Table 1
The annual costs of a smoker (in 2010 dollars)
| Best estimate | High range | Low range | |
|---|---|---|---|
| Excess absenteeism | $517 | $576 | $179 |
| Presenteeism | 462 | 1,848 | 462 |
| Smoking breaks | 3,077 | 4,103 | 1,641 |
| Excess healthcare costs | 2,056 | 3,598 | 899 |
| Pension benefits | -296 | 0 | -296 |
| Total costs | 5,816 | 10,125 | 2,885 |
[i] Source: Berman et al. (2014).
Notes: The table shows the differences in costs of employing a smoking employee versus a nonsmoking employee. “Presenteeism” refers to the costs arising from nicotine withdrawal.
Table 2
Descriptive statistics for The National Survey of Midlife Development
| Random | Sibling | Twin | All | |
|---|---|---|---|---|
| Age | 45.58 (10.53) | 47.33 (9.60) | 45.23 (10.01) | 45.67 (10.30) |
| Female | 0.50 (0.50) | 0.52 (0.50) | 0.53 (0.50) | 0.51 (0.50) |
| Employer insurance | 0.58 (0.49) | 0.57 (0.50) | 0.582 (0.49) | 0.583 (0.49) |
| (ESHI) | ||||
| Schooling | 14.244 (2.48) | 14.717 (2.37) | 14.1 (2.40) | 14.351 (2.46) |
| High school | 0.94 (0.23) | 0.97 (0.16) | 0.94 (0.24) | 0.95 (0.22) |
| Some college | 0.67 (0.47) | 0.76 (0.43) | 0.65 (0.48) | 0.69 (0.46) |
| College graduate | 0.41 (0.49) | 0.48 (0.50) | 0.39 (0.49) | 0.43 (0.50) |
| Non-white | 0.13 (0.33) | 0.05 (0.22) | 0.07 (0.26) | 0.10 (0.30) |
| Earnings | 51,830 (43,073) | 59,041 (46,269) | 52,508 (42,374) | 54,510 (44,322) |
| Log earnings | 10.44 (1.08) | 10.58 (1.11) | 10.47 (1.08) | 10.50 (1.08) |
| Smoke | 0.22 (0.41) | 0.19 (0.39) | 0.21 (0.41) | 0.21 (0.41) |
| Ever smoke | 0.52 (0.50) | 0.45 (0.50) | 0.46 (0.50) | 0.49 (0.50) |
| n | 5,615 | 5,681 | 4,078 | 11,306 |
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Standard deviations are under the mean values of the variables. Sample size represents person-year observations.
Abbreviation: ESHI, employer-supplied health insurance.
Table 3
Testing for sample selection: singletons vs. twins
| Question | Singletons | Twins | Difference | P-value |
|---|---|---|---|---|
| Mother’s education | ||||
| Has less than high school | 0.360 | 0.343 | -0.017 | 0.29 |
| Graduated high school | 0.402 | 0.403 | 0.009 | 0.59 |
| Attended some college | 0.129 | 0.130 | 0.009 | 0.45 |
| College graduate | 0.108 | 0.108 | 0.0002 | 0.98 |
| Schooling (years) | 11.20 | 11.44 | 0.242** | 0.03 |
| Father’s education | ||||
| Has less than high school | 0.409 | 0.408 | 0.007 | 0.68 |
| Graduated high school | 0.325 | 0.293 | -0.044** | 0.04 |
| Attended some college | 0.089 | 0.100 | -0.010 | 0.28 |
| College graduate | 0.177 | 0.191 | 0.014 | 0.33 |
| Schooling (years) | 11.04 | 11.11 | -0.076 | 0.60 |
| n | 5,615 | 4,078 |
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Sample size is in person-years. P-values are from Two sample t-test for equality of mean values between singletons and twins. Statistical significance is denoted by the following: **P < 0.05.
Figure 1
When do smokers initiate?
Source: The National Survey of Midlife Development (1996).
Figure 2
Log earnings of smokers versus nonsmokers.
Source: The National Survey of Midlife Development (1996, 2006, and 2014).
Table 4
Are smokers different than nonsmokers?
