State-level Variation Research Articles

Labour Market Impacts of Renewable Portfolio Standards

This paper examines how the U.S. Renewable Portfolio Standards (RPS) policy affects the jobs of renewable energy (RE) (solar, hydropower and wind) and conventional energy (CE) (coal and natural gas) industries through panel data. Exploiting the state-level variations in the RPS target rates, this paper also investigates if any spillover effects of the RPS exist from neighbouring states using a fixed-effects vector decomposition model. Findings indicate that an escalation in the RPS target rate increases employment opportunities within the RE sector, while simultaneously causing a decline in employment within the CE sector. Establishing a positive RPS target rate is crucial because the spillover effect from each state has a significantly positive impact. The decision of a state to set its own RPS target plays a crucial role in shaping the level of spillover effects on job creation.

A hybrid deep learning-based approach for optimal genotype by environment selection.

The ability to accurately predict the yields of different crop genotypes in response to weather variability is crucial for developing climate resilient crop cultivars. Genotype-environment interactions introduce large variations in crop-climate responses, and are hard to factor in to breeding programs. Data-driven approaches, particularly those based on machine learning, can help guide breeding efforts by factoring in genotype-environment interactions when making yield predictions. Using a new yield dataset containing 93,028 records of soybean hybrids across 159 locations, 28 states, and 13 years, with 5,838 distinct genotypes and daily weather data over a 214-day growing season, we developed two convolutional neural network (CNN) models: one that integrates CNN and fully-connected neural networks (CNN model), and another that incorporates a long short-term memory (LSTM) layer after the CNN component (CNN-LSTM model). By applying the Generalized Ensemble Method (GEM), we combined the CNN-based models and optimized their weights to improve overall predictive performance. The dataset provided unique genotype information on seeds, enabling an investigation into the potential of planting different genotypes based on weather variables. We employed the proposed GEM model to identify the best-performing genotypes across various locations and weather conditions, making yield predictions for all potential genotypes in each specific setting. To assess the performance of the GEM model, we evaluated it on unseen genotype-location combinations, simulating real-world scenarios where new genotypes are introduced. By combining the base models, the GEM ensemble approach provided much better prediction accuracy compared to using the CNN-LSTM model alone and slightly better accuracy than the CNN model, as measured by both RMSE and MAE on the validation and test sets. The proposed data-driven approach can be valuable for genotype selection in scenarios with limited testing years. In addition, we explored the impact of incorporating state-level soil data alongside the weather, location, genotype and year variables. Due to data constraints, including the absence of latitude and longitude details, we used uniform soil variables for all locations within the same state. This limitation restricted our spatial information to state-level knowledge. Our findings suggested that integrating state-level soil variables did not substantially enhance the predictive capabilities of the models. We also performed a feature importance analysis using RMSE change to identify crucial predictors. Location showed the highest RMSE change, followed by genotype and year. Among weather variables, maximum direct normal irradiance (MDNI) and average precipitation (AP) displayed higher RMSE changes, indicating their importance.

Identifying the Determinants of Recycling Rates in the US: A Multi-Level Analysis

As sustainability challenges become more urgent, concerns about resource depletion and the need for material recovery have brought recycling to the forefront of circular economy discussions. Compared to other developed nations, the US has underperformed in recycling, with its rate remaining relatively unchanged over the last two decades. However, limited academic research has explored the factors influencing recycling rates, and little is understood about how various elements, such as infrastructure and policy measures, affect state-level recycling. Utilizing publicly available data and multivariate regression analysis that considers demographic, infrastructural, ecological, policy, and political factors, this study investigated the state-level variations that contribute to the overall US recycling rate. The findings indicate that states with a high number of landfill sites tend to recycle less, whereas those with a high number of Superfundsites are more likely to recycle more. Furthermore, states that restrict local governments from banning plastic bags and straws are negatively associated with increased recycling. This research provides important insights into how states can improve their recycling rates, which, in turn, would enhance national recycling outcomes.

