השוואת שיטות

	Asset Poverty Trap Analysis	Asset Index Construction
תחום	Development Studies	Development Studies
משפחה	Process / pipeline	Process / pipeline
שנת המקור	2006	2001
הוגה השיטה	Michael R. Carter & Christopher B. Barrett	Deon Filmer & Lant Pritchett
סוג	Panel-data test for nonlinear asset dynamics and poverty traps	Composite socioeconomic-status proxy index
מקור מכונן	Carter, M. R., & Barrett, C. B. (2006). The economics of poverty traps and persistent poverty: An asset-based approach. Journal of Development Studies, 42(2), 178–199.	Filmer, D., & Pritchett, L. H. (2001). Estimating Wealth Effects without Expenditure Data—or Tears: An Application to Educational Enrollments in States of India. Demography, 38(1), 115-132.
כינויים	Poverty Trap Analysis, Asset Dynamics Analysis, Micawber Threshold Estimation, Dynamic Asset Poverty Analysis	Wealth Index, Asset Index, PCA Wealth Index, Socioeconomic Status Index
קשורות	4	4
תקציר	Asset Poverty Trap Analysis tests whether households face nonlinear asset dynamics that can trap them in persistent poverty, using panel data on what households own rather than on what they earn. Developed by Michael Carter and Christopher Barrett (2006), the approach estimates the asset recursion — how a household's asset stock this period maps into its stock next period — and looks for multiple equilibria. When that mapping is S-shaped, there is an unstable equilibrium, the Micawber threshold, below which households converge toward a low-asset trap and above which they accumulate toward a higher equilibrium. This yields a dynamic asset poverty line and a structural reading of who is poor and likely to stay poor.	Asset index construction builds a proxy for household wealth or socioeconomic status from observable possessions — durable goods, housing quality, and access to utilities — when reliable income or consumption data are unavailable. The dominant approach, popularized by Deon Filmer and Lant Pritchett in 2001, applies principal component analysis (PCA) to a set of asset variables and uses the first principal component as a set of weights, producing a single wealth score for each household. The method underlies the wealth quintiles reported in Demographic and Health Surveys and many other household surveys across low- and middle-income countries.