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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "xtcspqardl" in publications use:'
type: software
license: GPL-3.0-only
title: 'xtcspqardl: Cross-Sectionally Augmented Panel Quantile ARDL'
version: 1.0.2
doi: 10.32614/CRAN.package.xtcspqardl
identifiers:
- type: doi
  value: 10.32614/CRAN.package.xtcspqardl
abstract: Implements the Cross-Sectionally Augmented Panel Quantile Autoregressive
  Distributed Lag (CS-PQARDL) model and the Quantile Common Correlated Effects Mean
  Group (QCCEMG) estimator for panel data with cross-sectional dependence. The package
  handles unobserved common factors through cross-sectional averages following Pesaran
  (2006) <https://doi.org/10.1111/j.1468-0262.2006.00692.x> and Chudik and Pesaran
  (2015) <https://doi.org/10.1016/j.jeconom.2015.03.007>. Quantile regression for
  dynamic panels follows Harding, Lamarche, and Pesaran (2018) <https://doi.org/10.1016/j.jeconom.2018.07.010>.
  The ARDL approach to cointegration testing is based on Pesaran, Shin, and Smith
  (2001) <https://doi.org/10.1002/jae.616>.
authors:
- family-names: Alkhalaf
  given-names: Muhammad
  email: muhammedalkhalaf@gmail.com
  orcid: https://orcid.org/0009-0002-2677-9246
preferred-citation:
  type: manual
  title: Cross-Sectionally Augmented Panel Quantile ARDL
  authors:
  - family-names: Alkhalaf
    given-names: Muhammad Abdullah
    email: muhammedalkhalaf@gmail.com
    orcid: https://orcid.org/0009-0002-2677-9246
  year: '2026'
  notes: R package version 1.0.2
  url: https://CRAN.R-project.org/package=xtcspqardl
  doi: 10.32614/CRAN.package.xtcspqardl
repository: https://muhammedalkhalaf.r-universe.dev
repository-code: https://github.com/muhammedalkhalaf/xtcspqardl
commit: 80a53d40e8e401e733507bf37146c94a542fa3fd
url: https://github.com/muhammedalkhalaf/xtcspqardl
date-released: '2026-03-09'
contact:
- family-names: Alkhalaf
  given-names: Muhammad
  email: muhammedalkhalaf@gmail.com
  orcid: https://orcid.org/0009-0002-2677-9246