As a junior congress person you have been asked to help promote a bill to allow casino gambling in your state. There is much opposition to this bill. Using distributive bargaining, discuss the pros and cons which might arise toward the passing or defeatin

ALL IN: AN EMPIRICAL ANALYSIS OF LEGISLATIVE VOTING ON INTERNET GAMBLING RESTRICTIONS IN THE UNITED STATES

DENNIS HALCOUSSIS and ANTON D. LOWENBERG∗

In 2006, the U.S. Congress passed the Unlawful Internet Gambling Enforcement Act (UIGEA) which prohibited financial institutions from processing transactions arising from online gaming activities, thereby severely hindering U.S. residents from participating in online casino games, primarily poker. Enactment of this legislation followed lobbying and political pressure from a variety of interest groups. By examining House roll call votes, we identify empirically the sources of political influence that resulted in passage of the internet gambling legislation. We find that party affiliation was of primary importance, with Republicans more likely to vote in favor of the bill. The percentage of constituents who are Evangelical Christians and also the number of gambling establishments in the district were positively associated with votes for the bill. However, contributions from the gaming industry decreased the probability a congressman would vote for the bill. (JEL D72, L83)

I. INTRODUCTION

In September 2006, the U.S. Congress enacted the Unlawful Internet Gambling Enforce- ment Act (UIGEA), which prohibited the trans- fer of funds from U.S. financial institutions to internet gambling operators.1 Although not ban- ning online gambling itself, by neutralizing the ability of financial institutions to process gam- ing proceeds, the UIGEA had an immediate and significant effect on Americans’ participation in online casinos and on the industry in general. Large online gambling companies publicly listed on foreign stock exchanges, such as PartyGam- ing Plc. and 888 Holdings Plc., closed their operations to U.S. players (GamblingPlanet.org,

∗The authors are grateful for helpful comments from two anonymous referees, as well as Brent Rowe, Dallas Wood, and other participants in a session of the Western Economic Association International annual conference in San Diego, CA, July 2011. The authors also thank Zach Roof, Deborah Snyder, and Arpine Dallakyan for research assistance. All errors remain the responsibility of the authors alone. Halcoussis: Department of Economics, California State

University, Northridge, Northridge, CA 91330-8374. Phone 1-818-677-4566, Fax 1-818-677-6079, E-mail [email protected]

Lowenberg: Professor, Department of Economics, California State University, Northridge, Northridge, CA 91330- 8374. Phone 1-818-677-2462, Fax 1-818-677-6079, E-mail [email protected]

1. The UIGEA specifically excluded fantasy sports, online lotteries, and horse/harness racing (Online Gaming Association, accessed February 5, 2011).

accessed March 1, 2011). PartyGaming Plc., the holding company of the popular online poker room, PartyPoker.com, saw its stock drop almost 60% in a 24-hour period following pas- sage of the UIGEA (Online Gaming Associ- ation, accessed March 1, 2011). By February 2007, some 2,300 online books and casinos had exited the U.S. market, while customer accounts with the major wire-transfer services were frozen. NETeller, the primary wire-transfer company serving U.S. residents, had effectively ceased its U.S. operations when, in January 2007, its founders were arrested in Manhattan and charged with money laundering (Gambling- Planet.org, accessed March 1, 2011). The total value of online poker wagers within the United States has declined by 83% since 2010 (Berzon and Albergotti 2012).

Like other government policies, U.S. gam- bling laws have been shaped in part by interest- group politics. A predecessor to the UIGEA, the Internet Gambling Prohibition Act (IGPA), first introduced in 1997, was supported by such

ABBREVIATIONS

IGPA: Internet Gambling Prohibition Act ISP: Internet Service Provider NAFTA: North American Free Trade Agreement UIGEA: Unlawful Internet Gambling Enforcement

Act WTO: World Trade Organization

17 Contemporary Economic Policy (ISSN 1465-7287) Vol. 33, No. 1, January 2015, 17 – 28 Online Early publication March 13, 2014

doi:10.1111/coep.12054 © 2014 Western Economic Association International

18 CONTEMPORARY ECONOMIC POLICY

Christian conservative groups as Focus on the Family, the Moral Majority, and the Christian Coalition, but was ultimately defeated in 1999 due largely to the efforts of prominent Repub- lican lobbyist Jack Abramoff, who was hired by eLottery, Inc., a firm whose plans to sell state lottery tickets online was threatened by the IGPA (Schmidt and Grimaldi 2005). Even after the UIGEA was enacted, special interests con- tinued to exert pressure. In 2008, media reports indicated that the Traditional Values Coalition received a $25,000 donation from eLottery, again orchestrated by Abramoff, to oppose the UIGEA. Also in 2008, the Associated Press reported that the National Basketball Associa- tion spent $330,000 on lobbying to maintain the UIGEA in force (GamblingPlanet.org, accessed March 1, 2011). Some large casino companies unsuccessfully pushed bills to create a federal law repealing the UIGEA and legalizing online poker (Berzon 2011a).

