Hantao Liu

Junle Wang

Judith Redi

Patrick Le Callet

Ingrid Heynderickx

AN EFFICIENT NO-REFERENCE METRIC FOR PERCEIVED BLUR

Keywords: Image quality assessment, objective metric, perceived blur, edge, neural network 0

This paper presents an efficient no-reference metric that quantifies perceived image quality induced by blur. Instead of explicitly simulating the human visual perception of blur, it calculates the local edge blur in a cost-effective way, and applies an adaptive neural network to empirically learn the highly nonlinear relationship between the local values and the overall image quality. Evaluation of the proposed metric using the LIVE blur database shows its high prediction accuracy at a largely reduced computational cost. To further validate the performance of the blur metric on its robustness against different image content, two additional quality perception experiments were conducted: one with highly textured natural images and one with images with an intentionally blurred background 1 . Experimental results demonstrate that the proposed blur metric is promising for real-world applications both in terms of computational efficiency and practical reliability.

INTRODUCTION

Blur is one of the important attributes in image quality assessment [START_REF] Wang | Modern Image Quality Assessment[END_REF]. Developing an objective metric, which automatically quantifies perceived blur, is of fundamental importance to a broad range of applications, such as the optimization of auto-focus systems, super-resolution techniques, and sharpness enhancement in displays. In many real-world applications, there is no access to the distortion-free reference image, thus these objective metrics need to be of the no-reference (NR) type. This implies that the assessment of blur is based on the distorted image only. Achieving a NR metric that reliably predicts the extent to which humans perceive blur, while being computationally efficient for real-time applications, is still challenging. 1 The subjective data and the implementation of the metric are available on the web-site: http://mmi.tudelft.nl/iqlab/index.html Existing blur metrics are formulated either in the spatial domain or in the frequency transform domain. The metrics implemented in the transform domain (see e.g. [START_REF] Marichal | Blur determination in the compressed domain using DCT information[END_REF]- [START_REF] Hassen | No-reference image sharpness assessment based on local phase coherence measurement[END_REF]) usually involve a rather complex calculation of energy falloff in the DCT or wavelet transform domain. Moreover, some metrics require the access to the encoding parameters, which are, however, not always available in practical applications. A blur metric defined in the spatial domain generally relies on measuring the spread of edges in an image (see e.g. [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF]- [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF]). Perhaps, the simplest and most well-known edge-based blur metric is the one proposed in [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF], which estimates the overall blur annoyance by simply calculating the averaged local edge width. It, however, shows limitations in predicting perceived blur, partly due to its lack of including aspects of the human visual system (HVS). To improve the reliability of a blur metric, researchers investigated explicit simulation of the way human beings perceive blur (see e.g. [START_REF] Liang | A noreference perceptual blur metric using histogram of gradient profile sharpness[END_REF] and [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF]). The metric in [START_REF] Liang | A noreference perceptual blur metric using histogram of gradient profile sharpness[END_REF] refines the calculation of local blur by adjusting the edge detection and by adding an existing model for masking by the HVS. In [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF], a more dedicated human perception model of JNB (Just Noticeable Blur) is integrated in a blur metric. Both metrics in [START_REF] Liang | A noreference perceptual blur metric using histogram of gradient profile sharpness[END_REF] and [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF] are claimed to be more consistent with subjective data, but they heavily rely on the sophisticated and expensive modeling of the HVS. A known approach to avoid the explicit simulation of the assessment of overall quality is the use of a neural network (NN) (see e.g. [START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF]- [START_REF] Babu | No-reference JPEG-image quality assessment using GAP-RBF[END_REF]). However, these approaches usually start from the selection of active features from a set of generic image characteristics, a process that is rather ad hoc and computationally extensive.

In this paper, we propose a novel blur metric that combines the advantages of two approaches, i.e. the dedicated calculation of the local edge blur in the spatial domain, and the use of a NN to yield overall quality resulting from blur. The proposed metric is validated using the LIVE blur database, and is compared against alternatives existing in literature. Two additional subjective experiments for perceived quality induced by blur were conducted: one with highly textured, natural images and one with images having an intentionally blurred background. The resulting subjective data are highly beneficial to evaluate the performance of blur metrics for larger variations in image content.

PROPOSED NR BLUR METRIC

The schematic overview of the proposed NR blur metric is shown in Figure 1. It consists of two components: first, extraction of the features effectively describing the local edge blur, and second, the use of an adaptive NN to learn the highly nonlinear relationship between the dedicated features and the overall quality ratings. After appropriate training with subjective data, the NN yields a model that at run-time calculates the perceived quality from the extracted features without considerable computational effort. Details of the implementation are explained below.

Feature Extraction

Local Edge Blur Estimation

Measuring the smoothing or smearing effect on strong edges has been proved to be an effective approach to approximate perceived blur in an image [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF]- [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF]. To detect strong edges literature offers a wide variety of techniques (e.g. [START_REF] Liu | A No-Reference Metric for Perceived Ringing Artifacts in Images[END_REF] and its references). As already mentioned in [START_REF] Liu | Issues in the design of a no-reference metric for perceived blur[END_REF], an advanced edge detection method would be beneficial for improving the robustness of local edge blur estimation, but at the expense of computational efficiency. In this paper, we use a straightforward Sobel edge detector resulting in a gradient image, mainly to limit the metric s complexity. The location of the strong edges is then extracted applying a threshold to this gradient image (as such removing noise and insignificant edges). The threshold value is automatically set depending on the image content (e.g. using the mean of the squared gradient magnitude over the image).

Instead of calculating the distance between the start and end position of an edge (as described in [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF]), we propose to locally define edge blur in the gradient domain as the gradient energy of the edge related to its surrounding content within a limited extent. When the luminance channel of an image of M×N (height×width) pixels is denoted as I(i, j) for iΓ [1, M], jΓ [1, N], the local edge blur L blur-h along the horizontal direction is quantified as:

L blur-h (i, j)= å ¹ - = + 0 , ,..., ) , ( 2 1
) , (

x n n x h h x j i G n j i G (i, j) Γ {strong edges}(1)
where G h (i, j) indicates the gradient map along the horizontal direction, and is computed as:

G h (i, j)= ] 1 , 1 [ ) , ( ) 1 , ( - Î - + N j j i I j i I ( 2
)
and n determines the size of the template used to describe the local content. The size is determined as a balance between collecting sufficient information of the local content and avoiding noise from content too far away (i.e. n=3 in our experiments). L blur-v , i.e. the local blur in the vertical direction, can be calculated similarly. The lower the value of L blur-h and L blur-v , the larger the distortion of the blur artifact is. Figure 2 explains the reasoning behind the proposed approach of using gradient energy to detect blur.

