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Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model

OBJECTIVE: The provision of healthcare facilities remains high on the manifesto of various political parties in Pakistan and healthcare spending has witnessed a significant surge in the last two decades that is expected to positively influence health outcomes in the country. Therefore, this research...

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Autores principales: Ullah, Irfan, Ullah, Assad, Ali, Sher, Poulova, Petra, Akbar, Ahsan, Haroon Shah, Muhammad, Rehman, Alam, Zeeshan, Muhammad, Afridi, Fakhr E Alam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462281/
https://www.ncbi.nlm.nih.gov/pubmed/34584469
http://dx.doi.org/10.2147/RMHP.S316844
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author Ullah, Irfan
Ullah, Assad
Ali, Sher
Poulova, Petra
Akbar, Ahsan
Haroon Shah, Muhammad
Rehman, Alam
Zeeshan, Muhammad
Afridi, Fakhr E Alam
author_facet Ullah, Irfan
Ullah, Assad
Ali, Sher
Poulova, Petra
Akbar, Ahsan
Haroon Shah, Muhammad
Rehman, Alam
Zeeshan, Muhammad
Afridi, Fakhr E Alam
author_sort Ullah, Irfan
collection PubMed
description OBJECTIVE: The provision of healthcare facilities remains high on the manifesto of various political parties in Pakistan and healthcare spending has witnessed a significant surge in the last two decades that is expected to positively influence health outcomes in the country. Therefore, this research aims to explore the effects of healthcare expenditures on the actual health status of the masses in Pakistan for the period 1995Q1 to 2017Q1. METHODS: We apply the Quantile Autoregressive Distributed Lag (QARDL) approach for estimation purposes. This is the most recent and emerging estimation technique in time series analysis. RESULTS: Our findings confirm that public healthcare spending significantly impacts health outcomes in Pakistan both in the short-run and long-run. Public healthcare spending improves life expectancy and reduces death rate and infant mortality. CONCLUSION: The study concludes that public healthcare is the main focus of the current regime. It is noticed that spending on healthcare significantly contributes to the health outcomes in Pakistan. These efforts by the government significantly promote life expectancy and drop down the mortality ratio in the country. Based on these notable facts, the government should allocate sufficient resources towards the latest healthcare technologies and equipment to optimize health outcomes in the country.
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spelling pubmed-84622812021-09-27 Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model Ullah, Irfan Ullah, Assad Ali, Sher Poulova, Petra Akbar, Ahsan Haroon Shah, Muhammad Rehman, Alam Zeeshan, Muhammad Afridi, Fakhr E Alam Risk Manag Healthc Policy Original Research OBJECTIVE: The provision of healthcare facilities remains high on the manifesto of various political parties in Pakistan and healthcare spending has witnessed a significant surge in the last two decades that is expected to positively influence health outcomes in the country. Therefore, this research aims to explore the effects of healthcare expenditures on the actual health status of the masses in Pakistan for the period 1995Q1 to 2017Q1. METHODS: We apply the Quantile Autoregressive Distributed Lag (QARDL) approach for estimation purposes. This is the most recent and emerging estimation technique in time series analysis. RESULTS: Our findings confirm that public healthcare spending significantly impacts health outcomes in Pakistan both in the short-run and long-run. Public healthcare spending improves life expectancy and reduces death rate and infant mortality. CONCLUSION: The study concludes that public healthcare is the main focus of the current regime. It is noticed that spending on healthcare significantly contributes to the health outcomes in Pakistan. These efforts by the government significantly promote life expectancy and drop down the mortality ratio in the country. Based on these notable facts, the government should allocate sufficient resources towards the latest healthcare technologies and equipment to optimize health outcomes in the country. Dove 2021-09-16 /pmc/articles/PMC8462281/ /pubmed/34584469 http://dx.doi.org/10.2147/RMHP.S316844 Text en © 2021 Ullah et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Ullah, Irfan
Ullah, Assad
Ali, Sher
Poulova, Petra
Akbar, Ahsan
Haroon Shah, Muhammad
Rehman, Alam
Zeeshan, Muhammad
Afridi, Fakhr E Alam
Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title_full Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title_fullStr Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title_full_unstemmed Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title_short Public Health Expenditures and Health Outcomes in Pakistan: Evidence from Quantile Autoregressive Distributed Lag Model
title_sort public health expenditures and health outcomes in pakistan: evidence from quantile autoregressive distributed lag model
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462281/
https://www.ncbi.nlm.nih.gov/pubmed/34584469
http://dx.doi.org/10.2147/RMHP.S316844
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