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Multidimensional poverty comparisons can be sensitive to the choice of welfare indicators, the weights assigned to the indicators, as well as the aggregate poverty measure used. This paper examines the robustness of trends in multidimensional poverty in the Philippines to these choices by presenting estimates for three alternative weighting schemes and three measures of multidimensional poverty. The weighting schemes range from uniform weights similar to those used in the global multidimensional poverty indexes produced by the United Nations Development Programme, to weights based on inverse incidence of different deprivations and those derived from the estimated relationship of deprivations to a survey-based measure of subjective welfare. The multidimensional poverty measures similarly range from the "dual cut-off" indexes analogous to the United Nations Development Programme's global Multidimensional Poverty Index, to "union-based" indexes that count all deprivations, to indexes that are also responsive to the distribution of deprivations. Using data for 2004-13, the paper finds evidence of a significant decline in multidimensional poverty that is robust to these alternatives, although the magnitude of the decline in, and especially the dimensional contributions to, aggregate multidimensional poverty are quite sensitive to the alternatives considered.

Rural poverty rankings of Indian states in 1990 were very different from those of 1960. This unevenness in progress allows us to study the causes of poverty in a developing rural economy. We model the evolution of various poverty measures using pooled state‐level data for the period 1957–91. Differences in trend rates of poverty reduction are attributed to differing growth rates of farm yield per acre and differing initial conditions; states starting with better infrastructure and human resources saw significantly higher long‐term rates of poverty reduction. Deviations from trend are attributed to inflation (which hurt the poor in the short term) and shocks to farm and non‐farm output.