Global Descriptor

Direct application of all extracted values of local edge blur as input to a NN is problematic, since the dimensionality of these values is in general too large and varies with image content, and as such inappropriate for the network in terms of training. First, high dimensionality of the input might introduce noise and redundancies, with the consequent risk of over-fitting. Second, the architecture of a NN has to be fixed prior the training, therefore a varying number of input is not allowed. In this paper, the statistical description of an image feature as proposed in [START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF] and [START_REF] Redi | Color Distribution Information for the Reduced-Reference Assessment of Perceived Image Quality[END_REF]

{ ; { Î a j a ú û ù ê ë é + = 2 1 100 a j a F N (3)

NR Quality Estimator Based on a Neural Network

Computational intelligence tools are known for their ability of dealing with highly complex modeling problem. In particular, theory proves that feed-forward neural networks embedding a sigmoidal nonlinearity can support arbitrary mappings [START_REF] Hornik | Multilayered feedforward networks are universal approximators[END_REF]. In this paper, a feed-forward NN is employed to map the extracted feature vector describing the local edge blur into the associated rating of perceived quality. The implementation of this NN is already described in more detail in [START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF] and [START_REF] Redi | Color Distribution Information for the Reduced-Reference Assessment of Perceived Image Quality[END_REF], and is only briefly repeated here.

A Circular Back Propagation (CBP) [START_REF] Ridella | Circular backpropagation networks for classification[END_REF] network improves the conventional MultiLayer Perceptron (MLP) [START_REF] Rumelhart | Parallel distributed processing[END_REF] paradigm by adding one more input value, which is the sum of the squared values of all the network inputs (see Figure 1). The quadratic term boosts the network s representation ability without affecting the fruitful properties of an MLP structure.

The CBP architecture can be described as follows. For an input stimulus vector x={x 1 , , x ni }, the input layer connects the n i values to each of the n h neurons of a hidden layer. The j-th hidden neuron performs a nonlinear transformation of a weighted combination of the input values with coefficients ( weights ) w j,i (j=1, , n h , and i=1, , n i ):

) ( 1 2 1 , 1 , 0 , å å = + = + × + = i i i n i i n j n i i i j j j x w x w w sigm a (4)
where sigm(z)=(1+e -z ) -1 , w j,0 is a bias term, and a j is the neuron activation. The output layer provides the actual network response, y:

) ( 1 0 å = × + = h n j j j a w w sigm y ( 5
)
For a fixed architecture (i.e. n h is fixed empirically before the training, see [START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF] and [START_REF] Redi | Color Distribution Information for the Reduced-Reference Assessment of Perceived Image Quality[END_REF]), the CBP network is trained to optimize the desired input-output mapping, minimizing a cost function which measures the mean squared error between the actual NN output and the expected reference output (i.e. the MOS) for a sample of training patterns.

PSYCHOVISUAL EXPERIMENTS

A sub-set of the LIVE database comprising Gaussian blurred images [START_REF] Sheikh | LIVE Image Quality Assessment Database Release 2[END_REF] has been extensively adopted to validate blur metrics. It contains twenty-nine high-quality colored source images that reflect diversity in image content. These source images are filtered using a circularsymmetric 2-D Gaussian kernel of standard deviation B , ranging from 0.42 to 15 pixels, which results in a set of 174 stimuli (including the source images). Since the LIVE database is limited in its amount of demanding images, we performed two additional quality perception experiments. For example, the LIVE database includes only two source images with distinct foreground objects against a rather homogeneous background, as illustrated in Figure 3. In addition, also the amount of highly textured images is limited in the LIVE database. Evaluating how well a blur metric is able to handle these more demanding images is valuable for various applications; in particular the evaluation of images with a distinct foreground object against a homogeneous background is relevant for professional photography. Hence, we propose to extend the evaluation of the robustness of blur metrics with more image content. To that end, we make the data of two additional experiments of perceived quality resulting from blur available: one experiment used natural images of highly textured content, and the second experiment used images with an intentionally blurred background. Fig. 3. The two source images of the LIVE database [START_REF] Sheikh | LIVE Image Quality Assessment Database Release 2[END_REF] that have a distinct foreground object against a background.

Highly Textured Images (HTI) Database

The first quality perception experiment was conducted at the A University. A set of 12 images with highly textured content, as illustrated in Figure 4, was used as source material. These source images were high-quality colored images of size 512×768 (height×width) pixels. They were blurred in the same way and with the same range of B as the images of the LIVE database. Since each source image was blurred at five different levels, we obtained a test database of 72 stimuli (including the source images). The stimuli were displayed on a Dell 24 LCD screen with a native resolution of 1920×1200 pixels. The experiment was conducted in a standard office environment and the viewing distance was approximately 70cm. Eighteen participants, being ten males and eight females, were recruited for the experiment. A single-stimulus (SS) image quality assessment methodology as described in [START_REF] Redi | Comparing subjective image quality measurement methods for the creation of public databases[END_REF] was used and the raw data were processed according to the method described in [START_REF] Liu | A No-Reference Metric for Perceived Ringing Artifacts in Images[END_REF] to produce the mean opinion scores (MOS). The second quality perception experiment was conducted at the B University. A new set of 12 images having an intentionally blurred background, as illustrated in Figure 5, was extracted from [START_REF] Martin | A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics[END_REF]. Also these images were colored, and they had a size of 321×481 (height×width) pixels. Their background was blurred showing an obvious effect of depth of field. Since also these 12 images were blurred with the same five levels of B , again a database of 72 stimuli was obtained. The stimuli were displayed on a Samsung 22 LCD screen with a resolution of 1680×1050. They were viewed in a darkened room at a distance of approximately 60cm. Eighteen subjects participated in this experiment. They were requested to assess the overall image quality using again the single-stimulus (SS) image quality assessment methodology as described in [START_REF] Redi | Comparing subjective image quality measurement methods for the creation of public databases[END_REF]. The raw data were processed towards the MOS in the same way as for the HTI database.

Database of the Intentionally Blurred Background Images (IBBI)

EVALUATION OF METRIC PERFORMANCE

Performance Evaluation of the Proposed Metric

To fairly evaluate the performance of the proposed NR blur metric, a K-fold cross-validation method [START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF] was adopted. It randomized the statistical design problem by repeatedly splitting the available data into a training set and a test set. The source images were divided into several (i.e. six for the LIVE database and four for the HTI/IBBI database) groups. The entire procedure included six different trials for the LIVE database and four for the HTI/IBBI database. For each trial (hereafter referred to as run ) five/three (for the LIVE database and HTI/IBBI databases, respectively) groups of source images were used for training and the remaining one group of source images was used for testing. In our experiments, for each image, a vector containing eleven percentiles of the distribution of the local blur features was calculated as the input to the NN, which was equipped with three hidden neurons (i.e. n h =3).

