ARE MINIMUM WAGES A SILENT KILLER? NEW EVIDENCE ON FATALITIES Joseph J. Sabia, M. Melinda Pitts, and Laura M. Argys*

Abstract—In volume 94 of this REVIEW, Adams, Blackburn, and Cotti -related traffic fatalities involving teen drivers. (ABC), using Fatal Accident Reporting System data from 1998 to 2006, find that a 10% increase in the minimum wage is associated with a 7% to Across a wide set of specifications, estimated alcohol-related 11% increase in alcohol-related fatal traffic accidents involving teen dri- fatal accident elasticities are very small and consistently vers. We find this result does not hold when the analysis period is indistinguishable from 0 at conventional statistical levels. expanded to include 1991 through 2013. In addition, auxiliary analyses provide no support for income-driven increases in alcohol consumption, Auxiliary analyses of data from the Current Population Sur- the primary mechanism posited by ABC. Together, our results suggest vey (CPS), the Youth Risk Behavior Survey (YRBS), and the that minimum wage increases are not a silent killer. Behavioral Risk Factor Surveillance Survey (BRFSS) also provide little support for ABC’s proposed mechanism of I. Introduction income-induced increases in alcohol consumption. In fact, our results show that minimum wage increases are associated N volume 94, number 3 of this REVIEW. Adams, Black- with modest declines in teen alcohol consumption, likely due I burn, and Cotti (2012, hereafter ABC), use data on fatal to adverse labor demand effects. Together, our results sug- accidents from the Fatality Analysis Reporting System gest that minimum wage increases are not a silent killer. (FARS) between 1998 and 2006 and find that minimum wage increases are associated with increases in alcohol- II. Fatal Accidents Involving Teen Drivers related fatal traffic accidents involving drivers aged 16 to 20.1 They estimate elasticities ranging from 0.72 to 1.1, Our analysis begins with data from FARS, the same which suggest that a 10% increase in the minimum wage source as ABC. The FARS is a census of all accidents on would lead to an additional 115 to 176 fatal accidents invol- U.S. public roads that resulted in one or more fatalities ving teen drivers. These elasticities are surprisingly large within thirty days of the accident. Information from police given much smaller estimates of the impact of the minimum reports, medical records, driver licensing registries, state wage on earnings.2 The authors’ findings persist after con- highway departments, and medical examiners is combined trolling for changes in non-alcohol-related teen fatal acci- to provide a detailed picture of drivers, vehicles, and the dents, which they interpret as evidence that minimum wage circumstances surrounding each fatal accident.3 hikes increase alcohol consumption. We draw data from 1991 to 2013 and estimate an empiri- We reinvestigate ABC’s intriguing finding over a longer cal model identical to that of ABC: time period that includes many large state and federal mini- 1 0 mum wage increases, 1991 to 2013, and find little support for U ðÞ¼Fst Xstb1 þ b2MWst þ gs þ dt þ lst; (1) the claim that higher minimum wages lead to an increase in where Fst is the alcohol-related fatal accident rate for dri- vers ages 16 to 20 in state s during year t, using the National Received for publication February 10, 2017. Revision accepted for - lication December 11, 2017. Editor: Amitabh Chandra. Highway Traffic Safety Administration (NHTSA) imputed * Sabia: San Diego State University, University of New Hampshire, values when there is missing information on the blood alco- ESSPRI, and IZA; Pitts: Federal Reserve Bank of Atlanta; Argys: Univer- 4 hol content (BAC) of drivers ; Xst is a vector of controls sity of Colorado Denver and IZA. We thank Dhaval Dave, Jesse Hinde, and participants at the European used in the ABC study (beer taxes, BAC .08 driving law, Health Economics Association meetings at the University of Hamburg in teen unemployment rate, per capita income, non-alcohol- Hamburg, Germany, and the International Health Economics World Con- related teen traffic accidents, and state population); MW is gress at Trinity College in Dublin, Ireland, for