This paper will analyse one aspect of corruption that has been very present in the corruption literature after mid-1990s: the effect of wages on corruption. Van Rijckeghem’s and Weder’s model of the fair wage hypothesis will be first explained in this paper and then used on a cross-sectional study of 29 countries and on data from within Russia between the years 2001 – 2005. In doing so, Occam’s Razor will be applied by only analysing the effects of wages on corruption, ignoring all historic and institutional aspects of a particular country. The results do not prove the fair wage hypothesis beyond doubt, although some evidence point that satisfactory wages will reduce corruption.
Table of Contents
1 Introduction
1.1 Endemic corruption
1.2 How to fight corruption: the fair-wage hypothesis
2 Literature review
2.1 Maximising vs. Satisficing
2.2 Empirical Evidence
2.3 Literature on Corruption in Russia
3 Theoretical Model
3.1 Building the model
3.2 Empirical Evidence
3.2.1 Perceived corruption: International Country Risk Guide
3.2.2 Approximating actual levels of corruption: Enterprise Surveys
4 Methodolgy
5 Results
5.1 Critique
6 Evidence for the fair wage hypothesis in Russia?
7 Concluding remarks
8 Bibliography
Objectives & Key Themes
This research investigates the relationship between public sector wages and the prevalence of corruption, specifically testing the "fair wage hypothesis." By applying a rational choice framework, the study seeks to determine whether higher public sector salaries effectively deter corrupt behavior, utilizing cross-sectional data from 29 countries and specific observational data from Russia between 2001 and 2005.
- Analysis of the principal-agent-client model in corruption.
- Comparison between "maximising" and "satisficing" behavioral models.
- Use of World Bank Enterprise Surveys as a proxy for actual corruption.
- Regression analysis of wage ratios versus corruption levels.
- Assessment of anti-corruption policy effectiveness in the Russian context.
Excerpt from the Book
3.1 Building the model
Van Rijckeghem and Weber formulate the shirking (maximizing) hypothesis with the following equation: (1) EI = (1 - pC)(CB + Wg) + pC(Wp - f)), (Rijckeghem & Weder, 1997, p. 12) where EI represents the expected income, p the probability of detection of single corrupt act, C the number of corrupt acts, B the size of the bribe, Wg the wage in the public sector, Wp the wage in the private sector and f possible monetary and nonmonetary penalties. This equation states that if corruption is undetected, the government official will receive the government wage plus revenue from corrupt acts. If corruption is detected, the government official will receive the private sector wage minus penalties. This formulation is similar to that of Klitgaard.
While in the shirking hypothesis the number of corrupt acts can be chosen almost arbitrarily, the fair wage hypothesis states that agents will choose C so that EI equals EI*, with EI* being the wage which the agents regard as fair. Formally: (2) EI = (1 - pC)(CB + Wg) + pC(Wp - f) = EI *
The differences in the models can be seen best by looking at the results one gets by solving for the optimal solution for C, as well as the derivatives of corruption with respect to government wages and the probability of detection respectively, which are displayed below:
Summary of Chapters
1 Introduction: Provides a contextual overview of corruption in Russia, citing its "endemic" nature and highlighting the historical and ongoing struggle against systemic bribery.
2 Literature review: Explores theoretical foundations of corruption, specifically contrasting "maximising" agents against "satisficing" agents within the agency relationship.
3 Theoretical Model: Outlines the formal mathematical models used to explain how wage structures and detection probabilities influence the decision to engage in corrupt activities.
4 Methodolgy: Describes the use of Ordinary Least Squares (OLS) regression to analyze the relationship between public sector wage ratios and corruption indices across 29 countries.
5 Results: Presents the statistical findings of the regression analysis, demonstrating a negative correlation between wages and corruption, though noting that results are statistically insignificant at the 5% level.
6 Evidence for the fair wage hypothesis in Russia?: Examines longitudinal data from the INDEM foundation to determine if wage dynamics and administrative reforms in Russia support the proposed theories.
7 Concluding remarks: Synthesizes the study's findings, concluding that while raising wages provides some evidence for reducing corruption, it is not a standalone solution and requires broader institutional reform.
Keywords
Corruption, Fair Wage Hypothesis, Principal-Agent Model, Public Sector Wages, Enterprise Surveys, Rational Choice, Maximising, Satisficing, Russia, Regression Analysis, Anti-Corruption Policy, Bribes, Economic Incentives, Institutional Reform, Governance.
Frequently Asked Questions
What is the primary focus of this study?
The study focuses on the "fair wage hypothesis," which posits that paying public sector employees a wage deemed "fair" compared to the private sector reduces their incentive to engage in corrupt activities.
What are the core thematic areas?
The themes include principal-agent theory, behavioral economics regarding corruption (maximising vs. satisficing), the analysis of statistical corruption indices, and the specific case study of Russia's anti-corruption environment.
What is the central research question?
The research asks whether higher public sector wages lead to lower levels of corruption, testing this assumption across a cross-section of countries and specifically within the Russian Federation.
Which scientific methods are applied?
The author uses a formal mathematical model of corruption, followed by an Ordinary Least Squares (OLS) regression analysis utilizing data from World Bank Enterprise Surveys and LABORSTA.
What does the main body of the work cover?
The main body covers the theoretical model development, the critique of existing corruption measurements like the ICRG, the methodology of the regression analysis, and an empirical look at the Russian corruption process using INDEM data.
Which keywords characterize the work?
The work is characterized by terms such as Corruption, Fair Wage Hypothesis, Principal-Agent Model, Public Sector Wages, and Enterprise Surveys.
How does the author treat the data mismatch problem?
The author acknowledges the difficulty in conducting annual surveys and notes that while attempts were made to align the years of survey data with the years of wage data, some mismatches were inevitable and are documented in Table 3.
What is the significance of the "satisficing" concept?
The concept suggests that bureaucrats may engage in just enough corruption to reach a "fair" or target income level, rather than being constant "maximisers" who take as many bribes as possible.
Why does the author prefer Enterprise Surveys over perception indices?
The author argues that perception indices (like the CPI or ICRG) are often biased toward foreign businesses and prone to skewing by high-profile scandals, whereas firm-level Enterprise Surveys reflect actual experiences of the private sector.
What conclusion is drawn regarding anti-corruption policies?
The author concludes that while increasing wages for bureaucrats may help reduce corruption, it is insufficient on its own and must be paired with broader historical and institutional reforms to be truly effective.
- Citar trabajo
- Roman Scheffler (Autor), 2010, Do public sector wages affect corruption?, Múnich, GRIN Verlag, https://www.grin.com/document/177260