The purpose of this paper is to identify empir- ically the main forces driving U.S. policy on internet gambling, and in particular the UIGEA. This empirical analysis is based on a public choice perspective on the determinants of inter- net gambling policy. According to this approach, gambling regulation is supplied endogenously through a political process that weighs the impacts of online gambling on various interest groups. Owners and employees in industries that compete with online gambling, such as horserac- ing, sports books, and state lotteries, as well as other interest groups concerned about the moral or public health impacts of online gam- bling, might be expected to favor stricter con- trols on internet gambling, while industries that provide services complementary to online casi- nos, as well as the online gambling firms them- selves, will oppose such restrictions. The pref- erences of some industries might be ambivalent. For example, land-based casinos in Nevada and elsewhere, riverboat casinos, and Indian tribes might on the one hand perceive their services to be substitutes for online gambling, but on the other hand, exposure of potential customers to gambling opportunities on the internet might enhance their appetite for gaming and draw them to land-based casinos. We test these and other potential influences by examining the House roll call voting records of U.S. representatives on the

internet gambling bill,2 based on the assump- tion that political-support maximizing politi- cians will, to some degree, reflect the prefer- ences of their constituents in voting on such bills before Congress.

Our methodology follows in the tradition of the many studies that use district- or state-level data, combined with information on individ- ual legislators, to explain congressional roll call votes on specific pieces of legislation. The main thrust of this literature is to untangle the sep- arate effects of constituent interests, campaign contributions, and legislator ideology on vot- ing behavior. For example, congressional votes on international trade liberalization are generally found to be influenced by the expected impacts of trade on factor incomes in the legislator’s home constituency, by campaign contributions from business interests and organized labor, and by legislators’ political ideology or party affilia- tion.3 Legislative voting on immigration policy appears to be primarily motivated by the rela- tive abundance of skilled versus unskilled labor in the politician’s home district.4 In the area of financial services, a study of the 2008 Emer- gency Economic Stabilization Act finds that party affiliation, legislators’ tenure in office, and campaign contributions from the financial ser- vices industry all played an important role in determining House votes in favor of this bank bailout package (Couch et al. 2011).5

Along much the same lines, we investi- gate how congressional votes on internet gam- bling policy are affected by constituent inter- ests, as measured by economic and demographic

2. Our roll call voting data are for the Internet Gambling Prohibition and Enforcement Act of 2006, not the UIGEA itself, because the UIGEA was attached to a national security bill unrelated to internet gambling and therefore the vote on the UIGEA might have been tainted by legislator preferences on national security issues. Differences between the UIGEA and the Internet Gambling Prohibition and Enforcement Act are minimal and are described below.

3. Kahane (1996) investigates House and Senate voting patterns on the North American Free Trade Agreement (NAFTA), finding that a Congressman’s party affiliation as well as the presence of organized labor and expected labor-market and environmental impacts of NAFTA within the home district or state are significant predictors of the legislator’s vote.

4. Examining House votes on immigration bills from 1970 to 2006, Facchini and Steinhardt (2011) find that rep- resentatives from unskilled-labor abundant districts typically favored strict limits on unskilled immigration, whereas rep- resentatives from skilled-labor abundant districts tended to favor less restrictive immigration policies.

5. In the case of the Senate vote on this bill, only tenure in office and campaign contributions had statistically significant coefficients (Couch et al. 2011, 126 – 27).

HALCOUSSIS & LOWENBERG: INTERNET GAMBLING 19

attributes of legislators’ districts, by political contributions, and by legislators’ party affilia- tions. Our purpose is to identify the relative importance of economic factors, such as the presence of various forms of legal gambling in a district, and ideological factors such as party affiliation and religious beliefs, in explaining politicians’ votes.

Our study is one of very few in the liter- ature that attempts to develop a positive eco- nomic theory of government policy toward gam- bling, and the first to use a roll call voting model. Much of the existing economics litera- ture on gambling focuses on the determinants of gambling behavior.6 Some theorists have exam- ined the relative importance of skill in games of chance by evaluating the ability of players to affect outcomes through strategic choices.7

In the realm of public policy studies, Sauer (2001) develops an interest group model based on the economic theory of regulation to explain changes in U.S. gambling policy over time. The predictions of his model are broadly consistent with observed long-run fluctuations in the extent of gambling regulation in the United States. A public choice analysis of the determinants of U.S. state-level gambling policy is undertaken by Calcagno, Walker, and Jackson (2010), who identify the main factors causing states to legal- ize casinos. They find that the probability and timing of legalization is explained by a state’s fiscal condition, by its desire to prevent gam- bling tax revenues from leaking away to other jurisdictions, and by its interest in attracting tourism. Walker and Jackson (2011) investigate

6. Thus, for example, Pryor (2008), in a cross-national investigation of commercial gambling, shows that the share of gambling expenditure in disposable income is determined primarily by per capita income, macroeconomic uncertainty as measured by fluctuations in GDP, social welfare expen- diture, and cultural values held by the population. Kamis et al. (2010) study the influence of household income and expenditures on different forms of gambling behavior, find- ing that higher income is strongly associated with reduced myopic gambling, while higher levels of expenditure on necessities is associated with increased gambling. Forrest, Gulley, and Simmons (2010) demonstrate that the volume of sports, horseracing, and numbers betting is sensitive to the price of lottery tickets, indicating a rational substitution effect within betting portfolios, while Hunsaker (2001) finds that the presence of riverboat casinos, by enhancing con- sumers’ access to gambling experiences, boosts demand for casino resorts.

7. See Dreef, Borm, and van der Genugten (2004) and Campbell (2007). In the case of poker, Levitt and Miles (2011) measure players’ rates of return to tournament investments, concluding that poker is indeed a game of skill since accomplished players typically earn considerably higher rates of return than other players.

empirically the effects of legal gambling, such as horseracing, lotteries, and casinos, on state gov- ernment revenues. Cookson (2010) studies how legal and political institutions affect the incen- tives of tribal governments to establish casinos. He shows that those tribal governments that are able to negotiate gaming agreements with mul- tiple state governments and whose contracts are adjudicated in state courts are the most likely to operate casinos on tribal land.

