Presentation Title

Determining Medal Counts by Country at the 2016 Rio Olympic Games

Start Date

November 2016

End Date

November 2016

Location

HUB 260

Type of Presentation

Oral Talk

Abstract

Using data for each Olympic Games from 1992 through 2016, we examine the relationship between athletic performance and country-level economic (and social) development. More specifically, we extend the empirical model of Pfau (2006), which is an extension of Bernand and Busse (2004), to consider additional determinants of countries’ medal score values. Additionally, while previous studies have examined only the winter games, we examine both the summer and winter games. The resulting econometric model and several variants of the model, that are employed to consider the robustness of our primary findings, are estimated using the Ordinary Least Squares and, when appropriate, Generalized Least Squares techniques. The results are, generally speaking, in line with the previous literature. Countries’ past performances, in terms of medal scores, are the single-most important predictor of future success. Even so, we find that measures of economic (and social) development (i.e., real GDP per capita and the UN Human Development Index), employed in separate estimations, are positively related to the medal score of the typical country. Using the results to estimate future medal counts suggests strong performances from the United States, which is predicted to narrowly win over Norway in 2018 PyeongChang Games and to win by a larger margin, with China placing second, at the 2020 Tokyo Games.

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Nov 12th, 11:15 AM Nov 12th, 11:30 AM

Determining Medal Counts by Country at the 2016 Rio Olympic Games

HUB 260

Using data for each Olympic Games from 1992 through 2016, we examine the relationship between athletic performance and country-level economic (and social) development. More specifically, we extend the empirical model of Pfau (2006), which is an extension of Bernand and Busse (2004), to consider additional determinants of countries’ medal score values. Additionally, while previous studies have examined only the winter games, we examine both the summer and winter games. The resulting econometric model and several variants of the model, that are employed to consider the robustness of our primary findings, are estimated using the Ordinary Least Squares and, when appropriate, Generalized Least Squares techniques. The results are, generally speaking, in line with the previous literature. Countries’ past performances, in terms of medal scores, are the single-most important predictor of future success. Even so, we find that measures of economic (and social) development (i.e., real GDP per capita and the UN Human Development Index), employed in separate estimations, are positively related to the medal score of the typical country. Using the results to estimate future medal counts suggests strong performances from the United States, which is predicted to narrowly win over Norway in 2018 PyeongChang Games and to win by a larger margin, with China placing second, at the 2020 Tokyo Games.