Is the Boone-Indicator Applicable? Evidence from a Combined Data Set of German Manufacturing Enterprises

Abstract

Boone (2008a) proposes a new competition measure based on Relative Profit Differences (RPD) that, from its theoretical properties, proves to be more robust than the Lerner-Index. However, the proof of the empirical practicability and robustness of the Boone-Indicator is missing. To fill this gap, we use a rich, newly built, data set for German manufacturing enterprises and test its empirical validity using cartel cases. Since all of the identified cartels significantly restricted market competition, we expect fiercer competition after the uncovering. We asses the validity of the indicators by comparing the indicated competition levels before and after the cartelswere uncovered and stopped. The Boone-Indicator is calculated as RPDs and as a beta coefficient of a log-log regression. The Lerner-Index is used as a benchmark. Our analysis finds that the Boone-Indicator, based on a simple regression approach, fails to correctly indicate competition. Since the Boone-Indicator, based on pure RPDs, proves to be inapplicable, we propose an augmented indicator based on size-adjusted RPDs, which performs better. However, our findings suggest that, given the information typically available in census data, the Lerner-Index is still the only measure that correctly indicates competitive changes.