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

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

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

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

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

(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

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

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

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

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

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

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∙OTHPEN2 + ζ∙PRISON + λ∙CONTROLS + ε. AAI June 2010

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

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

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

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

Predicted Fines by President AAI June 2010

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

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

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