Race to the podium: separating and conjoining the car and driver in F1 racing

Abstract

ABSTRACT This paper provides a statistical estimate of the breakdown in race outcomes in Formula One races between the two most important inputs: driver skill and car technology. Financial data and racing results from the 2012–19 F1 seasons are used to estimate a combined driver and team fixed effects FGLS regression model for each season. Treating each season uniquely allows for the exclusion of weather and track specific variables common to other statistical studies of F1 racing. Our use of financial data provides an answer to the economic question of how should F1 teams allocate their scarce financial resources. The so-called “80-20” rule distinguishing team effects and driver effects is found to be a very rough approximation to the output shares for teams and drivers. A strong complementarity exists between driver skill and car technology that distorts the rule. The return to driver salaries and team budgets are both positive in term of race outcomes, but at diminishing rates.