Panel Investigation of the Factors Determining the Supply of Bank Loans in Bulgaria Using Microeconomic Data

Abstract This paper studies the factors affecting Bulgarian commercial banks’ loan supply over the period between Q1 2007 and Q4 2024. The analysis employs a panel of indicators derived from individual (microeconomic) commercial banks’ balance sheets and income statements, alongside macroeconomic variables. Combining cointegrated I(0) and I(1) data suggests the use of the Pooled Mean Group (PMG) ARDL model in panel data of Pesaran, et al. (1999). Our main findings are that the capital adequacy ratio (CAR), cost-to-income ratio (CTOI), yield on government bonds, and return on assets (ROA) exhibit negative association with loan growth, while market share (MS), loan-to-deposit ratio, interest rate on liabilities, GDP growth, housing prices, and inflation positively influence lending activity. The negative value of the Error-correction term of -0.11 and the p-value of 0.016 support the validity of a long-run relationship, indicating that loan growth adjusts toward the equilibrium state at a speed of 11% per quarter. Short-run dynamics reveal that changes in CAR, market share, and loan-to-deposit ratios significantly affect loan growth, while bank lending, economic growth, and bank efficiency indicators display lagged effects. The results of this study offer important insights into the operation of credit markets in small, open, and bank-dependent economies such as Bulgaria.

Authors

Institutions

Publication Details

Journal
Economics
Published
2025-09-01
DOI
https://doi.org/10.2478/eoik-2025-0076
Primary Topic
Global Financial Crisis and Policies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Panel Investigation of the Factors Determining the Supply of Bank Loans in Bulgaria Using Microeconomic Data

Petar Peshev, Radostina Stamenova
Economics
Global Financial Crisis and Policies
article

Panel Investigation of the Factors Determining the Supply of Bank Loans in Bulgaria Using Microeconomic Data

Petar Peshev, Radostina Stamenova
article en

Abstract

Abstract This paper studies the factors affecting Bulgarian commercial banks’ loan supply over the period between Q1 2007 and Q4 2024. The analysis employs a panel of indicators derived from individual (microeconomic) commercial banks’ balance sheets and income statements, alongside macroeconomic variables. Combining cointegrated I(0) and I(1) data suggests the use of the Pooled Mean Group (PMG) ARDL model in panel data of Pesaran, et al. (1999). Our main findings are that the capital adequacy ratio (CAR), cost-to-income ratio (CTOI), yield on government bonds, and return on assets (ROA) exhibit negative association with loan growth, while market share (MS), loan-to-deposit ratio, interest rate on liabilities, GDP growth, housing prices, and inflation positively influence lending activity. The negative value of the Error-correction term of -0.11 and the p-value of 0.016 support the validity of a long-run relationship, indicating that loan growth adjusts toward the equilibrium state at a speed of 11% per quarter. Short-run dynamics reveal that changes in CAR, market share, and loan-to-deposit ratios significantly affect loan growth, while bank lending, economic growth, and bank efficiency indicators display lagged effects. The results of this study offer important insights into the operation of credit markets in small, open, and bank-dependent economies such as Bulgaria.

EconomicsVol. 13(3)
University of National and World Economy (BG)
Openalex Percentile: Top 70%
Global Financial Crisis and Policies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.