Loan Loss Provisions in Alternative Banking Landscapes
©2024
Thesis
188 Pages
Series:
Schriftenreihe des Kärntner Instituts für Höhere Studien, Volume 22
Summary
This book comprises two empirical studies that use econometric techniques to examine loan loss provisions in Southeast Europe (SEE). The first study applies the Generalized Method of Moments estimator to a dynamic panel dataset, shedding light on specific loan loss provisioning practices. This study makes a unique contribution to the field, extending empirical evidence on discretionary and non-discretionary components of loan loss provisions in SEE. Additionally, the analysis of outlying observations offers interesting insights into potential motives influencing decisions on loan loss provisions. Filling a gap where research in SEE is infrequent, the second study uses individual structural vector auto-regression (SVAR) models for individual economies and panel SVAR models for SEE EU states and the Western Balkans, forecasting response functions of loan loss provisions to adverse GDP and employment shocks.
Excerpt
Table Of Contents
- Cover
- Title
- Copyright
- About the author
- About the book
- This eBook can be cited
- Contents
- List of tables
- List of figures
- List of abbreviations
- Executive summary
- Abstract
- 1 Introduction
- 2 Banking sectors in Southeast Europe
- 2.1 Bank reforms in transition economies
- 2.1.1 Advantages of the banking reform
- 2.1.2 Disadvantages of the banking reform
- 2.2 Bank reforms in Greece and Cyprus
- 2.3 Southeast Europe today
- 3 Loan loss provisions
- 3.1 Loan loss provisions as an indicator of credit risk
- 3.2 Components of loan loss provisions
- 3.3 Evolution of loan loss provisioning regulations
- 3.4 Loan loss provisions in Southeast Europe
- 3.5 Comparability of the data
- 4 Non-discretionary and discretionary components of loan loss provisions in Southeast Europe
- 4.1 Theoretical framework
- 4.1.1 Capital management
- 4.1.2 Income smoothing
- 4.1.3 Signaling
- 4.1.4 Pro-cyclicality
- 4.2 Empirical research
- 4.2.1 Data
- 4.2.1.1 Variables
- 4.2.1.2 Analysis of outliers
- 4.2.1.2 Descriptive statistics and correlations
- 4.2.2 Method
- 4.2.2.1 The two-step difference GMM estimation
- 4.3 Results
- 4.3.1 Within regions
- 4.3.2 Between regions
- 5 The effect of macroeconomic shocks on loan loss provisions in Southeast Europe
- 5.1 Theoretical framework
- 5.2 Empirical research
- 5.2.1 Data
- 5.2.1.1 Descriptive statistics
- 5.2.1.2 Analysis of outliers
- 5.2.2 Method
- 5.3 Results
- 5.3.1 Within regions
- 5.3.2 Between regions
- 6 Conclusions
- Bibliography
Details
- Pages
- 188
- Publication Year
- 2024
- ISBN (PDF)
- 9783631918241
- ISBN (ePUB)
- 9783631918258
- ISBN (Hardcover)
- 9783631918234
- DOI
- 10.3726/b21788
- Language
- English
- Publication date
- 2024 (November)
- Keywords
- Loan loss provisions business cycle income smoothing capital management signaling macro-financial stress test
- Published
- Berlin, Bruxelles, Chennai, Lausanne, New York, Oxford, 2024. 188 pp., 33 fig. b/w, 51 tables
- Product Safety
- Peter Lang Group AG