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Hamburg Contemporary Economic Discussions University of Hamburg Faculty Economics and Social Science Chair for Economic Policy Von-Melle-Park 5 D-20146 Hamburg | Germany Tel +49 40 42838 - 4622 Fax +49 40 42838 - 6251 http://www.uni-hamburg.de/economicpolicy/ Editor: Wolfgang Maennig Arne Feddersen University of Hamburg Faculty Economics and Social Science Chair for Economic Policy Von-Melle-Park 5 D-20146 Hamburg | Germany Tel +49 40 42838 - 4628 Fax +49 40 42838 - 6251 [email protected] André L. Grötzinger University of Hamburg Faculty Economics and Social Science Von-Melle-Park 5 D-20146 Hamburg | Germany Wolfgang Maennig University of Hamburg Faculty Economics and Social Science Chair for Economic Policy Von-Melle-Park 5 D-20146 Hamburg | Germany Tel +49 40 42838 - 4622 Fax +49 40 42838 - 6251 [email protected] ISSN 1865 - 2441 (Print) ISSN 1865 - 7133 (Online) ISBN 978 - 3 - 940369 - 46 - 8 (Print) ISBN 978 - 3 - 940369 - 47 - 5 (Online) Arne Feddersen, André L. Grötzinger, & Wolfgang Maennig Investment in Stadia and Regional Economic Development – Evidence from FIFA World Cup 2006 Abstract: Using the case of the new stadiums for the FIFA World Cup 2006 in Germany, this paper is the first multivariate work that examines the potential income and employment effects of new stadiums outside of the USA. This study is also the first work on this topic that conducts tests on the basis of a (serial correlation consistent) Difference-in-Difference model with level and trends. As a robustness check, we use the “ignoring time series information” model in a form that is modified for non- synchronous interventions. We were not able to identify income or employment effects of the con- struction of new stadiums for the FIFA World Cup 2006, which are significantly different from zero. Keywords: Sports Economics, Regional Economics, Stadia Infrastructure, Difference-in-Difference Model JEL classification: H54, L83, R12, R53 Version: October 2008 1 Introduction A series of studies on Metropolitan Statistical Areas (MSAs) in the USA revealed that new sport stadiums do not generate significant income and/or employment effects in their host cities,1 challenging the “boosters” view of many politicians and sport officials who claim beneficial effects for the local economy (and hence, a justification for public financial support). Using the case of the new stadiums for the FIFA World Cup 2006 in Germany, this paper is the first multivariate work that examines the potential income and em- ployment effects of new stadiums outside of the USA. Such a study is generally interesting set against the background of the different urban structures in the USA and Europe. In addition, a non-US study is especially interesting because of decade-long US tradition of allocating the stadiums in suburban areas, whereas 1 See BAADE (1987, 1994, 1996), BAADE & DYE (1990), BAADE & SANDERSON (1997), COATES & HUMPHREYS (1999, 2000, 2001, 2003). HCED 16 – Investment in Stadia and Regional Economic Development 2 European stadiums are mostly located near to the city center (FEDDERSEN & MAENNIG, 2008). NELSON (2001) argued that (US-)studies concluding insignifi- cant effects on the home cities of stadiums are misleading, since the data are based on stadia built in the 1960s-1980s. On closer examination of the economic impact, it is evident that stadiums built in Central Business Districts (CBD) or downtown sites have a positive effect, while for suburban stadiums the effects on regional economic development are insignificant or even negative.2 This study is also the first work on this topic that conducts tests on the basis of a Difference-in-Difference (DD) model with levels and trends. To address the problem of potential serial correlation in DD models (BERTRAND, DUFLO, & MULLAINATHAN, 2004), we use a serial correlation consistent arbitrary variance- covariance matrix. As robustness check we use the “ignoring time series informa- tion” (ITSI) model in a form that is modified for non-synchronous interventions. The paper is organized as followed. Section 2 elaborates on the data, section 3 presents methods and results, and section 4 concludes. 2 Data The FIFA World Cup 2006 in Germany was held in 12 different stadiums (Berlin, Cologne, Dortmund, Frankfurt, Gelsenkirchen, Hamburg, Hannover, Kaiserslau- tern, Leipzig, Munich, Nuremberg, Stuttgart). The investment costs for new con- struction or major renovations totaled an amount of nearly €1.6 billion for twelve stadiums (FIFA, 2006).3 Additional €1.6 billion was invested into stadia related infrastructure (BÜTTNER, MAENNIG, & MENßEN, 2005). As the aim of this analysis is to identify the effects of the FIFA World Cup stadiums, these twelve cities will be used as the treatment group in the DD model. During the period of observa- tion, several additional stadium construction projects were undertaken in Ger- 2 MELANIPHY (1996) and SANTEE (1996) also argued that stadiums in inner cities might be more efficient for the regional development of these cities. 