Detalhes bibliográficos
Ano de defesa: |
2017 |
Autor(a) principal: |
Afonso, Nathalie Gressler |
Orientador(a): |
Féres, José Gustavo |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
eng |
Instituição de defesa: |
Não Informado pela instituição
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Link de acesso: |
https://hdl.handle.net/10438/18359
|
Resumo: |
Collusive practices used by cartels have proven to be extremely harmful to economic efficiency and social welfare. Detecting these kind of practices has become a priority within antitrust agencies around the world. Regulators are constantly after effective ways to punish companies so that the costs of colluding outweighs its benefits. These punishments usually come in the form of fines or compensation payments that are calculated based on the estimated damages caused by the colluding firm. However, detecting cartel can pose a challenge to economists; it is a data intensive and time consuming process that involves estimating a competitive benchmark to compare with the suspected collusive behavior. The aim of this paper is to review the methods available for cartel damage quantification and apply it on a practical case. We start this study by understanding the harm that collusive practices used by cartels cause to economy and society. We then explore the different types of empirical methodologies used in calculating the estimated damages and the trade-offs of employing them. Next, we compare how antitrust agencies operate in the United States, European Union and Brazil and discuss their roles in calculating the damages and setting an appropriate fine to an antitrust violating firm. Finally, we take make an in depth analysis of a cartel in the Liquefied Petroleum Gas distribution market from February 2003 to April 2005 in the state of Pará, Brazil, employing the multivariate before and after and the difference-in-difference approaches. We found that the price overcharge for the cartel was between 10% to 13% in the first methodology and 16% to 17% in the latter. |