<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T17:38:15Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/103563" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/103563</identifier><datestamp>2026-06-16T18:54:37Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Olivier L. de Weck.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Collins, Ross D. (Ross Daniel)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Institute for Data, Systems, and Society.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Institute for Data, Systems, and Society</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="accessioned">2016-07-11T14:43:31Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2016-07-11T14:43:31Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/103563</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">938609318</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D., Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2015.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Vita. Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 227-237).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Inclusive wealth (IW) measures the productive base of an economy, which is a linear index of its capital asset stocks. Changes to IW per capita over time track changes to intergenerational human well-being, thus non-declining IW per capita indicates sustainable development. National IW has only been measured retrospectively; this dissertation models and projects IW prospectively, measuring the impact of alternative infrastructure plans on IW. The focus of the work is on electricity planning in oil-exporting countries. Domestic oil consumption in these countries, driven by increasing electricity use, threatens long-term development by reducing the export revenue on which the government and economy depends. First, I develop a system dynamics model that connects electric power capacity expansion with macroeconomic development, tabulating both infrastructure costs and impacts to the capital stocks of IW over time. The Kingdom of Saudi Arabia (KSA) is the primary case study. Second, I analyze the capital stock projections generated by the model across a range of scenarios and countries. Under the baseline IW formulation, KSA experiences a negative annual growth rate to inclusive wealth per capita to 2050. However, adjusted formulations allow the possibility of periods of positive growth, and a non-oil sector that is less dependent on the oil sector will shift the IW trajectory upwards. Compared to KSA, Kuwait is likely to experience larger per capita declines in IW. The United Arab Emirates (UAE), on the other hand, will potentially experience positive growth rates in per capita IW starting in 2028. Third, I analyze the IW impacts of non-fossil investments in electricity infrastructure, specifically nuclear and solar, between now and 2050. In KSA, the produced capital benefits of non-fossil investment outweigh the oil capital costs (to finance the infrastructure) across a range of uncertainties. Including human capital benefits raises net benefits by an order of magnitude. The optimal allocation of nuclear and solar power ultimately depends on the evaluation metric used. The UAE gains least from non-fossil investment, since it uses comparatively less oil in its electricity system, while Kuwait experiences gains similar to KSA. Importantly, using IW as the basis for electricity policy evaluation yields qualitatively different prescriptions than a least-cost capacity expansion model.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Ross D. Collins.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">290 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Institute for Data, Systems, and Society.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Using inclusive wealth as a measure of sustainability for infrastructure planning and evaluation</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Using IW as a measure of sustainability for infrastructure planning and evaluation</dim:field>
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   	&lt;Title>Using inclusive wealth as a measure of sustainability for infrastructure planning and evaluation&lt;/Title>
   	&lt;Subtitle>Using IW as a measure of sustainability for infrastructure planning and evaluation&lt;/Subtitle>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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        	&lt;DisplayName>Collins, Ross D. (Ross Daniel)&lt;/DisplayName>
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    &lt;Keyword>Institute for Data, Systems, and Society.&lt;/Keyword>
   	&lt;Abstract>Inclusive wealth (IW) measures the productive base of an economy, which is a linear index of its capital asset stocks. Changes to IW per capita over time track changes to intergenerational human well-being, thus non-declining IW per capita indicates sustainable development. National IW has only been measured retrospectively; this dissertation models and projects IW prospectively, measuring the impact of alternative infrastructure plans on IW. The focus of the work is on electricity planning in oil-exporting countries. Domestic oil consumption in these countries, driven by increasing electricity use, threatens long-term development by reducing the export revenue on which the government and economy depends. First, I develop a system dynamics model that connects electric power capacity expansion with macroeconomic development, tabulating both infrastructure costs and impacts to the capital stocks of IW over time. The Kingdom of Saudi Arabia (KSA) is the primary case study. Second, I analyze the capital stock projections generated by the model across a range of scenarios and countries. Under the baseline IW formulation, KSA experiences a negative annual growth rate to inclusive wealth per capita to 2050. However, adjusted formulations allow the possibility of periods of positive growth, and a non-oil sector that is less dependent on the oil sector will shift the IW trajectory upwards. Compared to KSA, Kuwait is likely to experience larger per capita declines in IW. The United Arab Emirates (UAE), on the other hand, will potentially experience positive growth rates in per capita IW starting in 2028. Third, I analyze the IW impacts of non-fossil investments in electricity infrastructure, specifically nuclear and solar, between now and 2050. In KSA, the produced capital benefits of non-fossil investment outweigh the oil capital costs (to finance the infrastructure) across a range of uncertainties. Including human capital benefits raises net benefits by an order of magnitude. The optimal allocation of nuclear and solar power ultimately depends on the evaluation metric used. The UAE gains least from non-fossil investment, since it uses comparatively less oil in its electricity system, while Kuwait experiences gains similar to KSA. Importantly, using IW as the basis for electricity policy evaluation yields qualitatively different prescriptions than a least-cost capacity expansion model.&lt;/Abstract>
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