1. PREDICTING U.S. CARTEL FINES
John M. Connor
Purdue University, W. Lafayette, IN
and
Douglas J. Miller
University of Missouri, Columbia, MO
AAI June 2010

2. ISSUES
DOJ sentencing of antitrust violators is not transparent (esp. partial Leniency discounts)
How well fines conform to optimal deterrence theory of crime is not known
DOJ officials say that fines are idiosyncratic, i.e., not predictable
Only one empirical study of U.S. criminal fines (Cohen 1998), but excludes antitrust violators
AAI June 2010

3. Importance
Becker’s theory of crime has received little empirical confirmation
The DOJ’s anti-cartel program is widely admired and imitated, so quantitative assessments have policy import
If prediction of fines is impossible, then deterrence impossible because would-be criminals need to make fine conjectures
AAI June 2010

4. OBJECTIVES
Fit a testable model of optimal deterrence to data on cartel fines imposed on corporate participants of global cartels by the DoJ from 1996 to March 2010.
Specification of the model and hypotheses also considers the policies and historical sentencing practices of the DOJ and the federal judiciary.
AAI June 2010

5. Optimal Deterrence Theory
In a nutshell, the optimal criminal fine is:
USF* =HARM/p - Other Penalties,
where HARM is the monetary injuries imposed on victims (or expected gain from the crime), p is the probability of detection and prosecution, and other penalties include expected future fines or civil settlements and the monetized penalties on individuals.
AAI June 2010

6. (Subjective) p Difficult to Measure
Proxies we developed include:
Cartels facing many buyers implies p is high
Large cartel membership (N) increases p
Asymmetry among members may decrease p
BID RIGGING harder to detect? (decreases p)
GOVT. main buyer may decrease p
Long lasting PROBE a sign that defendants covered up (decreases p)
AAI June 2010

7. Other Penalties
Optimal Deterrence theory predicts that other penalties are substitutes for U.S. fines (USF), to the extent that DOJ knows/expects them
OTHPEN= Non-US fines + PVT settlements
EXECS = number of executives of this corporate defendant that were penalized
PRISON= months served by executives
AAI June 2010

8. CONTROLS: Other Determinants from Laws, Guidelines, or DOJ Practices
Two industry dummies to represent demand elasticities, entry barriers, or collusion history
Time T because data covers 2 administrations
Cartel DURATION to correct for lower fines due to curtailment of collusive period
“Nationality” of firms to check proportionality
AAI June 2010

9. Data Sample
124 companies (out of 128) criminally fined by the DOJ for participation in 39 global cartels from 1996 to March 2010
All 124 convicted by guilty plea agreements
Half during Clinton, half during Bush II administration
Excludes about 30 Amnesty Program recipients
Excludes 206 apparently indictable cartelists penalized elsewhere (worthy of study in itself)
AAI June 2010

10. General Behavioral Model
USF = α + β∙(HARM) + γ∙(1/p) δ∙OTHPEN + λ∙CONTROLS + ε.
NB: Following U.S. Sentencing Guidelines, we use firm-level affected sales (ASus) as a proxy for harm. It is a good proxy.
AAI June 2010

11. Model Specification
LEADER, ASIA, TIME, PROBE, and EXECS were insignificant and were dropped
BIDRIG, GOVTBUYS, and SERVICE industry were nearly coincident, we kept BIDRIG
Ramsey’s RESET procedure indicated missing nonlinearities; we substituted LN(USF) for USF and OTHPER + OTHPEN2 for OTHPEN
AAI June 2010

12. Specific Regression Model
After noting large skewness in USF and HARM, dropping very weak explanatory variable, and finding the source of nonlinearities, our final specification is:
LN(USF) = α + β∙LN(ASus) + γ∙(1/p) δ1∙OTHPEN + d2∙OTHPEN ζ∙PRISON + λ∙CONTROLS + ε.
AAI June 2010

13. General Estimation Results
The OLS model explains 76% of variance in LN(USF) – very satisfactory
We also ran a Maximum Likelihood Tobit model, but no evidence that censored observations problematic.
White’s and BPG tests indicated a need to correct for collinearity, which we did.
Ramsey’s RESET test procedure showed no misspecification/nonlinearities present
AAI June 2010

14. Specific Results
Coef. of HARM is = 0.59 [this elasticity <1 => suboptimal deterrence, unless OTHPEN high]
Detection proxies results are disappointing
OTHPEN are complementary penalties (unless > $516 million, which applies to few obs.)
Prison length also complementary
TIME is nonsignificant, but BUSH1 and BUSH2 fines are lower than CLINTON (see figures)
AAI June 2010

15. US Affected Sales, Convicted Members of Global Cartels, Total Annual
AAI June 2010

16. US Affected Sales per Convicted Member of Global Cartels
AAI June 2010

17. Predicted Fines by President
AAI June 2010

18. Conclusions Sizes of global cartel fines are predictable
DOJ follows optimal deterrence principles wrt HARM, but does not adjust fines to reflect the difficulty of detection, not even for big rigging
PRISON is surprisingly complementary to USF
Unless other anticipated penalties are very large, then they are also complementary
Bush DOJ was lax in cartel fines
AAI June 2010

19. Predicted U.S. Cartel Fines by Presidential Administration
AAI June 2010

20. US Affected Sales, Convicted Members of Global Cartels, Total Annual
Billion dollars
AAI June 2010