Underweight Among Scheduled Tribe Non-Pregnant Adolescent Women: A Trend Analysis and Determinants from NFHS

BackgroundThis study examines the trends in underweight prevalence among non-pregnant adolescent women from Scheduled Tribes (ST) in India between 2015 and 2021. It also explores how demographic and socio-economic factors influence underweight status among ST adolescent women aged 15–19 and assesses state-level variations in prevalence.Data and MethodsThe analysis is based on secondary data from the fourth, and fifth rounds of the National Family Health Survey (2015–16 and 2019–21), including 42,164 ST non-pregnant adolescent women aged 15–19. Bivariate and multivariate logistic regression techniques were used.ResultsThe prevalence of underweight among ST non-pregnant adolescent women declined from 47.2% in 2005–06 to 42.6% in 2015–16 and 41.6% in 2019–21. Key factors associated with underweight status include religion, marital status, household wealth, dietary practices, anaemia, and region of residence.ConclusionST adolescent women represent a vulnerable group at high risk of undernutrition. Enhancing access to affordable, nutritious, and safe food and strengthening anaemia-focused interventions are critical to improving their health outcomes.

Abstract 4138275: Demographic, Regional, and State-level Trends of Mortality in patients with Atrial fibrillation in the United States, 1999 to 2020

Background: There exists a paucity of data regarding mortality trends among individuals with atrial fibrillation (AF) based on age, gender, race and ethnicity, and geographic regions. Objective: To investigate the trends in mortality in the United States (US) associated with AF among individuals aged ≥45 years. Methods: We reviewed the death certificate data from the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database to examine atrial fibrillation–related mortality trends from 1999 to 2020 in individuals ≥45 years of age. We calculated crude and age adjusted mortality rates (AAMRs) per 100 000 patients and annual percentage change (APC) with 95% CIs. Results: Between 1999 and 2020, 2,576,839 AF-related deaths were identified among US adults over 45 years of age. The age adjusted mortality rate (AAMR) for AF-related deaths rose significantly from 70.6 in 1999 to 149.1 in 2020. Initially, the AAMR remained stable from 1999 to 2009 (APC): 2.31; 95% CI: -0.57 to 5.84), then increased significantly from 2009 to 2018 (APC: 3.60; 95% CI: 2.12 to 4.75), and saw a sharp rise from 2018 to 2020 (APC: 8.46; 95% CI: 4.76 to 10.44). There were notable disparities among demographic groups. Men consistently had higher AAMRs than women from 1999 (men: 79.9, women: 64.4) to 2020 (men: 180.5, women: 125.3). Non-Hispanic (NH) White adults had the highest AAMR (108.6), followed by NH American Indian/Alaska Native (73.4), NH Black (66.7), Hispanic or Latino (55.5), and NH Asian or Pacific Islander adults (51.2). The age group 85+ consistently showed the highest mortality rates throughout the study period. Regional differences were also evident, with the residents of western region (109.5) and nonmetropolitan areas (109.6) having the higher AAMRs when compared to other regions (Midwest: 104.3, Northeast: 95.1, and South: 95.0) and metropolitan areas (98.3), respectively. State-level variations were also significant. Conclusion: Our study found a rise in AF-related mortality in the US from 1999 to 2020, with significant disparities among demographic and geographic subgroups. Higher AAMRs were noted in males, non-Hispanic Whites, adults over 85, and residents of the western and nonmetropolitan US. Addressing disparities in access to quality care, timely diagnosis, insurance maintenance, and implementing targeted health policies can help reduce AF-related mortality.

