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Casinos and Corruption 14th Intl. Conference on Gambling ...

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The Casino Industry and the Corruption of U.S. Public Officials in the U.S.
Douglas M. Walker and Peter T. CalcagnoCollege of CharlestonApril 1, 2011
What is corruption?
Criminal acts perpetrated by politicians or government employees, with the goal of illegitimate personal gainDeptof Justice reports that election crimes are good indicators of corruptionVote fraud, campaign finance crimes, political shakedownsBribes, favors for friends/family, racketeering, conspiracy, extortion, etc.Glaeserand Saks (2006) argue that federal corruption convictions are better indicators state crime convictionsIf the state is corrupt, it may affect the number of charges filed by the stateFederal conviction #s range from 0 to over 100 per year in a particular state
Anecdotal evidence of a link
Las Vegas has a history of organized crime and corruptionAtlantic City, NJ has a long-established bad reputationOver half of the last 9 mayors have been arrested on corruption chargesLouisiana governor Edwards convicted in 2000 of 17 corruption charges related to riverboat casino licensesIllinois governor Blagojevich being sued by Illinois casino operatorsFBI wiretaps indicate a shake-down of horse racetrack owners for support of a bill that requires casinos to share profits with the racetracksObservers in Kentucky suggest that corruption has started there, even before casinos are being builtIn AL, 11 people (including a few senators) were arrested for buying/selling votes related to casino legislation (2010)
Theoretical explanations for a link
Casinos are big, cash businessesSee Table 1, Figure 1Gambling industry PAC and individual contributions to politicians are largeSee Table 2Likely to be large illegal “contributions” too?Industry requires explicit government approval to existHuge rents are created by this restriction and regulation of the industryLaws and regulations that apply only to this industryRequires interaction between law makers and industryPoliticians can be influencedState legalization, local permits, regulatory framework, etc., are opportunities for corruption
Table 1: US Casino states, 2007Source: AGA (2008)
Table 2: Industry contributions to US politiciansSource: Center for Responsive Politics (
A perfect recipe for corruption?
Lots of casino revenues, tax revenuesLarge contributions to politicians from individuals & PACs related to casinos/gamblingGovernment approval needed for industry to existEvery facet of the industry is regulatedCorruptible politiciansBut there’s no empirical evidence of a link (at least, in the literature)…
Corruption literature
Numerous studiesRose-Ackerman (1978),Glaeser& Saks (2006),Fisman&Gatti(2002), Alt & Lassen (2008), Lee &Chelius(1989), etc.International studies (cross-sectional, at the national level)Corruption is worse when firms are shielded from foreign competitionNegative relationship between corruption andpolitical freedomdecentralization of powereconomic growth“Law and order” and “democratic accountability” reduce corruptionUS studies (at the state-level)Higher education and income reduce corruptionIncome inequality increases corruptionRacial “dissimilarity” (diversity?) increases corruptionNo studies that examine a specific industry as a potential cause of corruption
Our data
We are interested in determining if there is a link betweencommercialcasinos and corruptionCorruption is measured by federal corruption convictions of state/local government employeesBy year and state: 1985-2005, 11 casino statesCovers most legalization (1989-96), except PA, NV, NJData source: USDeptof JusticeCasino activity is measured by casino revenuesBy year and state, 1985-2005, 11 casino statesData source: State gaming regulatory agencies231 observations (11 states, 21 years)In most states there are several pre-casino observations[For all states, 21 years, we have 1050 observations. But the model isn’t determinate using all states.]
Granger causality analysis
Standard Granger causality for time series data (Granger,Econometrica1969):Xt=Xt-j+Yt-j+Y “causes” X if inclusion of Y improves prediction of XYt=Yt-j+Xt-j+X “causes” Y if inclusion of X improves prediction of YNot exactly the same meaning as the common concept of “causality”We cannot analyze casino legalization – an event – using this empirical analysisWe maybe should focus on this instead…
Granger causality for panel data
Walker & Jackson (1998) adapt Granger causality to panel data; we follow that methodWe have two series:CorruptandRevenueStep 1Detrendthe panel data series of state- and time-specific informationState dummies, time trend, state-trend interaction termsUse the residuals from each equationTest the residuals forstationarity; if hypothesis of unit root is rejected, move on
Empirical analysis, continued
Step 2Determine the autoregressive process that generates each series ofdetrendedresidualsWe want the fewest lag periods on which the variable must be regressed so that the residuals are white noiseIterative process, adding additional lag periods until correlograms and Box-PierceQ-statistics indicate residuals from these regressions are white noiseIf these residuals are white noise, then if adding the other variable’s residuals improves prediction of the first series, then Granger causality existsModels indicate thatCorruptrequires2lag periods;Revenuerequires3lag periodsSample size must be adjusted to account for these
Empirical analysis, continued
Step 3Run the regressions on eachdetrendedseries:(1)Corrt=a1+a2Corr(t-1)+a3Corr(t-2)+a4Rev(t-1)+a5Rev(t-2)+a6Rev(t-3)+ε(2)Revt=g1+g2Rev(t-1)+g3Rev(t-2)+g4Rev(t-3)+g5Corr(t-1)+g6Corr(t-2)+εGranger causality tests (F-tests):“Revenuedoes not causeCorruption”in equation (1) above, test coefficient restriction:a4=a5=a6= 0“Corruptiondoes not causeRevenue”in equation (2) above, test coefficient restriction:g5=g6= 0
Possible results
4 possible resultsCasino revenues Granger cause corruption convictionsCasino revenues are used to bribe politicians to expand the industry or loosen regulationCorruption convictions Granger cause casino revenuesCasinos are legalized in relatively corrupt statesIndependenceNo causal relationship either way“No result” is still an interesting result (fortunately)Feedback, or simultaneous determinationEach variable is contributing to the othere.g., quid pro quobetween casinos and politiciansTiming here must be examined
Actual results
Table 4. Granger causalitytest results
The first econometric evidence of a linkAnalysis does not indicatewhythere is a linkA reasonable story can be told whatever the resultSuggests that casinos may be more likely to be legalized in relatively corrupt statesAnecdotal evidence: IL, LA, NJ, MS; next AL?No evidence that casinos use revenues to corrupt politicians after casinos openCasino licenses are expensive; unlikely to be put at risk…Consistent with a public choice perspective, that politicians have the most power to extract rents when they are formulating casino legislationCorruption is most likely to occur at this point
Discussion, cont.
Analyze legalization point instead of revenue stream?Hazard modelCasino states only or all states?Timing issues need to be addressed:corruption ‘event’ and convictionscasino legalization and casino revenues[see the following scenario]Suggestions for robustness checks?Granger causality provides evidence for subsequent analysisCorruption leading to revenues/legalization
Figure 3. Possible timing of corruption convictions and casino revenues
Year 1Casinos proposedSome politicians solicit bribes to support casinos
Year 2Casino billpassesCorruption charges filed and trials begin; some trials end in conviction
Year 3Casino building beginsAdditional trials end in conviction
Year 4Casinos open for business (revenues begin)





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Casinos and Corruption 14th Intl. Conference on Gambling ...