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The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure
Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mecha...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201467/ https://www.ncbi.nlm.nih.gov/pubmed/35719624 http://dx.doi.org/10.3389/fpubh.2022.922574 |
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author | Li, Chengming Li, Daming He, Si Sun, Shiqi Tian, Yuan Wang, Zeyu |
author_facet | Li, Chengming Li, Daming He, Si Sun, Shiqi Tian, Yuan Wang, Zeyu |
author_sort | Li, Chengming |
collection | PubMed |
description | Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mechanism of big data-based digital payments on household healthcare expenditure. The empirical results of this paper show that the use of digital payments by households can significantly increase household healthcare expenditure with the empowerment of big data. This research employs the instrumental variable method to verify and produce consistent estimation results in order to address potential endogeneity issues such as measurement error and missing variables. We learn via mechanism analysis that household adoption of big data-driven digital payments can remove credit limitations and build social capital, resulting in higher household health-care spending. We also perform a heterogeneity analysis. The findings reveal that when a family's traditional financial accessibility is high, the head of the household is young or middle-aged, and the head of the household has a higher level of education, digital payment will play a larger role in encouraging household healthcare expenditure. The conclusions of this paper are still solid after changing the indicators of household healthcare expenditure substituting the indicators of digital payment, and adjusting the variables. As a result, this article provides micro-evidence for the usage of digital payments by households to enhance healthcare spending. JEL CLASSIFICATION: D12 G21 O30 O53 I12 |
format | Online Article Text |
id | pubmed-9201467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92014672022-06-17 The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure Li, Chengming Li, Daming He, Si Sun, Shiqi Tian, Yuan Wang, Zeyu Front Public Health Public Health Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mechanism of big data-based digital payments on household healthcare expenditure. The empirical results of this paper show that the use of digital payments by households can significantly increase household healthcare expenditure with the empowerment of big data. This research employs the instrumental variable method to verify and produce consistent estimation results in order to address potential endogeneity issues such as measurement error and missing variables. We learn via mechanism analysis that household adoption of big data-driven digital payments can remove credit limitations and build social capital, resulting in higher household health-care spending. We also perform a heterogeneity analysis. The findings reveal that when a family's traditional financial accessibility is high, the head of the household is young or middle-aged, and the head of the household has a higher level of education, digital payment will play a larger role in encouraging household healthcare expenditure. The conclusions of this paper are still solid after changing the indicators of household healthcare expenditure substituting the indicators of digital payment, and adjusting the variables. As a result, this article provides micro-evidence for the usage of digital payments by households to enhance healthcare spending. JEL CLASSIFICATION: D12 G21 O30 O53 I12 Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9201467/ /pubmed/35719624 http://dx.doi.org/10.3389/fpubh.2022.922574 Text en Copyright © 2022 Li, Li, He, Sun, Tian and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Li, Chengming Li, Daming He, Si Sun, Shiqi Tian, Yuan Wang, Zeyu The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title | The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title_full | The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title_fullStr | The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title_full_unstemmed | The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title_short | The Effect of Big Data-Based Digital Payments on Household Healthcare Expenditure |
title_sort | effect of big data-based digital payments on household healthcare expenditure |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201467/ https://www.ncbi.nlm.nih.gov/pubmed/35719624 http://dx.doi.org/10.3389/fpubh.2022.922574 |
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