Matthias Walter, Astrid Cullmann Chair of Energy Economics and Public Sector Management Agenda
Total Page：16
File Type：pdf, Size：1020Kb
Ermittlung möglicher Fusionseffekte im Add picture on öffentlichen Personennahverkehr – dark green area Eine Effizienzanalyse für Nordrhein-Westfalen (see slide 9 for an example) Konferenz Kommunales Infrastruktur-Management, Berlin 6. Juni 2008 Matthias Walter, Astrid Cullmann Chair of Energy Economics and Public Sector Management Agenda 1. German local public transport 2. Methodology 3. Data and mergers 4. Results 5. Conclusions -2- Market structure and subsidy payments in German local public transport are not sustainable CurrentCurrent challengeschallenges ofof locallocal publicpublic transporttransport inin GermanyGermany ••High High fragmentationfragmentation withwith severalseveral hundredhundred firmsfirms causescauses inefficiencyinefficiency (cp.(cp. HirschhausenHirschhausen et et al.al. 2008)2008) ••High High directdirect subsidiessubsidies (level(level ofof costcost coveragecoverage <<<< 1100%)00%) willwill notnot bebe sustainablesustainable ••Indirect Indirect subsidiessubsidies throughthrough lolossss compensationscompensations inin municipalmunicipal utilitiesutilities legallylegally questionablequestionable ••Political Political guidelinesguidelines differdiffer fromfrom statestate toto statestate andand chchangeange fromfrom timetime toto timetime Instruments to change the market structure TendersTenders MergerMerger && acquisitionsacquisitions ••Tenders Tenders inin orderorder toto ••“Geographically “Geographically random”random” a acquisitionscquisitions byby players with a strong capital base11 -- enforce enforce competitioncompetition players with a strong capital base -- decrease decrease subsidiessubsidies •• AcquisitionsAcquisitions ofof urbanurban providersproviders withwith companiescompanies fromfrom suburbssuburbs22 -- increase increase qualityquality (cp.(cp. KCWKCW 2007)2007) • Mergers of (relatively) equal partners in ••However, However, tenderstenders cannotcannot fullyfully resolveresolve thethe • Mergers of (relatively) equal partners in geographical nearness problemproblem ofof anan inefficiinefficientent marketmarket structurestructure geographical nearness (1) E.g. HHA, DB Stadtverkehr, Veolia (2) E.g. DVB with Meißen -3- Mergers seem best feasible with companies operating a common tram network in geographical proximity MergersMergers ofof (relatively)(relatively) equalequal partnerspartners inin Characteristics geographicalgeographical proximityproximity Characteristics ••Rhein-Neckar-Verkehr Rhein-Neckar-Verkehr (RNV): (RNV): foundedfounded asas ••Outstanding: Outstanding: MergersMergers ofof companiescompanies withwith joint-venturejoint-venture forfor thethe mobilitymobility divisionsdivisions ofof tramtram andand lightlight railwayrailway networksnetworks withwith MVVMVV (Mannheim),(Mannheim), HSHSBB (Heidelberg)(Heidelberg) andand connectingconnecting lineslines VBLVBL (Ludwigshafen)(Ludwigshafen) inin 20042004 ••Geographical Geographical proximityproximity asas necessarynecessary ••Meoline: Meoline: foundedfounded asas joint-venturejoint-venture forfor thethe conditioncondition forfor raisingraising sasavingving potentialspotentials andand mobilitymobility divisionsdivisions ofof EVAGEVAG (Essen)(Essen) andand communicationcommunication betbetweenween partnerspartners MVGMVG (Mülheim)(Mülheim) inin 20052005 ••KVB KVB andand SWB:SWB: TwoTwo mmergererger attemptsattempts inin 20032003 andand 20072007 ofof thethe mumunicipalnicipal utilitiesutilities fromfrom CologneCologne andand BonnBonn fafailediled becausebecause ofof politicalpolitical oppositionopposition OurOur objectiveobjective ••…… ••Evaluate Evaluate thethe gainsgains ofof potentialpotential mergersmergers •• OneOne moremore candidatcandidatee inin Germany:Germany: whichwhich areare geographicageographicallylly meaningfulmeaningful RheinbahnRheinbahn (Düsseldor(Düsseldorf),f), DVGDVG (Duisburg)(Duisburg) • North-Rhine Westphalia with its large urban andand SWKSWK (Krefeld)(Krefeld) • North-Rhine Westphalia with its large urban agglomerationagglomeration seemsseems toto bebe bestbest appropriateappropriate forfor aa casecase studystudy -4- Agenda 1. German local public transport 2. Methodology 3. Data and mergers 4. Results 5. Conclusions -5- We use Data Envelopment Analysis to evaluate efficiencies of individual and merged companies Output production technology = efficiency frontier B A + B A A’ inefficient firms 0 Input If economies of scale are present in a sector, in addition to technical efficiency gains further saving potentials (size effect) can be raised by a merger Source: Bogetoft & Wang 2005 -6- UUsseedd iinn pprraaccttiiccee iinn tthhee NNoorrwweeggiiaann EEnneerrggyy IInndduussttrryy nical efficiency and size gains, Additional to an