useful comments and sug- st gestions on an earlier draft of this paper. J.S. acknowledges grant funding the higher of the state or federal minimum wage (averaged from the Charles Koch Foundation used to support graduate research over the calendar year in 2006 dollars); Zs is a time-invar- assistants on this project at the University of New Hampshire and San iant state effect; d is a state-invariant year effect; and F1 Diego State University. We thank Brittany Bass, Thanh Tam Nguyen, and t Timothy Young for excellent research assistance. The views expressed here are our own and do not necessarily represent the views of the Federal 3 The intent of including BAC reports in the FARS data is to provide an Reserve Bank of Atlanta or the Federal Reserve System. accurate measure of alcohol content and the frequency of alcohol- A supplemental appendix is available online at http://www.mitpress impaired accidents. In the FARS data, 53.2% of all drivers involved in journals.org/doi/suppl/10.1162/rest_a_00761. fatal accidents since 1991 included no BAC test result. For these drivers, 1 This age range includes typical drivers below the . an imputed BAC, which depends on a number of observed characteristics, Though this group includes 20-year-olds, following ABC we refer to including driver age, gender, and driving record, an indicator of the tim- these as ‘‘teen drivers’’ throughout the paper. ing and nature of the crash, and an indicator that the officer at the scene 2 An extensive body of literature suggests that estimated hourly earn- suspected alcohol involvement, is estimated (see Subramanian, 2002, and ings elasticities with respect to the minimum wage range from 0.1 to 0.2 Subramanian & Utter, 2003, for a description of the imputation process). in recent studies of teens (Allegretto, Dube, & Reich, 2011; Neumark & 4 ABC describe their dependent variable as ‘‘the number of fatal acci- Wascher, 2008; Sabia, 2009). The magnitude of ABC’s estimated alco- dents in a state for which a 16- 20-year-old had a blood alcohol concentra- hol-related fatal accident elasticity is nearly four times larger than the tion that was greater than 0.’’ We infer that they count accidents in which expected hourly earnings elasticity. a 16- to 20-year-old driver has a positive BAC.

The Review of Economics and Statistics, March 2019, 101(1): 192–199 Ó 2019 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology doi:10.1162/rest_a_00761

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TABLE 1.—SUMMARY STATISTICS Means (Standard Deviation) [N] FARS (annual state-level counts for drivers ages 16–20) Average imputed alcohol-related fatal accidents 30.764 (33.273) [1,173] Total fatal accidents 129.15 (131.05) [1,173] Nighttime fatal accidents 70.633 (75.072) [1,173] Daytime fatal accidents 57.848 (56.615) [1,173] Weekend fatal accidents 58.219 (61.750) [1,173] Weekday fatal accidents 70.263 (69.541) [1,173] YRBS (individuals ages 16–18) Alcohol consumption in last 30 Days 0.486 (0.500) [640,017] in last 30 days 0.313 (0.464) [666,035] Binge drinking 3 or more times in last 30 days 0.147 (0.354) [666,035] Drunk driving 0.140 (0.347) [651,680] BRFSS (individuals ages 18–20) Alcohol consumption in last 30 days 0.418 (0.493) [114,958] Binge drinking in last 30 days 0.212 (0.409) [113,735] Binge drinking 3 or more times in last 30 days 0.106 (0.308) [113,735] Drunk driving 0.034 (0.180) [60,729] CPS (individuals ages 16–20) Hourly earnings/employment 7.29 (4.53) [233,336] Usual weekly earnings 80.33 (144.70) [588,180] Employment 0.384 (0.486) [588,180] Usual weekly hours/employment 26.72 (12.42) [233,336] Independent variables (state-level characteristics) MW (2006$) 6.19 (0.58) [1,173] Non-alcohol-related fatalities 98.385 (100.03) [1,173] rate per individual ages 16–20 0.0003 (0.0001) [1,173] State population 5,618,179 (6,268,267) [1,173] Beer tax (2006$) 0.284 (0.229) [1,173] .08 BAC law 0.626 (0.484) [1,173] Per capita personal income 31,552.62 (9,487.44) [1,173] Unemployment rates ages 16–20 (%) 15.863 (5.525) [1,173] Estimates from the BRFSS and CPS are weighted using relevant survey-provided sample weights. Estimates from the YRBS are weighted using SEER population weights.

