Are parliaments with more parties cheaper to bribe?

We collect data about 172 countries: their parliaments, level of corruption, perceptions of corruption of parliament and political parties. We find weak empirical evidence supporting the conclusion that corruption increases as the number of parties increases. To provide a theoretical explanation of this finding we present a simple theoretical model of parliaments formed by parties, which must decide whether to accept or reject a proposal in the presence of a briber, who is interested in having the bill passed. We compute the number of deputies the briber needs to persuade on average in parliaments with different structures described by the number of parties, the voting quota, and the allocation of seats among parties. We find that the average number of seats needed to be bribed decreases as the number of parties increases. Restricting the minimal number of seats a party may have, we show that the average number of seats to be bribed is smaller in parliaments without small parties. Restricting the maximum number of seats a party may have, we find that under simple majority the average number of seats needed to be bribed is smaller for parliaments in which one party has majority, but under qualified majority it hardly changes.

Introduction to data analysis

With the latest development in computer science, multivariate data analysis methods became increasingly popular among economists. Pattern recognition in complex economic data and empirical model construction can be more straightforward with proper application of modern softwares. However, despite the appealing simplicity of some popular software packages, the interpretation of data analysis results requires strong theoretical knowledge. This book aims at combining the development of both theoretical and applicationrelated data analysis knowledge. The text is designed for advanced level studies and assumes acquaintance with elementary statistical terms. After a brief introduction to selected mathematical concepts, the highlighting of selected model features is followed by a practice-oriented introduction to the interpretation of SPSS1 outputs for the described data analysis methods. Learning of data analysis is usually time-consuming and requires efforts, but with tenacity the learning process can bring about a significant improvement of individual data analysis skills.