behaviors. Bullies may also explicitly target victims who engage in risky behaviors as an observable signal of vulnerability.

This study circumvents empirical challenges faced by prior researchers by exploring the impacts of state anti-bulling laws (ABLs) on risky health behaviors. State ABLs require local school districts to implement anti-bullying policies that (i) identify perpetrators and victims of bullying, (ii) punish, educate, and rehabilitate offenders, and (iii) stigmatize bullying behavior. By increasing the probability of detection, increasing punishment, and reducing the psychic benefits of bullying, ABLs are hypothesized to raise the expected costs of bullying to potential perpetrators, thus curbing its occurrence. We posit that the enactment of state ABLs may generate a plausibly exogenous decline in bullying victimization. Thus, if there is a causal link between bullying victimization and teenage risky behaviors, we might expect such behaviors to decline following ABL enactment.

Using the National and State Youth Risk Behavior Surveys (YRBS) and variation in state level anti-bullying laws (ABL), Sabia and Marquez find that while ABLs are effective in reducing bullying victimization among U.S. high school students, there is no evidence that they lead to economically important or statistically significant changes in teenage binge drinking, tobacco cigarette use, marijuana consumption, risky sexual behavior, or body weight.

group of motorcycles parkedAlongside research on preventative measures to curb the spread of Covid-19, a number of “super spreader” events have been closely scrutinized by both public health researchers and the national media. In this study, Dhaval Dave, Drew McNichols, and Joseph Sabia examined the 80th Annual Sturgis Motorcycle Rally, a 10-day event with dozens of concerts, live performances, races, and bike shows that drew over 460,000 individuals to a city with a population of approximately 7,000 located in a county with a population of approximately 26,000. COVID-19 mitigation efforts at the Sturgis Rally were largely left to the “personal responsibility” of attendees and post-opening day media reports suggest that social distancing and mask-wearing were quite rare in Sturgis.

The Sturgis Motorcycle Rally represents a situation where many of the “worst case scenarios” for superspreading occurred simultaneously: the event was prolonged, included individuals packed closely together, involved a large out-of-town population (a population that was orders of magnitude larger than the local population), and had low compliance with recommended infection countermeasures such as the use of masks. The only large factors working to prevent the spread of infection were the outdoor venue and low population density in the state of South Dakota.

The authors document three key results. First, using anonymized smartphone data from SafeGraph, Inc., we demonstrate that non-resident cell phone pings rose in the census block groups where the Sturgis events look place over the 10-day period of the rally relative to other census block groups within South Dakota and in border states to South Dakota. Furthermore, we find that foot traffic at restaurants and bars, hotels, entertainment venues, and retail establishments in areas hosting Sturgis Rally events rose by up to 90 percent during the event. There was a 9.4 to 10.9 percent decline in median hours spent at home. Finally, turning to COVID-19 case data from the Centers for Disease Control and Prevention (CDC), we find that the Sturgis Rally caused spread of COVID-19 cases both locally and in the home counties of those who traveled to the Sturgis Rally and returned home.

The authors’ findings, published in the Southern Economic Journal, underscore that local COVID- 19-related policy decisions over events that generate large local economic benefits, but diffuse external health costs (such as the decision by South Dakota policy officials to hold the Sturgis event) may not be socially optimal.

Supreme Court sign, law books and gavelOn May 13, 2020, the Wisconsin State Supreme Court struck down Wisconsin’s “Safer at Home Order” in Wisconsin Legislature v. Palm. The force and effect of this legal ruling was dramatic and immediate. The entire statewide order was overturned, making Wisconsin the only U.S. state without a single statewide protective measure in place. Wisconsin’s Governor Tony Evers said that the ruling had “thrown the state into chaos,” and predicted that “people are going to get sick.”

Dhaval Dave, Andrew Friedson, Drew McNichols, Joseph Sabia, and Kyu Matsuzawa released a National Bureau of Economic Research Working Paper in 2020 to identify the causal effect of Wisconsin’s SIPO termination on social distancing and COVID-19 cases.

This study exploits the unique experiment to identify the causal effect of Wisconsin’s SIPO termination on social distancing and COVID-19 cases. First, using anonymized, geospatial smartphone data from SafeGraph, Inc. from May 3 through June 2, and a synthetic control approach, the authors find no evidence that the statewide legal order significantly affected net stay-at-home behavior as measured by the percent of time spent at home full-time (extensive margin) and median hours spent at home (intensive margin). Their analyses of “point of interest” data do, however, suggest some evidence that foot traffic at restaurants and bars rose following the Supreme Court decision.

Then, turning to data on COVID-19 cases and deaths collected by the New York Times from May 3 through June 12, synthetic control estimates fail to detect any evidence that the Wisconsin Supreme Court order affected COVID-19 cases up to a month following the state’s SIPO repeal. This post-treatment period (i) exceeds the incubation period of COVID-19 and (ii) represents a window during which studies of policy shocks or non-household gatherings have detected substantial changes in COVID-19 spread. The authors’ null results are robust to the choice of donor states and to matching variables used to create synthetic weights, including COVID-19 case rates per 100,000 population on all pre-treatment days, urbanicity rate, population density, COVID-19 testing rates, pre-treatment social distancing, and other business reopening policies. In summary, the authors’ findings suggest that the role of information may be particularly important in understanding asymmetry in the health effects of SIPO adoption and repeal.

 

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