Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F18%3A00315975" target="_blank" >RIV/68407700:21340/18:00315975 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s11749-017-0545-3" target="_blank" >http://dx.doi.org/10.1007/s11749-017-0545-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11749-017-0545-3" target="_blank" >10.1007/s11749-017-0545-3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models

Popis výsledku v původním jazyce

Poverty proportions are averages of dichotomic variables that can be explained by unit-level binomial-logit mixed models. The change between the poverty proportions of two consecutive years is an indicator describing the evolution of poverty. This paper applies a unit-level temporal binomial-logit mixed model for estimating poverty proportions and their changes. The model parameters are estimated by the maximum likelihood method for the Laplace approximation of the loglikelihood. The empirical best predictors (EBP) of proportions and changes are calculated and compared with plug-in estimators. The mean squared error of the EBP is estimated by a parametric bootstrap. A simulation experiment is carried out to study the empirical behavior of the EBP and the plug-in estimators. An application to the estimation of poverty proportions and changes in counties of the region of Valencia, Spain, is given.

Název v anglickém jazyce

Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models

Popis výsledku anglicky

Poverty proportions are averages of dichotomic variables that can be explained by unit-level binomial-logit mixed models. The change between the poverty proportions of two consecutive years is an indicator describing the evolution of poverty. This paper applies a unit-level temporal binomial-logit mixed model for estimating poverty proportions and their changes. The model parameters are estimated by the maximum likelihood method for the Laplace approximation of the loglikelihood. The empirical best predictors (EBP) of proportions and changes are calculated and compared with plug-in estimators. The mean squared error of the EBP is estimated by a parametric bootstrap. A simulation experiment is carried out to study the empirical behavior of the EBP and the plug-in estimators. An application to the estimation of poverty proportions and changes in counties of the region of Valencia, Spain, is given.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

TEST

ISSN

1133-0686

e-ISSN

1863-8260

Svazek periodika

27

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

25

Strana od-do

270-294

Kód UT WoS článku

000431692900002

EID výsledku v databázi Scopus

2-s2.0-85020754858