Government restrictions and the demand for casino and parimutuel wagering

Abstract

Growth in casino wagering in the United States from the mid-1980s forward has been extraordinary. Over the same period, however, parimutuel wagering has declined. Concern for this decline has prompted a number of states to allow parimutuel racetracks to offer casino-type gaming devices at their facilities. Such operations are commonly referred to as ‘racinos’. If the gaming devices at a racino are under the auspices of a state lottery, they are referred to as video lottery terminals (VLTs). Separate parimutuel and VLT wagering demand models were estimated for a racino facility. A number of restrictions were imposed on the VLT's at the beginning of the study period including: number of VLT's, type of game and machine, maximum bet per play and VLT location. The effect of these restrictions on VLT and parimutuel handles was a major focus of this article. Also of importance was an examination of the relationship between the VLT and parimutuel products. Relaxation of government restrictions on the VLT's was found to have resulted in a large increase in VLT wagering. On the other hand, parimutuel wagering was found to decrease with the relaxation of restrictions on the VLT's. The presence and growth of the VLT product was found to decrease parimutuel handle. The presence and growth of the parimutuel product was found to increase VLT handle.

Acknowledgements

This article was accepted for publication, subject to final edit, while the author was at the University of Louisville, Louisville KY, USA. The author would like to thank the West Virginia Racing Commission for making available the volumes of paper output on wagering statistics over the study period as well as providing historical information on events that occurred over that period. I would also like to thank the West Virginia Lottery Commission for making data available. Special thanks are due to Mountaineer Park Racetrack  & Gaming Resort for allowing access to detailed company data. Special thanks are also due to Dr M. M. Ali, Department of Economics, University of Kentucky, for his valuable input with respect to methodology. Finally, the author gratefully acknowledges the helpful comments of an anonymous reviewer. As is customary, the author assumes full responsibility for the analysis and the remaining errors.

Notes

¹ Includes land-based casino gaming, riverboat casino gaming, Indian casino gaming, legal bookmaking, card rooms and charitable gaming.

² Limited stakes poker machine gaming devices were permitted at racetracks and other locations such as truck stops, restaurants and lounges in 1992. Legislation resulting in casino style slot machines, restricted to racetracks, resulted in full-scale racinos beginning with Delta Downs racetrack in 2002.

³ Video lottery terminal gaming was offered as permitted by state statute in March 1994, and after local referendum beginning in September 1994. At that time, three of the four West Virginia parimutuel racetracks, Mountaineer Park, Wheeling Downs and Tri-State, became racinos. Charles Town installed VLT's in September 1997 after local referendum.

⁴ Although, New York passed enabling racino legislation in 2002, racinos did not come on-line in that state until 2004.

⁵ In 2004, racinos were authorized but not yet implemented in the states of Maine, Oklahoma and Pennsylvania. The gaming devices were not under the state lottery in any of these states.

⁶ In recent years, receipts from ticket-out machines can be used as input to other machines in lieu of receiving cash.

⁷ See MTR Gaming Group, Inc., United States Security and Exchange Commission, Form 10-K, Annual Report, 31 December 1996. The simulated slot machine game startup was obtained from earlier reports.

⁸ The overall explanatory power of the included demand determinants was virtually unaffected by this action. The adjusted coefficient of determination was 0.875 with VLT types included and 0.865 when they were excluded.

⁹ See MTR Gaming Group, Inc., United States Security and Exchange Commission, Form 10-K, Annual Report 31 December 2002. The simulated slot machine game startup was obtained from earlier reports.

¹⁰ Long-run elasticity computed as: α₁₅/(1  − α₁), where α₁ and α₁₅ are given in Equation 1 with corresponding values in Table 1.

¹¹ Long-run percent change in handle for each machine type is computed as: [exp(α _i/(1  − α ₁)(0.01))  − 1]100, i  = 16, 20, where α_i and α ₁ are given in Equation 1 with corresponding values in Table 1.

¹² Although the win percent could vary by machine, the aggregate win percent remained fairly constant over the study period.

¹³ Long-run elasticity computed as: α ₂₃/(1  − α ₁), where α ₁ and α ₂₃ are given in Equation 1 with corresponding values in Table 1.

