censored regressors, and binary regressions with interval data or measurement errors on regressors. We characterize the …

Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However …, regular series of strictly comparable data are only rarely available. Poverty prediction methods that track consumption … tested directly. This study analyses the performance of poverty prediction models based on small area estimation (SAE …

We consider the estimation of measures of persistent poverty in panel surveys with missing data, focusing on the … persistent poverty headcount, its duration-adjusted variant, and a related measure used by the European Union as an indicator of … the risk of persistent poverty. We develop a partial identification approach to allow for data missing-not-at-random, and …

Most poverty studies build on measures that take account of recurring incomes from sources such as labour or social … ways. Previous studies that have sought to incorporate assets into poverty measures suggest that (1) poverty estimates … including wealth are considerably lower than income‐based measures; (2) poverty rates of the elderly are more affected than …

of possible impacts of measurement errors on poverty analysis are briefly discussed. These experiments clearly show the …This paper firstly aims to evaluate the incidence of measurement error affecting the main variables collected in … the case of panel data, an estimation of the incidence of measurement error on the total variance can be obtained by …

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding … these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several … nature, classification errors play a similar role as measurement errors in continuous data. The paper also reviews some …