In the next section, we briefly discuss the evolution of online gambling regulation in the United States and the circumstances giving rise to the passage of the UIGEA. Section III describes the variables and data used in our empirical study, Section IV presents the results, and Section V concludes.

II. THE HISTORY AND POLITICS OF ONLINE GAMBLING REGULATION IN THE UNITED STATES

Until recently, the main instrument of fed- eral regulation of internet gambling was the 1961 Wire Act. Under this legislation, the use of “wire communications” to transmit bets or information that facilitate placing wagers on sporting events or contests, with the excep- tion of pari-mutuel horseracing, is prohibited (McBurney 2005 – 2006, 337). However, the Wire Act applies only to “persons or orga- nizations ‘engaged in the business of betting or wagering [who] knowingly use. . .a wire communication in interstate or foreign com- merce”’ (Lessani 1998). Although operators of online casinos fall within the scope of the Act, online gamblers and internet service providers (ISPs) are not covered because they are not “engaged in the business” of gambling (Lessani 1998).

In 1997, in an attempt to strengthen federal prohibition, U.S. Senator Jon Kyl of Arizona introduced the Internet Gambling Prohibition Act (IGPA), which would have imposed penal- ties not only on operators of online casinos, but also on individual gamblers and on ISPs that failed to block access to gambling sites (Lessani 1998). The bill failed to become law (although passed by the Senate), possibly due to problems of enforcement. As Lessani (1998) points out, the government could not possibly have ade- quate technological or manpower resources to detect and prosecute online gamblers, nor did it have jurisdiction to shut down offshore casino

20 CONTEMPORARY ECONOMIC POLICY

operators. Revised versions of the bill, intro- duced in 1999 by Sen. Kyl and in 2000 by Vir- ginia Representative Bob Goodlatte, also failed to pass (GamblingPlanet.org, accessed February 5, 2011).

Congressional opponents of internet gam- bling continued to press legislation to expand the scope of federal regulation. Thus, in 2002 Rep. Goodlatte sponsored a bill that updated the Wire Act to cover internet betting and pro- hibit online casinos, and in 2003 a bill making it illegal for banks and credit-card companies to process gambling transactions was passed by the House (GamblingPlanet.org, accessed February 5, 2011). The latter bill was a precursor to the Internet Gambling Prohibition and Enforcement Act of 2006, which passed the House by a vote of 317 to 93,8 but was not voted on by the Sen- ate. This act, like its predecessor, tackled the enforcement problem by prohibiting financial institutions from making payments to gambling sites, thereby effectively preventing Americans from gambling online. In order to ensure Senate passage of the legislation, Sen. Kyl and Ten- nessee Senator Bill Frist altered the wording of the bill to remove controversial text pertaining to the Wire Act,9 and then they attached the new bill, now renamed the Unlawful Internet Gambling Enforcement Act (UIGEA) to another piece of legislation, namely, the SAFE Port Act, which dealt with port security measures unre- lated to online gambling. The UIGEA was added to the SAFE Port Act in a Conference Report which was passed by the House by a vote of 409 to 2 and by the Senate unanimously at the last minute, on the Friday night just before Congress broke for the election recess (Rose 2006; Online Gaming Association, accessed February 5, 2011; GamblingPlanet.org, accessed March 1, 2011).

Interest-group politics continued unabated even after passage of the UIGEA. Gambling interests have successfully pushed for casino expansions through state legislatures, arguing that states should seek to capture revenue from residents who otherwise would be gambling

8. As noted above, Sen. Kyl’s 1999 bill had been opposed by lobbyist Jack Abramoff (WikiPedia, http://en.wikipedia.org/wiki/UIGEA, accessed February 5, 2011), but by 2006 Abramoff was caught up in a cor- ruption scandal and, with the Republican party desiring to distance itself from him, the climate in Washington became more friendly to antigambling legislation (Casinoad- visor.com, accessed February 5, 2011).

9. See the discussion in the next section of the dif- ferences between the UIGEA and the Internet Gambling Prohibition and Enforcement Act.

in neighboring states or online. As a result, land-based casino gambling has been expanded in several states, including Pennsylvania and Florida (Berzon 2011a).10 Much of the effort toward legalization of online gambling has also moved to the state and local level, where gov- ernments have been enticed by the prospect of new tax revenues. So-called intrastate gambling, in which individual states seek to legalize online gambling for their own residents, is an attempt to bypass the UIGEA which applies only to gambling transactions across state lines. The impetus for the legalization of intrastate gam- bling was provided by an important legal opin- ion issued by the U.S. Department of Justice in December 2011 which interpreted the Wire Act to apply only to sports betting (Schneider 2012; Rose 2012). Specifically, the Department of Justice memorandum contended that “the text of the Wire Act and the relevant legislative materials support our conclusion that the Act’s prohibitions relate solely to sports-related gam- bling activities in interstate and foreign com- merce” (Seitz 2011, 12). Although this ruling was intended to address the legality of online intrastate sales of state lottery tickets, it was immediately seized upon to mean that almost all intrastate gambling was legal under federal law (Rose 2012, 259). As a result, state legisla- tures felt empowered to explore various forms of online gaming confined to residents within their borders. Thus, for example, in June 2012 Delaware’s legislature passed a law making the state the first in the nation to open its citizens to a full range of legal online gambling, includ- ing poker, blackjack, and slot games. The vote in Delaware came about in part due to politi- cal pressure from the state’s racetrack casinos which complained of competition from casinos in neighboring states. In response, the admin- istration of Governor Jack Markell proposed that the state lottery run online gambling oper- ations and use the proceeds to help fund a

10. Other states that have extended land-based casino gambling include Ohio, Massachusetts, and Kansas. On May 31, 2011, the Illinois state legislature passed a bill extending casino gambling in that state. The bill allows for a new publicly owned Chicago casino that, if built, is expected to create 2,500 permanent casino jobs, 1,500 temporary construction jobs, and generate $650 million in gaming revenue annually and a further $130 million in nongaming revenue, a much needed boost for a city confronting a 2012 budget deficit of $587 million (Economist, June 18, 2011, p. 36).