TABLE 2.—ESTIMATES OF EFFECT OF MINIMUM WAGE ON ALCOHOL-RELATED TRAFFIC FATALITIES FOR INDIVIDUALS AGES 16 TO 20, 1991–2013 OLS with Transformed WLS with Transformed WLS with Dependent Variable Dependent Variable Log-Log (1) (2) (3) Average imputed alcohol-related fatal accidents 0.012 0.006 0.129 (0.011) (0.007) (0.135) Total fatal accidents 0.001 0.001 0.035 (0.003) (0.003) (0.035) Nighttime fatal accidents 0.002 0.001 0.023 (0.006) (0.006) (0.076) Daytime fatal accidents 0.004 0.003 0.016 (0.006) (0.004) (0.068) Weekend fatal accidents 0.006 0.005 0.114 (0.006) (0.006) (0.089) Weekday fatal accidents 0.003 0.003 0.051 (0.004) (0.004) (0.044) N 1,173 1,173 1,173 Significant at ***1%, **5%, and *10%. Data are drawn from 1991–2013 Fatality Accident Reporting System (FARS). All regressions include both state and year fixed effects, and controls for the unemployment rate for 16 to 20-year-olds, the presence of a .08 BAC law; state beer tax, teen unemployment rate, natural log of per capita income; natural log of state population; and natural log of the teen non-alcohol-related fatal accident rate. Standard errors (in parentheses) are clustered at the state level to allow for arbitrary patterns in heteroskedasticity and correlation in errors over time in a given state. If there was a count of 0 drunk- driving-related traffic fatalities, the count of fatalities was recoded as 0.1. is an inverse normal function.5 Summary statistics for fatal Log-Log). Standard errors clustered at the state level are in accidents, minimum wage, and state-level characteristics parentheses in each table (Bertrand, Duflo, & Mullainathan, are reported in table 1. 2004). Following ABC, we estimate equation (1) via an ordinary Table 2 presents our teen fatality results over the 1991 to least squares (OLS) grouped-probit estimator with state and 2013 period. In sharp contrast to ABC, we find no evidence year fixed effects (OLS with Transformed Dependent Vari- that minimum wage increases affect teen alcohol-related able) and weighted least squares (WLSwithTransformed fatal accidents. Estimated policy impacts are 75% to 80% Dependent Variable). We also estimate a more traditional smaller than those obtained by ABC and are never statisti- log-log specification via weighted least squares (WLS with cally distinguishable from 0 at conventional levels. The dif- ference in findings with ABC can be explained almost 5 Means of these variables appear in table 1. entirely by the addition of the 2007 to 2013 later period.

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FIGURE 1.—MINIMUM WAGE CHANGES IN THE UNITED STATES, 1991–2013

These counts include only binding minimum wage increases.

This is not surprising given that there is far more state mini- hol consumption and increased drunk driving. This mechan- mum wage variation in the post-2006 period than during ism is plausible, but it ignores other possible offsetting the 1991–1997 period (see figure 1).6 effects. If some workers lose their jobs after minimum wage In the remaining rows of table 2, we examine alternative hikes or if retained workers have their hours reduced, the measures of the dependent variable that do not rely on imputa- net effect of minimum wage increases on youth earnings is tion of alcohol involvement for crashes in which the driver’s ambiguous, and the effects on drinking and driving will be BAC is not reported. Previous research has used the total num- dependent on the impact of these effects on the distribution ber of fatal accidents involving teen drivers (row 2), as well as of income. Moreover, adverse employment effects could nighttime (row 3) and weekend (row 5) fatal accidents as a have an impact on parental monitoring and time spent in proxy for alcohol-related fatalities.7 Across each of these out- alcohol-related social activities.8 comes, we find no evidence that minimum wage increases are To understand the potential mechanisms through which associated with an increase in teen fatal accidents. We also minimum wages could affect traffic fatalities, we analyze find no evidence that minimum wages are related to daytime labor market outcomes and alcohol-related behaviors fol- (row 4) or weekday (row 6) teen fatal accidents. lowing the same identification strategy as ABC:

Yist ¼ b þ b MWst þ b Zit þ b Xst þ hs þ st þ eist; (2) III. Mechanisms: Income and Alcohol 0 1 2 3

where Yist is a measure of the labor market outcome or A. Approach alcohol-related behavior of individual i residing in state s at year t; Z is a vector of individual demographic controls ABC argue that minimum wage hikes will increase the it including age, race/ethnicity, and gender; and, as before, X earnings of young individuals, and because alcohol is a nor- st is a vector of the state-specific controls used in the ABC mal good, these earnings gains will result in increased alco- study. For dichotomous outcomes we estimate probit models, and for continuous outcomes we use OLS. All regressions are 6 Figure 1 shows the number of states changing their minimum wage each year and, in the lower panel, adds in the number of states experien- weighted by the relevant age-specific state population. cing a change when the federal minimum was increased above their state minimum. There are 379 minimum wage changes in the 1991–2013 per- iod, 166 of which are changes due to state legislatures that increased their B. Earnings and Employment Effects MWs above the prevailing federal MW. The federal minimum wage increases in 1991, 1996–1997, and 2007–2009 are largely captured in the First, we draw data from the Current Population Survey model’s year effects, but do contribute some identifying variation due to (CPS), the workhorse of the U.S. minimum wage literature. differential increases within states due to heterogeneous state minimum wages at the time of the federal increase. 7 Previous research has used weekend and nighttime fatalities as a 8 ABC try to mitigate these channels by controlling for the teen unem- proxy for alcohol-related fatalities (Chaloupkka, Saffer, & Grossman, ployment rate. However, some teens could have dropped out of the labor 1993; Ruhm, 1996; Dee, 1999; Young & Bielinska-Kwapisz, 2006; Free- force in response to a minimum wage increase. Moreover, estimating the man, 2007; Anderson, Hansen, & Rees, 2013; Yadov & Kobayashi, total impact of the minimum wage, including employment-related chan- 2015). nels, is arguably the more relevant policy parameter.

