Abstract
It is difficult to find another sport which makes so many people travel so many kilometres around the world every year more than Formula One does. However, when focusing on three major dimensions of this sport—the number of races, drivers, and constructors since 1950—we realize that only a few countries have had the experience of hosting Formula One races, of being the birth countries of Formula One drivers, and of being the headquarters of Formula One constructors. In this chapter, we are going to explain this diversity by using (ordinary) least squares regressions and binary outcome models. We found a consistent determinant for a country falling in love with Formula One: the share of national income allocated to R&D expenses. Therefore, if you rule a country and you want to rank it as a major power in motorsports in the medium term, you should pay more attention to current R&D. Other dimensions have also been found to affect Formula One numbers around the world. Let’s check them.
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Notes
- 1.
German racers entered in the season of 1951 and the Netherlands hosted its first Formula One race in 1952.
- 2.
These twenty-two countries are Albania, Armenia, Azerbaijan, Bolivia, Bulgaria, Cameroon, Congo Dem. Republic, Costa Rica, Cuba, Ecuador, Egypt, Guatemala, Honduras, Hong Kong, Latvia, Lithuania, Norway, Oman, Qatar, Peru, Philippines, and Saudi Arabia.
- 3.
We also tested for multicollinearity and endogeneity of R&D and real GDP per capita without serious threats. (More details are available upon request.)
- 4.
The p-value for accepting the hypothesis that the mean value of government budget surpluses for the countries without Formula One champions is higher than the mean value of government budget surpluses for the countries with Formula One champions is less than 0.001 in our sample of data.
- 5.
I remember that the odds of a successful event are equal to the ratio of the probability of success over the probability of failure. Imagine that the probability of a successful event is 80% and the probability of failure is 20%. The odds of success are 4. Now assume that an ulterior factor is observed changing the probability of success to 90% and the probability of failure to 10%. The new odds of success are 9. So, the ulterior factor increased the odds of success by 125%. Therefore, our estimates also show that R&D significantly increases the probability of a country having Formula One races, champions and constructors.
- 6.
We used this five-year lag for two major reasons. First, as observed in the chapter titled ‘The Oil in the Engines’, most sports cycles in motorsports run for four or five years (half the time of a Concorde Agreement in Formula One, technological cycles of engine upgrades, etc. The second reason relates to the intention of avoiding biases because of short-term impacts. Therefore, using a five-year lag allows the researchers to understand the influence of a medium- and long-term cycle in the current outputs (Mourão, 2015).
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Mourão, P. (2017). The Political Economy of Formula One. In: The Economics of Motorsports. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-60249-7_7
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DOI: https://doi.org/10.1057/978-1-137-60249-7_7
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