HALCOUSSIS & LOWENBERG: INTERNET GAMBLING 21

$7.75 million reduction in licensing fees paid by the racetrack casinos (Berzon 2012).11

In February 2013, New Jersey enacted a law that would allow Atlantic City casino companies to operate gaming websites for state residents (Berzon 2013).12 The New Jersey law obtained the support of the horseracing indus- try by promising that some of the new gam- bling revenue would be channeled to racetracks in exchange for their promise not to expand gambling at the track. The law was also sup- ported by companies that provide software for online gaming, but was opposed by Indian tribes and by some large casino companies, notably Caesars Entertainment, Inc., which preferred to hold out for a change in federal law (Berzon 2011a; Henderson 2011). Both the New Jer- sey law and a recent law passed in Nevada allow gambling regulators in those states to negotiate compacts with other states to pool player networks, thereby potentially enhancing the number of bettors in much the same way that lotteries have created pooled drawings for games across multiple states (Schneider 2013; Berzon 2013).

Legislation similar to that of Delaware or New Jersey has been introduced or consid- ered in other states, including Illinois, Iowa, California, Mississippi, and Florida. However, these efforts have been opposed by local inter- est groups such as Indian tribes, commercial casinos, convenience-store owners who sell lot- tery tickets, and those concerned about gambling addictions (Berzon 2011a, 2012, 2013).13

11. Online gambling was expected to generate revenue of at least $3.75 million for the state in the first 6 months after its implementation in early 2013, with the rest of the casino fees shortfall made up by other gambling expansions, such as electronic Keno in bars (Berzon 2012).

12. It is estimated that the new law will cre- ate over 1,500 jobs in New Jersey and generate $410 million in gambling revenue the first year, grow- ing to $590 million in subsequent years, from which the state will collect a 15% tax (Henderson 2011; Berzon 2011a, 2013).

13. U.S. gambling policy has produced conflicts with international treaty obligations. Thus, for example, in 2003 the Caribbean island nation of Antigua and Barbuda sued the United States at the World Trade Organization (WTO) on the grounds that various federal and state laws were discriminatory since they allowed online horseracing bets placed with U.S.-based casinos but not with foreign-based companies, many of which were located in Antigua. In April 2005 the WTO ruled in Antigua’s favor. The United States refused to amend the statutes in question, and in January 2007 the WTO again ruled that the United States was in violation of its treaty obligations by not granting full market access to online gambling companies based in Antigua and Barbuda (Online Gaming Association, accessed

In the next section, we describe the data that will be used in our study of the deter- minants of federal government policy toward internet gambling.

III. THE DATA

Our roll call voting data are for the Inter- net Gambling Prohibition and Enforcement Act, H.R. 4411, which passed in the House of Rep- resentatives by a vote of 317 to 93 on July 11, 2006. (H.R. 4411 was not voted on by the Sen- ate and never became law.) The UIGEA, as we have seen, was added to an unrelated piece of legislation, the SAFE Port Act, in a Confer- ence Report which was passed by the House on September 29, 2006, by a vote of 409 to 2, and unanimously by the Senate on Septem- ber 30, 2006. The overwhelming support for the UIGEA in the House likely reflected legislator preferences for the SAFE Port Act to which it was attached and which dealt with issues related to national security. A better gauge of legislator preferences regarding internet gambling is the voting record on H.R. 4411, which was con- cerned exclusively with this issue. Moreover, the roll call vote on H.R. 4411 contained a much larger number of “nays,” thereby provid- ing sufficient variation in the sample to facilitate econometric testing.

The content of the UIGEA is very similar to that of H.R. 4411, so that we can infer that the voting record on H.R. 4411 closely mirrored that which would have occurred if the UIGEA had been voted on by itself. In large measure, the UIGEA replicates the language of H.R. 4411, with one notable exception. H.R. 4411 included a provision introduced in an earlier bill spon- sored by Rep. Goodlatte, namely, H.R. 4777. The latter bill sought to significantly expand the scope of the Wire Act by amending the defini- tion of “the business of betting and wagering” to make it clear that the Act was not limited to sports gambling but also extended to online casinos and poker rooms (Casinoadvisor.com, accessed February 5, 2011; Doyle 2006, 3). This

March 1, 2011). In June 2007, Antigua and Barbuda filed a claim for $3.44 billion in compensation along with a request to be allowed to ignore U.S. patent and copyright laws (BBC News, 2013). In January 2013, the WTO’s dis- pute settlement body gave final authorization for Antigua and Barbuda to suspend U.S. intellectual property rights and to sell movie, music, game, and software down- loads without paying copyright fees to their U.S. owners (Pecquet 2013).

