OS PROGRAMAS DE LENIÊNCIA E COOPERAÇÃO NO BRASIL: UMA ANÁLISE EMPÍRICA PARA OS ANOS DE 1994 A 2014

Lima, Fernanda Mariana da Silva; Salgado, Lucia Helena; Fiuza, Eduardo Pedral Sampaio

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Revista de Economia Contemporânea

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Articles • Rev. econ. contemp. 23 (02) • 2019 • https://doi.org/10.1590/198055272325 copiar

OS PROGRAMAS DE LENIÊNCIA E COOPERAÇÃO NO BRASIL: UMA ANÁLISE EMPÍRICA PARA OS ANOS DE 1994 A 2014

Autoria SCIMAGO INSTITUTIONS RANKINGS

RESUMO

Os programas de leniência e cooperação são considerados ferramentas importantes para auxiliar na efetividade da política de defesa da concorrência e são desenhados para atenderem aos seguintes propósitos: no curto prazo facilitar a detecção de cartéis e no longo prazo desestabilizar cartéis existentes e desincentivar o surgimento de novos. O presente trabalho busca analisar empiricamente se o programa de leniência brasileiro tem atendido a estes propósitos. Para tanto, testaram-se em dados brasileiros as hipóteses desenvolvidas por Brenner (2009BRENNER, S. An empirical study of the European corporate leniency program. International Journal of Industrial Organization, v. 27, n. 6, p. 639-645, março 2009.) para avaliar a efetividade no programa de leniência da União Europeia.

PALAVRAS-CHAVE:
cartéis; defesa da concorrência; programa de leniência; compromisso de cessação; CADE

Result of estimation in OLS, using observations 1-73
Dependent variable : l_Fi
	coefficient	standard error	t-reason	p-value
Const	12.9621	1.13408	11.4296	6.64e-017 ***
LP	2.28844	0.916649	2.4965	0.01521 **
TCC	0.53639	0.724078	0.7408	0.46162
DC	-0.540541	0.388502	-1.3913	0.16909
DC2	0.0739388	0.0471694	1.5675	0.12208
DC3	-0.00245693	0.00148163	-1.6583	0.10232
NF	0.889738	0.308438	2.8847	0.00538 ***
NF2	-0.0711999	0.0351915	-2.0232	0.04737 **
NF3	0.00173657	0.00100725	1.7241	0.08968 *
SER	-1.57617	0.777991	-2.0259	0.04708 **
IND	2.9455	0.966699	3.0470	0.00339 ***
Average dep. variable		13.50679	S.D. dep. variable	3.299349
Sum of square residuals		217.7309	S.E. of regression	1.873977
R-square		0.722201	R- square squared	0.677394
F(10, 62)		16.11828	P-value(F)	8.52e-14
Likelihood log		−143.4697	Akaike’s Criteria	308.9395

Result of estimation in OLS, using observations 1-73
Dependent variable: l_RFi
	coefficient	standard error	t-reason	p-value
Const	12.9767	1.16617	11.1277	<0.00001 ***
LP	1.96145	0.942585	2.0809	0.04158 ***
TCC	-0.527652	0.744566	-0.7087	0.48119
DC	-0.697747	0.399494	-1.7466	0.08566 *
DC2	0.0896378	0.0485041	1.8480	0.06937 *
DC3	-0.00283031	0.00152356	-1.8577	0.06796 *
NF	1.06309	0.317165	3.3518	0.00137 ***
NF2	-0.0855047	0.0361873	-2.3628	0.02129 ***
NF3	0.00205391	0.00103575	1.9830	0.05180 *
SER	-1.51132	0.800004	-1.8891	0.06355 *
IND	2.935	0.994052	2.9526	0.00445 ***
Average dep. variable		13.28241	S.D. dep. variable	3.338130
Sum of square residuals		230.2266	S.E. of regression	1.927001
R-square		0.713043	R- square squared	0.666760
F(10, 62)		15.40603	P-value(F)	2.22e-13
Likelihood log		-145.5066	Akaike’s Criteria	313.0132

Result of the model estimation: Duration (Weibull), using observations 1-73
Dependent variable: DI
Standard errors based on Hessian
	coefficient	standard error	z	p-value
Const	0.80076	0.109576	7.3078	2.72e-013 ***
LP	0.277271	0.0978809	2.8327	0.00462 ***
DITCC	0.132157	0.00911632	14.4968	1.27e-047 ***
DC	0.0146627	0.0165356	0.8867	0.37522
DC2	0.00150761	0.000799911	1.8847	0.05947 *
NF	−0.00349199	0.00610727	-0.5718	0.56747
SER	−0.0291338	0.0837127	-0.3480	0.72782
IND	−0.00435532	0.123514	-0.0353	0.97187
Sigma	0.200056	0.018983
Average dep. variable		5.356164	S.D. dep. variable	3.155110
Chi-square(7)		136.5780	p-value	2.65e-26
Likelihood log		0.141052	Akaike’s Criteria	17.71790
Schwarz’s Criteria		38.33203	Hannan-Quinn’s Criteria	25.93298
1/sigma = 4.99859 (0.474308)

Result of the model estimation: Duration (Weibull), using observations 1-73
Dependent variable: DC
Standard errors based on Hessian
	coefficient	standard error	z	p-value
const	0.462523	0.27119	1.7055	0.08809 *
SR	0.599134	0.151218	3.9621	7.43e-05 ***
NF	0.0400338	0.0171978	2.3278	0.01992 ***
SER	0.890929	0.229511	3.8819	0.00010 ***
IND	1.09996	0.255058	4.3126	1.61e-05***
sigma	0.566719	0.0523196
Average dep. variable		6.164384	S.D. dep. variable	4.725856
Chi-square(7)		27.57926	p-value	0.000015
Likelihood log		−74.28854	Akaike’s Criteria	160.5771
Schwarz’s Criteria		174.3198	Hannan-Quinn’s Criteria	166.0538
1/sigma = 1.76454 (0.162903)

Instituto de Economia da Universidade Federal do Rio de Janeiro Avenida Pasteur, 250 sala 114, Palácio Universitário, Instituto de Economia, 22290-240 Rio de Janeiro - RJ Brasil, Tel.: 55 21 3938-5242 - Rio de Janeiro - RJ - Brazil
E-mail: rec@ie.ufrj.br

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[1] Corresponding author:
Fernanda Mariana Email address: fernandamariana@gmail.com

Period during which the cartel was detected	1994-1999	2000-2014
Numberofcases	35	38
Total penalties in BRL (without discounts)² 2 Sum of the penalties without the application of the discounts guaranteed by the leniency agreements with the penalties expected from the cases in which there were signed CDAs.	279.395.073,83	10.170.808.649,01
Total penalties in BRL (with discounts)³ 3 Sum of the penalties with the discounts guaranteed by the leniency agreements with the monetary contributions of the cases in which the CDAs were signed.	279.395.073,83	9.426.903.960,32
Average duration of cartels (years)	4,89	7,34
Averagenumberoffirms	2,83	4,18

	DC Ante	DC Post	NF Ante	NF Post
Average	4,885714286	7,342105263	2,828571429	4,184210526
Variance	6,280672269	34,71763869	18,85210084	25,61379801
Observation	35	38	35	38
Grouped variance	21,09993646		22,37580218
Average difference hypothesis	0		0
Df	71		71
Stat t	2,282555311		1,223261111
P(T<=t) one-tailed	0,01272729		0,112637808
t one-tailed critical	1,666599658		1,666599658
P(T<=t) two-tailed	0,02545458		0,225275616
ttwo-tailed critical	1,993943368		1,993943368