State-level variation in the prevalence of child psychopathology symptoms in the US: Results from the ABCD study

ObjectiveTo estimate the prevalence of clinically meaningful youth mood, anxiety, behavioral, and attention symptoms across US states. MethodData are drawn from the Adolescent Brain Cognitive Development (ABCD) study baseline wave, which included 11,876 children ages 9–10. Statistical weighting strategies generated projected state-specific prevalence estimates for the 17 states where ABCD collected data based on state socio-demographics. Twenty dimensions of mental health were assessed with the Child Behavior Checklist using recommended cut-scores to assess clinical and sub-threshold symptoms. ResultsPsychopathology symptom prevalence varied by state and outcome. Projected prevalence of internalizing problems ranged from 11.0% [95% CI: 9.8%, 12.2%; Oklahoma] to 7.9% [95% CI: 6.9%, 9.0%; Maryland] across states. Projected prevalence of externalizing problems ranged from 6.9% [95% CI: 6.1%, 7.8%; South Carolina] to 4.5% [95% CI: 3.7%, 5.4%; California]. Regions with high symptoms included sections of the South (e.g., Oklahoma, South Carolina) and Vermont. Conduct problems had the most variability across states (i.e., greatest state-level prevalence 91% higher than the lowest). Attention problems had the least variability across states (greatest state-level prevalence 26% higher than the lowest). ConclusionsClinically meaningful psychopathology symptoms are common in children across the US, with substantial state-level variability in prevalence. Understanding variability in the prevalence of psychopathology symptoms across the US can help to inform resource allocation to increase the availability of youth mental health services.

National Trends in and Concentration of Industry Payments to U.S. Psychiatrists, 2015-2021.

Industry payments to psychiatrists remain poorly characterized. Using data from the Centers for Medicare and Medicaid Services, the authors of this repeated cross-sectional study detail the extent and concentration of nonresearch industry payments to psychiatrists from 2015 to 2021. The proportion of psychiatrists receiving industry payments, payment distribution, and payment concentration among psychiatrists was assessed. Among 56,955 psychiatrists, 75.0% received any industry payments from 2015 to 2021. These payments, totaling $357,971,774, were highly concentrated: 1% of psychiatrists received 74.7% of industry payments, with notable state-level variations in concentration of top industry-paid psychiatrists. The median psychiatrist received $0 from industry each year.

Favorable Trends in Mortality among Patients with Concomitant Peripheral Arterial Disease and Diabetes Mellitus over Past Two Decades

BackgroundThis study examines the temporal trends in diabetes and peripheral artery disease (PAD)-related mortality in the United States, considering sociodemographic and regional factors, using data from death certificates in a national public database. MethodsData were extracted from the CDC WONDER (Centers for Disease Control and Prevention Wide Ranging Online Data for Epidemiologic Research) database from 1999 to 2020. Age-adjusted mortality rates (AAMR) per 100,000 individuals and annual percent changes (APC) with 95% confidence intervals (CI) were calculated. ResultsBetween 1999 and 2020, there were 2,252,252 PAD-related and 5,413,811 diabetes-related deaths, with 469,699 deaths involving both conditions. The overall AAMR for PAD and diabetes-related mortality (aged ≥ 25 years) decreased from 7.97 in 1999 to 6.37 in 2020, with a notable decline from 2001 to 2010 (APC: -6.16, 95% CI: -7.07, -5.23). The AAMR for PAD-related mortality fell from 40.25 to 30.56, while the AAMR for diabetes-related deaths rose from 76.71 to 93.63. Males and non-Hispanic (NH) Black individuals had higher AAMRs than females and other racial groups. The highest crude mortality rate (CMR) was in the 80-84 age group. Non-metropolitan areas consistently reported higher AAMRs than metropolitan areas, and states like Ohio, Vermont, District of Columbia, and West Virginia had significantly higher rates. ConclusionOver two decades, PAD and diabetes-related mortality trends show a positive overall reduction in AAMR. However, disparities persist, with higher rates among males, NH Black individuals, and residents of non-metropolitan areas. Significant state-level variations highlight the need for targeted interventions and tailored healthcare strategies.

Trends in racial/ethnic and geographic disparities in substance use disorders mortality in the United States, 2000-2019.