22 CONTEMPORARY ECONOMIC POLICY

amendment to the Wire Act was rolled into H.R. 4411, but when the UIGEA was added to the SAFE Port Act, the amendment was dropped (Doyle 2006, 3). Other provisions of H.R. 4411 that were dropped from the UIGEA included an increase in the maximum prison term for vio- lation of the Wire Act from 2 to 5 years and an authorization of $40 million in appropriations spread over 4 years for enforcement of the Wire Act (Doyle 2006, 5).14

We use probit regressions to investigate the relationship between representatives’ votes on H.R. 4411 and factors that measure the presence of gambling in the district of each representative, relevant economic and demographic informa- tion, campaign contributions, and the represen- tative’s party affiliation. Probit is an appropriate estimation method in this case, since the depen- dent variable is a binary choice variable (Greene 2003, 665 – 89). Probit has been used in previ- ous voting studies; for example, Lopez (2002), Abetti (2008), and Broz (2008) all use probit to examine congressional voting patterns.

The variables used in our regression models are as follows:

AYE = 1, if the representative voted for H.R. 4411; zero otherwise.

REPUBLICAN = 1, if the representative was registered Republican; zero otherwise.

GAMBLE_CONTRIB = the dollar amount of contributions given to each congressman by commercial and tribal casinos, racetracks, raci- nos (racetracks with casinos), and other pro- gambling interest groups (and their employees) from November 6, 2002 to July 10, 2006 (thus the contributions measured start with the previ- ous election cycle and end the day before the bill was voted on).

RELIGIOUS_CONTRIB = the dollar amount of contributions given to each congressman by religious groups (and their employees) from November 6, 2002 to July 10, 2006.

SPORTS_CONTRIB = the dollar amount of contributions given to each congressman

14. In addition to these extensions of the Wire Act that were included in H.R. 4411 but absent from the UIGEA, there are a few other more minor differences between the two. Thus, for example, H.R. 4411 allows the seizure of funds from an account maintained by an insured depository institution if the account is owned or controlled by a gambling business that violates the Act. The UIGEA, however, does not provide for injunctions on financial transaction providers, except in cases of fraud. H.R. 4411 prohibits “information assisting in the placing of bets or wagers” by a gambling business, whereas the UIGEA prohibits only information pertaining to the movement of funds to or from an account used for gambling purposes.

by professional sports organizations, arenas, and related sports service industries (and their employees) from November 6, 2002 to July 10, 2006.

GAMBLE_NUM = the total number of com- mercial and tribal casinos, racinos, horse tracks, and dog tracks in the congressional district in 2006.

EVANGELICAL = percentage of adults in the state who consider themselves to be asso- ciated with an Evangelical Christian denomina- tion, 2007.15

INCOME = median household income in the congressional district, 2006.

Data sources are listed in the appendix.

IV. EMPIRICAL RESULTS

Descriptive statistics for the variables defined above are presented in Table 1. The sample size is 408. There were 410 votes recorded for H.R. 4411, and EVANGELICAL is miss- ing for Hawaii’s two congressional districts. Table 2 shows the results of three probit regres- sion equations, all of which have AYE as the dependent variable, for the sample of 408 (the probit coefficients, as well as the slope estimates at the mean values of the independent variables, are shown). The first set of results in Table 2 is for a probit regression which includes all of the variables listed above.16 There are four coef- ficient estimates that are statistically different from zero at a 5% significance level or better, namely, the coefficient estimates of REPUBLI- CAN, GAMBLE_CONTRIB, GAMBLE_NUM, and EVANGELICAL. Below, for ease of inter- pretation, the marginal effects, represented by the slope estimates at the means, are used. (The levels of significance for the probit coef- ficients and the estimated slopes at the means are equivalent.)

The estimate of the slope for REPUBLI- CAN when all of the independent variables are assumed to take their mean value is positive and statistically significant at a 1% level. This indi- cates that Republican congressmen were more likely to vote for the bill than their Democratic Party counterparts. In fact, 201 of 218 voting Republicans (92.2%) voted for the bill, com- pared to only 115 of 191 Democrats (60.2%).

15. District-level data for 2006 are unavailable. 16. When all 410 observations are included and EVAN-

GELICAL is excluded, the results for the remaining inde- pendent variables and the overall fit of the regression model are similar to the first regression shown in Table 2.

HALCOUSSIS & LOWENBERG: INTERNET GAMBLING 23

TABLE 1 Descriptive Statistics

Variable Mean Standard Deviation Minimum Maximum

AYE 0.774 0.418 0.000 1.000 REPUBLICAN 0.534 0.499 0.000 1.000 GAMBLE_CONTRIB 13,610 40,626 −2,500.0a 463,793 RELIGIOUS_CONTRIB 693.89 1,745.2 −200.00a 15,200 SPORTS_CONTRIB 1,857.9 3,633.9 0.000 24,800 GAMBLE_NUM 1.319 3.419 0.000 36.000 EVANGELICAL 25.755 11.362 7.000 53.000 INCOME 50,119 13,331 21,088 97,753 N 408

aNegative values represent returned contributions. These values were included as they are likely to represent an unfavorable reaction on the part of the congressman to the contribution. When negative values for contributions are replaced by a 0, the regression results are very similar (see Table 2, Regression (3)).

