The impact of foreign players on international football performance

Transcription

1 MPRA Munch Personal RePEc Archve The mpact of foregn players on nternatonal football performance Orhan Karaca Ekonomst Magazne, Research Department October 008 Onlne at MPRA Paper No , posted 14. October :50 UTC

2 The mpact of foregn players on nternatonal football performance Orhan Karaca * Ekonomst Magazne, Research Department, Hurryet Medya Towers, 341, Gunesl, Istanbul, Turkey Abstract I nvestgate the mpact of foregn players on nternatonal football performance of club teams and natonal teams n ths paper. My emprcal fndngs show that foregn players have a postve effect on club teams nternatonal performance. Howewer, foregn players don t have any effect on performance of natonal teams. Keywords: Football; Foregn players Jel classfcaton: L83 1. Introducton Football 1 s one of the most popular sports n the world. It has gradually become a huge ndustry by lve matches, sponsorshps and lcensed products ncome. Amng to gan larger slces from the cake, the clubs are searchng for strengthenng ther teams to become more successful especally n the nternatonal contests. Therefore, doors are openng more and more to the foregn players. However, ths stuaton causes a bg debate n the world of football. It s accepted that soarng number of foregners has a postve mpact on the success of these teams. On the other hand, t s clamed that f ths number goes on ncreasng, natve players are becomng dscluded from the matches more and ther absence would have a very negatve reflecton on natonal team. Ths pont of vew has a wde acceptance throughout many countres and snce restrctons are appled on the number of foregn players. The am of ths paper s to nvestgate the mpact of foregn players on nternatonal football performance of club teams and natonal teams. To my knowledge, t s the frst to examne ths ssue. My man fndngs are: () foregn players have a postve effect on nternatonal performance of club teams; () foregn players don t have any effect on natonal teams performance. The rest of the paper s organzed as follows. Secton descrbes the model and data. Secton 3 presents the emprcal results. Secton 4 concludes the paper. * E-mal: okaraca@ekonomst.com.tr. 1 The term football s used meanng Assocaton Football n ths paper. Assocaton Football s known as soccer n some countres.

3 . Model and data In ths paper, I use a modfed verson of the model presented n Hoffmann et al. (00b). The specfcatons of model, for club teams and natonal teams, are: UEFA = α + β POP + χ GNI + δ ( TEMP 14) + η PFP + ε (1) FIFA = α + β POP + χ GNI + δ ( TEMP 14) + η PFP + ε () Defntons of the varables and sources of data are n Table 1. There are 36 countres n the sample, largely dctated by avalablty of the data on foregn players. The data on foregn players was constructed n the followng way. From European clubs and squads database, I collected players numbers and natonaltes n frst football leagues for 36 countres durng perod. Then, I calculated percentage of foregn players for perod average. To measure performance of natonal teams I use FIFA/Coca-Cola World Rankng ponts. These are calculated on a monthly bass usng the performance of a gven country s natonal team n all nternatonal matches over the prevous four years. Ths s also the measure used by Houston and Wlson (00), Hoffmann et al. (00b) and Hoffmann et al. (006). UEFA Country Rankng ponts was used to measure nternatonal performance of club teams. These are calculated on a yearly bass usng the performance of a gven country s club teams n the European Cups over the prevous fve years. In addton to these varables, I used populaton, per capta GNI and yearly average temperature data of each country. More populous countres can draw on a greater pool of potental football talent and therefore are expected to be relatvely more successful at ths sport. Hgher ncome s assocated wth the avalablty of better sportng nfrastructure as well as lesure tme for potental athletes. Yearly average temperature concerns the countres geographcal settng. Temperate clmates provde a more conducve geographcal settng for development of outdoor actvtes whch may promote sports success. Hoffmann et al. (00a) and Hoffmann et al. (00b) also found sgnfcant relatonshps between average temperature and sports success both n the Olympc summer games and nternatonal football. Followng Hoffmann et al. (00b), the varable was specfed as the devaton from an deal average annual temperature of 14 C. 3. Emprcal results Table shows regresson results for club teams nternatonal performance. I estmate three dfferent specfcatons n ths part of analyss. In the frst specfcaton, I regress UEFA Country Rankng ponts on the percentage of foregn players. The coeffcent on the percentage of foregn players s postve and statstcally sgnfcant. In the second A lst of the sample countres s: Austra, Belarus, Belgum, Bosna and Herzegovna, Croata, Cyprus, Czech Republc, Denmark, England, Estona, Fnland, France, Georga, Germany, Greece, Hungary, Iceland, Israel, Italy, Latva, Lthuana, Malta, Netherlands, Northern Ireland, Norway, Poland, Portugal, Romana, Russan Federaton, Scotland, Slovena, Span, Sweden, Swtzerland, Turkey and Ukrane.

