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This paper explores how a sports superstar's popularity aged by utilizing 28 years of Nielsen television viewer data for the Professional Golf Association's major events (i.e., the Masters, U.S. Open, PGA Championship, and the British Open; 1995–2022). Tiger Woods' major career has spanned this precise time frame, as his first major event was the 1995 Masters and his last major in which he made the cut was the 2022 Masters (at the time of this writing). Thus, we are able to specifically examine how this singular superstar has aged in terms of popularity over an extended time frame. Given that golf is an individual sport in which there are no externality effects from teammates that might confound the analysis, our current setting provides an ideal natural experiment where we can simultaneously account for superstar effects relating to participation, performance, and longevity. Our results suggest that Woods was most popular at the beginning of his career, and that, after controlling for productivity and other relevant factors, his popularity has subsequently waned. Even though Tiger Woods remains the most popular golfer in the world, his impact on viewership has continued to lessen as his career has progressed.

Research on third-party intervention into conflict has accelerated in recent years. Although some studies have explicitly assumed that third parties only value peace, recent theory has modeled parties to a conflict more flexibly. In addition, empirical results provide evidence that third-party motives are more complex than straightforward peacemaking. In particular, although the United Nations attempts peacemaking missions, evidence suggests that United Nations interventions prolong conflict. We sample the literature on interventions and offer directions for further research. On the empirical side, we suggest that third-party research should exploit recent applications of statistical modeling that unravel the complexity created by the fact that the decision to intervene in a conflict may depend on the same factors that contribute to the duration of the conflict. On the theoretical side, in contrast to previous studies, we suggest modeling the destruction that armed conflict causes as a choice variable.

While economists have previously noted that home field advantage is affected by crowd density, isolating this effect is difficult since crowd size is likely endogenous with team ability and game matchup. The COVID-19 pandemic has presented a unique natural experiment since local governments have introduced safety protocols that varies widely across the United States. These safety protocols have limited attendance in varying ways for live sporting events, including National Football League games. Given the differential (and exogenous) attendance restrictions, we were able to isolate three broad categories of attendance: 1) games without attendance restrictions (seasons 2016-2019), 2) games with limited in-person attendance, and 3) games without fans. We developed a model to predict the home team point differential, which allowed us to estimate home field advantage of these broad categories. We found that playing in partially full stadiums does not impact relative home team performance (compared to 2016-19 seasons). Conversely, we found that playing with no fans completely eliminates home field advantage. We also tested if fan density mattered in partial attendance game and found that attendance percentage does not statistically affect the home point differential. Hence, our results reveal that the presence of fans matters but the density of fans does not. Furthermore, we were able to compare these results with the 'predictions' offered by the betting market. We found that the betting market correctly predicted that games with partial attendance (due to social distancing) did not impact home field advantage in a statistically significant way and that home team performance would suffer in games played without attendance. Finally, we find evidence that the betting market exhibited a 'learning effect' since the market predicted an increasingly strong 'no fan' effect as the season progressed.

This paper develops a simple sequential-move game to characterize the endogeneity of third-party intervention in conflict. We show how a third party's 'intervention technology' interacts with the canonical 'conflict technologies' of two rival parties in affecting the sub-game perfect Nash equilibrium outcome. From the perspective of deterrence strategy, we find that it is more costly for a third party to support an ally to deter a challenger from attacking (i.e., to maintain peace or acquiescence), as compared to the alternative case when the third party supports the ally to gain a disputed territory by attacking (i.e., to create war), ceteris paribus. However, an optimally intervening third party can be either 'peace-making', 'peace-breaking', or neither depending on the characteristics of the conflict and the stakes the third party holds with each of the rival parties. [Copyright 2007 Elsevier B.V.]