TABLE 2 Probit Results by Congressional District (Dependent Variable Is AYE)

(1) Probit Coefficients

(t -stats)

(2) Probit Coefficients

(t -stats)

(3)a Probit Coefficients

(t -stats) Variable Slopes at Means Slopes at Means Slopes at Means

Constant −0.640 (−1.37)

−0.409∗ (−2.00)

−0.641 (−1.37)

REPUBLICAN 1.17∗∗ (6.79)

0.297∗∗

1.15∗∗ (6.93)

0.293∗∗

1.17∗∗ (6.79)

0.297** GAMBLE_CONTRIB −7.54×10−6∗∗

(−3.20) −1.85×10−6∗∗

−7.68×10−6∗∗ (−3.24)

−1.90×10−6∗∗ −7.54×10−6∗∗

(−3.20) −1.85×10−6**

RELIGIOUS_CONTRIB 5.49×10−5 (1.11)

1.34×10−5 5.46×10−5

(1.10) 1.34×10−5

SPORTS_CONTRIB −2.23×10−5 (−1.06)

−5.48×10−6 −2.23×10−5

(−1.06) −5.48×10−6

GAMBLE_NUM 0.096∗ (2.41)

0.0235∗

0.090∗ (2.30)

0.0222∗

0.096∗ (2.41)

0.0235* EVANGELICAL 0.0314∗∗

(3.61) 0.00771∗∗

0.0294∗∗ (3.81)

0.00773∗∗

0.0314∗∗ (3.62)

0.00772** INCOME 3.40×10−6

(0.51) 8.37×10−7

3.40×10−6 (0.51)

8.37×10−7 McFadden R2 0.242 0.237 0.242 % Predicted correctly 81.1% 79.7% 81.1% N 408 408 408

aFor this regression, all negative values indicating a returned contribution have been replaced with a 0 (negative values were present for GAMBLE_CONTRIB and RELIGIOUS_CONTRIB but not SPORTS_CONTRIB).

∗Significant at 5% level; ∗∗Significant at 1% level.

To interpret the 0.297 value of this estimate, consider an imaginary “typical” congressional district that has mean values for all of the independent variables. For convenience, call

the district “Seahaven.” Seahaven would be in a state where 25.76% of the constituents are Evangelical Christians. Pro-gambling groups, religious groups, and sports entities would

24 CONTEMPORARY ECONOMIC POLICY

give Seahaven’s congressman the campaign contributions shown as the means in Table 1, namely, $13,610, $693.89, and $1,857.90, respec- tively. Seahaven has one gambling establish- ment, a Republican congressman, and the median household income in Seahaven is $50,119.

Suppose that Seahaven had elected a Demo- cratic congressman instead of a Republican. The fitted value from the probit results shown in the first column of Table 2 would be 0.33. Recall that fitted values for probit regressions can be interpreted as z-scores, and then the cumulative normal probability distribution can be used to find the estimated probability of a district’s rep- resentative voting for the bill.17 The correspond- ing probability for the 0.33 fitted value is 0.63, meaning that there is a 63% chance that Sea- haven’s Democratic congressman would have voted for H.R. 4411. Since the slope estimate at the means for REBUPLICAN is 0.297, if Sea- haven’s congressman were Republican instead, the probability that the congressman would vote for H.R. 4411 would increase by 0.297 ceteris paribus so that there is now a 93% chance the congressman would support the bill. This shows the importance of party affiliation in this vote.

Here, and in the discussion below, keep in mind that the mean of AYE is 0.774, so that there is an overall unconditional 77% probability that a representative votes for H.R. 4411. The probability that Seahaven’s representative votes for the bill does not come out to 77% because we assumed that Seahaven’s congressman belongs to a particular party, not that he is somehow 53% Republican and 47% Democrat, which would be the average but would make no sense in this context. Below, we assume that Seahaven’s representative is a Republican, since there were more Republicans than Democrats in the House of Representatives at the time that H.R. 4411 was voted on. Likewise, we assume that Seahaven has one gambling establishment, not the mean of 1.34.

The estimated slope at the means for the gam- bling industry’s political contributions given to each district’s representative (GAMBLE_CON- TRIB) is significant at a 1% level with a neg- ative sign, meaning that the greater the amount of contributions a representative receives from pro-gambling groups, the more likely he would be to support online gaming by voting against H.R. 4411. This result is plausible since these

17. See Becker and Waldman (1989).

groups might see online gambling as a way to get people interested in gambling in gen- eral and promote traditional casinos and race- tracks. Industry groups dominated by land-based casino companies might therefore be opposed to H.R. 4411. Recall that the value of political contributions by gambling groups in Seahaven, our typical district, is the mean value, $13,610, and that there is a 93% probability that Sea- haven’s Republican congressman would vote for H.R. 4411. Now suppose that these contribu- tions increased by $1,000. Given the −1.85 × 10−6 slope at the means estimate, the probabil- ity that this district’s representative would vote for H.R. 4411 would decrease by approximately 0.185%.18 (The slope estimate is small because GAMBLE_CONTRIB is measured in dollars, and a one unit or one dollar change would have a small effect on the politician’s vote.)

The estimated slope at the means for the number of gambling establishments in a district, GAMBLE_NUM, is positive and statistically significant at a 5% level, indicating that the more places there are to gamble in the district, the more likely that district’s representative would be to vote in favor of H.R. 4411. Although, as we have seen, contributions from the gambling industry are associated with opposition to H.R. 4411, the presence of gambling establishments in a district is correlated with support for the bill. While national organizations may have per- ceived online gaming as a way to promote the gaming industry, it is reasonable to suppose that local casinos, racetracks, and similar establish- ments viewed H.R. 4411 as a way to eliminate competition from online casinos, in which case these constituents would have lobbied their local representative to vote for the bill in order to protect land-based businesses and employment within the district. We have assumed that Sea- haven has one gambling establishment within its borders, but suppose now that Seahaven had two gambling establishments instead. Using the slope at the means estimate of 0.0235, the prob- ability that Seahaven’s congressman would vote

18. It is approximate because the slope at the means estimate is most accurate for a small change right at the variable’s mean. In addition, for substantial changes in the independent variable, the effects are not symmetrical with regard to the change in the representative’s probability of voting for H.R. 4411. For example, a $10,000 increase in GAMBLE_CONTRIB would decrease the probability that the congressman votes for the bill by more than a $10,000 decrease would increase the probability that he votes for it. This asymmetry occurs because the z-scores behind the probabilities that are relevant here are located toward the right-hand side of the normal probability distribution.

