Precipitation Anomalies and Changes in Private Credit across Asia-Pacific Economies

Authors

  • Lazarus Mensah Kwarteng School of Science, Zhejiang University of Sinence and Technology, Hangzhou, 310023, China Author
  • Mengjie Zhang School of Economics, Zhejiang University of Sinence and Technology, Hangzhou, 310023, China Author
  • Yexuan Tai School of Science, Zhejiang University of Sinence and Technology, Hangzhou, 310023, China Author
  • Yanting Ji School of Economics, Zhejiang University of Sinence and Technology, Hangzhou, 310023, China Author

DOI:

https://doi.org/10.63313/SD.9020

Keywords:

Precipitation Anomalies, Private Credit, Climate Finance, Asia-Pacific, Public Data, Panel Fixed Effects

Abstract

Weather shocks can increase financing needs while simultaneously weakening income, collateral, investment, and repayment capacity, leaving their net effect on aggregate credit ambiguous. This paper examines whether annual precipitation anomalies are associated with subsequent changes in domestic credit to the private sector across Asia-Pacific economies. We combine GPCC Precipitation Analysis Monthly v2025 with World Development Indicators, UN M49, and fixed Natural Earth boundaries. The resulting unbalanced panel contains 950 economy-year observations for 49 economies over 2000-2024. Exposure is an annual dryness anomaly relative to each economy’s 1991-2020 mean precipitation, and the outcome is the change in private credit as a share of GDP from year t to t+1. Two-way fixed-effects estimates with economy-clustered standard errors are negative but imprecise. In the controlled specification, a 10-percentage-point increase in dryness is associated with a 0.233-percentage-point lower subsequent credit-to-GDP change (95% CI: -0.548 to 0.082). The point estimate remains negative under extended controls, an alternative exposure scale, economy-specific trends, and leave-one-economy-out checks, although inference is sensitive to the covariance estimator. Because the primary confidence interval includes zero and the outcome is an aggregate credit-to-GDP measure, the evidence supports a bounded country-level association rather than a causal or bank-supply interpretation. The study provides a reproducible public-data benchmark for aggregate weather-credit relationships in the region.

References

[1] Akpa, Emeka Okoro, Afees Idowu Olayiwola, Chigozie Mark Anthony Abuta, and Sheriff Badmus. (2023) “Climate Risk and Financial Instability in Asia-Pacific.” Asian Economics Letters 4 (3). https://doi.org/10.46557/001c.37144.

[2] Albuquerque, Pedro H., and Wassim Rajhi. (2019) “Banking Stability, Natural Disasters, and State Fragility: Panel VAR Evidence from Developing Countries.” Research in International Business and Finance 50:430–43. https://doi.org/10.1016/j.ribaf.2019.06.001.

[3] Auffhammer, Maximilian, Solomon M. Hsiang, Wolfram Schlenker, and Adam Sobel. (2013) “Using Weather Data and Climate Model Output in Economic Analyses of Climate Change.” Review of Environmental Economics and Policy 7 (2): 181–98. https://doi.org/10.1093/reep/ret016.

[4] Berg, Gunhild, and Jan Schrader. (2012) “Access to Credit, Natural Disasters, and Relationship Lending.” Journal of Financial Intermediation 21 (4): 549–68. https://doi.org/10.1016/j.jfi.2012.05.003.

[5] Bos, Jaap W. B., Runliang Li, and Mark W. J. L. Sanders. (2022) “Hazardous Lending: The Impact of Natural Disasters on Bank Asset Portfolio.” Economic Modelling 108:105760. https://doi.org/10.1016/j.econmod.2022.105760.

[6] Brei, Michael, Oskar Kowalewski, Piotr Śpiewanowski, and Eric Strobl. (2026) “Drought, Bank Lending, and Agricultural Financial Resilience.” Journal of Corporate Finance 100:103031. https://doi.org/10.1016/j.jcorpfin.2026.103031.

[7] Campiglio, Emanuele, Yannis Dafermos, Pierre Monnin, Josh Ryan-Collins, Guido Schotten, and Misa Tanaka. (2018) “Climate Change Challenges for Central Banks and Financial Regulators.” Nature Climate Change 8 (6): 462–68. https://doi.org/10.1038/s41558-018-0175-0.

[8] Celil, Hursit S., Seungjoon Oh, and Srinivasan Selvam. (2022) “Natural Disasters and the Role of Regional Lenders in Economic Recovery.” Journal of Empirical Finance 68:116–32. https://doi.org/10.1016/j.jempfin.2022.07.006.

