Inference for Income Mobility Measures in the Presence of Spatial Dependence/ (Record no. 14098)

MARC details
000 -LEADER
fixed length control field 02085nab a2200193 4500
005 - DATE & TIME
control field 20230731121255.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Kang, Wei
245 ## - TITLE STATEMENT
Title Inference for Income Mobility Measures in the Presence of Spatial Dependence/
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Sage,
Date of publication, distribution, etc 2020.
300 ## - PHYSICAL DESCRIPTION
Pages Vol 43, Issue 1-2, 2020( 10–39 p.)
520 ## - SUMMARY, ETC.
Summary, etc Income mobility measures provide convenient and concise ways to reveal the dynamic nature of regional income distributions. Statistical inference about these measures is important especially when it comes to a comparison of two regional income systems. Although the analytical sampling distributions of relevant estimators and test statistics have been asymptotically derived, their properties in small sample settings and in the presence of contemporaneous spatial dependence within a regional income system are underexplored. We approach these issues via a series of Monte Carlo experiments that require the proposal of a novel data generating process capable of generating spatially dependent time series given a transition probability matrix and a specified level of spatial dependence. Results suggest that when sample size is small, the mobility estimator is biased while spatial dependence inflates its asymptotic variance, raising the Type I error rate for a one-sample test. For the two-sample test of the difference in mobility between two regional economic systems, the size tends to become increasingly upward biased with stronger spatial dependence in either income system, which indicates that conclusions about differences in mobility between two different regional systems need to be drawn with caution as the presence of spatial dependence can lead to false positives. In light of this, we suggest adjustments for the critical values of relevant test statistics.<br/>
700 ## - Added Entry Personal Name
Added Entry Personal Name Rey, Sergio J.
773 0# - HOST ITEM ENTRY
Host Biblionumber 11129
Host Itemnumber 17016
Place, publisher, and date of publication Sage, 2019.
Title International regional science review
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1177/0160017619826291
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type E-Journal
100 ## - MAIN ENTRY--PERSONAL NAME
-- 56515
700 ## - Added Entry Personal Name
-- 56516
942 ## - ADDED ENTRY ELEMENTS (KOHA)
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