This paper uses t and f statistical tests to evaluate empirically the competitive conditions in the German banking system for the period 2003-2007. For this purpose we implement the non-structural estimation technique in logarithmic form (Hondroyiannis, Lolos, Papapetrou, 1999, p.377):
lnTrev = α1+α2 lnPL+α3 lnPK+α4 lnPF+α5 lnRISKASS+α6 lnASSET+α7 lnEMP
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Regression Results
- t and F statistical tests
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This paper empirically analyzes the competitive conditions within the German banking system for the period 2003-2007. The study utilizes t and f statistical tests and implements a non-structural estimation technique to achieve its objectives.
- Assessing the competitiveness of the German banking system
- Analyzing the relationships between various financial variables and bank revenue
- Evaluating the statistical significance of independent variables on the dependent variable
- Applying t and F statistical tests to determine the influence of independent variables on bank revenue
Zusammenfassung der Kapitel (Chapter Summaries)
- Introduction: This section outlines the purpose and methodology of the paper, introducing the non-structural estimation technique used to analyze the competitive conditions in the German banking system. The variables and their expected relationships are presented, laying the groundwork for the subsequent analysis.
- Regression Results: This section presents the regression results, including coefficient estimates, standard errors, t-statistics, and probability values. It provides a comprehensive overview of the statistical significance of the independent variables in explaining variations in bank revenue.
- t and F statistical tests: This section delves into the application of t and F statistical tests to evaluate the significance of individual coefficients and the overall model. It explains the principles behind these tests and provides a detailed analysis of the results.
Schlüsselwörter (Keywords)
The paper focuses on the competitiveness of the German banking system, utilizing statistical tests to analyze the relationship between bank revenue and financial variables such as assets, employees, interest expenses, and capital expenses. Key concepts explored include non-structural estimation, t and F statistics, and the statistical significance of variables in determining bank revenue.
Frequently Asked Questions
What is the focus of this banking report?
The report empirically assesses the competitive conditions of the German banking system between 2003 and 2007 using statistical tests.
Which statistical methods were used in the analysis?
The study implements a non-structural estimation technique in logarithmic form, utilizing t and F statistical tests.
What variables influence bank revenue in this model?
The model considers variables such as total assets, number of employees, interest expenses (PL), capital expenses (PK), and risk-associated factors.
Why are t and F tests important for this study?
The t-test evaluates the significance of individual coefficients, while the F-test determines the overall significance and fit of the regression model.
What does the "non-structural estimation" approach mean?
It refers to a method that assesses competition by observing how changes in input prices are reflected in total revenues, rather than looking at market structure alone.
- Quote paper
- Dimitar Vasilev (Author), 2010, Report on assessing competitiveness of the German banking system (2003-2008), Munich, GRIN Verlag, https://www.grin.com/document/180771