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TABLE 3.—ESTIMATES OF THE EFFECTS OF MINIMUM WAGE ON LABOR MARKET 0.02 in column 3), consistent with the prior literature (see OUTCOMES, 1991–2013 Neumark & Wascher 2008; Sabia, Burkhauser, & Hansen, Ages Ages Ages 2012, 2016). We also uncover some evidence that, condi- 16–20 16–18 18–20 tional on employment, minimum wage increases are asso- (1) (2) (3) ciated with a decline in usual hours of work (row 4), parti- Ln hourly earnings/employment 0.017*** 0.025*** 0.010** cularly for older teens (column 3). (0.004) (0.005) (0.004) The results in table 3 are consistent with minimum N 233,336 116,078 165,830 Usual weekly earnings 1.347 1.120*** 1.835 wage–induced income redistribution among teens rather (0.868) (0.392) (1.514) than any net income gains for teens overall. Thus, in order N 588,180 374,264 330,433 to explain the findings of ABC, the distribution of earnings Employment 0.006** 0.009*** 0.001 (0.002) (0.003) (0.003) gains and losses would have had to change in such a way as N 588,180 374,264 330,433 to increase alcohol consumption and drunk driving. Usual weekly hours/employment 0.227* 0.155 0.314** (0.124) (0.143) (0.155) N 233,336 116,078 165,830 C. Alcohol Effects Significant at ***1%, **5%, and *10% level. Data are drawn from the 1991–2013 Current Population Survey (CPS) Outgoing Rotation Groups (ORG). All regressions include both state and year fixed effects, the presence of a .08 BAC law, state beer tax, teen unemployment rate, natural log of per capita To examine the effect of minimum wages on alcohol income, natural log of state population, and natural log of the teen non-alcohol-related fatal accident rate. 11 With the exception of the employment regressions, all models also control for the unemployment rate for use, we turn to the National and State Youth Risk Beha- 16- to 20-year-olds. Estimates are weighted and standard errors corrected for clustering on the state are vior Survey (YRBS) and the Behavior Risk Factor Surveil- in parentheses. lance Survey (BRFSS).12 The YRBS is coordinated by the These data have been widely used to estimate the effects of Centers for Disease Control and Prevention (CDC) and 9 is administered as an in-school survey to high school stu- minimum wages on labor market outcomes. To parallel the 13 FARS analysis, we focus on the 1991–2013 period.10 Table dents attending ninth through twelfth grades. When weighted, these estimates are representative of the popula- 3 shows estimates of the effect of minimum wage increases 14 on the natural log of hourly wages of teen workers (row 1), tion of U.S. high school students. While the YRBS largely unconditional weekly earnings (row 2), employment (row 11 One recent working paper, using Canadian data, compares drinking 3), and hours worked among employed individuals (row 4). patterns among youths employed in sectors covered by minimum wages We present results for 16- to 20-year-olds (column 1); to drinking patterns of those not employed or employed in uncovered sec- younger teens, ages 16 to 18 (column 2); and older teens, tors. Stro¨bel, Peden, and Forget (2014) find little evidence that employ- ment in the covered sector is associated with increased frequency of alco- ages 18 to 20 (column 3) to match our alcohol analysis. hol use but some evidence of increased drunkenness. We find consistent evidence that minimum wage 12 As Anderson (2010) and Sabia and Anderson (2016) show, combin- increases are associated with increases in the hourly earn- ing the national and state YRBS maximizes the amount of state-level pol- icy variation available for identification given that some states do not ings of employed teenagers (row 1, table 3). The implied appear in the national YRBS but do appear in the state YRBS and vice wage elasticity with respect to the minimum wage is versa. approximately 0.10 for the full sample, but over twice as 13 Our National and State Youth Risk Behavior Survey (YRBS) data were obtained from the Centers for Disease Control and Prevention. Data large for younger teens (0.15) as compared to older teens from some states were obtained through restricted-use