Estimation of poverty measures with auxiliary information in sample surveys (original) (raw)

Estimating Income Poverty in the Presence of Missing Data and Measurement Error

Journal of Business & Economic Statistics, 2011

This series presents research findings based either directly on data from the German Socio-Economic Panel Study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and behavioral sciences: economics, sociology, psychology, survey methodology, econometrics and applied statistics, educational science, political science, public health, behavioral genetics, demography, geography, and sport science.

Variance estimation for poverty measures in EU-SILC

2005

The objective of the research reported here is to contribute to the development of methodology and practical tools for computing sampling errors and design effects for complex statistics based on complex sampling designs, specifically sampling error of measures of poverty and inequality. It is taken as given that for the 'typical' social surveys, based on reasonably large samples but with

Poverty Comparisons with Absolute Poverty Lines Estimated from Survey Data

Review of Income and Wealth, 2007

The objective of measuring poverty is usually to make comparisons over time or between two or more groups. Common statistical inference methods are used to determine whether an apparent difference in measured poverty is statistically significant. Studies of relative poverty have long recognized that when the poverty line is calculated from sample survey data, both the variance of the poverty line and the variance of the welfare metric contribute to the variance of the poverty estimate. In contrast, studies using absolute poverty lines have ignored the poverty line variance, even when the poverty lines are estimated from sample survey data. Including the poverty line variance could either reduce or increase the precision of poverty estimates, depending on the specific characteristics of the data. This paper presents a general procedure for estimating the standard error of poverty measures when the poverty line is estimated from survey data. Based on bootstrap methods, the approach can be used for a wide range of poverty measures and methods for estimating poverty lines. The method is applied to recent household survey data from Mozambique. When the sampling variance of the poverty line is taken into account, the estimated standard errors of Foster-Greer-Thorbecke and Watts poverty measures increase by 15 to 30 percent at the national level, with considerable variability at lower levels of aggregation.

Estimating income poverty in the presence of measurement error and missing data problems

2007

Reliable measures of poverty are an essential statistical tool to evaluate public policies aimed at reducing poverty. In this paper we consider the reliability of income poverty measures based on survey data which are typically plagued by measurement error and missing data problems. Neglecting these problems can bias the estimated poverty rates. We show how to derive upper and lower bounds for the population poverty rate using only the sample evidence and an upper limit on the probability of misclassifying people into poor and non-poor. By using the European Community Household Panel, we compute bounds for the poverty rate in eleven European countries and study the sensitivity of poverty comparisons across countries to measurement errors and missing data problems.

Statistical Inference of Poverty Measures Using U-Statistics Approach

International Journal of Intelligent Technologies and Applied Statistics, 2011

Poverty measures are used to measure poverty levels or degrees of poverty in a population. Statistical inferences of poverty measures have been discussed by many authors in the literature. In this paper, U-statistics is introduced and used to estimate poverty measures. Hypotheses tests on poverty measures are obtained. For illustration, our results are applied to the real data sets collected in Egypt 2008-2009.

Hybrid Survey to Improve the Reliability of Poverty Statistics in a Cost-Effective Manner

Policy Research Working Papers, 2014

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

The optimization problem of quantile and poverty measures estimation based on calibration

Journal of Computational and Applied Mathematics, 2020

New calibrated estimators of quantiles and poverty measures are proposed. These estimators combine the incorporation of auxiliary information provided by auxiliary variables related to the variable of interest by calibration techniques with the selection of optimal calibration points under simple random sampling without replacement. The problem of selecting calibration points that minimize the asymptotic variance of the quantile estimator is addressed. Once the problem is solved, the definition of the new quantile estimator requires that the optimal estimator of the distribution function on which it is based verifies the properties of the distribution function. Through a theorem, the nondecreasing monotony property for the optimal estimator of the distribution function is established and the corresponding optimal estimator can be defined. This optimal quantile estimator is also used to define new estimators for poverty measures. Simulation studies with real data from the Spanish living conditions survey compares the performance of the new estimators against various methods proposed previously, where some resampling techniques are used for the variance estimation. Based on the results of the simulation study, the proposed estimators show a good performance and are a reasonable alternative to other estimators.