The performance of our metric was quantified by the Pearson linear correlation coefficient (CC) and the root mean squared error (RMSE) (note: the scores are normalized to the scale [START_REF] Wang | Modern Image Quality Assessment[END_REF][START_REF] Babu | No-reference JPEG-image quality assessment using GAP-RBF[END_REF] before the calculation of the RMSE) between the subjective quality ratings (the MOS) and the predictions of the metric. Figure 6 illustrates the scatter plot of the MOS versus the quality prediction for the test images of the LIVE, HTI and IBBI databases, respectively. The corresponding CC and RMSE values are listed in Table 1. Both the figure and the table show that our proposed metric consistently results in a high prediction performance for all runs of each database. Since the performance for the more demanding images of the HTI/IBBI databases is largely comparable to the performance for the images of the LIVE database, our proposed NR blur metric demonstrate its robustness against a large variation in image content. To make an even more critical evaluation of our metric, we trained it with one database, and tested it with the other two databases (i.e. referred to as cross database evaluation). Table 2 lists the corresponding CC values. Our metric indeed demonstrates its promising performance; e.g. when training it with the limited HTI/IBBI databases, it still yields a high CC value (over 0.9) on the LIVE database.

Comparison to Alternative Metrics

In the image quality community, researchers are accustomed to compare the performance of their metric to that of alternatives available in literature. This allows these researchers to better understand the strengths and weaknesses of all metrics. For practical reasons the comparison of our proposed metric to alternative NR blur metrics is limited to the metric described in [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF] (hereafter referred to as NRPB) and the one described in [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF] (hereafter referred to as JNBM). Table 3 lists the performance of these metrics in terms of Pearson correlation coefficient.

In order to check whether the numerical differences in metric performance are statistically significant or not, a variance-based hypothesis test was conducted. It is based on the residuals between the quality predicted by the blur metric and the MOS (hereafter referred to as BM-MOS residuals) [START_REF] Vqeg | Final report from the video quality experts group on the validation of objective models of video quality assessment, phase II[END_REF]. The results of the statistical significance tests are presented in Table 4, whereas the results of the Gaussianity tests are given in Table 5. It should, however, be noted that statistical significance testing is not straightforward, and the conclusions drawn from it largely depend e.g. on the number of sample points, on the selection of the confidence criterion, and on the assumption of Gaussianity of the residuals.

The NRPB metric is simple, but its performance is limited as compared to our proposed metric, as can be seen from Table 3. The lower performance might be a direct consequence of the fact that the NRPB simply maps the averaged local blur to the quality scores with a nonlinear transformation only. Our proposed metric clearly outperforms NRPB, yet without introducing additional computational cost. Our metric also exhibits a better performance than the JNBM metric. In addition, since the latter contains sophisticated modeling of the HVS, our proposed metric has its advantages in terms of computational complexity.

CONCLUSIONS

In this paper, we present an efficient NR metric for the assessment of perceived image quality induced by blur. It calculates local edge blur in a computationally inexpensive way, and leaves the simulation of the HVS for the perceived overall quality to an adaptive neural network. The proposed metric is validated with the sub-set of blur images of the LIVE database and with the content of two newly created databases of demanding images. The performance of our metric is compared to state-of-the-art alternatives in the literature and shows to be highly consistent with subjective data at a largely reduced computational complexity. Combined with its practical reliability and computational efficiency, our metric is a good alternative for real-time implementation.

Table 3. Performance comparison in terms of CC between our proposed metric and state-of-the-art NR blur metrics (a nonlinear regression (see [START_REF] Vqeg | Final report from the video quality experts group on the validation of objective models of video quality assessment, phase II[END_REF]) is applied to NRPB [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF] and JNBM [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF]).

NR Blur Metric LIVE (174) HTI (72) IBBI (72) NRPB [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF] 0.8959 0.9413 0.9136 JNBM [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF] 0.8425 0.9490 0.9238 Proposed 0.9633 0.9840 0.9733 Table 4. Matrix representing the results of the statistical significance tests based on BM-MOS residuals. Each entry in the table is a codeword consisting of three symbols. The position of the symbol in the codeword represents the databases (from left to right): LIVE, HTI and IBBI. Each symbol gives the result of the hypothesis test: 1 means that the blur metric for the row is statistically significantly better that the blur metric for the column, 0 means that it is statistically significantly worse, andmeans that there is no difference.

NRPB [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF] JNBM [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF] Proposed NRPB [START_REF] Marziliano | A no-reference perceptual blur metric[END_REF] ---0--0--JNBM [START_REF] Ferzli | A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)[END_REF] 1-----000 Proposed 1--111 ---Table 5. Gaussianity of the BM-MOS residuals: 1 means that the residuals can be assumed to have a normal distribution since the Kurtosis lies between 2 and 4.

Fig. 1 .

 1 Fig. 1. Schematic overview of the proposed NR blur metric.

Fig. 2 .

 2 Fig. 2. Illustration of the calculation of local edge blur: (a) image patch extracted from an image (i.e. img86 of the LIVE blur database [15]) [the red dot indicates the location of the detected edge at (252, 101) in this image, and the template indicates the area in which the local blur is calculated for this edge], (b) the intensity profile over the pixels within the template of (a), (c) the gradient profile of (b), (d) the same image patch of a blurred version of image (a) i.e. img139 of the LIVE database, (e) the intensity profile over the pixels within the template of (d), and (f) the gradient profile of (e).

Fig. 4 .

 4 Fig. 4. Source images of the HTI database.

Fig. 5 .

 5 Fig. 5. Source images of the IBBI database.

Fig. 6 .

 6 Performance of the proposed NR blur metric: (a) (b) and (c) are the scatter plot of the MOS versus the proposed metric of all runs for the LIVE, HTI and IBBI databases, respectively.

  is adopted. It unifies the local blur values to a single vector using percentiles. Having computed the local values f i (i=1, , N F , and N F is the total number of the local values) per image (i.e. L blur calculated in both the horizontal and vertical direction on the detected edges), these values are sorted in ascending order of magnitude. The outline of the obtained distribution is then expressed in a global descriptor f by taking 11 of its percentiles ナ:

	f=	, 10 , 0	, 30 , 20	}}; 100 , 90 , 80 , 70 , 60 , 50 , 40

Table 1 .

 1 Performance evaluation of the proposed NR blur metric (based on the K-fold cross-validation method used in[START_REF] Gastaldo | Neural networks for the no-reference assessment of perceived quality[END_REF]). LIVE, HTI and IBBI refer to each of the databases. CC and RMSE refer to the Pearson linear correlation coefficient and the root-meansquare error, respectively.