contractual (0.06). Thus, higher minimum wages did raise the earnings arrangements with state departments of health and human services and of some employed teens. education. We used data from all states provided to the national YRBS data set. From the state YRBS, our data included information from the Despite these wage gains for employed teens, we find no following states: Alabama (1991–2013), Alaska (1995–2013), Arizona evidence that minimum wage hikes are associated with (2003–2013), Arkansas (1995–2013), Colorado (2005–2011), Connecticut increases in unconditional weekly earnings (table 3, row 2), (1997–2013), Delaware (1999–2013), Florida (2001–2013), Georgia (1991–2013), Idaho (2001–2013), Illinois (2007–2013), Indiana (2003– the primary mechanism for increased alcohol consumption 2011), Iowa (2005–2011), Kansas (2005–2013), Kentucky (2003–2013), posited by ABC. The lack of net earnings gains can be Louisiana (2007–2013), Maine (1995–2013), Maryland (2005–2013), explained by adverse labor demand effects, as shown in the Massachusetts (1993–2013), Michigan (1997–2013), Mississippi (1993– 2013), Missouri (1995–2013), Montana (1993–2013), Nebraska (1991– final two rows of table 3. First, we find evidence that mini- 2013), Nevada (1993–2013), New Hampshire (1993–2013), New Jersey mum wage increases significantly reduce the employment (2001–2013), New Mexico (1991–2013), New York (1997–2013), North of teenagers (row 3, column 1). We estimate an employ- Carolina (1993–2013), North Dakota (1999–2013), Ohio (1993–2013), Oklahoma (2003–2013), Pennsylvania (2009), Rhode Island (1997– ment elasticity that is larger and more negative for younger 2013), South Carolina (1991–2013), South Dakota (1991–2013), Tennes- as compared to older teens (0.20 in column 2 versus see (1993–2013), Texas (2001–2013), Utah (1991–2013), Vermont (1993–2011), Virginia (2011–2013), West Virginia (1993–2013), Wisconsin (1993–2013), and Wyoming (1995–2013). Interested research- 9 These labor market outcomes include wages (Autor, Manning, & ers may contact the relevant state agencies and the CDC to obtain the Smith, 2016), personal earnings and household income (Neumark et al. above data. 2005; Dube 2013; Sabia 2014b), employment (Burkhauser et al. 2000; 14 To further address issues with combining the national and state Dube, Lester, & Reich, 2010; Allegretto et al., 2011; Neumark, Salas, & YRBS data sets, we collected state-by-year population data from the Wascher, 2014; Sabia 2014a), and work hours (Burkhauser, Couch, & National Cancer Institute’s Surveillance Epidemiology and End Results Wittenburg, 2000). Program (http://seer.cancer.gov/popdata/). We used these data to assign 10 Means from the dependent variables in the CPS sample are reported population weights to each respondent based on state of residence, age, in table 2. gender, and race.

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TABLE 4.—ESTIMATES OF EFFECTS OF MINIMUM WAGE ON ALCOHOL CONSUMPTION AND DRUNK DRIVING, 1991–2013 YRBS BRFSS Ages 16–18 Ages 18–20 All Employed Nonemployed (1) (2) (3) (4) Alcohol consumption in last 30 days 0.002 0.021*** 0.020** 0.019** (0.007) (0.007) (0.010) (0.008) N 640,017 114,958 48,503 65,836 Binge drinking in last 30 days 0.002 0.011 0.005 0.012 (0.005) (0.008) (0.009) (0.010) N 666,035 113,735 47,956 65,164 Binge drinking 3 or more times 0.004 0.006 0.006 0.005 in last 30 days (0.006) (0.005) (0.009) (0.005) N 666,035 113,735 47,956 65,164 Drunk driving 0.004 0.003 0.005 0.003 (0.004) (0.002) (0.005) (0.002) N 651,680 60,729 26,770 33,644 Significant at ***1%, **5%, and *10%. Data are drawn from the 1991–2013 Youth Risk Behavior Surveys (YRBS) and Behavioral Risk Factor Surveillance Survey (BRFSS). All regressions include both state and year fixed effects, and controls for the unemployment rate for 16- to 20-year-olds, the presence of a .08 BAC law, state beer tax, teen unemployment rate, natural log of per capita income, natural log of state population, and natural log of the teen non-alcohol-related fatal accident rate. Estimates are weighted and standard errors corrected for clustering on the state are in parentheses.