| Non-smoker | Smoker | Difference | P-value | |||
|---|---|---|---|---|---|---|
| Mean | STD | Mean | STD | |||
| Age | 48.11 | 12.10 | 45.24 | 10.91 | 2.87 | <0.01*** |
| Female | 0.50 | 0.50 | 0.51 | 0.50 | 0.01 | 0.72 |
| Employer insurance | 0.57 | 0.50 | 0.53 | 0.50 | 0.04 | <0.01*** |
| Schooling | 14.60 | 2.46 | 13.19 | 2.24 | 1.41 | <0.01*** |
| High school | 0.96 | 0.20 | 0.89 | 0.32 | 0.07 | <0.01*** |
| Some college | 0.72 | 0.45 | 0.52 | 0.50 | 0.20 | <0.01*** |
| College graduate | 0.48 | 0.50 | 0.21 | 0.41 | 0.27 | <0.01*** |
| Non-white | 0.10 | 0.30 | 0.10 | 0.31 | 0.00 | 0.98 |
| Earnings | 55,221 | 45,972 | 41,744 | 35,082 | 13,477 | <0.01*** |
| Log earnings | 10.47 | 1.14 | 10.24 | 1.05 | 0.23 | <0.01*** |
| Body mass index | 30.38 | 16.54 | 28.99 | 16.65 | 1.39 | 0.01** |
| n | 8,998 | 2,308 | ||||
[i] -
Table 5
The earnings impact of smoking for the full sample
| Full sample | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Panel A | ||||
| Smoker | ||||
| n = 8,975 | -0.235*** (0.022) | -0.168*** (0.024) | 0.063 (0.089) | 0.064 (0.090) |
| Panel B | ||||
| Former-smoker | ||||
| n = 7,280 | -0.061** (0.025) | -0.019 (0.025) | -0.041 (0.072) | -0.041 (0.072) |
| Covariates | ||||
| Education | Yes | No | Yes | Yes |
| Individual | No | Yes | No | Yes |
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are in the parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. Panel A compares the earnings of smokers to nonsmokers, whereas Panel B compares ever smokers or former-smokers to never-smokers. Statistical significance denoted by the following: **P < 0.05 and ***P < 0.01.
Table 6
The earnings impact of smoking for the family sample
| Family level | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Panel A: Siblings (n = 4,080) | ||||
| Smoker | -0.270*** (0.033) | -0.199*** (0.037) | -0.165** (0.072) | -0.156** (0.073) |
| Former-smoker | -0.023 (0.038) | -0.024 (0.038) | -0.079 (0.101) | -0.062 (0.103) |
| Panel B: Twins (n = 2,774) | ||||
| Smoker | -0.287*** (0.038) | -0.182*** (0.045) | -0.195** (0.078) | -0.163** (0.080) |
| Former-smoker | 0.014 (0.046) | 0.045 (0.047) | -0.120 (0.107) | -0.112 (0.112) |
| Covariates | ||||
| Education | No | Yes | No | Yes |
| Family | No | No | Yes | Yes |
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. The first two columns compare across siblings/twins, and the last two columns measure smoking within siblings/twin sets. The coefficient on smoke compares the earnings of smokers to nonsmokers, whereas the coefficient on former-smoker compares ever-smokers or former-smokers to never-smokers. Statistical significance is denoted by the following: **P < 0.05 and ***P < 0.01.
Table 7
The earnings impact of smoking by ESHI
| ESHI | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| Full sample | Siblings | Twins | ||||
| Panel A: no ESHI | ||||||
| Smoker | -0.214*** | -0.159*** | -0.218 | -0.202 | -0.148 | -0.141 |
| (0.037) | (0.039) | (0.307) | (0.311) | (0.326) | (0.327) | |
| n | 4,029 | 4,029 | 1,851 | 1,851 | 1,253 | 1,253 |
| Panel B: ESHI | ||||||
| Smoker | -0.211*** | -0.154*** | -0.282*** | -0.269*** | -0.209** | -0.202** |
| (0.021) | (0.023) | (0.104) | (0.102) | (0.098) | (0.098) | |
| n | 4,946 | 4,946 | 2,229 | 2,229 | 1,521 | 1,521 |
| Panel C: DiD | ||||||
| Smoker*ESHI | -0.094 | -0.086 | -0.092 | -0.084 | ||
| (0.163) | (0.147) | (0.157) | (0.0158) | |||
| n | 4,368 | 4,368 | 3,062 | 3,062 | ||
| Covariates | ||||||
| Education | No | Yes | No | Yes | No | Yes |
| Family Fixed | No | No | Yes | Yes | Yes | Yes |
| Effects (FE) | ||||||
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. Panel A contains the effect of smoking for individuals without ESHI. Panel B contains the effect of smoking for individuals with ESHI. Panel C contains the DiD estimates of individuals with ESHI who also smoke. Statistical significance is denoted by the following: **P < 0.05 and ***P < 0.01.
Abbreviations: ESHI, employer-supplied health insurance; FE, fixed effects; DiD, difference-in-differences.
