Borrower‐based macroprudential measures and credit growth: How biased is the existing literature?
对34项研究中的700多个估计值进行元分析，发现现有文献存在显著的发表偏倚，校正后借款人措施使信贷增长减少0.6至1.1个百分点，远低于未调整的平均值。
Abstract This paper analyzes over 700 estimates from 34 studies on the impact of borrower‐based measures (such as loan‐to‐value, debt‐to‐income, and debt‐service‐to‐income ratios) on bank loan provision. Our dataset reveals notable fragmentation in the literature concerning variable transformations, methods, and estimated coefficients. We run a meta‐analysis on a subsample of 422 semi‐elasticities from 23 studies employing a consistent estimation framework to draw an economic interpretation. We confirm strong publication bias, particularly against positive and statistically insignificant estimates. After correcting for this bias, the effect indicates a credit growth reduction of −0.6 to −1.1 percentage points following the occurrence of borrower‐based measures, significantly lower than the unadjusted simple mean effect of the collected estimates. Additionally, our study examines the contexts of these estimates, finding that beyond publication bias, model specification and estimation method are vital in explaining the variation in reported coefficients.