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http://dx.doi.org/10.7465/jkdi.2013.24.6.1199

Generalized kernel estimating equation for panel estimation of small area unemployment rates  

Shim, Jooyong (Department of Data Science, Inje University)
Kim, Youngwon (Department of Statistics, Sookmyung Women's University)
Hwang, Changha (Department of Applied Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.24, no.6, 2013 , pp. 1199-1210 More about this Journal
Abstract
The high unemployment rate is one of the major problems in most countries nowadays. Hence, the demand for small area labor statistics has rapidly increased over the past few years. However, since sample surveys for producing official statistics are mainly designed for large areas, it is difficult to produce reliable statistics at the small area level due to small sample sizes. Most of existing studies about the small area estimation are related with the estimation of parameters based on cross-sectional data. By the way, since many official statistics are repeatedly collected at a regular interval of time, for instance, monthly, quarterly, or yearly, we need an alternative model which can handle this type of panel data. In this paper, we derive the generalized kernel estimating equation which can model time-dependency among response variables and handle repeated measurement or panel data. We compare the proposed estimating equation with the generalized linear model and the generalized estimating equation through simulation, and apply it to estimating the unemployment rates of 25 areas in Gyeongsangnam-do and Ulsan for 2005.
Keywords
Generalized estimating equation; generalized kernel estimating equation; generalized linear model; kernel technique; panel data; panel estimation; small area estimation;
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Times Cited By KSCI : 8  (Citation Analysis)
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