Table 8
Does the earnings impact vary by age?
| Age | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| Full sample | Siblings | Twins | ||||
| Panel A: old | ||||||
| Smoker | -0.273*** | -0.218*** | -0.283*** | -0.275*** | -0.253*** | -0.320*** |
| (0.031) | (0.033) | (0.095) | (0.095) | (0.097) | (0.095) | |
| n | 5,255 | 5,255 | 2,431 | 2,431 | 1,582 | 1,582 |
| Panel B: young | ||||||
| Smoker | -0.192*** | -0.119*** | -0.051 | -0.049 | -0.096 | -0.090 |
| (0.030) | (0.031) | (0.117) | (0.117) | (0.109) | (0.110) | |
| n | 3,729 | 3,729 | 1649 | 1,649 | 1,192 | 1,192 |
| Covariates | ||||||
| Education | No | Yes | No | Yes | No | Yes |
| Family Fixed | No | No | Yes | Yes | Yes | Yes |
| Effects (FE) | ||||||
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. Panel A contains individuals who are between 25 and 45 years, and Panel B contains individuals who are between 46 and 66 years. Statistical significance is denoted by the following: ***P < 0.01.
Table 9
Does the earnings impact vary by gender?
| Gender | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| Full sample | Siblings | Twins | ||||
| Panel A: men | ||||||
| Smoker | -0.257*** | -0.203*** | -0.222** | -0.198* | -0.176 | -0.162 |
| (0.026) | (0.031) | (0.113) | (0.114) | (0.124) | (0.123) | |
| n | 4,417 | 4,417 | 1,894 | 1,894 | 1,282 | 1,282 |
| Panel B: women | ||||||
| Smoker | -0.219*** | -0.140*** | -0.200 | -0.204 | -0.201 | -0.204 |
| (0.036) | (0.036) | (0.131) | (0.130) | (0.141) | (0.142) | |
| n | 4,558 | 4,558 | 2,186 | 2,186 | 1,492 | 1,492 |
| Covariates | ||||||
| Education | No | Yes | No | Yes | No | Yes |
| Family Fixed | No | No | Yes | Yes | Yes | Yes |
| Effects (FE) | ||||||
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race and age. Statistical significance is denoted by following: *P < 0.10, **P < 0.05, and ***P < 0.01.
Table A1
Does smoking or ever-smoking influence labor market participation?
| Labor supply | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| Full sample | Siblings | Twins | ||||
| Panel A: full time | ||||||
| Smoker | -0.001 | 0.018 | 0.060 | 0.059 | 0.054 | 0.052 |
| (0.011) | (0.011) | (0.045) | (0.045) | (0.056) | (0.056) | |
| Former-smoker | -0.011 (0.010) | -0.004 | -0.033 | -0.032 | -0.035 | -0.034 |
| (0.010) | (0.073) | (0.074) | (0.087) | (0.088) | ||
| Panel B: part time | ||||||
| Smoker | -0.021** | -0.017* | -0.008 | -0.008 | 0.006 | 0.007 |
| (0.007) | (0.007) | (0.031) | (0.031) | (0.038) | (0.038) | |
| Former-smoker | -0.004 | -0.001 | 0.054 | 0.055 | 0.040 | 0.041 |
| (0.007) | (0.007) | (0.056) | (0.056) | (0.056) | (0.056) | |
| Covariates | ||||||
| Education | No | Yes | No | Yes | No | Yes |
| Family Fixed | No | No | Yes | Yes | Yes | Yes |
| Effects (FE) | ||||||
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. Statistical significance is denoted by the following: *P < 0.10 and **P < 0.05.
Abbreviations: FE, fixed effects.
Table A2
The effect of smoking on earnings by zygosity
| Twin sample | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Panel A: monozygotic | ||||
| Smoker | -0.322*** (0.066) | -0.280*** (0.074) | -0.213* (0.111) | -0.213* (0.111) |
| Panel B: dizygotic – | ||||
| same | ||||
| Smoker | -0.262*** (0.063) | -0.178** (0.069) | -0.198* (0.117) | -0.199* (0.117) |
| Panel B: dizygotic – different | ||||
| Smoker | -0.232*** (0.070) | -0.138** (0.079) | -0.223 (0.150) | -0.193 (0.152) |
| Education | No | Yes | No | Yes |
| Twin Fixed | No | No | Yes | Yes |
| Effects (FE) | ||||
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race, gender, and age. Statistical significance is denoted by the following: *P < 0.10, **P < 0.05, and ***P < 0.01.
Table A3
The effect of smoking on earnings by gender and schooling
| College | No college | |||
|---|---|---|---|---|
| Male | Female | Male | Female | |
| Full sample | -0.220*** (0.041) | -0.134*** (0.045) | -0.190*** (0.048) | -0.144 (0.059) |
| Siblings | -0.271*** (0.049) | -0.239*** (0.047) | -0.234*** (0.050) | -0.249*** (0.048) |
| Twins | -0.313*** | -0.252*** | -0.239*** | -0.115 |
| 0.083 | 0.070 | 0.082 | 0.103 | |
[i] Source: National Survey of Midlife Development (1996, 2006, and 2014).
Notes: Huber–White clustered standard errors are given in parentheses. All individuals are between 25 and 66 years, and all regressions include controls for race and age. Statistical significance is denoted by the following: ***P < 0.01.