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How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning

Yan Fang, Yinglin Liu, Yi Yang, Brian Lucey, Mohammad Abedin Orcid Logo

Research in International Business and Finance, Volume: 74, Start page: 102728

Swansea University Author: Mohammad Abedin Orcid Logo

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DOI (Published version): 10.1016/j.ribaf.2024.102728

Abstract

This paper employs the double machine learning model to investigate the impact of urban investment bonds on economic resilience. To deal with a broad set of macroeconomic and industry variables, LASSO is used for model estimation. The sample consists of 239 Chinese cities that issued debt and loan i...

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Published in: Research in International Business and Finance
ISSN: 0275-5319
Published: Elsevier BV 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa68661
first_indexed 2025-01-09T20:34:06Z
last_indexed 2025-01-09T20:34:06Z
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spelling 2025-01-08T11:55:29.8148706 v2 68661 2025-01-08 How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning 4ed8c020eae0c9bec4f5d9495d86d415 0000-0002-4688-0619 Mohammad Abedin Mohammad Abedin true false 2025-01-08 CBAE This paper employs the double machine learning model to investigate the impact of urban investment bonds on economic resilience. To deal with a broad set of macroeconomic and industry variables, LASSO is used for model estimation. The sample consists of 239 Chinese cities that issued debt and loan instruments between 2016 and 2021. The results show that 1) urban investment bonds have a positive, inverted U-shaped effect on economic resilience; 2) the ability to recover from an economic shock plays an important role in constructing the Chinese economic resilience index. The heterogeneity analysis reveals that the impact of urban investment bonds on economic resilience varies according to cities’ locations, industrial structure, and financial structure. Furthermore, the mechanism analysis demonstrates that urban investment bonds enhance economic resilience by promoting infrastructure development. These findings provide helpful guidance for China and other developing countries to ensure financing security and maintain robust economic growth. Journal Article Research in International Business and Finance 74 102728 Elsevier BV 0275-5319 Economic Resilience, Urban Investment Debts, Double Machine Learning, LASSO Technique, Heterogeneity Analysis 1 2 2025 2025-02-01 10.1016/j.ribaf.2024.102728 https://doi.org/10.1016/j.ribaf.2024.102728 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) This paper was supported by the Major Program of the National Social Science Foundation of China (Grant No. 21BTJ047) 2025-01-08T11:55:29.8148706 2025-01-08T11:48:12.4916043 Faculty of Humanities and Social Sciences School of Management - Business Management Yan Fang 1 Yinglin Liu 2 Yi Yang 3 Brian Lucey 4 Mohammad Abedin 0000-0002-4688-0619 5
title How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
spellingShingle How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
Mohammad Abedin
title_short How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
title_full How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
title_fullStr How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
title_full_unstemmed How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
title_sort How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Mohammad Abedin
author Mohammad Abedin
author2 Yan Fang
Yinglin Liu
Yi Yang
Brian Lucey
Mohammad Abedin
format Journal article
container_title Research in International Business and Finance
container_volume 74
container_start_page 102728
publishDate 2025
institution Swansea University
issn 0275-5319
doi_str_mv 10.1016/j.ribaf.2024.102728
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
url https://doi.org/10.1016/j.ribaf.2024.102728
document_store_str 0
active_str 0
description This paper employs the double machine learning model to investigate the impact of urban investment bonds on economic resilience. To deal with a broad set of macroeconomic and industry variables, LASSO is used for model estimation. The sample consists of 239 Chinese cities that issued debt and loan instruments between 2016 and 2021. The results show that 1) urban investment bonds have a positive, inverted U-shaped effect on economic resilience; 2) the ability to recover from an economic shock plays an important role in constructing the Chinese economic resilience index. The heterogeneity analysis reveals that the impact of urban investment bonds on economic resilience varies according to cities’ locations, industrial structure, and financial structure. Furthermore, the mechanism analysis demonstrates that urban investment bonds enhance economic resilience by promoting infrastructure development. These findings provide helpful guidance for China and other developing countries to ensure financing security and maintain robust economic growth.
published_date 2025-02-01T20:37:09Z
_version_ 1821348650680320000
score 11.04748

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