comprises those ages 14 to 18, we focus on a sample of with 95% confidence. For 18- to 20-year-old respondents to 16- to 18-year-olds, the younger half of individuals in the BRFSS, we find that minimum wage increases are asso- ABC’s treatment group.15 ciated with a statistically significant decline in alcohol con- The BRFSS is an analogous health survey to the YRBS sumption, as measured on the extensive margin. A $1 but is administered by telephone to adults ages 18 to 99. increase in the minimum wage (in 2006 dollars) is asso- We draw a sample of respondents ages 18 to 20 to mirror ciated with a 2.1 percentage point decline in the probability the older teenagers captured in ABC’s treatment group. of prior thirty-day drinking (column 2). This represents When weighted, the BRFSS is designed to be representative about a 5.0% decline relative to the mean and corresponds of the U.S. population.16 to a drinking elasticity with respect to the minimum wage Both the YRBS and the BRFSS gather information on of 0.31. This decline may be explained by minimum alcohol consumption, heavy drinking, and driving after wage–induced earnings losses caused by adverse labor drinking in the thirty days prior to the survey. We generate demand effects. dichotomous indicators for prior thirty-day alcohol consump- An important advantage to the BRFSS over the YRBS is tion, prior thirty-day binge drinking (five or more alcoholic that these data include information on teen employment. beverages in a single sitting for males and four or more alco- While caution should be taken in interpreting results strati- holic beverages for females), prior thirty-day binge drinking fied by an endogenous variable, it is interesting to note that on at least three occasions, and driving after drinking. drinking declines are observed among employed (column Table 4 presents our findings on alcohol use. We find no 3) and nonemployed (column 4) teens. This result is consis- evidence that minimum wage increases affected prior tent with adverse employment and conditional hours effects thirty-day alcohol consumption among 16- to 18-year-old or, perhaps, a mechanism related to the increased opportu- high school students in the YRBS (row 1, column 1). The nity cost of time spent in alcohol-related social activities. precision of this estimate is such that we can rule out posi- Most important, there is little support for ABC’s hypothesis tive drinking participation elasticities of greater than 0.20 that higher minimum wages increase alcohol consumption among all or employed teens. In rows 2 and 3, we explore another margin of alcohol 15 There are a few drawbacks of the YRBS worthy of note. First, there is no information on employment or income in the YRBS, so we cannot consumption, binge drinking, which a number of studies examine the effect of minimum wage increases on drinking-related beha- have linked to both drinking and driving behavior and traf- viors separately for those who remain employed. Second, because the fic fatalities.17 We find no evidence that minimum wage YRBS is a school-based survey, there may be sample selection bias intro- duced if minimum wages affect the distribution of teenagers who remain hikes increase the probability of binge drinking in the past in school and if this selection process is related to alcohol consumption. month (row 2) or binge drinking three or more times in the However, the literature provides little consistent evidence that minimum past month (row 3). Estimated effects are uniformly nega- wage increases affect high school dropout rates (see, e.g., Sabia, 2015, for a discussion). tive and statistically insignificant. Together with our find- 16 There are several advantages to the BRFSS over the YRBS. First, ings in row 1, these results suggest that minimum wage because it is not a school-based sample, we avoid concerns that minimum wages change the composition of students remaining in school. Second, while the YRBS is an unbalanced panel of states and years (see Sabia & 17 Duncan (1997) and Duncan et al. (1999) link binge drinking to drunk Anderson, 2016; appendix tables 1 and 2), states represented in BRFSS driving. Carpenter (2007) and Carpenter, Dobkin, and Warman (2016) appear fairly continuously over the 1991–2011 period, allowing us to link traffic fatalities to extreme drinking at the upper end of the binge- exploit identifying variation closest to that used by ABC. drinking range.

