Many efforts have been undertaken over the years in the collection of poverty-related data. Nonetheless, poverty studies face several challenges including definitional issues and analytical limitations. Moreover, while the level of disaggregation of household survey data has significantly improved, the resulting data are often difficult to summarize and to digest. This paper first takes a broad look at analysis tools and highlights definitional and methodological issues that transpire from the literature. Emphasis is on the multidimensionality aspect of poverty, with implications on the limits of the measurement instruments often used. As an attempt to address the issue of measurablity of this multidimensional phenomenon, the paper offers a methodology for constructing indixes of wealth using transformed qualitative variables that are easy to collect. This methodology includes the traditional Principal Components analysis based on the Z-scores (i.e. the Standard Normal Scores) and a new Principal Components approach based on a new set of scores called U-scores (i.e. the standardized uniform transformation of discrete, and categorical variables). Applied to the data from the Living Standard Measurement Survey of the Cote d‘Ivoire, the U-scores methodology yields the Housing Index, a composite index based on discrete housing characteristics. This U-scores approach is validated by investigating how well the resulting composite index compare with the Household Total Expenditure in explaining education achievement. Both a graphic investigation and a \"generalized\" Log-linear model suggest that very different rural and urban school outcomes be better explained by the Housing Index as opposed to the per capita expenditures.