Main Questions:
How does the federal minimum wage affect alcohol related fatalities among teens?
Does adding to disposable income for teens raise the expenditures of teenagers on alcoholic beverages and driving activities?
Main Findings:
Previous research suggested that an increase in the beer tax causes a decrease in alcohol consumption and decrease in alcohol related fatalities.
Found there was a positive relationship between the minimum wage and alcohol related fatalities among teens.
Found there to be a negative relationship between the beer tax and alcohol related fatalities among teens.
Found there to be a negative relationship between the BAC law and alcohol related fatalities among teens.
mwdef: The coefficient of 0.02054 represents that a one dollar per hour increase in the minimum wage is associated with a 2.054% increase in number of alcohol-related traffic fatalities for adults over age 26. (Note: This variable is not significant at the 5% level of significance)
realbeertax: The coefficient of -0.05437 represents that a $1 increase in beer tax per gallon is associated with a 5.437% decrease in number of alcohol-related traffic fatalities for adults over age 26. (Note: This variable is not significant at the 5% level of significance)
##
## Call:
## lm(formula = ln_ANYBAC26 ~ mwdef + realbeertax + ln_NOBAC26 +
## ln_pop26 + unempr, data = Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.21094 -0.12920 0.00221 0.15446 0.64812
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.89770 0.31263 -2.871 0.00428 **
## mwdef 0.02054 0.02238 0.918 0.35925
## realbeertax -0.05437 0.05600 -0.971 0.33208
## ln_NOBAC26 0.87636 0.03597 24.365 < 0.0000000000000002 ***
## ln_pop26 0.05154 0.03533 1.459 0.14535
## unempr 0.01646 0.01026 1.604 0.10930
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2483 on 452 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.9396, Adjusted R-squared: 0.9389
## F-statistic: 1406 on 5 and 452 DF, p-value: < 0.00000000000000022If we were to include state fixed effects in our regression, that would allow for the control of omitted variables that differ across states, but not over time. One possible variable that would be controlled for if we add state fixed effects to our previous regression would be something like the drinking culture across different states.
The coefficients on the real minimum wage and real beer tax compared to the coefficients obtained in the previous regression, seem quite different for the real beer tax which is a good indication that the original model did suffer from omitted variable bias. This seems logical as there is likely a correlation between the state and the real beer tax. This indicates that our coefficient in the previous model was biased and inconsistent.
##
## Call:
## lm(formula = ln_ANYBAC26 ~ mwdef + realbeertax + ln_NOBAC26 +
## ln_pop26 + unempr + factor(state), data = Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.98966 -0.06680 0.00515 0.07491 0.50112
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.243228 3.327279 0.674 0.500576
## mwdef 0.032911 0.023517 1.399 0.162448
## realbeertax -0.383378 0.128450 -2.985 0.003012 **
## ln_NOBAC26 0.233280 0.062461 3.735 0.000215 ***
## ln_pop26 0.132081 0.222127 0.595 0.552433
## unempr -0.016480 0.008534 -1.931 0.054181 .
## factor(state)2 -1.498388 0.451332 -3.320 0.000983 ***
## factor(state)4 -0.343164 0.093646 -3.664 0.000281 ***
## factor(state)5 -0.572290 0.133828 -4.276 0.00002376621271931 ***
## factor(state)6 0.361443 0.470778 0.768 0.443082
## factor(state)8 -0.660370 0.093061 -7.096 0.00000000000583681 ***
## factor(state)9 -1.065535 0.112483 -9.473 < 0.0000000000000002 ***
## factor(state)10 -1.629312 0.377977 -4.311 0.00002050059661609 ***
## factor(state)11 -2.300022 0.458904 -5.012 0.00000080898233905 ***
## factor(state)12 0.447157 0.314505 1.422 0.155866
## factor(state)13 -0.046954 0.153064 -0.307 0.759184
## factor(state)15 -1.337586 0.305730 -4.375 0.00001549034332635 ***
## factor(state)16 -1.200275 0.289854 -4.141 0.00004216976727007 ***
## factor(state)17 -0.108209 0.246099 -0.440 0.660392
## factor(state)18 -0.524342 0.113429 -4.623 0.00000511274204677 ***
## factor(state)19 -1.103999 0.122550 -9.009 < 0.0000000000000002 ***
## factor(state)20 -0.852325 0.141129 -6.039 0.00000000352577534 ***
## factor(state)21 -0.486795 0.092753 -5.248 0.00000024908709387 ***
## factor(state)22 -0.060101 0.073640 -0.816 0.414901
## factor(state)23 -1.541961 0.268965 -5.733 0.00000001940729573 ***
## factor(state)24 -0.790000 0.106779 -7.398 0.00000000000081112 ***
## factor(state)25 -0.970538 0.151410 -6.410 0.00000000040829427 ***
## factor(state)26 -0.217643 0.196815 -1.106 0.269463
## factor(state)27 -0.762020 0.093882 -8.117 0.00000000000000590 ***
## factor(state)28 -0.109385 0.130392 -0.839 0.402029
## factor(state)29 -0.170406 0.109673 -1.554 0.121029
## factor(state)30 -0.920419 0.356623 -2.581 0.010207 *
## factor(state)31 -1.226629 0.229250 -5.351 0.00000014753120295 ***
## factor(state)32 -0.896753 0.180637 -4.964 0.00000102022532252 ***
## factor(state)33 -1.452682 0.289701 -5.014 0.00000079944834484 ***
## factor(state)34 -0.773167 0.180033 -4.295 0.00002196848486598 ***
## factor(state)35 -0.731862 0.215073 -3.403 0.000734 ***
## factor(state)36 -0.472559 0.341365 -1.384 0.167028
## factor(state)37 -0.014912 0.153067 -0.097 0.922443
## factor(state)38 -1.570756 0.445757 -3.524 0.000474 ***
## factor(state)39 -0.103829 0.226048 -0.459 0.646251
## factor(state)40 -0.480113 0.089987 -5.335 0.00000015959938918 ***
## factor(state)41 -0.847374 0.113569 -7.461 0.00000000000053416 ***
## factor(state)42 -0.063688 0.252919 -0.252 0.801316
## factor(state)44 -1.783587 0.331193 -5.385 0.00000012328191333 ***
## factor(state)45 0.237133 0.077679 3.053 0.002418 **
## factor(state)46 -1.261356 0.402298 -3.135 0.001842 **
## factor(state)47 -0.089591 0.108387 -0.827 0.408965
## factor(state)48 0.669716 0.348007 1.924 0.055006 .
## factor(state)49 -1.654163 0.200077 -8.268 0.00000000000000202 ***
## factor(state)50 -1.920120 0.431400 -4.451 0.00001108916260629 ***
## factor(state)51 -0.443063 0.137862 -3.214 0.001416 **
## factor(state)53 -0.580907 0.128586 -4.518 0.00000823131680679 ***
## factor(state)54 -0.857360 0.204500 -4.192 0.00003396407492759 ***
## factor(state)55 -0.374266 0.108164 -3.460 0.000598 ***
## factor(state)56 -1.372682 0.490949 -2.796 0.005423 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1391 on 402 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.9832, Adjusted R-squared: 0.9808
## F-statistic: 426.5 on 55 and 402 DF, p-value: < 0.00000000000000022If we were to include year fixed effects in our regression, that would allow for the control of omitted variables that differ over time, but not across states. One possible variable that would be controlled for if we add year fixed effects to our previous regression would be something like the drinking regulations at the federal level changing over time.
mwdef: The coefficient of 0.023123 represents that a one dollar per hour increase in the minimum wage is associated with a 2.3123% increase in number of alcohol-related traffic fatalities for adults over age 26. (Note: This variable is not significant at the 5% level of significance)
realbeertax: The coefficient of -0.384406 represents that a $1 increase in beer tax per gallon is associated with a 38.4406% decrease in number of alcohol-related traffic fatalities for adults over age 26. (Note: This variable is significant at the 5% level of significance)
The coefficients on the real minimum wage and real beer tax compared to the coefficients obtained in the previous regression, seem relatively close, indicating that the previous model did not suffer from omitted variable bias. This makes sense as changes over time, if any, are likely to be small across this time period.
##
## Call:
## lm(formula = ln_ANYBAC26 ~ mwdef + realbeertax + ln_NOBAC26 +
## ln_pop26 + unempr + factor(state) + factor(year), data = Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95996 -0.06501 0.00568 0.07629 0.46383
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.619070 5.059304 -0.518 0.604976