		LIVE	HTI	IBBI
		CC	RMSE	CC	RMSE	CC	RMSE
	RUN1	0.9468	1.0256	0.9896	0.4732	0.9596	1.0460
	RUN2	0.9597	0.8147	0.9822	0.5723	0.9743	0.6862
	RUN3	0.9554	1.2555	0.9825	0.5749	0.9780	0.9872
	RUN4	0.9804	0.5234	0.9819	0.6489	0.9812	0.6229
	RUN5	0.9515	0.6766
	RUN6	0.9857	0.4536
	MEAN	0.9633	0.8216	0.9840	0.5673	0.9733	0.8356

Table 2 .

 2 Cross database evaluation of the proposed NR blur metric (based on training with one database and testing on the other two).

	Training Set	LIVE (174)	Test Set HTI (72)	IBBI (72)
	LIVE (174)		0.9770	0.9652
	HTI (72)	0.9394		0.9758
	IBBI (72)	0.9028	0.9602


Wladimir Andreff

WHY TAX INTERNATIONAL ATHLETE MIGRATION?The 'Coubertobin' tax in a context of financial crisis

International athlete migration is not a new economic fact. English football spread to France in the late XIXth century simply British players moved to Paris and created a football club there, the so-called Racing Club. As early as in the 1950s, the Argentine football player Di Stefano, the Hungarian Puskas and the French Kopa were playing together in the Real Madrid squad..More recently, the growth of international athlete migration has increased significantly in the past fifteen years due to economic globalization and a change in regulation of European professional sports (Andreff, 2006a).

. The global market for all sporting goods and services, in 2004, was assessed to be in the range of Euro 550-600billion. The global market for football is valued at Euro 250 billion. The market for all sporting goods is valued at about Euro 150 billion. The value of broadcasting rights related to sport events is estimated at Euro 60 billion while the global market for sports sponsorship is nearly Euro 18 billion. In 2006, the global market for doping was assessed at Euro 6 billion. Even if these figuresare not exact , the trend towards globalization of sport business is crystal clear. By the same token, the market for high-level sporting talents has also globalized. It is a labour market in which professional players and other highly talented athletes are internationally transferredfrom a club in one country to a club located abroad.

International transfers of football players skyrocketed in this global labour market since it was entirely de-regulated in 1995. Then, this deregulation has affected international labour market

in other professional sports and, finally, in all high level sport. Football recently has become the most investigated global market in the sports economy, giving rise to serious concerns with regards to transfer of teenage players below the age of 18. In the face of a teenage trade sometimes compared to trafficking of human beings or even new (international) slavery, some recipes have been suggested to supervise and regulate international athlete migration, including the design of a specific taxation. In the new context of financial crisis and global economic recession it is as yet unclear if this is likely to put a brake on such migration or to boost it.

The chapter is structured as follows. First, some empirical evidence is provided as regards to the magnitude of international athlete migration, including the international transfer of teenage athletes or players.Then, the focus is on the economic determinants of such migration and some of its outcomes. A model of international player transfer taxation more specifically geared towards hindering teenage transfers is elaborated on, which strengths and weaknesses are compared to former and existing (FIFA) regulation in football. Did the whole picture change with the emergence of current financial and economic crisis? Since the latter is not over and an economic analysis of its consequences is not stabilised yet, only some hints about its impact on international athlete migration will be sketched in the conclusion.

Empirical evidence of international athlete migration

The First significant international player transfers in football can be traced us to the 1950s. In the same decade, an outflow of baseball players from the Dominican Republic towards North American baseball leagues started to becomemore significant . However, it is globalisation of the labour market for talents which has really boosted athlete international migration, sometimes coined a "feet drain" or, better, a "muscle drain" [START_REF] Andreff | The Correlation between Economic Underdevelopment and Sport[END_REF] by analogy with the long lasting brain drain in the global economy. Such globalisation was triggered by the Bosman case (1995) in football. A similar jurisprudence was extended to different sports and citizens of Central Eastern Europe and CIS countries by Malaja, Kolpak and Simutenkov cases [START_REF] Andreff | Pistes de réflexion économique[END_REF]. Then, in 2000, a Cotonou agreement signed by the European Union with 77 African, Caribbean and Pacific countries allowed athlete transfers from the latter area under the qualification of "assimilated Europeans", which means under the same conditions as those players who could claim benefiting from Bosman, Malaja, Kolpak and Simutenkov jurisprudences. The outcome is a global labour market for player talents.

After 1995, the international mobility of football players grew and the percentage of foreign players in European football leagues was on average more than twice higher in 2008 compared with 1996. In particular, an increasing percentage shows up in the five major European football leagues. According to data collected by Loïc Ravenel and Raffaele Poli (Table 1) regarding the five major European football leagues, 38.7% of all players involved in 2006 were foreign, that is 277 players of which 50.2% had migrated from other European countries. We basically witness a North-North international migration in European football. English Premier League is the most internationalised labour market in European football.

Such evidence has triggered the publication of the Meltdown Report, 2007 in the U.K., in December 2007, that is a report attempting to understand why the English national squad had not been able to qualify for the Euro 2008 final stage. The major reason put forward is that, in 2007-08, only 196 players in operation in the English Premier championship were not foreign while foreigners originated from 66 different countries. This was compared with 23 foreigners playing in the Premier League when it was created in 1992. International teenage player transfers is the mostcontentious and possibly illegal , international migration business, since FIFA rules adopted in 2001 absolutely forbid transferring from abroad football players below the age of eighteen. Indeed, such transfers emerged in the late 1980s, but importing teenage players from developing countries was boosted by liberalisation and resulting globalisation of the football labour market after 1995.

Many clubs increasingly looked for a substitute to more mobile European superstar players in recruiting new young and cheap talents in the Third World.

During the 1990s, 4,809 foreign players, aged from six to sixteen, originating from Latin American and African countries were found in Italian football clubs. In the Netherlands, 33

football clubs had been sued by the immigration office for illicit importation of Latin American and African players. Belgian football clubs wereand still areutilised as "nursery hubs" for training African players before their transfer to major European leagues. In 2000, 15 young African players lodged a complaint in the Belgian court against professional clubs and players" agents, complaining "trade and trafficking of human beings". And eventually they won [START_REF] Bakadiababu | Le commerce et la traite des footballeurs africains et sudaméricains en Europe[END_REF].

Often spotted by players" agents at the African Cup of Nationswhich is nicknamed the "cattle fair" -, teenage players are invited to be tested in European clubs, and recruited when the test is successful. When it is not, they are abandoned by both clubs and players" agents without a labour contract and return airplane ticket to their home country. Thus they are left de facto in a position of illegal migrant workers and, sometimes, cracked down by the police.

Some cases were so much outrageous in France that the French Minister for Sports, Ms.

