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Albers and Hubl (1997) analyze how the individuals in Germany spend their money in legal gambling and what are their consumption patterns towards it by using a probit technique. They conducted a survey in Germany, using a sample of 1,586 adults to estimate for all types of commercial gambling, the separate functions of participation, and in order to provide explanatory variables about the socioeconomic characteristics like education, gender, age, income, employment and family status, occupation, home ownership, and the relevance of the highest prizes in explaining the gambler’s participation or not in the various types of gambling including Draw lotteries, lotto, soccer toto pools, TV-lotteries, casinos, gaming machines and horse-race betting. Their results show that income has positive impact and major effect on the consumption pattern of commercial games. People with a higher income will tend to spend more on gambling. However, it has been found out that income has no effect on Lotto and that the demand for Soccer Toto falls as income rises.
Worthington, et al. (2003) estimate the patterns of gambling in Australia by using a regression model. So they have collected data from the Australian Bureau of Statistics Household Expenditure that has conducted a survey on 6892 households. They examine eight kinds of gambling spending ranging from casino games to lottery tickets and analyze causal factors like family composition, gender, income, age, geographic location, ethnicity and race. They reach the conclusion that lottery pattern in Australia is highly determined by household composition, ethnicity and age.
Kearney (2005) finds that domestic lottery spending is funded exclusively by a fall in non-gambling costs when analyzing multiple sources of micro-level data. The analysis considered data from the 1982 to 1998 Interview Survey files of the Bureau of Labor Statistics (BLS) Consumer Expenditure Survey (CEX). 21 states applied a national lottery during this time. The empirical analysis compares the change household expenditures among the households in states that implemented a lottery to those in states that do not. Introducing national lottery leads to an average fall of $46 (2.4%) per month in household’s non-gambling expenditures. This amount indicates that there is a fall in household expenses of $24 for each adult each month as compared to an average of the sale of lottery per month which is $18 for each lottery-state adult From the CEX Interview sample, the non-gambling expenses for the households of low income group are fell by 2.5% on average and 3.1% while the national lottery offered instant games. Furthermore, the data prove that the level of expenses decreases considerably in households. The consumption of food eaten at home decreases by almost 2.8% and 5.8% for bills like rent and home mortgage. However, The information do not specify which lottery tickets has been purchased by which households, thus these average effects are not considered since a subsequent proportion of households are not involve in lottery gambling. Households that are engaged in lottery gambling and buy tickets of lottery will therefore experience a greater downfall in their non-gambling expenses.
Lottery gambling can be considered as investment and entertainment at the same time. It is an investment as consumers are making choices over risky assets. Assuming that the entertainment and pecuniary components of the lottery gamble are separable, maximizing behavior predicts that consumer demand for lottery products should depend positively on its expected return, holding constant game characteristics. To evaluate whether this prediction holds Kearney (2005) investigates from 91 lotto games the weekly sales and characteristics data from 1992 and 1998. The study concludes that the estimated value of a gamble affects positively the level of sale, controlling for higher-order moments of the gamble and non-wealth creating characteristics. This finding is strong to alternative specifications, including controlling for unobserved product fixed effects. The data also revealed that buyers of lotto games react to creation of non-wealth creating and “entertaining” game features. These two outcomes together find out that gamblers are considered as being partially and possibly entirely rational and informed consumers. In accordance with the results, she states that gamblers derive an amusement equivalent to the cost of gambling (1-expected value) and that they are informed assessors of bets as long as they are making investments. These two outcomes together observe that gamblers are considered as being partially and possibly entirely rational and informed consumers. In accordance with the results, she states that gamblers derive an amusement equivalent to the cost of gambling (1-expected value) and that they are informed assessors of bets as long as they are making investments.
Kearney (2005) analyses micro level proof on who plays the lottery from the National survey carried out in 1998 by the National Opinion Research Council (NORC) on gambling. The data disclose the following overall trends. First of all, lottery gambling extends through races, sexes, and income and education groups. Second, black respondents spend nearly twice as much on lottery tickets as do white or Hispanic respondents. The average reported expenditure among blacks is $200 per year, $476 among those who played the lottery last year. Those who have the highest average gambling expenses are the Black men. Thirdly The average dollar amount of money spend on lottery per annum is almost the same among the low, medium and high income groups which can be concluded that on average as compared to other households, the low-income ones’ spend a higher proportion of their total capital on lottery tickets.
Clotfelter and Cook (1993) and Terrell (1994) make available the evidence which exist about the “gambler’s fallacy” between lottery players. “Gambler’s fallacy” means that people wrongly ascertain on the expectations of prize and their chance of winning. They believe that the first draw will adversely impact on the second draw. For example, if game has been won last year, the probability that the same game win for two consecutive years is low as the prize cannot be won twice for a short period of time. Thus, people would prefer to wait some times before playing. They collect information from the Maryland and New Jersey numbers games respectively and conclude that the sum of cash bet on a certain number clearly falls after the number is drawn and that after various months, it increasingly returns to its previous level.
Grinols and Mustard (2004) analyze the link between casinos and the rate of crime by obtaining information about the level of crime in each country examined using the 7 FBI Index 1 offenses from 1977 to 1996 such as murder, robbery, burglary, larceny and aggravated assault. They analyze all the 3165 countries find in the United States and observe the opening of casinos and their impact in all these countries except Nevada. The types of casinos that they examine are tribal-owned, riverboat and land-based casinos. After analysis, they notice that after casinos have been set up in these countries, the rate of crimes has increased considerably. Their result show that after a casino has opened, the rate of crime is low and then increases considerably overtime. They estimate that where countries have opened casinos in 1996, 8% of crime rate is associated to casinos and in average adults spend at around $75 in casinos per annum. They also support the fact that boundary countries are also affected by the level of crime rate which keeps increasing throughout the year, and propose that as compared to just relocating crime from one state to another, casinos increase aggregate crime.
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