Substance use disorders (SUD) are a major public health concern in the United States. This study examined racial/ethnic and state-level disparities in SUD mortality in the United States from 2000 to 2019. Age-standardized mortality rates for SUD were obtained for 5 racial/ethnic groups (White respondents, Black respondents, Latino, Asian-Pacific Islander [API], American Indian/Alaska Native [AIAN]) by state and sex from 2000 to 2019. Joinpoint regression analysis was used to model temporal trends overall and by demographic factors. From 2000 to 2019, the overall mortality rate increased from 8.0 to 28.8 deaths per 100,000 population across all groups. AIANs had the highest mortality in 2019 (57.8 per 100,000), followed by Black respondents, White respondents, Latinos, and APIs. Significant increases occurred across all racial/ethnic groups, with the greatest average annual percentage change (AAPC2000-2019) among White respondents (6.7%; 95% confidence interval [CI]: 6.2%-7.3%), APIs (6.0%, 95% CI: 5.6%-6.2%), and AIANs (5.9%, 95% CI: 5.6%-6.2%). Mortality rates increased more rapidly for females than males among White respondents, AIANs, Black respondents, and Latinos. Substantial state-level variation emerged, with the highest mortality rates in 2019 seen in West Virginia, the District of Columbia, Delaware, Ohio, and Pennsylvania. Racial/ethnic and geographic disparities in SUD mortality have widened significantly from 2000 to 2019, highlighting priority areas for prevention efforts. This study provides detailed insights into long-term trends in racial, ethnic, and geographic disparities in SUD mortality across the United States, informing targeted prevention and intervention strategies.

Global and national burden of type 2 diabetes mellitus attributable to PM2.5 air pollution: An analysis of the GBD study from 1990 to 2019.

Epidemiological studies have established a link between air pollution and an elevated risk of type 2 diabetes mellitus (T2DM). This study aims to measure the impact of T2DM related to fine particulate matter (PM2.5) pollution by examining death rates and disability-adjusted life years (DALYs) from 1990 to 2019 in the United States of America. Using data from the Global Burden of Disease (GBD) database, we examined death and DALY rates per 100,000 populations in T2DM patients, specifically focusing on ambient particulate matter pollution (APMP) and household air pollution (HAP). We assessed average annual percentage change (AAPC) across various age and gender groups, states, and socio-demographic index (SDI) categories. Our findings reveal a significant decline in death rates and DALYs in the United States of America over the last 30 years, with more pronounced decreases among females and older adults. Despite national progress, state-level variations indicate complex interactions between environmental regulations, healthcare access, and socio-economic factors. Some states, such as Oregon, Idaho, and Alaska, exhibited increased AAPC. Our study emphasizes the need for targeted policies and interventions to reduce PM2.5 exposure and further address regional disparities, ensuring continued improvement in public health outcomes.

S497 Unraveling State-level Variations in Early-Onset Colorectal Cancer: A Comprehensive Analysis From USCS Database Across 50 U.S. States

S497 Unraveling State-level Variations in Early-Onset Colorectal Cancer: A Comprehensive Analysis From USCS Database Across 50 U.S. States

Trends in pre-biopsy MRI usage for prostate cancer detection, 2007-2022.

Clinical guidelines favor MRI before prostate biopsy due to proven benefits. However, adoption patterns across the US are unclear. This study used the Merative™ Marketscan® Commercial & Medicare Databases to analyze 872,829 prostate biopsies in 726,663 men from 2007-2022. Pre-biopsy pelvic MRI within 90 days was the primary outcome. Descriptive statistics and generalized estimating equations assessed changes over time, urban-rural differences, and state-level variation. Pre-biopsy MRI utilization increased significantly from 0.5% in 2007 to 35.5% in 2022, with faster adoption in urban areas (36.1% in 2022) versus rural areas (28.3% in 2022). Geographic disparities were notable, with higher utilization in California, New York, and Minnesota, and lower rates in the Southeast and Mountain West. The study reveals a paradigm shift in prostate cancer diagnostics towards MRI-guided approaches, influenced by evolving guidelines and clinical evidence. Disparities in access, particularly in rural areas and specific regions, highlight the need for targeted interventions to ensure equitable access to advanced diagnostic techniques.

