In:
PLOS ONE, Public Library of Science (PLoS), Vol. 16, No. 12 ( 2021-12-14), p. e0261144-
Abstract:
This paper considers the quantile regression model with individual fixed effects for spatial panel data. Efficient minimum distance quantile regression estimators based on instrumental variable (IV) method are proposed for parameter estimation. The proposed estimator is computational fast compared with the IV-FEQR estimator proposed by Dai et al. (2020). Asymptotic properties of the proposed estimators are also established. Simulations are conducted to study the performance of the proposed method. Finally, we illustrate our methodologies using a cigarettes demand data set.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0261144
DOI:
10.1371/journal.pone.0261144.g001
DOI:
10.1371/journal.pone.0261144.g002
DOI:
10.1371/journal.pone.0261144.t001
DOI:
10.1371/journal.pone.0261144.t002
DOI:
10.1371/journal.pone.0261144.t003
DOI:
10.1371/journal.pone.0261144.t004
DOI:
10.1371/journal.pone.0261144.t005
DOI:
10.1371/journal.pone.0261144.s001
DOI:
10.1371/journal.pone.0261144.s002
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2267670-3
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