Wasted GDP in the USA

The article asks how Human Development Index (HDI) data can be used to assess the relationship between income levels and welfare performance, and to what extent GDP is wasted when it does not improve welfare. HDI data are suitable because they include both income and nonincome components (health and education), with the latter combined as nonincome HDI. The USA is chosen as a case study due to its high average income, major global economic and political influence, distinct liberal welfare regime, and initially top HDI rank in 1990. Despite strong income growth, the USA has seen its HDI rank fall to 21st as of 2021, and it performs much worse on the Planetary pressures-adjusted HDI (PHDI), highlighting a tension between high development levels and environmental impact. The study develops the concept of "wasted GDP"—GDP not contributing to welfare—and explores associated ecological pressures by linking wasted GDP to CO2 emissions and material footprint. The estimates are conservative because they benchmark against current best performers (who may themselves have waste) and rely on PPP-based income measures, which yield lower waste estimates than market exchange rates.

The paper situates its contribution within several strands of research: (1) Progress and sustainability: Since the 1970s, scholars have critiqued growth for its environmental costs and proposed alternatives (Daly’s steady-state economics; ISEW/GPI). There is an ongoing shift from GDP toward wellbeing metrics, with numerous alternative indices. (2) Wellbeing and GDP growth: Evidence shows mixed relationships. While income correlates with levels of health and education, changes in income do not consistently drive changes in these nonincome outcomes. Some studies suggest diminishing or threshold effects of income on quality of life; others find subjective wellbeing continues to rise with income. Policy choices (e.g., public provisioning) can yield better social outcomes at similar income levels. (3) Daly’s uneconomic growth: Growth can become uneconomic when marginal costs exceed benefits, implying reduced net welfare. This concept overlaps with wasted GDP but focuses on growth margins rather than efficiency of existing GDP. (4) Human development and sustainability: High HDI levels correlate with high environmental impact. New indices (e.g., PHDI, SDI) integrate environmental pressures, often reshuffling rankings and revealing incompatibility between income-heavy development models and ecological stability. The SDI and PHDI illustrate how methodology shapes country assessments. The concept of wasted GDP complements these by using established HDI/nonincome HDI and benchmarking efficiency across countries.

Wasted GDP is defined under the assumption that the purpose of economic activity is to support human welfare. Welfare performance is proxied by nonincome HDI, the geometric mean of the health and education indices (health based on life expectancy at birth; education based on expected and mean years of schooling). For country X, identify countries Y…Z that have higher nonincome HDI but lower GDP per capita. The share of GDP deemed wasted is: Wasted GDP (%) = [(GDP per capita of X − weighted average GDP per capita of Y…Z) / (GDP per capita of X)] × 100. Weighted averages are population-weighted. Two benchmarks are used: (a) all better performers with lower GDP per capita; and (b) the top 5 performers among these with the lowest GDP per capita. Methodological positioning: Unlike approaches positing an optimal economic scale (e.g., GPI, Degrowth, steady-state), wasted GDP can be used purely as an efficiency measure; unlike Daly’s uneconomic growth, it focuses on GDP levels rather than growth; unlike Hickel’s SDI, it does not significantly alter HDI methodology, relying instead on nonincome HDI. Estimating ecological pressures: CO2 emissions and material footprint attributable to wasted GDP are estimated by multiplying wasted GDP (%) by national totals for CO2 emissions and material footprint (same sources as UNDP’s PHDI). This assumes a proportional relationship between GDP and environmental pressures across sectors, recognized as a simplification; sectoral variation and contribution to welfare by sector are not analyzed.

• The USA’s HDI rank fell from #1 (1990) to #21 (2021) despite strong income growth; by nonincome HDI it ranks #28. - Twenty-seven countries have higher nonincome HDI than the USA; 21 of these also have lower GDP per capita than the USA. - Top 5 better performers by nonincome HDI with the lowest GDP per capita (Greece, Spain, Slovenia, Japan, Cyprus) achieve a population-weighted nonincome HDI of 0.923 (+0.029 vs USA’s 0.894) with average GDP per capita of $39,403 vs USA’s $63,018—37.5% lower. - All better performers (with lower GDP per capita) achieve a weighted nonincome HDI of 0.931 (+0.037) with average GDP per capita of $46,093—26.9% lower. Including all 26 better performers (even those with higher GDP per capita) yields the same nonincome HDI (0.931) and an average GDP per capita 24.0% lower than the USA. - Emissions and resource use linked to wasted GDP: Based on wasted GDP shares, US CO2 emissions could be 1.268–1.767 million tonnes lower (3.6–5.0% of global emissions), and material footprint 2.625–3.659 million tonnes lower (2.7–3.8% of the global material footprint). - Indicator-level contrasts: The USA ranks #5 globally in mean years of schooling (13.7 years) but only #31 in expected years of schooling (16.3 years) and #45 in life expectancy (77.2 years), underscoring nonincome performance gaps.

The findings show that many countries deliver better health and education outcomes (nonincome HDI) than the USA with substantially less GDP per capita, indicating a sizable share of US GDP does not translate into welfare—i.e., wasted GDP. This directly addresses the research question by using nonincome HDI to benchmark welfare performance relative to income. The efficiency gaps suggest policy configurations—particularly in public provisioning, health systems, education, and social protection—can achieve higher welfare at lower income levels. The ecological implications are substantial: eliminating wasted GDP could reduce significant shares of US CO2 emissions and material footprint without sacrificing nonincome human development. This reinforces arguments to prioritize policies that directly promote wellbeing and reduce environmental impacts. However, even eliminating wasted GDP in rich countries will not alone achieve ecological sustainability; best performers themselves likely have remaining inefficiencies and high planetary pressures, pointing to broader systemic changes needed.

The paper introduces and operationalizes the concept of wasted GDP using established HDI methodology, demonstrating that the USA could match or exceed current nonincome human development outcomes at much lower GDP per capita, with associated reductions in CO2 emissions and material footprint. This efficiency-based perspective complements existing critiques of growth-centric metrics and provides a practical benchmarking tool. Policy-wise, prioritizing human wellbeing and needs-oriented provisioning can improve welfare and lower ecological pressures. Future research should: (1) apply the wasted GDP framework across diverse income groups and regions; (2) explore sectoral variations in the GDP–welfare–impact nexus; (3) assess alternative income measures (e.g., MER vs PPP) and distributional aspects; and (4) investigate institutional arrangements that enable high nonincome HDI at lower environmental cost.

Estimates are intentionally conservative. Benchmarks assume current best-performing countries represent attainable efficiency, though they may themselves waste GDP. Income is measured in PPP terms; using market exchange rates would yield higher wasted GDP estimates. The approach assumes proportionality between GDP and environmental pressures across sectors, which is not strictly true. The study does not analyze sectoral differences in carbon/material intensity nor identify which sectors contribute most to human development.