Wasted GDP in the USA

The paper asks how HDI data can be used to assess correlations between income levels and welfare performance, and to what extent GDP is "wasted" when it does not improve welfare. It motivates the USA as a case study due to its high income, global influence, distinctive welfare regime, and early top HDI ranking, yet recent slippage in HDI rank. The study positions wasted GDP as an efficiency lens within the HDI framework, linking income, welfare, and ecological pressures. It frames the analysis against debates about growth, wellbeing, and sustainability, noting the USA’s strong income growth but relative decline in HDI ranking and much lower performance on PHDI. The goal is to quantify the share of US GDP that is not translating into nonincome human development and estimate associated avoidable ecological pressures.

The article situates its inquiry within several strands of scholarship: (1) Sustainability and progress: critiques of growth due to environmental costs and proposals such as steady-state economics, ISEW, and GPI (Meadows et al., Daly, Wackernagel & Rees, Steffen et al., Wiedmann et al.). Debates emphasize wellbeing for present and future generations, sufficiency, and questions about green growth (Hickel; Hickel & Kallis). (2) Wellbeing and GDP growth: mixed evidence on income’s relation to subjective wellbeing (Easterlin; Kahneman & Deaton; Killingsworth), policy-driven differences in social outcomes at similar income levels (Sen; Cereseto & Waitzkin), and the threshold hypothesis (Max-Neef) and GPI trends (Kubiszewski et al.). (3) HDI methodology and nonincome HDI: evolution of HDI indicators and geometric aggregation; weak correlation between income growth and changes in nonincome HDI (Gidwitz et al.; Klugman et al.; UNDP HDRO training materials). (4) Human development and sustainability: strong correlation between high HDI and environmental impact (Moran et al.; Jain & Jain). Introduction of PHDI and alternative SDI (Hickel), which heavily penalizes high incomes and planetary pressures, leading to much lower US rank by SDI and PHDI compared to HDI. The paper positions "wasted GDP" alongside Daly’s "uneconomic growth" but as an operational efficiency measure grounded in established HDI and nonincome HDI constructs.

Definition: GDP is considered wasted to the extent that it does not support welfare, with welfare proxied by nonincome HDI. Nonincome HDI is the geometric mean of the health and education indices: Nonincome HDI = (Health index × Education index)^(1/2). Health is measured by life expectancy at birth; Education by expected years of schooling and mean years of schooling. Wasted GDP estimation: A country X is compared to countries that have higher nonincome HDI but lower GDP per capita. The share of wasted GDP is inferred as the proportional excess of GDP per capita in country X over the (population-weighted) average GDP per capita of the better-performing comparison group: Wasted GDP (%) = [(GDP per capita of X − weighted GDP per capita of better performers) / GDP per capita of X] × 100. Two comparisons are used: (a) all better performers with lower GDP per capita; (b) the top 5 better performers ranked by lowest GDP per capita. Methodological distinctiveness: Unlike measures premised on an optimal economic scale (e.g., GPI, Degrowth, steady-state), wasted GDP can serve as a welfare efficiency metric regardless of views on economic scale. It focuses on GDP levels rather than GDP growth (unlike Daly’s "uneconomic growth") and builds on existing HDI methodology (unlike SDI’s substantial reweighting and thresholds). Environmental pressures linked to wasted GDP: CO2 emissions and material footprint associated with the wasted share are estimated by multiplying the wasted GDP percentage by the country’s total CO2 emissions and material footprint, respectively, using the same sources as PHDI (Global Carbon Project; UNEP). This assumes proportionality between GDP and environmental pressures across sectors; estimates are rough and sectoral variation is not analyzed.