individual tech Output quantity 3 >> output 2 synergy gains are possible A + B Input 2 Output quantity 2 = 2 x output 1Input 1 Output quantity 1 2 x B A B are the real merger gains -7- 0 Size and synergy gains together Agenda 1. German local public transport 2. Methodology 3. Data and mergers 4. Results 5. Conclusions -8- We use physical inputs and outputs of 41 companies as data basis for our analysis Data facts • 41 companies from North-Rhine Westphalia1 - 12 multi-outputs including Rheinbahn (Düsseldorf), bogestra (Bochum), KVB (Köln) etc. - 29 pure bus operators plus BVG (Berlin), HHA (Hamburg) and MVG (Munich) as benchmark for very big mergers • Inputs “labor” and “capital”: - # of employees (FTE; adjusted to outsourcing following Leuthardt 1986 and 2005) - # of seats in trams, light railways and metros - # of seats in buses • Outputs: - # of seat-kilometers in trams, light railways and metros - # of seat-kilometers in buses • Source: Statistics of the Association of German Transport Undertakings 2006 (VDV Statistik) • Use of cost data not possible due to limited availability of balance sheets (in particular for smaller companies) • Introduction of a structural variable in an additional analysis: tram index defined as seats in trams divided by seats in all rail-bound vehicles (in order to account for different investments and operation costs) (1) After deleting outliers (e.g. due to measurement errors) -9- We propose 14 mergers of local public transport companies in North- Rhine Westphalia Merger geography Statistics Extertal • 73 potential mergers evaluated, the map Münster Bielefeld shows selected the 14 (with up to 4 Detmold Gütersloh companies) Oberhausen Hamm • 3 mergers of companies with tram and Herten Kamen Soest light railway networks with connecting Herne Moers Dortmund lines Duisburg Essen Bochum Krefeld Mülheim Hagen Wuppertal Düsseldorf Ennepetal • 4 mergers of a company with a tram and Viersen Solingen Lüdenscheid light railway network and up to 2 bus Gladbach Neuss Rem- Dormagen scheid Gummersbach companies Leverkusen Monheim Geilenkirchen Köln • 7 mergers of pure bus companies Troisdorf Siegen Düren • 5 companies remain unmerged1 Aachen Bonn Euskirchen Rhein (1) Although VWS (Siegen) is part of Legend: Tram or light railway operators in bold font Stadtwerke Bonn, we also considered Not merged companies possibilities in which this combination is parted again -10- Agenda 1. German local public transport 2. Methodology 3. Data and mergers 4. Results 5. Conclusions -11- Merger gains are in particular inherent for mergers of tram and light railway operators with bus operators Merger gains decomposition with respect to company size1 Mergers 1. Köln, Bonn 30% Technical Efficiency Gains 2. Duisburg, Düsseldorf, 9 Krefeld, Neuss 3. Mülheim, Essen, 10 12 14 Oberhausen, Moers 4. Dortmund, Hagen 20% 3 1 5. Bochum, Herne 6 5 4 6. Wuppertal, Ennepetal 7 11 7. Aachen, Geilenkirchen 2 8 10% 8. Bielefeld, Detmold, Extertal 9. Troisdorf, Euskirchen, 13 Düren Synergy and Size Gains 0% 10. Gummersbach, -30% -20% -10% 0% 10% 20% 30% Remscheid, Solingen Legend: Pure bus merger 11. Dormagen, Gladbach, Bus and tram / light railway merger Viersen Bus and tram / light railway merger on a common network 12. Hamm, Kamen Bubble size reflecting company size (in total seat-kilometers) 13. Monheim, Leverkusen 14. Gütersloh, Soest (1) For Variable returns to scale (VRS), i.e. acknowledging that there is an optimal firm size -12- The real merger effects mainly rely on synergy effects with possible interdependencies to size effects Merger gains decomposition1 Merger Overall Technical Real Synergy Size potential efficiency merger effect effect effect effect effect 1) Köln, Bonn 30% 15% 17% 16% 2% 2) Duisburg, Düsseldorf, Krefeld, Neuss 20% 14% 6% 3% 3% 3) Mülheim, Essen, Oberhausen, Moers 21% 17% 5% 7% -2% 4) Dortmund, Hagen 23% 15% 10% 11% -1% 5) Bochum, Herne 21% 17% 5% 3% 2% 6) Wuppertal, Ennepetal 0% 15% -17% 6% -24% 7) Aachen, Geilenkirchen -3% 14% -20% 9% -32% 8) Detmold, Extertal, Bielefeld 23% 12% 12% 3% 10% 9) Troisdorf, Euskirchen, Düren 10% 28% -25% 3% -29% 10) Gummersbach, Remscheid, Solingen 20% 22% -3% 0% -3% 11) Dormagen, Gladbach, Viersen 5% 14% -11% 2% -13% 12) Hamm, Kamen 24% 23% 2% 0% 1% 13) Monheim, Leverkusen 12% 3% 9% 7% 2% 14) Gütersloh, Soest 27% 23% 4% 2% 3% (1) For Variable returns to scale (VRS), i.e. acknowledging that there is an optimal firm size -13- NNoottee:: SSoommee mmeerrggeerr ccoommppoossiittiioonn hhaavvee cchhaannggeedd 1 Mergers when accounting for differences in , Bonn 1. Köln y size with tram index 2. (a) Duisburg,Düsseldorf, Krefeld , Hagen 3. (a) Mülheim, Essen 4. Dortmund , Detmold, Technical Efficiency Gains 7. Aachen, Geilenkirchen on with respect to compan 30% Extertal 1 8. Bielefeld Merger gains mostly remain stable 14 12 tram and light railway