Teletrauma Use in US Emergency Departments

Nearly 30 million predominantly rural US residents lack timely access to trauma care expertise available at level I or II trauma centers. Telehealth is an established approach to improve access to health care expertise using remote consultation; however, the prevalence of use of telehealth in trauma (teletrauma) across the US is not known. To examine the prevalence of, trends in, and factors associated with teletrauma use and adoption among US emergency departments (EDs). This survey study included data from the National Emergency Department Inventory (NEDI)-USA survey from January 1, 2016, to December 31, 2020. Each year, a 1-page survey was sent to the directors of nonfederal, nonspecialty EDs by mail and email up to 3 times; nonresponders were further contacted via telephone to complete the survey. Data were analyzed from January to March 2023. The primary outcome was self-reported ED use of teletrauma for each year studied. Additional measures included data regarding self-reported use of any other telehealth service and ED characteristics. Multivariable logistic regression analyses were performed to assess ED characteristics associated with teletrauma use in 2020 and teletrauma adoption between 2017 and 2020. Of 5586 EDs in the US in 2020, 4512 had available teletrauma survey data (80.8% response rate); 379 (8.4%) of these EDs reported teletrauma use. In contrast, 2726 (60.4%) reported use of any other telehealth service. Teletrauma use (among EDs with any telehealth use) ranged between 0% in Alabama; Connecticut; Washington, DC; Indiana; New Jersey; Nevada; Oklahoma; Oregon; Rhode Island; and South Carolina to more than 60% in Arkansas (39 of 64 [60.9%]), South Dakota (31 of 41 [75.6%]), and North Dakota (30 of 35 [85.7%]). Factors associated with teletrauma use included rural location (odds ratio [OR], 2.44; 95% CI, 1.77-3.36), critical access hospital (OR, 2.67; 95% CI, 1.83-3.88), and basic stroke hospital vs nonstroke hospital (OR, 1.74; 95% CI, 1.32-2.30) designations. Factors associated with adoption of teletrauma by 2020 included critical access hospital (OR, 1.98; 95% CI, 1.35-2.90) and basic stroke hospital vs nonstroke hospital (OR, 1.42; 95% CI, 1.04-1.94) designation. This survey study found that teletrauma use lagged significantly behind use of other telehealth services in US EDs in 2020. While most EDs using teletrauma were located in rural areas, there was significant state-level variation in teletrauma use. Future research is needed on how teletrauma is being used and to identify barriers to its wider implementation.

A multi-state analysis on the effect of deprivation and race on PICU admission and mortality in children receiving Medicaid in United States (2007–2014)

IntroductionIn the United States (US), racial and socioeconomic disparities have been implicated in pediatric intensive care unit (PICU) admissions and outcomes, with higher rates of critical illness in more deprived areas. The degree to which this persists despite insurance coverage is unknown. We investigated whether disparities exist in PICU admission and mortality according to socioeconomic position and race in children receiving Medicaid.MethodsUsing Medicaid data from 2007–2014 from 23 US states, we tested the association between area level deprivation and race on PICU admission (among hospitalized children) and mortality (among PICU admissions). Race was categorized as Black, White, other and missing. Patient-level ZIP Code was used to generate a multicomponent variable describing area-level social vulnerability index (SVI). Race and SVI were simultaneously tested for associations with PICU admission and mortality.ResultsThe cohort contained 8,914,347 children (23·0% Black). There was no clear trend in odds of PICU admission by SVI; however, children residing in the most vulnerable quartile had increased PICU mortality (aOR 1·12 (95%CI 1·04–1·20; p = 0·0021). Black children had higher odds of PICU admission (aOR 1·04; 95% CI 1·03–1·05; p < 0·0001) and higher mortality (aOR 1·09; 95% CI 1·02–1·16; p = 0·0109) relative to White children. Substantial state-level variation was apparent, with the odds of mortality in Black children varying from 0·62 to 1·8.ConclusionIn a Medicaid cohort from 2007–2014, children with greater socioeconomic vulnerability had increased odds of PICU mortality. Black children were at increased risk of PICU admission and mortality, with substantial state-level variation. Our work highlights the persistence of sociodemographic disparities in outcomes even among insured children.

