Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India*

By D. Filmer, L. Pritchett. 2001

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Subfields: Education, Safety Research, Sociology and Political Science

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Citations in the corpus

Causal Effect Inference with Deep Latent-Variable Models (2017, neutral): “Understanding what is the best way to derive and measure possible proxy variables is an important part of many observational studies [13, 29, 55].”
Socioeconomic Status Measurement with Discrete Proxy Variables (2009, positive): “We discussed several options that may be useful in performing the principal component analysis in the presence of categorical variables: using ordinal variables as if they were continuous; using the group means implied by a normal distribution; using the dummy variables for categories as suggested b”
Using publicly available satellite imagery and deep learning to understand economic well-being in Africa (2020, methodology): “We then construct an asset index at the household level from the ﬁ rst principal component of these survey responses, a standard approach in development economics 13,16 .”
Mapping South African farming sector vulnerability to climate change and variability: A subnational assessment (2009, methodology): “Following Filmer and Pritchett (2001), the assigned weights are then used to construct an overall vulnerability index by applying the following formula: i k i ijiij sxab / 1 (4) 4 The eigenvalue is a measure of standardized variance, with a mean of 0 and standard deviation of 1.”
Constrained Gazelles: High Potentials in West Africa’s Informal Economy (2012, methodology): “This index is constructed using principal component analysis (Filmer and Pritchett, 2001; Sahn and Stifel, 2000).”
Smallholder farmer cropping decisions related to climate variability across multiple regions (2014, positive): “Since we expect farmers’ capacity to make on-farm changes to be influenced by wealth, we constructed an asset index to characterize household wealth (Filmer and Pritchett, 2001).”
Estimating the Impacts of Bolivia's Protected Areas on Poverty (2012, methodology): “To ensure that our poverty indexes are comparable across time we pool the asset data from the 1992 and 2001 census data similar to Cavatassi et al. (2004) (see also Filmer & Pritchett, 2001).”
School Attendance, Child Labour, and Remittances from International Migration in El Salvador (2011, background): “See Filmer and Pritchett (2001) and McKenzie (2005b) for further details on the application of First Principal Component techniques in the construction of asset indexes and their advantage in approximating wealth levels.”