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oai:dspace.mit.edu:1721.1/1570372024-09-25T04:05:44Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Knittel, Christopher R. Heller, Peter J. Massachusetts Institute of Technology. Institute for Data, Systems, and Society Technology and Policy Program 2024-09-24T18:28:14Z 2024-09-24T18:28:14Z 2024-05 2024-07-25T14:17:38.653Z https://hdl.handle.net/1721.1/157037 https://orcid.org/0000-0002-8064-5671 Guaranteeing sufficient and affordable access to energy services is increasingly critical as climate change continues to worsen, energy costs increase due to the need to meet decarbonization goals, and the trend in general inequality among citizens persists. To ensure the affordability of energy services, in this thesis, I analyze the design of policies and programs addressing energy poverty according to the four strategy decisions that I argue must be made during their ideation: assistance, targeting, funding, and governance. I focus on the strategies designed and implemented in the US and the EU and discuss the benefits and disadvantages of the different approaches followed in both contexts. Based on this comparative analysis, I find there are changes to US federal policy design that should be implemented to better serve households living in energy poverty. Specifically, current allocations under the US Low Income Home Energy Assistance Program (LIHEAP) to states have been nearly static since 1984, while the distribution of energy poverty is dynamic in location and time. To improve the allocation of federal resources, I produce a novel machine learning approach based on sociodemographic and geographical information to estimate energy burden in each US census tract for 2015 and 2020. This analysis reveals an increase in the average household energy burdens, and the range of households experiencing energy poverty broadened. To improve the targeting strategy of LIHEAP, I design an optimized allocation structure that illustrates a shift in funding to the southern US from northern states. To better match household assistance needs, this analysis urges policy makers to revise the distribution of resources to reflect where concentrations of energy poverty exist in the US. S.M. Massachusetts Institute of Technology Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/ Assessing United States Energy Poverty Policy: Regulatory Design Alternatives and Resource Allocation Thesis application/pdf Master Master of Science in Technology and Policy Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="0ed2ab6e-d5de-4549-af50-1db0c802a3fc"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Assessing United States Energy Poverty Policy: Regulatory Design Alternatives and Resource Allocation</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2024-05</PublicationDate> <Authors> <Author> <DisplayName>Heller, Peter J.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Abstract>Guaranteeing sufficient and affordable access to energy services is increasingly critical as climate change continues to worsen, energy costs increase due to the need to meet decarbonization goals, and the trend in general inequality among citizens persists. To ensure the affordability of energy services, in this thesis, I analyze the design of policies and programs addressing energy poverty according to the four strategy decisions that I argue must be made during their ideation: assistance, targeting, funding, and governance. I focus on the strategies designed and implemented in the US and the EU and discuss the benefits and disadvantages of the different approaches followed in both contexts. Based on this comparative analysis, I find there are changes to US federal policy design that should be implemented to better serve households living in energy poverty. Specifically, current allocations under the US Low Income Home Energy Assistance Program (LIHEAP) to states have been nearly static since 1984, while the distribution of energy poverty is dynamic in location and time. To improve the allocation of federal resources, I produce a novel machine learning approach based on sociodemographic and geographical information to estimate energy burden in each US census tract for 2015 and 2020. This analysis reveals an increase in the average household energy burdens, and the range of households experiencing energy poverty broadened. To improve the targeting strategy of LIHEAP, I design an optimized allocation structure that illustrates a shift in funding to the southern US from northern states. To better match household assistance needs, this analysis urges policy makers to revise the distribution of resources to reflect where concentrations of energy poverty exist in the US.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>