Geographic trends in overall and long-acting opioid prescriptions under Medicaid and Medicare Part D in the United States, 2013–2021

ABSTRACT Background: Amid the national opioid epidemic, it is important to assess trends in opioid prescriptions. Long-acting opioids (LAOs) are of particular interest as they are among the most intensely misused prescription opioids. Moreover, understanding geographic trends in opioid prescriptions may help identify state-level variations, illustrating state-specific disparities. Objectives: The study aims to determine geographic trends in overall and LAO prescriptions under Medicaid and Medicare Part D from 2013 to 2021. Methods: We used data from the Centers for Medicare & Medicaid Services on opioid prescriptions from 2013 to 2021. The opioid prescribing proportion was calculated as the number of opioid claims divided by the total number of overall drug claims. The LAO prescribing proportion was calculated as number of LAO claims divided by total opioid claims. Results: Despite a general decrease nationwide, Medicaid opioid prescribing proportions increased in Iowa, Montana, and Virginia. There was an increasing trend in the national-level Medicaid LAO prescribing proportion from 2017 to 2021, with a 14.1% point increase (p for the annual percent change [APC]<0.05). For Medicare Part D, the overall prescribing proportions fell by 1.7% points from 2013 to 2021, while the LAO prescribing proportion fell by 3% points from 2016 to 2021 (p for APC < .05). Conclusions: The increasing trends in national-level Medicaid LAO prescribing and Medicaid opioid prescribing in Iowa, Montana, and Virginia are concerning, and have implications for clinical opioid prescribing. The decreasing trends in Medicare Part D may reflect ongoing efforts in opioid prescription management.

The effects of SNAP emergency allotments on state-level SNAP benefits and enrollment during the COVID-19 pandemic.

During the COVID-19 pandemic, all US states provided emergency allotments (EA) to enrollees of the Supplemental Nutrition Assistance Program (SNAP) to alleviate rising food insecurity. However, 18 states opted out of the SNAP-EA program before its official expiration in February 2023. Using a staggered difference-in-differences model to account for state-level variation in the timing of the SNAP-EA opt-out decisions, we analyzed SNAP and SNAP-EA data from the US Department of Agriculture Food and Nutrition Service to quantify the impact of state opt-out decisions on SNAP benefit size and enrollment. We found that the average SNAP monthly benefit among 18 SNAP opt-out states was reduced by $183 (95% confidence interval [CI]: -$214, -$152) per beneficiary. The percentage of the state population enrolled in the SNAP program among the opt-out states modestly decreased by 0.35 (95% CI: -0.61, -0.10) percentage points. Additionally, we employed logistic regression models to associate state opt-out decisions with state-level characteristics. We found that the state governor's political party being Republican was the only significant predictor for the state's opt-out decisions. Our findings help explain why opting out of SNAP-EA has been associated with higher food insufficiency and shed light on the impact of political decisions to opt out of SNAP-EA on the lives of millions of Americans.

Pediatric Inpatient Psychiatric Capacity in the US, 2017 to 2020

This cross-sectional study assesses US pediatric inpatient psychiatric capacity and identifies state-level variation in access to pediatric inpatient psychiatric beds.

