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Прикладная эконометрика / Applied Econometrics  / №1 2015

Fast methods for jackknifing inequality indices (150,00 руб.)

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Первый авторKaroly
АвторыSchröder C.
Страниц14
ID429036
АннотацияThe jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper develops fast algorithms for jackknifing inequality indices with only a few passes through the data. The number of passes is independent of the number of observations. Hence, the method provides an efficient way to obtain standard errors of the estimators even if sample size is large. We apply our method using micro data on individual incomes for Germany and the US.
Fast methods for jackknifing inequality indices [Электронный ресурс] / Karoly, Schröder // Прикладная эконометрика / Applied Econometrics .— 2015 .— №1 .— С. 125-138 .— Режим доступа: https://rucont.ru/efd/429036

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L. A. Karoly, C. Schrцder APPLIED ECONOMETRICS ПРИКЛАДНАЯ ЭКОНОМЕТРИКА № 37 (1) 2015 L. A. Karoly, C. Schrцder Fast methods for jackknifing inequality indices The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. <...> Hence, the method provides an efficient way to obtain standard errors of the estimators even if sample size is large. <...> The delta method is based on the asymptotic distribution of the index, whereas the jackknife and the bootstrap are distribution free resampling methods. <...> The bootstrap samples with replacement from the original sample1. <...> The delta method, if applicable to an inequality index, has as advantages that it derives the asymptotic distribution using the central limit theorem, and that the computational burden to estimate the asymptotic variance consistently is low. <...> For example, one difficulty arises if cross-sections of a panel survey are used as the empirical database, as it is the case for available micro datasets including the Luxembourg Income Study (LIS)3, probably the most frequently used database for distributional analyses worldwide. <...> Then for testing for inter-temporal changes in inequality indices the inter-temporal covariance structure of incomes must be considered. <...> W 1 For the validity of the bootstrap technique in inequality analyses see (Biewen, 2002). 2 For the theoretical justification for the jackknife and other related resampling techniques see (Efron, 1982). 3 http://www.lisdatacenter.org/. 4 Modarres and Gastwirth (2006) show that regression estimates of the standard error for the Gini index can be biased «as it does not account for the correlation introduced in the error terms once the data are sorted» (p. 387). 5 Decomposition analyses impose restrictions on the functional forms of regression models (see (Fields, Yoo, 2000), or (Morduch, Sicular, 2002)). <...> The delta method, bootstrapping and jackknifing are popular methods for performing statistical inference on inequality indi № 37 (1) 2015 ПРИКЛАДНАЯ ЭКОНОМЕТРИКА APPLIED ECONOMETRICS Aforementioned limitations of the delta method explain the interest in resampling methods6. <...> The central advantage of the jackknife over other resampling methods such as the bootstrap is that it allows the replication of results. <...> A disadvantage of standard jackknife procedures is that for large sample sizes the computational <...>