Buffet, ordered a report [START_REF] Donzel | Rapport sur le recrutement, l'accueil et le suivi des jeunes étrangers (hors Union européenne) dans les centres de formation de football professionnels en France[END_REF] which confirmed the existing extremely bad practices of clubs and players" agents as regards to African teenage players. After a decade of such devastating teenage transfers, UEFA reacted in 2001 with a new regulation article 19 which stated "international transfer is allowed only if the player is at least eighteen". However, three exceptions left the door open to regulation being circumvented: teenage transfers were allowed when their parents move abroad for reasons that are not linked to football, when it is a transfer across EU countries, and, when a teenage player is living close to the border of a foreign country. As a consequence, teenage muscle drain has not vanished even though it is clearly illegal. One can still find some cases reported by the press.For example, in 2002 , Isa Mohammed (Nigeria) was transferred to a first division Polish nursery club, and his transfer was supposed to develop his international career in a major European football league.

Unfortunately, he was injured, excluded from the team and eventually abandoned by the club.

A small, though rapidly increasing, share in international migration of sporting talents comes when an athlete or player changes his/her citizenship (naturalisation), which is the most visible and sometimes contentious part of muscle drain. The number of naturalized citizens in national squads competing at Athens Olympics 2004 and Beijing Olympics 2008 was far from negligible [START_REF] Andreff | Pistes de réflexion économique[END_REF]. A forthcoming issue resulting from increasingly numerous naturalisations, which has urgently to be dealt with, is what will be the meaning, status and recognition of national squads in the future. The Qatari strategy of naturalising African and Latin American athletes is of particular concern.

Economic determinants of international athlete migration

Some determinants of international athlete migration are not economic, for instance, when an athlete simply follows his/her parents international relocation for non sport motives or looks for the opportunity of better training conditions abroad or is willing to practice in a country with a better weather and so on. In economic terms and with reference to North-North international athlete migration, a major determinant is wage differentials across different sports and different developed market economies. If one compares average monthly wages in different sports in a same country, money distribution appears to be very much uneven. In 2007, the average individual wage was €44,000 per year in French football

Ligue 1, €11,000 in Ligue 2, €12,500 in cycling Pro Tour, €7,000 in basketball A (1 st division), €6,500 in rugby Top 14, and €1,500 in athletics Ligue Pro (about 30 times less than in footballs first league). It is crystal clear that the French labour market for sporting talents is unevenly attractive to migrant athletes depending on the sport discipline. Available data also provides an insight into the impact of wage differentials in the same sport across developed market economies. For instance, average wage in English football Premier League was €145,000 in 2007 (three times higher than in the French league) and €45,500 in second division (four times higher than in French second division). This obviously explains why so many French football players move to English clubs and so few (if any) English players are hired by French clubs.

A comprehensive explanation of wage differentials between English and French football leagues would lead us into an economic theory of professional sports leagues (Andreff, 2009a) and variants of league regulation in European football [START_REF] Luengo | Broadcasting Rights and Competition in European Football[END_REF], i.e.

beyond the limits of this chapter. In a nutshell, wage differentials are resulting from club revenue differentials relying on different club attractiveness and access to gate receipts, sponsorship money, TV rights revenues, merchandising and naming2 . In this respect, English football clubs" attractiveness is stronger than French clubs. Chelsea could afford a €190 million payroll in 2007-08, that is 70% of overall payroll for the whole French Ligue 1 (€268 million). Seen from transferred player revenues, wage differentials trigger their decision to move from French to English clubs.

A second determinant is league regulation and its impact on a more or less balanced contest, the so-called competitive balance. The more unbalanced a championship, the more a players move to a top club of this unbalanced league will translate into a substantial wage increase.

French players often migrate from the more balanced French Ligue 1 to less balanced Italian Lega Calcio, Spanish Liga de Futbol and English Premier League in view of significant wage gains. A more unbalanced domestic championship raises the probability of its top clubs to qualify for (or even win) the Champions League and then increases revenue expectations for players (including bonuses, sponsorship contracts, etc.). Playing in a successful club such as a Champions League winner, finalist or semi-finalist will increase the value of a players human capital which would materialize in a more profitable international transfer fee afterwards.In South-North athlete migration, again wage gap is obviously the most effective determinant. In the Brazilian first football league in 2007, average wage was €12,000 while in African leagues it was below €2,000 in different countries, seldom over €5,000 anywhere in Africa.

English and French football wages are extremely appealing, even if paid below average, to any Latin American or African player.

A third determinant is economic underdevelopment of the Third Worldand to some extent transitioncountries [START_REF] Andreff | The Correlation between Economic Underdevelopment and Sport[END_REF]. Developing countries are usually plagued with a shortage of sport teachers and coaches, a low domestic sports financing, limited sport facilities and equipment, fewer world-level sport performances than developed countries, namely few Olympic medals since the number of medals is markedly determined by GDP per capita and population of participating countries [START_REF] Bernard | Who Wins the Olympic Games: Economic Resources and Medal Totals[END_REF][START_REF] Andreff | Les déterminants économiques de la performance sportive: Prévision des médailles gagnées aux Jeux de Pékin[END_REF]).

These countries are not capableof hosting more than a few sport mega-events; they suffer from widespread corruption in sport, embezzlements and wage arrears in professional clubs.

Therefore, for a domestic athlete, moving to the North means that he/she will find there better training conditions, better technologies in sport equipment and medical care, better expectations to win at world level and more competitive athletes to compete with. In addition, he/she can access a better standard of living and purchasing power in a developed market economy. The same determinants obviously apply to teenage muscle drain from developing

countries. An additional one is the "dream of a personal achievement as a future superstar player" in the North with all associated benefits, a dream continuously fuelled by unscrupulous players" agents painting an enticingthough fallacious -picture of assumed advantages.

Major outcomes of international athlete migration may be sketched as follows. For athletes, when a transfer is successful, a major effect is higher wage and revenues, and consequently, a better way of life. When unsuccessful, the player is left aside by the host club or resold on the labour market or simply abandoned in the case of teenagers. If unsuccessful, a player has to drift toward another club, usually in a lower division, or find a way to return home. For host clubs, they become multinational companies [START_REF] Andreff | Un club de football européen est-il une firme multinationale[END_REF] sampling players and coaches from different countries. They offer sport shows and events of a better quality due to their recruitment of the best players/athletes abroad and they increase their probability to win on the pitch. Consequently, they attract more money from fans, sponsors and TV channels. Since they earn more money, host clubs for foreign players are more capable to recruit international superstars which can prolong their capacity to win, to earn more money and so on, in a sort of winners" "virtuous circle".

With regards to professional sports leagues, the impact depends on whether a host country is net importer of players or not. For instance, despite a significant number of French football players enrolled abroad, French Ligue 1 had a deficit transfer balance in the early 2000s, which jeopardized the league financial equilibrium, due to even more significant imports of players from European and developing countries.When it comes to the economic impact of importing foreign athletes on the host country"s economy overall, an obvious gain consists in having higher quality domestic sport contests without having financed the cost for education and training foreign players/athletes involved in the domestic championship. With superstar foreign players, host countries" teams may enjoy winning prestigious (and profitable) international contests like the European football Champions League. However, a possible "windfall cost" may happen with regard to the host country"s national squad, as it has been witnessed with the English football squad unable to qualify for the final stage of Euro 2008.