• The USA’s HDI value rose from 0.872 (1990) to 0.930 (2019) but declined to 0.921 (2021); its HDI rank fell from #1 (1990) to #21 (2021).
• By PHDI, the USA ranks #57, 36 places lower than by HDI, reflecting higher planetary pressures.
• The USA’s nonincome HDI in 2021 is 0.894, ranking #28 globally; 27 countries have higher nonincome HDI than the USA. Of these, 21 outperform the USA on nonincome HDI despite having lower GDP per capita.
• Top 5 better performers with the lowest GDP per capita (Greece, Spain, Slovenia, Japan, Cyprus) achieve a population-weighted average nonincome HDI of 0.923 versus the USA’s 0.894, with an average GDP per capita of $39,403 vs. the USA’s $63,018 (2017 PPP), i.e., 37.5% lower. This implies 37.5% of US GDP is "wasted" under this benchmark.
• Across all better performers with lower GDP per capita, the weighted average nonincome HDI is 0.931, with average GDP per capita $46,093 (26.9% lower than the USA), implying 26.9% wasted GDP under this benchmark.
• Using total US CO2 emissions of 4.713 million tonnes (2020) and material footprint of 9.758 million tonnes (2019): • CO2 emissions attributable to wasted GDP are estimated at 1.268 million tonnes (26.9% case; ~3.6% of global) to 1.767 million tonnes (37.5% case; ~5.0% of global). • Material footprint attributable to wasted GDP is estimated at 2.625 million tonnes (26.9% case; ~2.7% of global) to 3.659 million tonnes (37.5% case; ~3.8% of global).
• Indicator-specific standings: USA ranks #45 in life expectancy (77.2 years), #31 in expected years of schooling (16.3), and #5 in mean years of schooling (13.7), underscoring that nonincome dimensions lag relative to income.

The findings address the research question by demonstrating that many countries achieve higher nonincome human development with substantially lower GDP per capita than the USA, indicating a significant portion of US GDP does not translate into welfare gains as captured by health and education outcomes. This "wasted GDP" quantification highlights inefficiency in converting economic capacity into nonincome human development. The analysis further links this inefficiency to avoidable ecological pressures: if the wasted share were eliminated, the USA could attain at least comparable or better nonincome HDI with markedly lower CO2 emissions and material footprint. The results reinforce evidence that income growth and nonincome HDI progress are weakly coupled, suggesting that policy choices and social provisioning systems are pivotal for converting resources into welfare. The implications are that prioritizing policies that directly improve health and education outcomes—drawing on practices in better-performing countries—could improve welfare while reducing ecological impacts. However, even eliminating wasted GDP would not by itself achieve ecological sustainability, indicating the need for broader systemic changes and efficiency gains across all countries, including current top performers.

The paper introduces and operationalizes the concept of wasted GDP as an efficiency metric grounded in nonincome HDI, and applies it to the USA. It shows that the USA could match or exceed current nonincome HDI outcomes at substantially lower GDP per capita, implying 26.9–37.5% of GDP is not supporting human development. Associated avoidable ecological pressures are large, equivalent to 3.6–5.0% of global CO2 emissions and 2.7–3.8% of the global material footprint. The contribution is a conservative, transparent method that complements HDI/PHDI by focusing on the welfare efficiency of GDP. Policy implications include reorienting economic and social policies toward direct wellbeing improvements (health, education, equitable provisioning) to boost nonincome HDI while reducing environmental pressures. Future research should: (a) extend wasted GDP analysis to other countries and income groups; (b) explore sectoral resource/emissions intensities and their relation to welfare gains; (c) refine methodological choices (e.g., PPP vs. MER); and (d) assess how systemic economic reforms could further reduce wasted GDP beyond current best-performer benchmarks.

• Conservativeness of benchmarks: Comparisons use today’s better-performing countries under prevailing profit-based systems; even these likely have room to improve efficiency, so wasted GDP is underestimated.
• Income measure choice: The analysis uses PPP-based GDP (and GNI in HDI); using market exchange rates would yield higher wasted GDP estimates.
• Proportionality assumption: Environmental estimates assume a constant relationship between GDP and CO2/material footprint across sectors; real economies have heterogeneous intensities, making results rough approximations.
• Scope constraints: The study does not identify which sectors most contribute to human development or analyze sectoral variation in carbon/material intensities.
• Data limitations: Liechtenstein GDP data unavailable in the IMF source; reliance on UNDP, IMF, Global Carbon Project, and UNEP datasets as referenced.