¹⁴ Long-run elasticity computed as: α ₂₄/(1  − α ₁), where α ₁ and α ₂₄ are given in Equation 1 with corresponding values in Table 1.

¹⁵ Long-run percent change in handle computed as: [exp((α ₂₄/(1  − α ₁))(ln(FULLCARD{18})  − ln(FULLCARD{4}))  − 1]100, where α ₁ and α ₂₄ are given in Equation 1 with corresponding values in Table 1.

¹⁶ Long-run impact of one live day computed as: [exp((α ₂₅/(1  − α ₁))LIVECARD{1/7})  − 1]100.

¹⁷ Long-run percent change in handle computed as: [exp((α ₂₅/(1  − α ₁))(LIVECARD{1}  − LIVECARD{0})  − 1]100, where α ₁ and α ₂₅ are given in Equation 1 with corresponding values in Table 1.

¹⁸ To test the robustness of the positive relationship between the parimutuel variables and VLT handle, Equation 2 was re-estimated without LVLTS. The coefficients of LDAYSPARI, LFULLCARD and LIVECARD, all remained positive and significant.

¹⁹ Long-run percent change in handle computed as: [exp((α ₁₅/(1  − α ₁))(LVLTS{3000}  − LVLTS{400}))  − 1]100, where α ₁ and α ₁₅ are given in Equation 1 with corresponding values in Table 1.

²⁰ Long-run impacts computed using: exp((α _i/(1  − α ₁))(s_{i ,2002−} s_{i ,1994}))  − 1, i  = 16, 20, where α_i and α ₁ are given in Equation 1 with corresponding values in Table 1. S_{i ,2002} and s_i ,₁₉₉₄ are shares of each machine type as shown in Table 2.

²¹ Joint long-run percent change computed as: [exp(Σ(α_i /1  − α ₁))(s_{i ,2002−} s_{i ,1994}))  − 1]100, i  = 16, 20, where α ₁ and α_i are given in Equation 1 with corresponding values in Table 1. S_{i ,2002} and s_{i ,1994} are shares of each machine type as shown in Table 2.

²² Long-run percent change in handle computed as: [exp((α ₂₁/(1  − α ₁))(VLT_LODGETOTRACK{3.4})  − VLT_LODGE TOTRACK{1}))  − 1]100, where α ₁ and α ₂₁ are given in Equation 1 with corresponding values in Table 1.

²³ Long-run percent change in handle computed as: [exp((α ₂₂/(1  − α ₁))(VLT_BETLIMIT2TO5{1}  − VLT_ BETLIMIT2TO5{0}))  − 1]100, where α ₂₂ and α ₁ are given in Equation 1 with corresponding values in Table 1.

²⁴ Long-run elasticity computed as: β ₁₄/(1  − β ₁), where β ₁₄ and β ₁ are given in Equation 2 with corresponding values in Table 3.

²⁵ Long-run elasticities computed as: β ₁₈/(1  − β ₁) and β ₁₉/(1  − β ₁), where β ₁₈, β ₁₉ and β ₁ are given in Equation 2 with corresponding values in Table 3.

²⁶ Long-run percent change in handle computed as: [exp((β ₁₉/(1  − β ₁))(ln(FULLCARD{18))  − ln(FULLCARD{4}))  − 1]100, where β ₁₉ and β ₁ are given in Equation 2 with corresponding values in Table 3.

²⁷ Long-run percent change in handle computed as: [exp((β ₂₀/(1  − β ₁))(LIVECARD{1/7}))  − 1]100, where β ₁ and β ₂₀ are given in Equation 2 with corresponding values in Table 3.

²⁸ Long-run percent change in handle computed as: [exp((β _20/(1  − β ₁))(LIVECARD{1}  − LIVECARD{0}))  − 1]100, where β ₂₀ and β ₁ are given in Equation 2 with corresponding values in Table 3.

²⁹ Long-run elasticity computed as: β ₂₁/(1  − β ₁)(RLIVEPURSE{mean}), where RLIVEPURSE{mean} is the sample mean, β ₂₁ and β ₁ are given in Equation 2 with corresponding values in Table 3.

³⁰ Long-run percent change computed as: [exp(β_i /(1  − β ₁))  − 1]100, where β ₁ and β_i , i  = 22, 26 are given in Equation 2 with corresponding values in Table 3.

