Small area estimation of general parameters under complex sampling designs

Guadarrama, María; Molina, Isabel; Rao, J. N. K.

doi:10.1016/j.csda.2017.11.007

Cited by 23 publications

(23 citation statements)

References 17 publications

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“…Thus, estimators of the MSE of PEB estimators under the model are proposed here. The considered procedure is a similar bootstrap procedure as in [20], based on the parametric bootstrap method for finite populations introduced by […”

Section: Parametric Bootstrap Mse Estimatormentioning

confidence: 99%

“…Poverty maps are an important source of information on the regional distribution of poverty and are currently used to support regional policy-making and to allocate funds to local jurisdictions. Good examples are the poverty and inequality maps produced by the World Bank for many countries all over the world [19]. Most poverty indicators are non-linear functions of a welfare variable such as income or expenditure.…”

Section: Introductionmentioning

confidence: 99%

“…Most poverty indicators are non-linear functions of a welfare variable such as income or expenditure. This makes many of the current small area estimation methods, typically developed for the estimation of linear characteristics, such as means, not applicable [20]. The first method designed to estimate general non-linear parameters in small areas is ELL method [21], used by the World Bank (WB) to construct poverty maps at local level.…”

Section: Introductionmentioning

confidence: 99%

“…The empirical best (EB) method of [22] gives an approximation to the best estimates in terms of mean squared error (MSE), provided that the log incomes (or other one-toone transformation of the welfare variable) are normally distributed. For estimation of general non-linear parameters in small areas, [20] proposed pseudo empirical best (PEB) method that incorporates the sampling weights and reduces considerably the bias of the un-weighted empirical best (EB) estimators under informative selection mechanisms.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Small Area Procedures for Estimating Income and Poverty in Egypt

Saied

Talat

Gohary

2019

AJPAS

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In recent years, the demand for small area statistics has greatly increased worldwide. A recent application of small area estimation (SAE) techniques is in estimating local level poverty measures in Third World countries which is necessary to achieve the Millennium Development Goals. The aim of this research is to study SAE procedures for estimating the mean income and poverty indicators for the Egyptian provinces. For this goal the direct estimators of mean income and (FGT) poverty indicators for all the Egyptian provinces are presented. Also this study applies the empirical best/Bayes (EB) and the pseudo empirical best/Bayes (PEB) methods based on the unit level - nested error - model to estimate mean income and (FGT) poverty indicators for the Egyptian border provinces with (2012-2013) income, expenditure and consumption survey (IECS) data. The (MSEs) and coefficient of variations (C.Vs) are calculated for comparative purposes. Finally the conclusions are introduced. The results show that EB estimators for poverty incidence and poverty gap are smaller than PEB for all selected provinces. EB figures indicate that the largest poverty incidence and gap are for the selected municipality at the scope of the border south west of Egypt (New Valley). The PEB figures indicate that the largest poverty incidence and gap are for the selected municipality at the scope of the border north east of Egypt (North Sinai). As expected, estimated C.Vs for EB of poverty incidence and poverty gap estimators are noticeably larger than those of PEB estimators in all selected provinces.

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Section: Parametric Bootstrap Mse Estimatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Small Area Procedures for Estimating Income and Poverty in Egypt

Saied

Talat

Gohary

2019

AJPAS

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“…the sampling plan is uninformative. The informative situation needs more careful treatment (Guadarrama et al, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Small Area Quantile Estimation

Chen

Liu

2018

Int Statistical Rev

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Summary Sample surveys are widely used to obtain information about totals, means, medians and other parameters of finite populations. In many applications, similar information is desired for subpopulations such as individuals in specific geographic areas and socio‐demographic groups. When the surveys are conducted at national or similarly high levels, a probability sampling can result in just a few sampling units from many unplanned subpopulations at the design stage. Cost considerations may also lead to low sample sizes from individual small areas. Estimating the parameters of these subpopulations with satisfactory precision and evaluating their accuracy are serious challenges for statisticians. To overcome the difficulties, statisticians resort to pooling information across the small areas via suitable model assumptions, administrative archives and census data. In this paper, we develop an array of small area quantile estimators. The novelty is the introduction of a semiparametric density ratio model for the error distribution in the unit‐level nested error regression model. In contrast, the existing methods are usually most effective when the response values are jointly normal. We also propose a resampling procedure for estimating the mean square errors of these estimators. Simulation results indicate that the new methods have superior performance when the population distributions are skewed and remain competitive otherwise.

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Malnourished but Not Destitute: The Spatial Interplay Between Nutrition and Poverty in Madagascar

Matekenya,

Mulangu,

Newhouse

2024

J of Intl Development

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Hidden hunger is a global issue that affects an astounding 2 billion people, demanding targeted interventions for better resource allocation. However, conventional methods for identifying high‐prevalence areas often prove impractical in developing countries. This study introduces a cost‐effective and practical approach to detecting hidden hunger, combining household budget data with health surveys and applying these methods to Madagascar. By using small‐area estimation techniques, the study achieves precise commune‐level estimates, addressing the limitations of survey data representativeness. The findings challenge poverty‐based targeting, revealing that 17.9% of stunted children belong to non‐poor households. Additionally, 21.3% of non‐stunted children are found in impoverished households, supporting Sen's argument that malnutrition extends beyond destitution. The analysis further highlights key commune‐level determinants of hidden hunger, including access to healthcare, improved roads, telecommunication networks and productive agricultural activities.

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Small area estimation of general parameters under complex sampling designs

Cited by 23 publications

References 17 publications

Small Area Procedures for Estimating Income and Poverty in Egypt

Small Area Procedures for Estimating Income and Poverty in Egypt

Small Area Quantile Estimation

Malnourished but Not Destitute: The Spatial Interplay Between Nutrition and Poverty in Madagascar

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