For developing countries which basically are net exporters of sporting talents, the main issue is that home country and the nursery club are not compensatedor not enoughfor educational and training costs they have covered before their players have been transferred.

An absent or limited compensation deepens the gap between a developing home country"s and a developed host country"s sports economy and undermines the sporting substance of developing countries as well as their expectations and probability to win international contests or Olympic medals. Developing countries" national squads are often weakened by European or American clubs" reluctance to release their Third World players, which erodes the home country"s capacity to field its most talented athletes in international contests. And when players are released, the national squad of a home country is less and less national in some sense insofar as most of its players are expatriate workers. Since they are not compensated enough for transferred players, professional clubs and leagues in developing countries remain poor and unable to keep their best players or to get a reasonably high price (transfer fee) for them on the global market.

Regarding the role of players" and athletes" agents, the more they transfer players, the bigger their revenues since they levy a percentage on each transfer fee and/or initial wage. Transfers of teenage players are illegal and undertaken under outrageous and infamous conditions offered to young players. Increasing turnover in the labour force and growing international athlete mobility still occur and destabilizes the manpower of many sport teams, with the exception of the richest. Such consequences of free movement in a global market calls for the introduction of more regulation. Another outcome is the emergence of an underground (black) market for teenage players after the introduction of new FIFA regulations released in 2001.

These regulations prohibit the transfer of players below the age of 18. With player transfers from developing countries, players" agents often cheat on player birth dates in order to either "rejuvenate" rather old players or give the appearance that a minor player is older than eighteen. This "trade" is run by unregistered players" agents unsupervised by FIFAtherefore to outlaw agents (which compose nearly 80% of agents in operation in the French football league). Hence, there is a high risk of fuelling the "bung" culture of bribes, embezzlements and so on, as pointed at by Lord Stevens" report (2006) in the U.K.. Sometimes, a conflict of interest emerges when there are tight links between host club managers and players" agents.All in all, developing countries are losers in the athlete migration business. An issue to be solved is one of losers" compensation by winners basically located in developed host countries: clubs, leagues and players" agents. This has not been tackled yet since sport globalisation has emerged.

A model of international player transfer taxation: the Coubertobin tax

In the face of similar issues with excess international mobility of short term capital on global financial markets, James Tobin, a Nobel Prize winner in Economics suggested to "throw sand in the wheels of international finance" and designed a 1% Tobin tax to put a brake on short term capital movements [START_REF] Tobin | A Proposal for International Monetary Reform[END_REF]. Such a tax has not been implemented so far but with the current financial crisis partly resulting from too much free capital movements through banks, financial markets, fiscal paradises, etc., the Tobin tax may come back to the fore in the coming months and years.

Thus it is recommended here to design and introduce what I call a "Coubertobin" tax on international player transfers [START_REF] Andreff | The Taxation of Player Moves from Developing Countries[END_REF] with the four following objectives:

1. The tax is to extensively cover educational and training costs of teenage athletes in their home countries.

2. The tax is likely to slowdown international athlete migration from developing countries to professional players markets in developed countries.

3. The tax should provide a strong disincentive to transferring teenage players or even children.

4. Tax revenues would accrue to a fund for sport development in developing home countries and could finance sport facilities building and maintenance, training, sports at school and sport for all.

The idea is to levy the Coubertobin tax at a 1% rate on all transfer fees and initial wages agreed on in each labour contract signed by players moving from developing countries with foreign partners in developed host countries (for the technicalities of the tax, see the appendix below). Regarding transfers of teenage and very young talents, a graduated surcharge would be added to the 1% tax itself, the younger the player, the higher rate of surcharge.

The Coubertobin tax obviously is not designed to be a panacea. A number of issues would have to be resolved if one wants such a tax to be enforced. Which would be the accurate body to levy the tax and take over tax administration? It could be a World Bank or UN department or an international body specifically created to manage the tax. An international agreement is necessary between host and home countries and sport federations; otherwise the tax will not be implemented on a global scale, the only relevant scale. Political willingness seems to be missing so far in favour of such tax. The current financial crisis with its impact on professional finance and a hardened budget constraint on wages and transfer fees might well create a window of opportunity for those convinced that the global market for sporting talents must be regulated.

Table 4x: A model of a Coubertobin tax FR = (Pi -r.Vl) . T, if a > a1

(1)

FR = (Pi -r.Vl) . [T + s1 (a -a1)], if a1 < a < a2

(2)

FR = (Pi -r.Vl) . [T + s2 (a -a2)], if a2 < a < a3

(3)

FR = (Pi -r.Vl) . (T + s3), if a < a3 (4)

FR: revenues rose through taxation for home developing countries, Pi: international transfer price (fee) + initial annual wage of transferred player, Example: a1 = 18 years, a2 = 14 years, and a3 = 10 years.

Vl
If a1 < a < a2 , the tax surcharge s1 = 2% more for each month under the age of 18 at the date of transfer; transferring a player of 16 would cost a 48% surcharge).

If a2 < a < a3 , the surcharge s2 = 10% more for each month below the age of 14 at the date of transfer; transferring a player of 12 would cost a 240% surcharge.

If a < a3 , the surcharge s3 = 1000% lump sum tax.

When it comes to regulating international athlete migration, there are at least two other options than the Coubertobin tax. A first option is the one adopted in the 2001 FIFA rules.

First, teenager transfers are prohibited. The problem is that prohibition usually creates very strong incentives to either find some excuse that triggers an exception status or develop an international black market for teenage players, which already exists. Second, FIFA rules establish training costs compensation for players transferred over twenty-three with a 5% solidarity mechanism which distributes compensation on a pro rata basis among all nursery clubs involved in a player"s training from the age of twelve to twenty-three. In a nutshell, the comparison between FIFA rules and Coubertobin tax (details in [START_REF] Andreff | The Correlation between Economic Underdevelopment and Sport[END_REF][START_REF] Andreff | FIFA Regulation of International Transfers and the Coubertobin Tax: Enforcement, Scope and Return. A Rejoinder to Bill Gerrard[END_REF][START_REF]The Muscle Drain, Coubertobin-Type Taxes and the International Transfer System[END_REF] comes out with FIFA rules being more profitable over twenty-three, much less below eighteen. A main limitation of FIFA rules, comparatively to the tax, is that they are restricted to football while Coubertobin tax targets all sports. On the other hand, FIFA rules have been adopted while the tax is still in prospect. In some sense, FIFA rules are a step in the right direction, but it is not in tackling the less desirable effects of international athlete migration.

