Eyup DoganM. Teresa MadalenoRoula Inglesi-LotzDilvin TaşkınTaskin, DilvinInglesi-Lotz, RoulaDogan, EyupMadaleno, Mara2025-10-062022014098830140-98831873-618110.1016/j.eneco.2022.1059082-s2.0-85125715539https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125715539&doi=10.1016%2Fj.eneco.2022.105908&partnerID=40&md5=1b04cc6afe314849268023ffe467650dhttps://gcris.yasar.edu.tr/handle/123456789/8730https://doi.org/10.1016/j.eneco.2022.105908Even though energy poverty has been widely discussed in many countries only a few studies attempt to understand the nexus of race and energy poverty. To fill the gap in the literature this study analyses the effect of race on energy poverty by employing the U.S. representative household panel data with 9043 complete surveys. This research addresses possible endogeneity issues by employing the novel method proposed by Oster (2019) as a robustness check in addition to the application of logistic regressions and ordinary least squares estimates. The empirical results show that the probability of exposure to poverty is higher for African-American households. The empirical outcome also presents that health and income are significant factors through which race influences energy poverty. This study suggests that subsidy programs would be beneficial in ensuring the breakage of the link between race and energy poverty by providing preferential discounted rates and easier access to energy to specific demographics of the population. At least ending with the housing segregation of African-Americans in the USA would be a way to surpass these difficulties and decrease energy poverty. Further discussions are presented in this study. © 2025 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAfrican-americans, Endogeneity, Energy Poverty, Race, Economic And Social Effects, African American, Check-in, Endogeneity, Energy, Energy Poverties, Logistics Regressions, Novel Methods, Ordinary Least Squares Estimates, Panel Data, Race, Least Squares Approximations, Empirical Analysis, Energy Conservation, Energy Management, Energy Market, Household Energy, Racial Disparity, United StatesEconomic and social effects, African American, Check-in, Endogeneity, Energy, Energy poverties, Logistics regressions, Novel methods, Ordinary least squares estimates, Panel data, Race, Least squares approximations, empirical analysis, energy conservation, energy management, energy market, household energy, racial disparity, United StatesEnergy PovertyAfrican-americansEndogeneityRACEArticle