JRR variance estimates for longitudinal fuzzy measures of multi-dimensional poverty

This chapter explores variance estimation to longitudinal multi-dimensional fuzzy poverty measures. The measures considered are based on a fuzzy representation of individuals’ propensity for deprivation in monetary and diverse non-monetary dimensions and are derived from sample surveys with complex designs and fairly large samples. The design recommended by Eurostat is developed and described in Verma and Betti. It involves a rotational panel in which a new sample of households and individuals is introduced each year to replace one-quarter of the existing sample. All micro-level data have been weighted for variations in selection probabilities, non-response, other shortcomings in implementation, calibration on the basis of external data and population size. The cross-sectional component covers information pertaining to the current and recent periods, such as the preceding calendar year. The empirical analysis indicates that in general the fuzzy measures have smaller standard errors than conventional measures.