Economic Prediction of Medal Wins at the 2014 Winter (original) (raw)
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Economic Prediction of Medal Wins at the 2014 Winter Olympics
To the best of our knowledge nobody has attempted to elaborate on an economic model for predicting medal wins at Winter Olympics so far. This contrasts with Summer Olympics for which about thirty studies have estimated economic determinants of sporting performances. Namely, it has been empirically verified that the number of medals a country can make at Summer Olympics significantly depends on its population and GDP per inhabitant (Andreff, 2001). On the other hand, in the past decade, a number of papers have started to provide economic predictions of medal distribution per country at the next Olympic
International Journal of Economic Policy in Emerging Economies, 2013
Starting from an econometric model successfully used to explain and then predict the distribution of medal wins across nations at the Beijing Summer Olympics, a similar model is elaborated on with some different explanatory variables for estimating the determinants of medals won per nation at Winter Games. A Tobit estimation of the model based on data from 1964 to 2010 shows that GDP per capita, population, the endowment in ski and winter sports resorts, and a host country dummy are significant determinants of medal wins at Winter Olympics. Then the estimated model is used for predicting the sporting outcomes at the 2014 Sochi Games with a focus on Russia and China. The Russian team is expected to perform better than in Vancouver 2010 and to be ranked fourth behind the USA, Germany and Canada while the Chinese team would be ranked ninth, a performance doomed to improve in the future given China's swift economic development.
Who wins the Olympic Games: Economic resources and medal totals
Review of Economics and Statistics, 2004
This paper examines determinants of Olympic success at the country level. Does the U.S. win its fair share of Olympic medals? Why does China win 6% of the medals even though it has 1/5 of the world's population? We consider the role of population and economic resources in determining medal totals from 1960-1996. We also provide out of sample predictions for the 2000 Olympics in Sydney. * 100 Tuck Hall, Hanover, NH 03755,
Economic Determinants of Success in Olympic Games
turkish journal of sport and exercise, 2021
Sport economics is defined as the application of economic theories for analyzing of sport activities in which Olympic Games are the most famous ones. Activities in such games are measured by the number of medals that a certain country obtains. One way to predict medals winning by countries is to consider economic strength of the country in addition to the abilities of athletics. In this study, the effect of the most important economic factors on medals winning, such as Population, GDP per capita, and also hosting and the experience from past times in Olympics as explanatory variables are considered, which have not been reflected so far in the related studies. These variables are appropriate for the assessment of the potential of countries' success in Olympics. The data which is used, is in form of discrete data. Accordingly, Poisson Regression model is suitable for the purpose of this study. The period of examination is from 1992-2016 for evaluating the availability of having more medals in Olympics. The results, indicate a positive and significant relationship between economic factors, hosting and experiences in Olympic progressing. Since, countries expect from Olympics Games to derive more medals after the use of their resources, which have been allocated for this purpose, the study suggests that success in the Olympic need to consider the importance of economic factors.
Who Wins The Olympic Games: Economic Development and Medal Totals
SSRN Electronic Journal, 2000
This paper examines determinants of Olympic success at the country level. Does the U.S. win its fair share of Olympic medals? Why does China win 6% of the medals even though it has 1/5 of the world's population? We consider the role of population and economic development in determining medal totals from 1960-1996. We also provide out of sample predictions for the 2000 Olympics in Sydney. * 100 Tuck Hall, Hanover, NH 03755,
Forecasting national team medal totals at the Summer Olympic Games
International Journal of Forecasting, 2010
The paper reports the results of an exercise to forecast national team medal totals at the Beijing Olympic Games, 2008. Forecasts were released to the media before the competitions commenced. The starting point was an established statistical model based on a regression analysis of medal totals in earlier Games, with past performance and GDP among the principal covariates. However, we based our own forecasts on a model with additional regressors, including a measure of public spending on recreation. This adaptation is shown to have improved the forecasting performance. We also made subjective, judgemental adjustments before releasing our final public forecasts, and we demonstrate that this led to a further increase in accuracy. These final forecasts were successful in predicting the principal changes in medal shares relative to the 2004 Games, namely the surge in medals for China and Great Britain and the substantial fall in medals for Russia.
Economic evaluation of the Olympic Games
International Journal of Advance Research, Ideas and Innovations in Technology, 2019
The purpose of this paper and study i.e. to figure which key economic factors can help us explain country performance (medals) in the Olympics. The paper focuses on 3 key objectives, namely: To produce a list of possible key economic factors that can explain Olympic performance. To produce a simple Mathematical model based on these factors which could possibly predict the Olympic tally at a country level. To identify the degree to which these factors will influence Olympic performance the study has been carried out in a way to develop a conceptual model and to analyze the hypotheses. I have considered the Beijing Olympics 2008 Games, sampled with 83 countries and 946 medals for the study. Based on the findings of the study, a few recommendations have been made, which if implemented in developing countries like India, may contribute to improving the sport performance of these countries in the future.
An analysis of country medal shares in individual sports at the Olympics
European Sport Management Quarterly, 2016
Research question: Several studies report modelling relating countries' medal shares at the Olympics to population and per capita income (host status and political system are typically included as controls). This paper uses a similar model but disaggregates to the level of the individual sport to ask questions such as whether some sports have a less steep relationship with income levels than others and whether hosting effects are more pronounced in some sports than others. Research methods: Employing a random effects tobit model, data on medal shares are modelled across fifteen sports at six editions of the Games (1992-2012). Marginal effects, calculated for the case of cycling, illustrate how far many poor countries are from reasonable expectation of achieving medals. Results and findings: Income is influential on outcomes in all sports, its effects most pronounced in sports with substantial requirements for specific capital equipment; the distribution of medals is less unequal in sports practised in multi-sports venues. Gains from hosting vary in magnitude, performance tending to be elevated most in sports with outcomes strongly influenced by judges. Implications: For poorer countries, the paper identifies a small group of sports on which it would be most realistic to focus resources. For Games organisers, who must decide which sports to include, it provides information relevant to the goal of spreading success more evenly across countries. For example, proposals to exclude wrestling are shown to have been potentially harmful to medal prospects of poorer countries.