Abstract
Age is often used in law and public policy as a low-cost proxy for competency, maturity, and ability. Age is also used in numerous sport (and non-sport) labor markets to determine workplace eligibility. We exploit the enactment of the women’s professional tennis minimum age rule (AR) in 1995 to estimate the effects of ARs on short-run and long-run labor market outcomes. We find very limited evidence that the AR has had any systematic beneficial effect on players’ career longevity or success. Our results suggest that sport governing bodies should (re-)evaluate the efficacy and necessity of “one size fits all” age eligibility rules.
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Notes
We note that Otis et al. (2006) was presented as a “review” as opposed to an original research article typically found in academic journals. As such, the discussion of estimation methodology and results appears truncated.
Our empirical methods allow us to control for player characteristics such as height, handedness, birth month, and socio-economic background. Their study does not appear to account for such variables.
Although not stated explicitly, it appears that the authors only analyzed data on performance from 1986 to 2004. In other words, they did not collect data on the entire careers of the players in their sample, just data on the years they used to select players into the sample.
We acknowledge that, since many players might not have been good enough as teenagers to play as many professional tournaments as they would have liked, the AR would not be a binding constraint for all players. However, given that the AR limits both WTA Tour and “minor league” ITF Circuit tournaments and even relatively weak players could play in many such ITF Circuit tournaments, the AR would likely limit the number of ranking-earning tournaments for teenagers with professional aspirations at all ability levels.
Injury-related data collection for all the players in our full sample was complicated by the relatively large number of obscure players whose injury information was unavailable in any publicly-available medium. As such, we were only able to collect injury data for sub-sample players. For coding purposes, the scope of one’s “injury” was broadly defined so as to capture all of the maladies McGuire (2007) identified as rationales for the AR. Accordingly, in addition to physical ailments, injuries included drug use and rehabilitation (e.g., Jennifer Capriati), personal problems (e.g., Mirjana Lucic), family issues (e.g., Jelena Dokic), and mental burnout (e.g., Justine Henin). For the avoidance of doubt, the 1993 on-court knife attack of Monica Seles was not coded as an injury given its extenuating circumstances and unforeseeable nature. Similarly, when Angelica Galvadon took an 18 month sabbatical from professional tennis in order to complete high school and Lindsey Lee-Waters stepped away from competition during and after her pregnancy, neither absence was coded as an injury.
Players unranked in either year are excluded since a majority of such players were never ranked until they were 20 or older and were unlikely to be affected by the AR. Of the 102 players in our full sample, seven were excluded on this basis.
The teenagers noted by McGuire (2007) and other more recent examples (e.g., Anna Kournikova, Anastasia Myskina, Mirjana Lucic, Jelena Dokic, and Alexandra Stevenson) thought to have career problems possibly due to starting professional tennis at too young an age experienced declines in performance or career cessation (temporary or permanent) well before their ninth year after making the top 50.
Results are also similar when we include years prior to the first year the player made the top 50 for the YRS RNK(9year) variable. The variables YRS 10(9year) and YRS 50(9year) are of course unaffected by whether we include those years.
We define age of retirement as age during the last year a player was ranked in our sample. If a player was ranked in 2009, her age of retirement would be her age that year. Since all players were at least 26 that year, any player ranked in 2009 would be coded zero for RET 25. We re-coded RET 25 to equal zero for Kimiko Date-Krumm, who retired at age 25 in 1996, but made a comeback in 2008 and earned a WTA Tour ranking in 2009.
We also examined models estimated on samples restricted to years in which the player was ranked or had been ranked in a previous season (to be sure her career had started), and was on or before her retirement age (as defined above), to account for players entering and exiting the sample at different times. Results are similar. We prefer to use the estimate from the less restricted sample, since age effects provide controls for these issues.
Non-linear models, such as probit or logit with random effects, are difficult to estimate in the presence of many age and year fixed effects.
Career is defined as the first year ranked in the top 50 and the subsequent 9 years.
For the short-run analysis, this variable is defined as best rank at ages other than 19 and 20, so that it is not endogenous.
Among our sub-sample of similarly precocious players more likely to be impacted by the AR, the AR coefficients are (non-significantly) positive in all three models, providing weak evidence that AR players earned worse mean rankings than non-AR players when young (RNK 19-20 ). For the avoidance of doubt, a “worse” ranking when dealing with ordinal data such as tennis rankings means a rank that is larger numerically (e.g. being ranked #75 is worse than being ranked #25), hence the weak evidence derived from AR coefficients that are positive.
For the avoidance of doubt, a negative coefficient for a dummy independent variable such as AR vis-à-vis our three cumulative ranking-based dependent variables would imply that AR players experienced worse career outcomes.
To investigate the role of precocity in professional tennis career outcomes, we also estimated all ranking-based models (full sample and sub-sample) with an independent variable equal to a player’s age when first ranked in the top 50 and found it to be a statistically significant predictor of success across every model. Such finding reinforces the importance of precocity and suggests that it is rare to find a “late bloomer” at the elite level of women’s professional tennis, even after the enactment of the AR in 1995.
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Acknowledgement
The authors would like to thank Marcel Battre, Kevin Thom, Andrew Nutting, Jeremy Arkes, Andrea Eagleman, Michelle Humowiecki, and conference participants at the Western Economics Association, Southern Economic Association, and Northern California Symposium on Statistics and Operations Research in Sports for helpful comments. Amanda Coble, Young Do Kim, and Jun Woo Kim provided excellent research assistance.
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Rodenberg, R.M., Stone, D.F. The Short and Long-Run Labor Market Effects of Age Eligibility Rules: Evidence from Women’s Professional Tennis. J Labor Res 32, 181–198 (2011). https://doi.org/10.1007/s12122-011-9108-7
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DOI: https://doi.org/10.1007/s12122-011-9108-7