HALCOUSSIS & LOWENBERG: INTERNET GAMBLING 25

for H.R. 4411 would increase from 93% to approximately 95%.

EVANGELICAL also has a statistically sig- nificant slope at the means estimate. This pos- itive and highly significant result (1% level) indicates that voters associated with Evangeli- cal churches generally do not approve of online gambling and that their representatives are more likely to support H.R. 4411. If the percent- age of adults in Seahaven’s state who asso- ciate themselves with an evangelical Christian denomination increased by one, the probabil- ity that Seahaven’s representative would vote for H.R. 4411 would increase by the slope at the means estimate, 0.00771 or 0.771%. Over- all, the regression correctly predicts 81.1% of congressional votes.

Clearly, party affiliation is critical here. Polit- ical contributions from the gambling industry, the number of gambling establishments in the district, and the percentage of evangelical Chris- tians in the state are also relevant. However, median household income, as well as two other variables which measure political contributions, were not close to having statistically significant coefficients at a 5% level. Variance inflation factor tests as well as an examination of the correlation coefficient matrix do not reveal any multicollinearity problem that would be gener- ating this lack of results. As a test of robust- ness, the second regression equation reported in Table 2 shows probit results with the indepen- dent variables that had insignificant coefficients removed. The results are very similar in terms of the probit coefficient estimates and slope at means estimates, significance levels, and the percent predicted correctly (79.7% instead of 81.1%).

As pointed out in a footnote to Table 1, the variables that measure political contribu- tions contain some negative values represent- ing returned contributions. The third regression model in Table 2 reports the results when these negative values are replaced by zeros in the data set; these results are very similar to those that include the negative values as reported in the first regression.

V. CONCLUSION

Passage of the UIGEA in 2006, and sub- sequent actions to implement the Act, had a significant impact on the online gambling indus- try in the United States. The law prohibited

U.S. financial institutions from processing pay- ments to gambling sites, thereby raising sub- stantial barriers to online gambling by U.S. cit- izens, with the result that most of the largest internet casinos and poker rooms either ceased to operate in the United States or were forced to close.

We have examined empirically the main fac- tors determining congressional roll call votes on internet gambling legislation, focusing our atten- tion on the 2006 Internet Gambling Prohibition and Enforcement Act, H.R. 4411, a precursor to the UIGEA which passed in the House but was not voted on in the Senate. H.R. 4411 had very similar provisions to the UIGEA but, unlike the UIGEA, was not attached to unrelated leg- islation at the time it was voted on. A main purpose of our study has been to separate out the effects of representatives’ ideologies and those of their constituents, as reflected in party affilia- tion and religious beliefs, from economic condi- tions, such as the presence in a district of other gambling industries, in driving a representative’s vote on H.R. 4411.

Our results indicate that party affiliation is a prominent influence on representatives’ votes on H.R. 4411, with Republicans significantly more likely to vote for the legislation than Democrats. In addition, we find that the larger the per- centage of a state’s population that is associ- ated with an evangelical Christian denomination, the more likely a representative from that state would be to vote for H.R. 4411. The presence of gambling establishments in a district is also associated with a higher probability of voting for the legislation, suggesting that politicians responded to local political pressure to protect land-based casinos and jobs within their dis- tricts from the threat of competition from online gambling. However, at the margin, political con- tributions from the gambling industry diminish legislator support for H.R. 4411. National indus- try groups would have an interest in promoting gambling in general and might view online casi- nos as providing exposure to gambling expe- riences that could ultimately attract customers to land-based outlets too. Our findings of the importance of party affiliation, campaign con- tributions, and economic variables, such as in this case the presence of land-based gambling establishments within a politician’s district, are consistent with the literature on the determi- nants of congressional roll call voting discussed in Section I, e.g., Kahane (1996), Facchini and Steinhardt (2011), and Couch et al. (2011).

26 CONTEMPORARY ECONOMIC POLICY

Despite the passage of the UIGEA, a consid- erable number of Americans continue to gam- ble online. According to the Poker Players’ Alliance, even though transactions are compli- cated by the UIGEA’s prohibition on finan- cial institutions’ acceptance of payments, some 10 million people in the United States play poker online (Berzon 2011a).19 In 2010, the online poker industry in the United States com- prised $18 billion in wagers (Berzon and Alber- gotti 2012). The global online gaming indus- try’s revenues have risen steadily in recent years and are now close to $30 billion a year (Economist, April 23, 2011, p.68). In 2007, and again in 2009, Massachusetts Representa- tive Barney Frank sponsored a bill to legalize online gambling at the federal level by pro- viding for the licensing of gaming websites by the Treasury Department (Library of Congress, accessed March 3, 2011; Longino 2009). Frank also sought legislation to halt enforcement of the UIGEA (Longino 2009). In March 2011 Frank, together with California Representative John Campbell, again introduced a bill to reg- ulate and tax online gaming. So far, however, none of these bills has reached the floor of either the House or the Senate, despite some favorable votes in the House Committee on Financial Ser- vices (Masnick 2010; Popper and Hsu 2011).

