Abstract
The optimization of fines to deter and detect cartel behavior is one of the main goals of competition policy. Although it is generally argued that fines should be high to be deterrent, the debate on what constitutes an optimal fine is unsettled and some authors suggest using profits (rather than turnover) to calculate "optimal" fines. We exploit data on cartel convictions by the Competition Commission of India (CCI) between 2009 and 2021, which is particularly useful to study this issue as it allows for fines to be calculated using profits or turnover. We examine how much cartel members can “save” in monetary sanctions relative to its legal maximum. In doing so, we also examine the determinants of fines and leniency program reductions for firms, associations and individuals. We find that: (i) using a profit metric leads to larger relative fines; (ii) multiple offenders can save a larger proportion of the fine; and (iii) firms in larger cartels receive lower relative fines. We also show how the cartel type affects the relative savings from fines (RSF); and that fines are far from the legal maximum (thus decreasing the incentive to apply for leniency)