The Health Effects of Automobile Fuel Economy Standard Through Improving Air Quality Qing Shi UNCG 2015

Background Automobile driving has externalities (eg. air population) Fuel economy standard - Corporate Average Fuel Economy (CAFE) plays the primary role in US to regular mobile source pollution Health effects of CAFE standard?

Research Questions Does fuel economy standard lead to better health outcomes? Is there evidence for air pollution as the mechanism (mediator) Welfare gain/lost of CAFE Policy advice More fuel efficient cars Less air pollutants Better Health Outcome Less Fuel consumption

Statistical Mediation Effects Baron and Kenny's (1986) steps 1.Y =  X (path C) 2.M ~  X (path A) 3.Y ~  M +  X (path A B)  <  Significant  Source(X) Outcome (Y) Mediator (M) A B C Empirical models

Data Vehicle and fuel sales data (US DOT Highway Statistics) State level vehicle miles, fuel consumption and derived MPG 2001 – 2011, state-year panel Air Quality System Data (US EPA AQS) County level annual  average to state level PM2.5, Carbon monoxide, Nitrogen dioxide 2001 – 2013, state-year panel Behavioral Risk Factor Surveillance Survey (BRFSS) Asthma incidence/status 2003 – 2011, state-year pooled cross section

Automobile Fuel Economy improvement Data source: US DOT NTSUS DOT NTS

PM2.5 Averaged Across States

Econometric models

Empirical Approach Run Stepwise logit model select significant Xs, every year Run logit regression of Asthma on MPG + X Run logit regression of asthma on pollutants and MPG + X Run OLS of Pollutants on MPG

Individual Characteristics Weight Body Mass Index – BMI BMI Categories – normal, overweight, obese Income Level - 50K Gender, Race Smoking status Age, Age category - =65 Has healthcare coverage

Summary Statistics of Model Variables 1. BRFSS (individual, 2001 ~2012) N = , after data cleaning Variablemeanstd. dev.minmedianmax Health Outcomes Has Asthma Has COPD Has Diabetes Demographics Age Age > Current Smoker Caucasian Female Has Healthcare coverage Education status Income level Weight (lb) Body Mass Index

2. State level Aggregate N = 490, after data cleaning From vehicles of surveyee Variablemeanstd. dev.minmedianmax Health Outcomes Has Asthma Has Diabetes Air Pollutants PM2.5 - the 98% PM2.5 - Annual Mean CO - the 2nd highest CO - the 2nd highest 8-hour average NO2 - the 98% Average fuel economy (MPG)* Demographic, State average Age Age > Current Smoker Caucasian Female Has Healthcare coverage Education status Income level Weight (lb) Body Mass Index

Model Estimates 1. Pollutants on MPG change (Fixed effects* model) PM2.5 - the 98% PM2.5 - Annual Mean CO - the 2nd highest 1-hour measure CO - the 2nd highest 8-hour averageNO2 - the 98% Intercept < < <.0001 MPG GDP (per Capita) < E E E E <.0001 * From 49 States and DC,

Model Estimates 2. Asthma on PM1, PM2, CO1, CO2, NO and MPG, Model estimates in 2003, control for demographic characteristics (all sig. at )

Conclusion Statistically Significant effect of Fuel Economy on Asthma Statistically Significant effect of PM2.5 and CO on Asthma Statistically Significant effect of Fuel Economy on Air pollutants Empirical evidence of the link among More efficient cars Less air pollutants Better Health Outcome

Appendix Summary Statistics of Data

Summary Statistics 1. Vehicle Miles Traveled Data Yearmeanstd. dev.minmedianmax ,50549,2703,46538,489276, ,67150,0663,31638,095278, ,20351,7753,32638,840285, ,53252,9553,30740,261290, ,77154,3973,46241,205300, ,91856,1013,49841,771306, ,85056,9783,75043,244310, ,99558,6443,54743,545320, ,68459,4024,15044,156323, ,08861,0473,74245,891328, ,62461,5463,71347,019329, ,10061,6813,62347,742327, ,40862,0533,60947,572328, ,30460,9663,61147,534327, ,97660,2523,60846,230324, ,18260,2793,59146,940322, ,85159,8983,56846,606320, ,22460,3973,57246,889326, ,59561,2223,52746,996329,534 * 51 Observations (States, DC) per year Unit: Million Miles

Summary Statistics 2. Motor Fuel Consumption Data Yearmeanstd. dev.minmedianmax 19952,819,2942,814,409172,5792,242,01815,211, ,891,1942,894,570160,3232,357,79715,511, ,955,1412,945,592167,9052,316,54215,874, ,047,1633,041,332166,0712,409,44616,213, ,154,1833,154,373167,1372,480,22816,777, ,181,8793,221,068167,1752,529,56817,080, ,216,6553,293,103151,6322,748,23117,460, ,319,3333,429,090151,4182,601,28618,297, ,350,9313,401,700143,4472,722,40617,795, ,433,3973,523,439147,1752,582,30518,647, ,437,2783,563,084150,0292,629,39418,860, ,465,7003,576,027126,8452,642,08718,711, ,479,6113,605,670130,4852,703,81018,842, ,360,8893,474,344110,4982,733,26317,829, ,307,7743,399,097114,0242,560,72617,450, ,348,5583,438,297108,0812,690,58117,464, ,308,2663,415,52895,9122,601,60817,233, ,318,0933,438,66795,5662,728,07017,118, ,348,0233,490,11389,2102,725,96017,287,862 * 51 Observations (States, DC) per year Unit: Thousand Miles

Summary Statistics 3. Fuel Economy Data Yearmeanstd. dev.minmedianmax * 51 Observations (States, DC) per year Unit: Miles Per Gallon

Summary Statistics 4. Air Pollutants (PM 2.5 ) Data * 49 Observations per Year (48 States and DC) Variable Yearmeanstd. dev.minmedianmax PM2.5 - the 98% of the daily average PM2.5 - the Weighted Annual Mean