{"title":"更多信贷,更少增长的悖论:调查发展中国家的信贷增长之谜","authors":"Elwaleed Ahmed Talha","doi":"10.1016/j.frl.2025.108507","DOIUrl":null,"url":null,"abstract":"<div><div>This paper investigates the credit-growth puzzle across 121 developing countries from 2015 to 2024 using Panel Threshold Regression Models (PTRMs). It addresses two key questions: (i) At what level does credit expansion begin to hinder economic growth? and (ii) How does institutional quality influence this threshold? The analysis examines how credit’s impact on growth changes at varying credit-to-GDP ratios while controlling for macroeconomic, financial, and institutional factors. The baseline model identifies thresholds at 20 %, 40 %, and 68 %, with growth effects diminishing beyond 68 %. Incorporating institutional quality and financial depth controls raises these thresholds to 79 %, indicating that stronger institutions enhance a country’s credit absorption capacity. Sub-sample analysis confirms this. Countries with strong institutions have a higher threshold 73 %, whereas those with weaker institutions face a lower threshold 49 %. To address endogeneity, a Two-Stage Least Squares (2SLS) regression validates these nonlinear, institution-dependent credit-growth dynamics, underscoring the importance of pairing credit expansion with institutional reforms and financial sector strengthening for sustainable growth. The paper concludes with policy recommendations, urging central banks to enhance credit monitoring by integrating country-specific credit-to-GDP thresholds for timely, targeted interventions.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"86 ","pages":"Article 108507"},"PeriodicalIF":6.9000,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The paradox of more credit, less growth: Investigating the credit-growth puzzle in developing countries\",\"authors\":\"Elwaleed Ahmed Talha\",\"doi\":\"10.1016/j.frl.2025.108507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper investigates the credit-growth puzzle across 121 developing countries from 2015 to 2024 using Panel Threshold Regression Models (PTRMs). It addresses two key questions: (i) At what level does credit expansion begin to hinder economic growth? and (ii) How does institutional quality influence this threshold? The analysis examines how credit’s impact on growth changes at varying credit-to-GDP ratios while controlling for macroeconomic, financial, and institutional factors. The baseline model identifies thresholds at 20 %, 40 %, and 68 %, with growth effects diminishing beyond 68 %. Incorporating institutional quality and financial depth controls raises these thresholds to 79 %, indicating that stronger institutions enhance a country’s credit absorption capacity. Sub-sample analysis confirms this. Countries with strong institutions have a higher threshold 73 %, whereas those with weaker institutions face a lower threshold 49 %. To address endogeneity, a Two-Stage Least Squares (2SLS) regression validates these nonlinear, institution-dependent credit-growth dynamics, underscoring the importance of pairing credit expansion with institutional reforms and financial sector strengthening for sustainable growth. The paper concludes with policy recommendations, urging central banks to enhance credit monitoring by integrating country-specific credit-to-GDP thresholds for timely, targeted interventions.</div></div>\",\"PeriodicalId\":12167,\"journal\":{\"name\":\"Finance Research Letters\",\"volume\":\"86 \",\"pages\":\"Article 108507\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Finance Research Letters\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1544612325017611\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Finance Research Letters","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1544612325017611","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
The paradox of more credit, less growth: Investigating the credit-growth puzzle in developing countries
This paper investigates the credit-growth puzzle across 121 developing countries from 2015 to 2024 using Panel Threshold Regression Models (PTRMs). It addresses two key questions: (i) At what level does credit expansion begin to hinder economic growth? and (ii) How does institutional quality influence this threshold? The analysis examines how credit’s impact on growth changes at varying credit-to-GDP ratios while controlling for macroeconomic, financial, and institutional factors. The baseline model identifies thresholds at 20 %, 40 %, and 68 %, with growth effects diminishing beyond 68 %. Incorporating institutional quality and financial depth controls raises these thresholds to 79 %, indicating that stronger institutions enhance a country’s credit absorption capacity. Sub-sample analysis confirms this. Countries with strong institutions have a higher threshold 73 %, whereas those with weaker institutions face a lower threshold 49 %. To address endogeneity, a Two-Stage Least Squares (2SLS) regression validates these nonlinear, institution-dependent credit-growth dynamics, underscoring the importance of pairing credit expansion with institutional reforms and financial sector strengthening for sustainable growth. The paper concludes with policy recommendations, urging central banks to enhance credit monitoring by integrating country-specific credit-to-GDP thresholds for timely, targeted interventions.
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