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increases are associated with declines in light to moderate lized, there is no significant minimum wage effect found in drinking participation among teens, but not heavier, more any of these models. frequent drinking most associated with drunk driving. Third, we estimate the impact of minimum wage Finally, we explore whether minimum wages affected increases on alcohol-related fatal accident rates for 16- to the likelihood of drinking and driving.18 For younger teens, 17-year-olds, 18-year-olds, and 19- to 20-year-olds sepa- estimated elasticities are negative, while for older teens rately to test for heterogeneity in effects by age near the they are positive, but in all cases, the estimated elasticities time of high school graduation. We uncover no evidence are statistically indistinguishable from 0. that minimum wage increases affected fatal accident rates for any of these subgroups. Fourth, we examine the earnings, employment, and alco- IV. Sensitivity Analysis hol effects of higher minimum wages during the ABC per- iod (1998–2006). It could be that minimum wages increased Our findings suggest that the ABC results are largely alcohol consumption during the period when ABC find idiosyncratic. They appear to be tied to a specific time win- large increases in alcohol-related traffic fatalities. While we dow with no changes in the federal minimum wage and find that labor market effects are similar in the 1998–2006 without strong support for an underlying mechanism. We and 1991–2013 periods, there is even stronger evidence of undertake a number of sensitivity tests to explore the minimum wage–induced declines in teen alcohol consump- robustness of the above finding, which are available on tion during the ABC period. request. First, we examine the sensitivity of estimated mini- Next, we explore other drinking margins that could have mum wage effects to additional controls, including cigarette been affected by higher minimum wages: (a) the intensive taxes, zero-tolerance drunk driving laws, vertical ID cards margins of alcohol consumption and drinking-and-driving, that identify underage card holders, false ID laws with scan- measured by the frequency of these activities and (b) drink- ner provisions, repeals of Sunday sales bans, prescription ing effects for the least-skilled 18- to 20-year-olds without drug monitoring programs, medical and recreational access a high school diploma. We find no evidence that minimum to marijuana, and state-specific linear time trends. The find- wage increases are associated with an increase in frequency 19 ings are qualitatively similar. We also experiment with of binge drinking and number of drinks consumed. And omitting ABC’s control for the teen unemployment rate in when we examine those 18- to 20-year-olds without a high fatal accident regressions to more fully capture the mini- school diploma, we find that minimum wage increases mum wage’s net impact. Fatal accident elasticities with are negatively related to the probability of drinking and respect to the minimum wage are smaller in these specifica- driving. tions and, as expected, are never statistically distinguishable Finally, given that teen drivers involved in alcohol- from 0 at conventional levels. related fatal accidents are overwhelmingly male (National Second, we examined the sensitivity of results to imputa- Highway Traffic Safety Administration, 2009, 2013), we tion of alcohol-related fatalities by estimating models that examine the alcohol effects of minimum wage increases by counted fatal accidents without using imputation (assigning gender. Estimated effects for both males and females are a 0 to fatal crashes with a missing BAC report) as well as largely small in magnitude, negative in sign, and statisti- using a more liberal imputation method (assigning a 1 to cally indistinguishable from 0. fatal crashes with a missing BAC report and any positive predicted probability of BAC over 0). Regardless of the measure of alcohol involvement in the fatal accident uti- V. Conclusion 18 It should be noted that in the BRFSS, in contrast to the alcohol con- An intriguing study by ABC concluded that minimum sumption questions that are asked every year, the drunk-driving question is asked only in alternate years after the 2000 interview. Although the wage increases have the unintended deadly consequence of alcohol consumption questions are quite similar for the YRBS and the substantially increasing alcohol-related fatal accidents BRFSS, the same is not true of the drinking and driving questionnaire involving teen drivers. This research explores the robust- items. YRBS: ‘‘During the past 30 days, how many times did you drive a car or other vehicle when you had been drinking alcohol? (Possible ness of the ABC estimates to the period under study and the Responses: 0 to 6 or more).’’ BRFSS: ‘‘During the past 30 days, how mechanisms through which such a causal link might exist. many times have you driven when you’ve had perhaps too much to drink? Using data from the FARS from 1991 to 2013, we find (Responses include 0 to 30 days).’’ The BRFSS questionnaire item could be problematic given that the responses do not refer to an objective drink- no evidence that minimum wage increases led to an ing standard, but instead requires respondents to judge whether they have increase in alcohol-related fatal accidents involving teens. driven when they ‘‘had perhaps too much to drink.’’ Geographic-specific Our estimated elasticities are 75% to 80% smaller than changes in societal attitudes toward what it means to have had ‘‘too much to drink’’ could, at least in theory, be related to labor policy changes such those obtained by ABC and are uniformly statistically indis- as increases in the minimum wage. tinguishable from 0. These findings persist when we exam- 19 Employment effects are noticeably affected by the inclusion of con- ine all fatal accidents involving teens, as well as those trols for state-specific linear time trends, consistent with much of the minimum wage literature (Neumark et al., 2014; Neumark & Wascher, occurring on weeknights versus weekdays and nighttime 2017; Allegretto et al., 2011). versus daytime.