## mwdef 0.023123 0.024098 0.960 0.337881
## realbeertax -0.384406 0.129638 -2.965 0.003208 **
## ln_NOBAC26 0.245642 0.063736 3.854 0.000136 ***
## ln_pop26 0.457848 0.340629 1.344 0.179681
## unempr -0.014407 0.011881 -1.213 0.225987
## factor(state)2 -0.803509 0.694108 -1.158 0.247723
## factor(state)4 -0.399431 0.106311 -3.757 0.000198 ***
## factor(state)5 -0.403049 0.183868 -2.192 0.028960 *
## factor(state)6 -0.301621 0.705645 -0.427 0.669293
## factor(state)8 -0.650762 0.093379 -6.969 0.0000000000134898 ***
## factor(state)9 -0.960061 0.131418 -7.305 0.0000000000015466 ***
## factor(state)10 -1.038783 0.584805 -1.776 0.076457 .
## factor(state)11 -1.595834 0.696801 -2.290 0.022536 *
## factor(state)12 -0.012171 0.475456 -0.026 0.979590
## factor(state)13 -0.254919 0.222496 -1.146 0.252604
## factor(state)15 -0.891023 0.459793 -1.938 0.053352 .
## factor(state)16 -0.771537 0.434916 -1.774 0.076837 .
## factor(state)17 -0.440827 0.364729 -1.209 0.227526
## factor(state)18 -0.622349 0.141220 -4.407 0.0000135335726846 ***
## factor(state)19 -0.955544 0.164031 -5.825 0.0000000118498527 ***
## factor(state)20 -0.670964 0.194086 -3.457 0.000606 ***
## factor(state)21 -0.460954 0.094059 -4.901 0.0000013977750683 ***
## factor(state)22 -0.042403 0.074427 -0.570 0.569187
## factor(state)23 -1.128816 0.411806 -2.741 0.006402 **
## factor(state)24 -0.849199 0.121082 -7.013 0.0000000000101815 ***
## factor(state)25 -1.074738 0.181040 -5.936 0.0000000063929553 ***
## factor(state)26 -0.483348 0.291507 -1.658 0.098093 .
## factor(state)27 -0.786943 0.098772 -7.967 0.0000000000000176 ***
## factor(state)28 0.050383 0.179574 0.281 0.779189
## factor(state)29 -0.248783 0.129497 -1.921 0.055435 .
## factor(state)30 -0.385935 0.540941 -0.713 0.475988
## factor(state)31 -0.889353 0.343300 -2.591 0.009936 **
## factor(state)32 -0.649387 0.256812 -2.529 0.011840 *
## factor(state)33 -1.024429 0.434299 -2.359 0.018821 *
## factor(state)34 -0.990348 0.254782 -3.887 0.000119 ***
## factor(state)35 -0.423134 0.319070 -1.326 0.185559
## factor(state)36 -0.956555 0.516042 -1.854 0.064538 .
## factor(state)37 -0.226289 0.224552 -1.008 0.314200
## factor(state)38 -0.895133 0.680242 -1.316 0.188971
## factor(state)39 -0.415333 0.337379 -1.231 0.219035
## factor(state)40 -0.387140 0.113763 -3.403 0.000735 ***
## factor(state)41 -0.751538 0.128056 -5.869 0.0000000093180054 ***
## factor(state)42 -0.411409 0.376946 -1.091 0.275752
## factor(state)44 -1.278092 0.498241 -2.565 0.010681 *
## factor(state)45 0.264720 0.081523 3.247 0.001265 **
## factor(state)46 -0.650472 0.617653 -1.053 0.292924
## factor(state)47 -0.181977 0.133581 -1.362 0.173880
## factor(state)48 0.160499 0.531078 0.302 0.762648
## factor(state)49 -1.365727 0.296502 -4.606 0.0000055460465364 ***
## factor(state)50 -1.238800 0.672473 -1.842 0.066204 .
## factor(state)51 -0.601978 0.189002 -3.185 0.001563 **
## factor(state)53 -0.659709 0.150133 -4.394 0.0000143161393038 ***
## factor(state)54 -0.569328 0.297025 -1.917 0.055991 .
## factor(state)55 -0.431971 0.121876 -3.544 0.000441 ***
## factor(state)56 -0.630683 0.750861 -0.840 0.401447
## factor(year)1999 -0.005283 0.028258 -0.187 0.851801
## factor(year)2000 0.016127 0.029242 0.551 0.581607
## factor(year)2001 0.029588 0.029803 0.993 0.321424
## factor(year)2002 0.003026 0.033564 0.090 0.928215
## factor(year)2003 -0.003558 0.036357 -0.098 0.922089
## factor(year)2004 -0.044088 0.037186 -1.186 0.236497
## factor(year)2005 -0.029882 0.039329 -0.760 0.447820
## factor(year)2006 -0.037412 0.041830 -0.894 0.371664
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.139 on 394 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.9835, Adjusted R-squared: 0.9809
## F-statistic: 372.7 on 63 and 394 DF, p-value: < 0.00000000000000022##
## Minimum Wage and Teen Drinking Car Accidents
## ==================================================================================================
## Dependent variable:
## ------------------------------------------------------------------------------
## ln_ANYBAC26
## (1) (2) (3)
## --------------------------------------------------------------------------------------------------
## mwdef 0.021 (0.022) 0.033 (0.024) 0.023 (0.024)
## realbeertax -0.054 (0.056) -0.383*** (0.128) -0.384*** (0.130)
## ln_NOBAC26 0.876*** (0.036) 0.233*** (0.062) 0.246*** (0.064)
## ln_pop26 0.052 (0.035) 0.132 (0.222) 0.458 (0.341)
## unempr 0.016 (0.010) -0.016* (0.009) -0.014 (0.012)
## Constant -0.898*** (0.313) 2.243 (3.327) -2.619 (5.059)
## --------------------------------------------------------------------------------------------------
## Observations 458 458 458
## R2 0.940 0.983 0.983
## Adjusted R2 0.939 0.981 0.981
## Residual Std. Error 0.248 (df = 452) 0.139 (df = 402) 0.139 (df = 394)
## F Statistic 1,406.122*** (df = 5; 452) 426.509*** (df = 55; 402) 372.653*** (df = 63; 394)
## ==================================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01