Racial, Ethnic, and Geographic Disparities in Digestive Diseases Mortality in the United States, 2000–2019

Background and aimThe global burden of digestive diseases mortality has been increasing over the last three decades. However, little is known about disparities in digestive diseases-specific mortality in the United States. This study aimed to examine racial, ethnic, state- and county-level disparities in digestive diseases mortality rate in the United States between 2000-2019. MethodsWe used the Institute of Health Metrics and Evaluation, Global Health Data Exchange to gather digestive diseases age-standardized mortality rates for five racial and ethnic groups (White, Black, Latino, American-Indian/Alaska Native [AIAN], and Asian-Pacific Islanders [API]) by sex, state, and county between 2000-2019. We used joinpoint regression analysis to evaluate the overall temporal trends by demography. ResultsThe overall cause-specific mortality rate decreased from 36.0 to 34.5 deaths per 100,000 population across all groups (2000-2019). In 2019, AIAN individuals had the highest mortality rate (86.2), followed by White (35.5), Latino and Black (both at 33.6), and API individuals (15.6). Significant increases occurred across some of the racial and ethnic groups, with an increased average annual percentage change (AAPC2000-2019) among AIAN (0.87%, 95% CI: 0.77-0.97) and White individuals (0.12%, 0.02-0.22) particularly among females, while Latino, Black, and API individuals showed reduced AAPC2000-2019. AIAN constitutes the main race affected in the top ten counties. Substantial state-level variation emerged, with the highest mortality rates in 2019 seen in West Virginia. ConclusionsDespite an overall decrease in digestive diseases mortality, significant disparities persist across racial and ethnic groups. AIAN and White individuals experienced increased mortality rates, particularly among females. Targeted interventions and further research are needed to address these disparities and improve digestive health equity.

Restrictions to civil liberties in a pandemic and satisfaction with democracy

In times of crises, democracies face the challenge of balancing effective interventions with civil liberties. This study examines German states’ responses during the early stages of the COVID-19 pandemic, focusing on the trade-off between civil liberties and public health. Using state-level variation in mobility restrictions, we employ a difference-in-differences design to show that stay-at-home orders notably increased satisfaction with democracy and shifted political support towards centrist parties. Stay-at-home orders increased satisfaction with democracy most among individuals who had been exposed to the authoritarian regime of the German Democratic Republic, possibly because they have gotten used to more restrictive state interventions.

Which state is the cleanest of them all? Pricing long run heterogeneity in carbon abatement costs across America

Electric vehicles (EVs) feature prominently in the United States' efforts to decarbonize the light-duty vehicle fleet and mitigate climate change. To spur EV adoption, public policy offers procurement incentives for individuals willing to purchase an EV instead of an internal combustion engine vehicle (ICEV). How cost-effective are such policies? To what extent does their efficiency vary across states? We address these questions using state-level data on projected electric grid carbon intensity and fuel prices, as well as models of vehicle utilization. Our approach focuses on comparable vehicle models that enable us to jointly estimate the lifecycle emissions and total cost of ownership (TCO) associated with ICEVs, hybrid electric vehicles (HEVs), and EVs. Our findings are fourfold. First, although EVs offer the largest emissions benefit relative to ICEVs, there exists significant state-level heterogeneity. Compared to HEVs' emissions advantage of 20.54 tons of CO2e, EVs' emissions advantage ranges from 10.18 to 58.83 tons of CO2e across states. Second, HEVs offer a more favorable cost-to-emissions advantage nationwide, with an average cost of $59/ton CO2e reduced compared to $192/ton CO2e reduced via EVs. Third, state-level variation in fuel prices and grid carbon intensity enable HEVs to offer emissions reductions at a minimum cost of $3/ton CO2e reduced, while EVs' minimum cost is $76/ton CO2e reduced. Fourth, envisioned grid decarbonization efforts are insufficient for EVs to deliver economically efficient cost-to-emissions advantages due to EVs' relatively high TCO. If EVs produced zero emissions in totality, realizing cost-effective emissions reductions would still necessitate lowering their TCO by an average of at least $3200. We conclude that favorable abatement cost realization necessitates better targeting of procurement incentives at both the federal and state level. We demonstrate that this outcome can be achieved by incentivizing the adoption of HEVs and high-utilization EVs in the short run and by improving EVs’ cost and continuing to invest in EV battery longevity in the long run.