A third option is to revert to the pre-Bosman quotas system of domestic players, such as the 6 + 5 rule which would compel any football club to field at least six domestic ("national") players, and no more than five foreign players, in each match that counts for a contest. This rule is strongly supported by Sepp Blatter, , and more recently he has been joined by the former French State Secretary for Sports, Mr. Bernard Laporte. The incumbent UEFA president, Mr. Michel Platini, is apparently less in favour of quotas. Nevertheless, the number of "locally trained" players that must be fielded in UEFA contests has been increased from 4, to 6 and then 8 players since 2007-08. In the Italian Lega Calcio, the quota is now of at least 50% Italian players. A quota of locally trained players is also discussed in the French rugby Top 14. The concept of a locally trained player is rather blurred and must be further clarified in the near future, otherwise it could be considered as an attempt at breaching the Bosman ruling and the Treaty of Rome article which guarantees international labour mobility to all EU citizens. Finally, the Andrew Webster case at the Sport Arbitration Court seems to be a recent U-turn compared with the Bosman case, since it allows a playerconsidered as a free agentwho breaches their labour contract before the deadline, to obtain a compensation though not higher than cumulative wages until the end of contract. This sounds similar to the previous transfer fee system which had been abolished by the Bosman case. If player quotas based on citizenship were to be re-introduced, they would be subject to criticism by the European Court of Justice.

The most urgent regulation of international athlete migration may well be a quite tighter supervision of players" agents business. According to FIFA rules those who start up a players" agent business must exhibit a clean police record, must not be an attorney, must pass an interview with his/her domestic football federation and must open a bank deposit in Swiss francs. A number of agents do operate without fulfilling these rules. This regulation should be more tightly supervised, to say the least. Another option would be to forbid affiliated clubs (affiliated to sport federations) to deal with outlaw players" agents and to fine those which do not align to such rule. Some doubt may be raised about the efficiency of supervision as long as players" agents and host clubs have converging, confusing or merged interests. Creating an international association of players" agents on the model of the Bar (association of barristers) has also been suggested [START_REF] Bakadiababu | Le commerce et la traite des footballeurs africains et sudaméricains en Europe[END_REF]) that would define and supervise honorariums and fees, and rule the whole agents business. Here again, like for Coubertobin tax, such reform requires political willingness which is missing so far. What is urgently needed is to build up an exhaustive data collection process about all international transfers (in all sports and not only for football as in [START_REF] Poli | Annual Review of the European Football Players, The Professional Football Players Observatory[END_REF] and incurred transfer fee amounts. The latter is absolutely unknown and is only publicised through estimates and speculation by journalists or through acquaintances with some players.

International athlete migration and regulation in times of crisis

The development of the sub-prime bubble, its propagation into a global financial crisis that subsequently triggered a global economic recession may provide new support to economic regulation at the world level. Perhaps, time is ripe for implementing such a thing as a Coubertobin tax on international labour migration. There are several reasons to consider this.

First, which is the impact of financial and economic crisis on sport? Based on first observations regarding sport financing in Europe [START_REF] Andreff | Etude du financement public et privé du sport, Etude réalisée dans le cadre de la présidence française de l"Union européenne[END_REF]Andreff, 2009c;Andreff, Dutoya & Montel, 2009 a & b), major channels for crisis transmission to sports are household and local authority sport expenditures, then government sport budget and private money flowing into sports through sponsorship and the media. TheGlobal crisis affects household revenues downwards and thus, through a decreasing purchasing power, it shrinks household sport consumption expenditures. Let us imagine a 5% cut in household expenditures. If sports products and services are normal goods, considered as a usual part of European way of life, the decrease of sport expenditures would be about 5% on average since it is the expected fall in European GDP in 2009. Deep national disparities will occur around the average, depending on how hard each domestic economy will be hit by the crisisfor instance harder in the new EU members (Andreff, 2009d). The crisis may have a substitution effect in household expenditures between sport practice (and paying ticketed sport events) on the one hand and, on the other hand, sport events that can be watched for free or at a reasonably low price (sport In most EU member countries, local authorities have financed local clubs, athletes and infrastructures on the basis of money borrowing from the banking system. As a result, a number of local authorities are now indebted to banks which has negative implications for sport finance. Local authorities will not be able to maintain existing amounts of sport finance or, at least, will select the most significant clubs, athletes, sport events and infrastructures.

The global economic crisis has obviously an impact on governments" budgets. The great bulk of fiscal deficit is simply due to the recession crisis itself which lowers tax receipts while it increases public expenditures (unemployment, social protection) and debt. Increased public debt will have to be reimbursed soon and this will trigger an austerity fiscal policy as soon as the deepest of the recession will be over. With 0.01% to 0.88% of government budget in European countries, sports ministries will suffer more than other ministries from budgetary cuts because of their low priority. A second strategy is simply to reduce the amount of sport sponsorship without giving up all sport support (AIG, Northern Rock, XL charter, Fortis, Dexia). Sponsors also diminish wages of sponsored athletes. Rossignol is bargaining on limiting to half previous wage agreements with skiers".

Other sport sponsorslike Lacoste for example -prefer to concentrate reduced finance on a few very high profile professional athletes and clubs, and on sport mega-events. This means that amateur sport clubs and events which previously benefited from sponsorship will suffer more from financial shortages than professional sports. However, even some professional football clubs have found it difficult to attract aa sponsor for 2008-09 like e.g. Aston Villa, Sheffield Wednesday and Leicester City.

In the case of media (TV channels) which basically finance sport through broadcasting rights, the crisis impact is less crystal clear. Recession affects advertising budgets of numerous enterprises downwards, and this would reduce the revenues offered for broadcasting sport events, in general. A countervailing tendency may be the following: if the viewing figures were to increase during the crisis, the audience rates of TV channels would increase and its attraction for advertisers would increase since, in a period of crisis, enterprises need to reach more potential consumers for their products (in order to maintain sales). On the other hand, the number of (sport) TV viewers might well increase during the crisis due to reduced purchasing power available for paying for leisure and sport. Moreover, the number of sport TV viewers would increase if the above mentioned substitution effect of free sport TV broadcasts to sport practice and paid sport shows materialised. A number of broadcasting contracts between TV channels and different sports, including football, have already been revised downwards in Europe.

In the current model of professional sport finance3 , professional clubs can afford pushing wages and transfer fees up to acquire superstar players, and do it in a sort of arms race (Andreff, 2009a) as long as nobody impose a hard budget constraint and good corporate governance on them This applies even in the French and German cases where football clubs are more tightly supervised by auditing bodies than elsewhere in Europe (Andreff, 2007a).