4 specfcaton I nclude populaton, per capta GNI and yearly average temperature as control varables. Howewer, n ths specfcaton the coeffcent on per capta GNI s statstcally nsgnfcant. Therefore, I drop per capta GNI n the thrd specfcaton. In ths specfcaton, the coeffcent on the percentage of foregn players remans postve and statstcally sgnfcant. Ths ndcates that countres wth a hgher number of foregn player of club teams tend to be more succesfull n the European Cups. Table 3 presents regresson results for natonal teams performance. I estmate three dfferent specfcatons n ths part of analyss, too. At frst, I regress FIFA/Coca-Cola Rankng ponts on the percentage of foregn players. In ths specfcaton, the coeffcent on the percentage of foregn players s postve and statstcally sgnfcant. In the second specfcaton, I nclude populaton, per capta GNI and yearly average temperature as ndependent varables. The coeffcent on per capta GNI s statstcally nsgnfcant n ths specfcaton. Therefore, I drop per capta GNI n the followng specfcaton. The coeffcent on the percentage of foregn players s postve but statstcally nsgnfcant n thrd specfcaton. 4. Concluson In ths paper I have nvestgated the mpact of foregn players n frst leagues on nternatonal football performance of club teams and natonal teams. My emprcal fndngs show that foregn players have a postve effect on nternatonal performance of club teams. Howewer, foregn players don t have any effect on natonal teams performance. When FIFA/Coca-Cola rankng ponts are regressed on the percentage of foregn players alone, the coeffcent of ndependent varable s postve and statstcally sgnfcant. Howewer, when control varables are ncluded n the analyss, the coeffcent on the percentage of foregn players s statstcally nsgnfcant. References Hoffmann, R., L.C. Gng and B. Ramasamy, 00a, Publc polcy and olympc success, Appled Economcs Letters 9, Hoffmann, R., L.C. Gng and B. Ramasamy, 00b, The soco-economc determnants of nternatonal football performance, Journal of Appled Economcs 5, Hoffmann, R., L.C. Gng, V. Matheson and B. Ramasamy, 006, Internatonal women s football and gender nequalty, Appled Economcs Letters 13, Houston, R.G. and D.P. Wlson, 00, Income, lesure and profcency: an economc study of football performance, Appled Economcs Letters 9,

5 Table 1 Descrpton of varables n regressons Varable Descrpton UEFA UEFA Country Rankng ponts (007). Data source: FIFA FIFA/Coca-Cola World Rankng ponts (December 007). Data source: POP Country s share of world populaton (003, %). Data source: and (for England, Northern Ireland and Scotland). GNI TEMP GNI per capta (003, USD). Data source: and (for England, Northern Ireland and Scotland). Average annual Celsus temperature n country s captal. Data source: PFP Percentage of foregn players n frst football league of country ( average, %) Data source: and author s calculaton. ε Error term α, β, χ, δ, η Parameters

6 Table Regresson results for club teams nternatonal performance Varable (1) () (3) Constant (0.059) (1.857)*** (1.797)*** POP (.833)* (.559)** GNI (1.18) TEMP ( 14) (-.645)** (-.365)** PFP (5.364)* (1.891)*** (3.448)* R-squared Adjusted R-squared Dependent varable: UEFA. Number of observatons s 36. t statstcs are n parantheses. * sgnfcant at 1%, ** sgnfcant at 5%, *** sgnfcant at 10%

7 Table 3 Regresson results for natonal teams performance Varable (1) () (3) Constant (4.959)* (5.543)* (5.388)* POP (.34)** (1.860)*** GNI (1.473) TEMP ( 14) (-.437)** (-.009)*** PFP (.813)* (-0.034) (1.176) R-squared Adjusted R-squared Dependent varable: FIFA. Number of observatons s 36. t statstcs are n parantheses. * sgnfcant at 1%, ** sgnfcant at 5%, *** sgnfcant at 10%