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What Have We Learnt About Attendance Demand in Sports During the Last Decades? A Meta-Regression Analysis X IASE ANNUAL CONFERENCE -----------------------------------------

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Presentation on theme: "What Have We Learnt About Attendance Demand in Sports During the Last Decades? A Meta-Regression Analysis X IASE ANNUAL CONFERENCE -----------------------------------------"— Presentation transcript:

1 What Have We Learnt About Attendance Demand in Sports During the Last Decades? A Meta-Regression Analysis X IASE ANNUAL CONFERENCE ----------------------------------------- MAY 2008 Jaume García (U. Pompeu Fabra) Guillermo Villa & Plácido Rodríguez (Universidad de Oviedo)

2 Attendance n Siegfried (1980) n Kesenne (1987) n Baade (1990) n Downward (2000) n Forrest & Simmons (2002) n Fort (2003)

3 Surveys n Schofield (1983) n Cairns (1990) n Downward & Dawson (2000) n Dobson & Goddard (2001)

4 Variables n Economics variables n Quality variables n Loyalty n Outcome Uncertainty n Oportunity Cost n Others

5 Specific Surveys n García & Rodríguez (2003) n Borland & MacDonald (2003)

6 Meta-analysis n It is a technique of synthesizing research results by using various statistical methods to retrieve, select, and combine results from previous independent but related studies.

7 Applications n Biology n Medicine n Social Science

8 Characteristics: n focuses on empirical research, rather than theoretical. n produces quantitative results, rather than qualitative findings. n examines the same constructs and relationships. n provides findings that are comparable in statistical form (effect size).

9 The effect size (e.g. elasticities) n is a standardized index that makes comparison possible. n is the dependent variable of the meta-analysis. n represents the magnitude and direction of the relationship of interest. n is independent of the sample size.

10 Strengths: n It imposes a discipline on the process of summing up research findings. n It represents findings in a more sophisticated manner than conventional reviews. n It allows finding relationships across studies that are obscured in other approaches. n It protects against over-interpreting differences across studies. n It can handle a large number of studies.

11 Weaknesses: n It requires a good deal of effort. n It assumes that studies are really comparable. n It is highly influenced by the selection bias.

12 Data n Papers 102 n Regressions 481 n Years 1973-2007 n Authors 148 n Countries 16 n Sports 9 n Journals 35

13 Methodology: Meta-regression n It examines the relationship between one or more study-level characteristics and the sizes of effect observed in the studies. n In our case, price and income elasticities are expressed as a function of several estimation- level characteristics. Since each paper usually provides more than one estimation, further statistical modeling will be required (hierarchical models and estimation weights).

14 Preliminary data analysis n Different mean elasticities by countries n Different results depending on the sample unit n Different results depending on sports


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