Nevertheless, lobbying efforts to repeal the UIGEA have intensified as land-based casinos join forces with online gaming companies to press for legalization and to form strategic part- nerships to operate gambling sites in the event of an end to prohibition.20 The situation changed rather dramatically on April 15, 2011, when the U.S. Attorney in Manhattan indicted three

19. See also Popper and Hsu (2011) and Economist (April 23, 2011, p. 68).

20. Thus Caesars Entertainment, Inc. teamed up with 888 Holdings Plc., an online poker site operating outside the United States, and Wynn Resorts partnered with Isle of Man- based PokerStars with the specific intent of lobbying for federal legalization and then, if successful, jointly operating new online sites for U.S. customers (Berzon 2011b). Shortly thereafter, Fertitta Interactive, a company established by the owners of Station Casino, teamed up with Ireland-based Full Tilt Poker, again with the intention of lobbying for a change in the federal regulatory regime and of preparing to jointly operate future online sites (Berzon 2011c; Economist, April 23, 2011, p. 68). Both Wynn Resorts and Fertitta Interactive supported a Nevada bill that provided for the state’s gaming commission to draft regulations for online gambling, to take effect on approval from Congress or the Justice Department (Economist, April 23, 2011, p. 68). Such approval was forthcoming with the Justice Department’s December 2011 finding, and shortly thereafter Nevada’s gaming commission proceeded to authorize companies within the state to offer online poker (Berzon 2012).

of the largest online poker sites on charges of bank fraud, money laundering, and violat- ing gambling laws (Rose 2011), whereupon the land-based casinos immediately dissolved the partnerships they had previously forged with their online counterparts (Popper and Hsu 2011; Economist, April 23, 2011, p.68).21 Still, the U.S. casino industry as a whole, represented by the American Gaming Association, continues to lobby for federal, as opposed to state-level, reg- ulation of online gambling and for legalization of online poker specifically (American Gaming Association, accessed August 2, 2013).

That large land-based gambling companies clearly have aspirations to enter the online mar- ket themselves has important implications for the future of internet gambling policy in the United States. Our empirical analysis indicates that political contributions from the gambling industry have the effect of diminishing legisla- tor support for prohibition of online gambling, no doubt in part due to the interests of land- based casinos in establishing their own online presence. This finding suggests that ultimate repeal of the UIGEA and liberalization of fed- eral gambling policy more generally, including legalization of online sports betting, becomes more probable as the political efforts of industry groups gain momentum.

DATA APPENDIX

Data sources are listed below. AYE: Govtrack, http://www.govtrack.us/congress/vote.

xpd?vote=h2006-363. REPUBLICAN: Govtrack, http://www.govtrack.us/cong

ress/vote.xpd?vote=h2006-363. GAMBLE_CONTRIB: Center for Responsive Politics

reported by www.maplight.org. This variable consists of contributions by commercial casinos, tribal casinos, race- tracks, racinos, and other pro-gambling interest groups and their employees.

21. Prosecutors alleged that, after passage of the UIGEA, the three indicted companies — PokerStars, Full Tilt Poker, and Absolute Poker — disguised their customers’ deposits as payments to fictional merchants for products such as jewelry and golf balls (Economist, April 23, 2011, p. 68). When some banks started to balk at this practice, the accused companies, in an “elaborate criminal fraud scheme,” allegedly tricked or bribed small struggling banks to pro- cess payments (Popper and Hsu 2011; Economist, April 23, 2011, p. 68). The Justice Department seized and shut down the three indicted companies’ websites and filed a civil suit against them for penalties of $3 billion. Within hours of the indictments being handed down, Wynn Resorts and Fer- titta Interactive ended their partnerships with PokerStars and Full Tilt Poker, respectively (Economist, April 23, 2011, p. 68).

HALCOUSSIS & LOWENBERG: INTERNET GAMBLING 27

RELIGIOUS_CONTRIB: Center for Responsive Politics reported by www.maplight.org. This variable consists of contributions made by religious groups and their employees.

SPORTS_CONTRIB: Center for Responsive Politics reported by www.maplight.org. This variable consists of contributions made by professional sports teams, leagues, arenas, and related equipment and service groups, and their employees.

GAMBLE_NUM: For commercial casinos, racinos, and tribal casinos, state-level data are from State of the States, American Gaming Association, 2006. http://www.american gaming.org/files/aga/uploads/docs/sos/aga-sos-2006.pdf.

For dog tracks, tracks existing in 2006 and their addresses are from The American Greyhound Track Opera- tors, 2006. http://www.agtoa.com/PDF/06/06%20AGTOA% 20National%20Report.pdf.

For horseracing, tracks existing in 2006 and their cities or towns are from Official USA, http://www.officialusa.com/ stateguides/horseracingtracks/index.html.

These data were then used along with Google Maps and various other internet sites belonging to casinos and gam- bling organizations to identify the addresses of the appro- priate establishments that existed in 2006. The mapping site www.nationalatlas.gov was then used to sort the estab- lishments into the appropriate congressional districts (from 2006) so that the number of such establishments in each district could be determined.

EVANGELICAL: U.S. Religious Landscape Survey, 2008. http://religions.pewforum.org/pdf/report-religious-lan dscape-study-full.pdf.

INCOME: 109th Congressional District 2006 Demo- graphics, http://proximityone.com.

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