3 Every World Cup stadium was at least renovated. The average expenditure per city was €116.7 million with a minimum investment of €36.0 million (Dortmund) and a maximum investment of €280.0 million (Munich). HCED 16 – Investment in Stadia and Regional Economic Development 3 many. To avoid biased results, in addition to the FIFA World Cup stadiums, all re- levant stadium construction projects (including the FIFA World Cup stadiums) were used as the treatment group in a second DD regression. Tab. 1 Relevant Stadium Construction Projects in Germany, 1996 to 2005 Construction City Stadium Capacity Team(s) Costs Start End Berlin Olympiastadion 74,000 Hertha BSC Berlin 242.0 Aug 2000 Aug 2004 Bremen Weserstadion 42,100 Werder Bremen 18.0 May 2003 Jul 2004 Cologne RheinEnergy-Stadion 50,374 1. FC Köln 117.5 Jan 2002 Jul 2004 Cottbus Stadion der Freundschaft 22,746 FC Energie Cottbus 12.0 Apr 2002 Jul 2003 Dortmund Signal Iduna Park 83,000 Borussia Dortmund 36.0 May 2002 Jul 2003 Düsseldorf LTU arena 52,000 Fortuna Düsseldorf 218.0 Sep 2002 Jan 2005 Duisburg MSV-Arena 31,514 MSV Duisburg 43.0 Oct 2003 Jan 2005 Frankfurt Commerzbank-Arena 51,500 Eintracht Frankfurt 126.0 Jul 2002 May 2005 Gelsenkirchen Veltins-Arena 61.524 FC Schalke 04 192.0 Nov 1998 Jul 2001 Hamburg HSH-Nordbank-Arena 57,000 Hamburger SV 97.0 Jun 1998 Aug 2000 Hannover AWD-Arena 49,000 Hannover 96 63.0 Feb 2003 Jan 2005 Kaiserslautern Fritz-Walter-Stadion 48,500 1, FC Kaiserslautern 48.3 Aug 2004 Apr 2006 Leipzig Zentralstadion 44,193 Sachsen Leipzig 90.6 Dec 2000 March 2004 Magdeburg Stadion Magdeburg 27,000 1, FC Magdeburg 30.9 March 2005 Dec 2006 Mönchengladbach Borussia-Park 54,057 Borussia M’gladbach 87.0 Jan 2002 Jul 2004 Munich Allianz Arena 69,901 FC Bayern München 280.0 Feb 2002 May 2005 Nuremberg easyCredit-Stadion 46,780 1, FC Nürnberg 56.0 Nov 2003 Jul 2005 Rostock DKB-Arena 30000 FC Hansa Rostock 55.0 May 2000 Aug 2001 Stuttgart Gottlieb-Daimler-Stadion 55,896 VfB Stuttgart 51.6 Jan 2004 Jan 2006 Wolfsburg Volkswagen Arena 29,161 VfL Wolfsburg 51.0 May 2001 Nov 2002 Source: SKRENTNY (2001); FIFA (2006); STADIONWELT (2007); FIFA World Cup 2006 stadia are marked in bold letters. The analytical framework for this study comprises data of the 118 most popu- lated large urban districts (“Kreisfreie Städte”) in Germany in 1995, as reported by the ARBEITSKREIS VOLKSWIRTSCHAFTLICHE GESAMTRECHNUNG DER LÄNDER (2007b).4 As variables for the regional economic development, the income of pri- vate households per capita (ARBEITSKREIS VOLKSWIRTSCHAFTLICHE GESAM- 4 See Table A1 in the annex for a complete list of the large urban districts. HCED 16 – Investment in Stadia and Regional Economic Development 4 TRECHNUNGEN DER LÄNDER, 2007b) as well as the number of people employed (ARBEITSKREIS VOLKSWIRTSCHAFTLICHE GESAMTRECHNUNGEN DER LÄNDER, 2007a) in these 118 large urban districts are considered. Fig. 1. Large Urban Districts in Germany and Stadia Construction Projects Notes: World Cup venues are marked in black, German large urban districts are marked in grey. Own illustration. For the income of private households, the period of observation is 1995 to 2005, i.e. a time Span of 11 years; the period from 1996 to 2005, i.e. a time Span of ten years, is considered for employment data. As the data availability starts in 1995, no structural breaks due to German reunification have to be considered.5 Several additional indicators of the regional economic development could be con- sidered. HOTCHKISS, MOORE, & ZOBAY (2003), for instance, suggested that the DD equation could be estimated for population. As one easily can see, a sport ve- nue or sport franchise (sport club) might increase the attractiveness of a city from 5 Start and end of the observation periods are determined by data availability from EUROSTAT and VGRDL. HCED 16 – Investment in Stadia and Regional Economic Development 5 a resident’s point of view. As a consequence, migration into the city may occur. Thus, initially, it might be appropriate to test for a population effect. However, since it is difficult to assume that unemployed persons will migrate due to the increased attractiveness of a city, we can assume that most migrants will be working in their new city. Thus a strong correlation between population and em- ployment exists and an additional DD analysis on population is unnecessary. 3 Method and Results 3.1 DD Model with Level and Trend The aim of this paper is to examine if stadium construction projects in Germany – especially those of the FIFA World Cup 2006 – have a significant impact on the economic development of the regions in which they are located. For this purpose, we use a DD estimation. This is a common approach for identifying the effect of a specific intervention or treatment.