[9] Chen, Sichong, Qiyuan Xu, Jingjing Zeng, and Yunfeng Zhao. (2025) “Ark Amidst Floods: Evidence from Personal Credit at a Chinese Bank.” International Review of Financial Analysis 106:104514. https://doi.org/10.1016/j.irfa.2025.104514.

[10] Cortés, Kristle Romero, and Philip E. Strahan. (2017) “Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters.” Journal of Financial Economics 125 (1): 182–99. https://doi.org/10.1016/j.jfineco.2017.04.011.

[11] Damania, R., S. Desbureaux, and E. Zaveri. (2020) “Does Rainfall Matter for Economic Growth? Evidence from Global Sub-National Data (1990–2014).” Journal of Environmental Economics and Management 102:102335. https://doi.org/10.1016/j.jeem.2020.102335.

[12] Do, Viet, Thu Ha Nguyen, Cameron Truong, and Tram Vu. (2021) “Is Drought Risk Priced in Private Debt Contracts?” International Review of Finance 21 (2): 724–37. https://doi.org/10.1111/irfi.12294.

[13] Hong, Harrison, G. Andrew Karolyi, and José A. Scheinkman. (2020) “Climate Finance.” The Review of Financial Studies 33 (3): 1011–23. https://doi.org/10.1093/rfs/hhz146.

[14] Ivanov, Ivan T., Marco Macchiavelli, and João A. C. Santos. (2022) “Bank Lending Networks and the Propagation of Natural Disasters.” Financial Management 51 (3): 903–27. https://doi.org/10.1111/fima.12388.

[15] Kahn, Matthew E., Kamiar Mohaddes, Ryan N. C. Ng, M. Hashem Pesaran, Mehdi Raissi, and Jui-Chung Yang. (2021) “Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis.” Energy Economics 104:105624. https://doi.org/10.1016/j.eneco.2021.105624.

[16] Klomp, Jeroen. (2014) “Financial Fragility and Natural Disasters: An Empirical Analysis.” Journal of Financial Stability 13:180–92. https://doi.org/10.1016/j.jfs.2014.06.001.

[17] Kotz, Maximilian, Anders Levermann, and Leonie Wenz. (2022) “The Effect of Rainfall Changes on Economic Production.” Nature 601 (7892): 223–27. https://doi.org/10.1038/s41586-021-04283-8.

[18] Li, Shouwei, and Xin Wu. (2023) “How Does Climate Risk Affect Bank Loan Supply? Empirical Evidence from China.” Economic Change and Restructuring 56 (4): 2169–2204. https://doi.org/10.1007/s10644-023-09505-9.

[19] Mohamed, Abdikadir Ahmed, Omar Mohamud Ahmed Mohamed, Zahra Abdullahi Hussein, and Mahdi Mohamed Omar. (2026) “Climate Change as a Macro-Financial Risk Multiplier: Evidence from Private Sector Credit in Fragile Sub-Saharan Africa.” Frontiers in Climate 8. https://doi.org/10.3389/fclim.2026.1872050.

[20] Natural Earth. (2022) “Admin 0 – Countries, Version 5.1.1.” https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/.

[21] Noth, Felix, and Ulrich Schüwer. (2023) “Natural Disasters and Bank Stability: Evidence from the u.s. Financial System.” Journal of Environmental Economics and Management 119:102792. https://doi.org/10.1016/j.jeem.2023.102792.

[22] Rustemeier, Elke, Peter Finger, Zora Schirmeister, and Markus Ziese. (2025) “GPCC Precipitation Analysis Monthly Version 2025 at 0.25 Degree.” https://opendata.dwd.de/climate_environment/GPCC/html/gpcc_precipitation_analysis_monthly_v2025_doi_download.html.

[23] United Nations Statistics Division. (2026) “Standard Country or Area Codes for Statistical Use (M49).” https://unstats.un.org/unsd/methodology/m49/.

[24] World Bank. (2026) “World Development Indicators.” https://databank.worldbank.org/source/world-development-indicators.

[25] Zhang, Yun, and Hui Ming. (2025) “Climate Risk Exposure and Bank Risk-Taking Behavior: New Evidence from China.” Humanities and Social Sciences Communications 12 (1). https://doi.org/10.1057/s41599-025-06232-6.

Downloads

Published

2026-10-13

Issue

Section

Articles

How to Cite

Precipitation Anomalies and Changes in Private Credit across Asia-Pacific Economies. (2026). Sustainable Development, 2(1), 20–31. https://doi.org/10.63313/SD.9020