A Multidimensional Framework for Welfare-Adjusted Growth Accounting

Thesis Abstract

This study addresses the gap between conventional growth accounting and welfare considerations by proposing a Multidimensional Framework for Welfare-Adjusted Growth Accounting (WAGA) that integrates monetary and non-monetary well-being dimensions into a coherent growth metric. The problem motivating the research is that traditional GDP-based measures obscure distributional and welfare trade-offs, leading to policy misalignment when growth does not translate into societal welfare improvements. The aim is to develop a theoretically grounded and empirically implementable framework that decomposes growth into welfare-relevant components, enabling more accurate assessment of progress. Specific objectives are (1) to identify and operationalize core welfare dimensions—material living standards, health, education, environmental quality, and subjective well-being—within a unified accounting framework; (2) to construct a composite Welfare-Adjusted Growth (WAG) index that augments GDP with quality-of-life indicators and environmental costs; (3) to specify and estimate a production-function-type model that links factor inputs, technology, and welfare outcomes; (4) to conduct cross-country and within-country panel analyses to examine the consistency and sensitivity of WAG across development levels; and (5) to evaluate policy implications by comparing WAG with GDP growth under various policy scenarios. Methodologically, the study adopts a mixed-methods research design anchored in both quantitative econometric modeling and qualitative validation. The population comprises 30 advanced economies and 40 emerging economies over the 1995–2023 period, yielding a panel of approximately 1,400 observations after removing missing data. A stratified random sampling approach ensures representation across income groups and geographic regions. Data collection employs secondary datasets from the World Bank World Development Indicators, the OECD Better Life Index, the Global Reporting Initiative environmental metrics, and national statistical agencies to construct a comprehensive panel dataset capturing output, health, education, living standards, environmental indicators, and life satisfaction measures. Instruments include standardized indicators such as GDP per capita, years of schooling, life expectancy, pollution-adjusted welfare measures, and respondent-rated life satisfaction scores. Validity and reliability checks incorporate cross-source triangulation, unit-root tests, and cointegration assessments. The analysis proceeds in two stages. First, a theoretical model specification extends the PIW (physical, informational, and welfare) framework into a Welfare-Adjusted Growth model, integrating a production function with a welfare-enhancing technology component T that elevates welfare outcomes given capital K and labor L, while incorporating environmental costs E and distributional weights to reflect inequality aversion. Second, econometric estimation employs fixed-effects and system GMM estimators to address endogeneity, with robust standard errors and cross-sectional dependence controlled via Driscoll-K compounded standard errors. The WAG index is constructed as a weighted aggregate of GDP per capita, health-adjusted life years, mean years of schooling, a pollution-adjusted living standard measure, and a subjective well-being component, normalized to enable comparability across countries and years. Hypotheses test whether WAG provides a statistically significant deviation from GDP growth in capturing welfare gains, and whether cross-country heterogeneity is explained by institutions, governance quality, and policy stringency. Expected findings include (i) WAG will exhibit stronger explanatory power for long-run welfare outcomes than GDP alone, particularly in economies with high inequality or environmental degradation; (ii) the welfare components will display varying marginal contributions across development stages, with health and education playing larger roles in low- and middle-income contexts, and environmental quality gaining prominence in advanced economies; (iii) policy simulations will indicate that growth strategies prioritizing human capital and environmental sustainability yield higher WAG in the long run, even if short-run GDP gains are modest. The study contributes to knowledge by integrating welfare dimensions into growth accounting, providing a replicable empirical framework, and offering policy-relevant insights for macroeconomic management, social policy design, and sustainable development discourse. The main conclusion is that welfare-adjusted growth offers a more comprehensive gauge of economic progress, and recommendations emphasize embedding welfare metrics in national accounts, adopting balanced growth strategies, and enhancing data harmonization for robust WAG estimation.