Clubs are often stuck in a vicious circle between increasing broadcasting rights negotiated with TV channels in order to cover their wage and transfer fee increases, which in turn requires a new negotiation for higher TV rights later on and so on (Andreff, 2007b); such a vicious cycle derails into pandemic clubs" deficits. Thus, the creeping financial crisis which affects European football [START_REF] Lago | The Financial Crisis in European Football: An Introduction[END_REF] Lyon, Marseille and Bordeaux. This downward trend is tightly linked to the crisis since it is triggered by the sterling pound depreciation in terms of euro and a more stringent English tax system (in reaction to the crisis) which hits higher revenueearners , which include football players. To compensate for their loss of players, English clubs will have to increase wages and transfer fees, which few of them can afford.

It might be that the crisis, by itself, would put a brake on international athlete migration in a sort of market "self-regulation". Does it mean that there is no longer any need for a Coubertobin tax? A slowdown in international athlete transfers does not resolve at all the issue of outlaw teenage players" transfers. There is still a significant room for regulation in particular when this global crisisends , and international athlete migrationgains further momentum .

  Except in a few industries, a number of industrial and commercial enterprises have been seriously hit by economic recession since the last trimester 2008, and some of them have gone bankrupt. Since their sales and profits are down they reduce their "less useful" expenditures, including sport sponsorship. Sponsors are changing their strategy towards sports since the crisis. Some simply quit sport sponsorship. A number of cases have been witnessed since September 2008: Honda, ING Royal Bank of Scotland and Crédit Suisse have left Formula 1, Kawasaki has abandoned its Moto GP team, banks have left the golf PGA Tour, Kodak has given up Nascar, Nomura the Japan Olympic team, Vodafone has withdrawn from UK cricket and horse racing and breached Tiger Woods" sponsorship contract one year in advance.

Table 1 : Share of foreign players in professional football, pre-and post-Bosman (%)

 1

	1st division championship	1995	1996	1999	2005	2006

Table 2

 2

provides a snapshot of the global market for football players with regards to the thirty major exporting (home) and thirty major importing (host) countries. It is to be noticed that major European leagues are both exporting and importing, which means that two way transborder flows are a characteristics of international athlete migration across major developed market economies. The only dividing line among European countries is that some countries are net importers of foreign players (England, Greece, Germany, Italy, Spain) whereas some others are net exporters (France, Belgium, Portugal, Denmark).

Table 2 : Migrant football players in 2008: thirty major leagues

 2 On the other hand, outside Western Europe, some countries appear to be net exporters, first of all Brasil, Argentina and Serbia, but also the Czech Republic, Croatia, Nigeria, Bosnia & Herzegovina, Cameroon, Slovakia, Uruguay, Ivory Coast, Senegal, Ghana and Macedonia, i.e. in a nutshell Latin American, Central Eastern European and African countries. Thus, South-North athlete mobility is a crucial facet of international athlete migration, even more so than North-North player transfers. Nearly half of foreign players operating in the five major

	Home country	Number of migrant Host country	Average number of
	league	football players league	foreign players per
				club
	Brasil	551	England	15,6
	France	233	Greece	13,3
	Argentina	222	Portugal	13,2
	Serbia	192	Russia	12,9
	Portugal	121	Germany	12,8

European football leagues are originating from developing countries. The percentage is even higher if we look at second rank leagues like Belgium or Portugal and second and third division clubs of the big five European football countries. For example, in the French professional football league (Ligue du Football Professionnel), 50% of foreign players are from African countries. Southern (and Eastern European) countries usually are net exporters and Northern countries are net importers in player trade with the South (and Eastern Europe).

Table 3 : Transfers of Brazilian players abroad

 3

	2002	2003	2004

Table 4 : Geographic distribution of domestic team affiliation, African 2002 World Cup players

 4 The same observation is made at each football African Cup of Nations. The extreme case was the Ivory Coast team all the players of which were registered in foreign leagues and clubs.

	Domestic team affiliation Cameroon Nigeria Senegal S. Africa Tunisia	Total
	Home country	-	2	1	7	14	24
	Africa	-	-	1	-	-	1
	England	4	4	-	3	-	11
	France	7	3	20	-	2	32
	Germany	1	-	-	2	1	4
	Italy	3	-	-	1	3	7
	Spain	4	1	-	-	-	5
	Other European	3	11	1	10	3	28
	Rest of World	1	2	-	-	-	3
	Total	23	23	23	23	23	115
	Source: Gerrard (2002).
	The other side of the coin is the selection of players enrolled abroad in an increasing number
	of national squads. During the football World Cup 2006 the overall number of players
	selected in national squads was 736 out of which 392 (53%) were playing abroad. The 2006
	French football squad encompassed 13 players registered abroad. National squads of
	developing (and transition) countries now comprise of many players whose club affiliations
	are outside their home domestic league. This is even more clearly exhibited with African
	national squads participating to the football World Cup final stage (Table 4). For the five
	African squads that qualified in 2002, only 21% of players were affiliated to their home
	domestic league.

  TV broadcasts). In fact, sales of sport goods have dropped after September 2008. Adidas sales worldwide have dropped by 6% in the first trimester of 2009 and its profit by 97% (Puma"s profit fell by 94%), Nike"s global sales have decreased by 2% in the same trimester and the company has cut 1,400 out of its 35,000 jobs. Shrinking household purchasing power is also a threat for professional sports clubs. Stadium attendance has dropped in various sports in the past months, but not that much in European football where attendances have still increased in English Premier League and German Bundesliga while they are stagnating in French Ligue 1 and decreasing in Italian Lega Calcio. Another crisis index is that sports specialised newspapers, such as L'Equipe in France, are facing a fall in their sales.

  , and other professional sports to a lesser extent, is going to deepen with the global financial crisis and recession. The English Premier League deficit has reached €3.8 billion overall in October 2008, Arsenal, Chelsea, Liverpool and Manchester United being accountable for two thirds of it. The deficit of Spanish Liga de Futbol was up to €2.8 billion in December 2008, Real Madrid, FC Barcelona, Atletico Madrid and Valencia being the most substantially in the red. As a consequence of such financial woes in European football clubs, the mercato 4 transfer market collapsed in winter 2008-09 due to a sponsorship shortage in French Ligue1, German Bundesliga, Italian Lega Calcio and to a lesser degree inSpanish Liga de Futbol. Again, the exception of to this was the English Premier League. Eventually, the summer 2009 market for international transfer has also slowed down in English Premier League. For the first time in many years, Manchester United, Liverpool, Chelsea and Arsenal have spent much less on foreign players than clubs such as

Naming refers to an increasing number of professional sport teams that have sold the naming rights for their facilities to private firms.

Primarily based on media finance (TV broadcasting rights), then on corporate finance, merchandising, labour market (players transfers) and capital market (flotation of clubs" shares at the stock exchange), see[START_REF] Slack | The Evolving European Model of Professional Sports Finance[END_REF].

Mercato is the annual re-opening of the transfer market during the season"s winter break.