Besides different measures of match-specific UOO, we also have detailed information on a variety of influence factors, such as entertainment and team quality proxies (short and long term), economic factors, and weather conditions.
From Equation (1), it is revealed that we adopt the standard approach in the sports economics literature with respect to the functional form for the match uncertainty measures (UOO): At first glance, it might seem as if we explicitly ruled out the possibility that the influence from UOO on match attendance demand varies with the quality of the teams involved as there is no interaction effect including team quality and UOO in Equation (1).
It should be clear that--whereas several measures of UOO are applied across different specifications (see also below) -the variables from the other regressor groups always remain the same.
that is, [beta] is the partial effect from UOO on attendance demand rather than attendance.
With respect to the implementation of our estimation procedure, it is important to point at the fact that the censored quantile regression (CQR) coefficient estimate, for example, on UOO, [^.
The different UOO model specifications are separated by two horizontal lines, where each model includes only one measure for the ex-ante degree of match uncertainty of outcome.
Based on data from professional German soccer in the period 1999-2004, our empirical analysis clearly reveals two important facts: First, match UOO is found to be only a "second-order" influence factor for attendance demand.