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Using the Washington Nationals case, which moved from Montreal, Canada, to Washington, DC in 2005, as a natural experiment, I examine the impact of MLB games on crime in a host city. To address endogeneity concerns, this paper applies a synthetic control method with using 21 large cities which host an MLB team as a “donor pool” and employs a triple difference-in-difference approach to estimate the change in crime before and after the Nationals coming, between MLB season and off-season, and Washington, DC and the synthetic Washington. With using monthly crime data from the Uniform Crime Report, only assaults increased by 7–7.5% annually after the Nationals moved to DC; other crimes were unchanged. This result is supported by statistical significance and in-space placebo tests, and several alternative specifications in robustness check. These increases in assaults could be associated with additional costs, annually from $20 to $35 million. Little to no evidence of a causal relationship between MLB games and other types of crime.

The Olympic legacy framework was proposed by the International Olympic Committee; however, it has not yet been discussed much in academia. This study identified a set of key dimensions and items out of 7 dimensions and 39 items from the Olympic legacy framework, along with the weight of each dimension and item. Based on the judgments of 12 Korean Olympic experts collected via the Delphi-analytical hierarchal process method, the results indicate that social development through sport is the most significant dimension, followed by economic value and brand equity, and urban development. The results also reveal that the most crucial of the 39 items are health and well-being benefits from the practice of recreational sport and physical activity from the social development through sport dimension, while the intangible cultural heritage of Olympism from the culture and creative development dimension was considered the least important. The results provide useful insight for evaluating the Olympic legacy framework for host or candidate cities and countries, as well as the International Olympic Committee.

This study performed a direct test of reference-dependent preferences with loss aversion in National Football League fans. For the 2021 and 2022 seasons, we collected all comments from YouTube game highlights. Subsequently, we identified each user's supporting team and performed sentiment analysis to estimate sentiment scores using a pre-trained deep learning model. Least squares dummy variable regressions were applied to examine reference-dependent preference and loss aversion, using win and win probability and upset results with the sentiment score of comments as an outcome. The results consistently showed that fans posted comments as reference-dependent preference predicts. We also provide evidence supporting loss aversion using upset outcomes after correcting for sample selection bias.

This study aims to analyze fans' demand for live football matches in the German 2. Bundesliga, focusing on match-outcome uncertainty. To examine the decision to attend sporting events, a fixed effects regression and the Tobit model were used to test the uncertainty of game outcomes and reference-dependent preferences with loss aversion. The estimated fans' demand for attending live football matches is represented by the logged attendance of 2,442 matches from the 2010/2011 to the 2017/2018 seasons of the 2. Bundesliga. Our findings indicate that fans prefer certain game outcomes over uncertain ones. In other words, reference-dependent preferences with loss aversion dominate the desire for close competition. We estimated our main model using various proxies of uncertainty as robustness checks, and the results confirmed our findings.

This study aims to analyze fans’ demand for live football matches in the German 2. Bundesliga, focusing on match-outcome uncertainty. To examine the decision to attend sporting events, a fixed effects regression and the Tobit model were used to test the uncertainty of game outcomes and reference-dependent preferences with loss aversion. The estimated fans’ demand for attending live football matches is represented by the logged attendance of 2,442 matches from the 2010/2011 to the 2017/2018 seasons of the 2. Bundesliga. Our findings indicate that fans prefer certain game outcomes over uncertain ones. In other words, reference-dependent preferences with loss aversion dominate the desire for close competition. We estimated our main model using various proxies of uncertainty as robustness checks, and the results confirmed our findings.

Hosting sport events is costly, but the positive impact of hosting sport events has not been studied well. We consider the promotion of physical activity, known as the trickle-down effect, to be a new dimension of this kind of impact. Using exogenous variations in promotion and relegation in the Bundesliga 1, we test the effect of the presence of a Bundesliga 1 club on local non-profit football club membership. Using German city-level annual non-profit sport club membership data from the metropolitan Rhine-Ruhr, we group cities with experience of either promotion or relegation as treatment cities and other cities as the comparison group. Difference-in-difference analyses show that promotion (using a strict definition of promotion) of local professional football clubs increases non-profit football club membership by 14% while relegation does not affect membership. The presence of Bundesliga 1 clubs in a city increases non-profit football club membership by 11%. Falsification tests support the idea that the impact of promotion on membership results in a net increase in membership.

While assessment of team-level marketing performance for a professional sport franchise is important for both the team marketer and the researcher to develop a marketing strategy and understand marketing performance, no evidence using a full set of teams for a long period of time currently exists. We propose that marketing performance can be estimated with a stochastic frontier model. Using twenty seasons of Major League Baseball (MLB) attendance data, we estimate the frontier attendance (i.e., the maximal attendance a team can reach) after controlling for factors unrelated to marketing, and we argue that the efficiency (i.e., the difference between the frontier and the actual attendance) represents the team's marketing performance. We also test whether our estimates capture marketing performance successfully by using the honeymoon and novelty effects, both of which are clearly shown in our estimates.

Some professional athletes still face monopsony power in labor markets, underscoring the importance of estimating players’ marginal revenue product to assess its effects. We introduce two new empirical approaches, spline revenue functions and fixed-effects stochastic production functions, into the standard Scully (1974) approach to marginal revenue product estimation and calculate Monopsony Exploitation Ratios (MERs) for position players in Major League Baseball over the 2001–2011 seasons. Estimates indicate that MERs are about 0.89 for rookie players, 0.75 for arbitration eligible players, and 0.21 for free agents. Recent collective bargaining agreements have reduced MERs for free agents, but had no effect on MERs for other players.

While assessment of team-level marketing performance for a professional sport franchise is important for both the team marketer and the researcher to develop a marketing strategy and understand marketing performance, no evidence using a full set of teams for a long period of time currently exists. We propose that marketing performance can be estimated with a stochastic frontier model. Using twenty seasons of Major League Baseball (MLB) attendance data, we estimate the frontier attendance (i.e., the maximal attendance a team can reach) after controlling for factors unrelated to marketing, and we argue that the efficiency (i.e., the difference between the frontier and the actual attendance) represents the team's marketing performance. We also test whether our estimates capture marketing performance successfully by using the honeymoon and novelty effects, both of which are clearly shown in our estimates.

While assessment of team-level marketing performance for a professional sport franchise is important for both the team marketer and the researcher to develop a marketing strategy and understand marketing performance, no evidence using a full set of teams for a long period of time currently exists. We propose that marketing performance can be estimated with a stochastic frontier model. Using twenty seasons of Major League Baseball (MLB) attendance data, we estimate the frontier attendance (i.e., the maximal attendance a team can reach) after controlling for factors unrelated to marketing, and we argue that the efficiency (i.e., the difference between the frontier and the actual attendance) represents the team’s marketing performance. We also test whether our estimates capture marketing performance successfully by using the honeymoon and novelty effects, both of which are clearly shown in our estimates.