³¹ Long-run elasticity computed as β ₁₅/(1−β ₁)(VLTS{mean}), where VLTS{mean} is the sample mean, and β ₁ and β ₁₅ are given in Equation 2 with corresponding values in Table 3.

³² Long-run percent change in handle computed as: [exp((β ₁₅/(1  − β ₁))(VLTS{3000}  − VLTS{400}))  − 1]100, where β ₁ and β ₁₅ are given in Equation 2 with corresponding values in Table 3.

³³ Long-run percent change in handle computed as: [exp((β ₁₆/(1  − β ₁))(VLT_LODGETOTRACK{3.4})  − VLT_LODGE TOTRACK{1}))  − 1]100, where β ₁ and β ₁₆ are given in Equation 2 with corresponding values in Table 3.

³⁴ VLT_BETLIMIT2TO5 was not significant at the 10% level. Long-run percent change in handle computed as: [exp((β ₁₇/(1  − β ₁))(VLT_BETLIMIT2TO5{1}  − VLT_ BETLIMIT2TO5{0}))  − 1]100, where β ₁₇ and β ₁ are given in Equation 2 with corresponding values in Table 3.

³⁵ The joint long-run percent change in VLT handle can be computed as: [exp(Σα_i /(1  − α ₁)(x_{i ,2002}  − x_{i ,1994}))  − 1]100, i  = 15, 22, where α ₁ and α_i are given in Equation 1 with corresponding values in Table 1. x_{i ,1994} and x_{i ,2002} are the variables of interest. Due to the logarithmic equation specification, this formula can be also be written as: [(1  + g ₁)(1 +g ₂).. (1  + g_n )  − 1]100, where g_i is the computed growth rate for variable x_i : exp(α_i /(1  − α ₁)(x_{i ,2002}−x_{i ,1994}))  − 1.

³⁶ The elasticity of total (live and full-card) handle is computed relative to live race purse. It is expected that the elasticity of live race handle relative to live race purse would be greater than elasticity relative to total handle.

³⁷ Revenue per dollar of export parimutuel handle, approximately 3% of the amount wagered, is much smaller than revenue per dollar from on-track handle.

³⁸ On-track parimutuel revenue is computed using a weighted takeout rate of 21% (23% for live race wagering and 20% for on-track simulcast wagering after payment of a 3% host fee to the sending racetrack).

³⁹ The joint long-run percent change in VLT handle can be computed as: [exp(Σβ_i /(1  − β ₁)(x_{i ,2002}−x_{i ,1994}))  − 1]100, i  = 15, 17, where β ₁ and β_i are given in Equation 2 with corresponding values in Table 2. x_{i ,2002} and x_{i ,1994} are the variables of interest. Due to the logarithmic equation specification, this formula can also be written as: [(1  + g ₁)(1  + g ₂)  … (1  + g_n )  − 1]100, where g_i is the computed growth rate for variable x_i : exp(β_i /(1  − β ₁)(x_{i ,2002}  − x_{i ,1994}))  − 1.

⁴⁰ Long-run percent change in handle from purses computed as: [exp((β ₂₁/(1  − β ₁))(RLIVEPURSE{$90 659}  − RLIVEPURSE{$15 653}))  − 1]100, where β ₂₁ and β ₁ are given in Equation 2 with corresponding values in Table 3, and the number in brackets, {}, are real average live purse at the end and start of the study period.

⁴¹ Computed as increase in 2002 on-track handle of $39 million multiplied by weighted average on-track takeout rate of 21%.

⁴² Computed as actual 2002 live race handle of $16.2 million at a takeout rate of 23%.

⁴³ Computed as 2002 export handle of $268.3 million evaluated at a payment to Mountaineer of 3% of handle wagered at the receiving racetrack.

⁴⁴ Computed as 2002 VLT handle of $2.6 billion multiplied by the percent reduction in VLT handle from reducing the number of live races per wagering day from 0.63 (4.4 days per week) to 0 evaluated at the win percent of 0.085. The long-run percent reduction in VLT handle from elimination of live racing is computed as: [exp((α ₂₅/(1− α ₁))(LIVECARD{0}  − LIVECARD{0.63))  − 1]100  = −18%, where α ₂₅ and α ₁ are given in Equation 1 with corresponding values in Table 1.