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Analyses of the CPS, YRBS, and BRFSS provide little Bertrand, Marianne, Esther Duflo, and Sendhil Mullainathan, ‘‘How Much Should We Trust Difference and Difference Estimates?’’ support for the primary mechanism posited by ABC: Quarterly Journal of Economics 119 (2004), 249–275. income-induced increases in alcohol consumption. First, Burkhauser, Richard V., Kenneth A. Couch, and David C. Wittenburg, because of adverse employment and hours effects, we find ‘‘Who Minimum Wage Increases Bite: An Analysis Using that minimum wage increases redistributed income among Monthly Data from the SIPP and CPS,’’ Southern Economic Jour- nal 67 (2000a), 16–40. teens rather than increased their net income. Second, we ———. ‘‘A Reassessment of the New Economics of the Minimum Wage find no evidence that minimum wage hikes increased teen Literature with Monthly Data from the Current Population Sur- alcohol consumption but, rather, some evidence they were vey,’’ Journal of Labor Economics 18 (2000b), 653–680. Carpenter, Christopher S., ‘‘Heavy Alcohol Use and Crime: Evidence associated with declines in drinking at the extensive margin from Underage Drunk-Driving Laws,’’ Journal of Law and Eco- among 18- to 20-year-olds. nomics 50 (2007), 539–557. A number of data limitations in our study are worthy of Carpenter, Christopher S., Carlos Dobkin, and Casey Warman, ‘‘The Mechanisms of Alcohol Control,’’ Journal of Human Resources 51 note. As ABC note, missing information on drivers’ BAC in (2016), 328–357. the FARS could lead to mismeasurement of alcohol-related Chaloupka, Frank J., Henry Saffer, and Michael Grossman, ‘‘Alcohol- fatal accidents, which could, at least in theory, be related to Control Policies and Motor-Vehicle Fatalities,’’ Journal of Legal Studies 22:1 (1993), 161–186. minimum wages. In addition, the YRBS lack data on Dee, Thomas S., ‘‘State Alcohol Policies, Teen Drinking and Traffic employment, which preclude us from estimating the impacts Fatalities.’’ Journal of Public Economics 72 (1999), 289–315. of minimum wages on drinking behaviors of employed Dube, Andrajit, ‘‘Minimum Wages and the Distribution of Family Incomes,’’ University of Massachusetts–Amherst working paper (2013). younger teens. And, because 16- and 17-year-olds in the Dube, Andrajit T., William Lester, and Michael Reich, ‘‘Minimum Wage YRBS sample are all high school students (per the survey Effects across State Borders: Estimates Using Contiguous Coun- design), we are unable to analyze drinking affects among ties,’’ this REVIEW 92 (2010), 945–964. Duncan, David, ‘‘Chronic Drinking, Binge Drinking and Drunk Driving,’’ 16- to 17-year-old dropouts. Moreover, drinking and driving Psychological Reports 80 (1997), 681–682. measures differ in the YRBS and BRFSS in ways that could Duncan, David, Joseph Donnelly, Thomas Nicholson, and John White, generate differing results. Finally, the FARS data do not per- ‘‘Chronic Drinking, Binge Drinking and Drunk Driving II,’’ Psy- chological Reports 84 (1999), 145–146. mit us to examine alcohol-related accidents not involving a Freeman, Donald, ‘‘Drunk Driving Legislation and Traffic Fatalities: New fatality, nor do they contain information on employment and Evidence on BAC08 Laws,’’ Contemporary Economic Policy 25 earnings histories of drivers that would permit estimation of (2007), 293–308. National Highway Traffic Safety Administration, ‘‘Traffic Safety Facts effects of minimum wages on affected workers. (2008 Data): Young Drivers,’’ DOT HS 811 169 (2009), http://www Despite these limitations, the results of our study cast -nrd.nhtsa.dot.gov/Pubs/811169.pdf. doubt on the policy conclusions of ABC. The lack of evi- ——— ‘‘Traffic Safety Facts (2012 Data): Alcohol-Impaired Driving,’’ DOT HS 811 870 (2013), http://www-nrd.nhtsa.dot.gov/Pubs dence for minimum wage–induced increases in teen drinking /811870.pdf. and, in fact, some evidence for just the opposite, is surpris- Neumark, David, Ian Salas, and William Wascher, ‘‘Revisiting the Minimum ing, particularly given ABC’s large teen alcohol-related fatal Wage-Employment Debate: Throwing Out the Baby with the Bath- water?’’ Industrial and Labor Relations Review 67 (2014), 608–648. accident elasticity. That the relationship between minimum Neumark, David, Mark Schweitzer, and William Wascher, ‘‘The Effects wages and teen fatal accidents disappears when examining a of Minimum Wages on the Distribution of Family Incomes: A longer time period suggests, at a minimum, that ABC’s result Non-Parametric Analysis,’’ Journal of Human Resources 40 (2005), 867–894. is quite fragile. 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