Determinants of Pay in the NHL

Vincent, Claude; Eastman, Byron D.

doi:10.1177/1527002508327519

Cited by 31 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…His approach is to use a quantile regression model, which detects the subtleties of discrimination at different quantiles. Vincent and Eastman also employ quantile regression to examine the impact of performance on salary at different quantiles of the NHL wage distribution (Vincent and Eastman 2009). They claim that the standard conditional expectations model employed by OLS misses some important subtleties of the earnings determination in the NHL, as opposing effects at different quantiles may cancel each other out in a single mean conditional $500,000 $1,000,000 $1,500,000 $2,000,000 $2,500,000 $3,000,000 $3,500,000 $4,000,000…”

Section: Literature Reviewmentioning

confidence: 99%

Country of Origin Effects on the Average Annual Values of NHL Player Contracts

Fenn

Gerdes

Rothstein

2019

IJFS

View full text Add to dashboard Cite

Using data from 2005 to 2016, this paper examines if players in the National Hockey League (NHL) are being paid a positive differential for their services due to the competition from the Kontinental Hockey League (KHL) and the Swedish Hockey League (SHL). In order to control for performance, we use two different large datasets, (N = 4046) and (N = 1717). In keeping with the existing literature, we use lagged performance statistics and dummy variables to control for the type of NHL contract. The first dataset contains lagged career performance statistics, while the performance statistics are based on the statistics generated during the years under the player’s previous contract. Fixed effects least squares (FELS) and quantile regression results suggest that player production statistics, contract status, and country of origin are significant determinants of NHL player salaries.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Country of Origin Effects on the Average Annual Values of NHL Player Contracts

Fenn

Gerdes

Rothstein

2019

IJFS

View full text Add to dashboard Cite

show abstract

“…Quantile regressions, whether segregated into quartiles, quintiles or other grouping, allows for the effect of the independent variables to vary across the distribution, with the assumption that the conditional th segment of the dependent variable is a linear combination of the independent variables. There are several examples of quantile regression in the sports labor market, including Keefer (2013) and Vincent and Eastman (2009).…”

Section: A Modelmentioning

confidence: 99%

Compensation Discrimination for Wide Receivers: Applying Quantile Regression to the National Football League

Burnett¹

2013

J. Rev. Global Econ.

View full text Add to dashboard Cite

Keefer's recent article in the Journal of Sports Economics (2013) finds evidence of wage discrimination in the National Football League (NFL) market for linebackers. We examine the market for NFL wide receivers using similar techniques as Keefer, though we explore only rookies rather than all current players and wide receivers rather than linebackers. While we would expect to find stronger evidence of discrimination in the rookie market, as rookies are captured sellers, we find no pervasive pattern of pay discrimination by race in this market.

show abstract

“…Franck & Nüesch, 2012; Frick, 2011; Lehmann & Schulze, 2008; Lucifora & Simmons, 2003) and other professional team sports (e.g. Miceli & Huber, 2009; Vincent & Eastman, 2009; Wallace, 1988). Our findings reveal that relative grades (expert evaluations) and relative team wage bills (sports economists) are highly correlated and have a significant effect on relative points in separate estimations.…”

Section: Introductionmentioning

confidence: 99%

Football experts versus sports economists: Whose forecasts are better?

Frick

Wicker

2015

European Journal of Sport Science

View full text Add to dashboard Cite

Given the uncertainty of outcome in sport, predicting the outcome of sporting contests is a major topic in sport sciences. This study examines the accuracy of expert predictions in the German Bundesliga and compares their predictions to those of sports economists. Prior to the start of each season, a set of distinguished experts (head coaches and players) express their subjective evaluations of the teams in school grades. While experts may be driven by irrational sentiments and may therefore systematically over- or underestimate specific teams, sports economists use observable characteristics to predict season outcomes. The latter typically use team wage bills given the positive pay-performance relationship as well as other factors (average team age, tenure, appearances on national team, and attendance). Using data from 15 consecutive Bundesliga seasons, the predictive accuracy of expert evaluations and sports economists is analysed. The results of separate estimations show that relative grade and relative wage bill significantly affect relative points, while age, tenure, appearances, and attendance are insignificant. In a joint model, relative grade and relative wage bill are still statistically significant, suggesting that the two types of predictions are complements rather than substitutes. Consequently, football experts and sports economists seem to rely on completely different sources of information when making their predictions.

show abstract

Determinants of Pay in the NHL

Cited by 31 publications

References 14 publications

Country of Origin Effects on the Average Annual Values of NHL Player Contracts

Country of Origin Effects on the Average Annual Values of NHL Player Contracts

Compensation Discrimination for Wide Receivers: Applying Quantile Regression to the National Football League

Football experts versus sports economists: Whose forecasts are better?

Contact Info

Product

Resources

About