Presentation on theme: "The Political Economy of Infrastructure Planning in Sweden Johanna Jussila Hammes VTI, TEK-Stockholm."— Presentation transcript:
The Political Economy of Infrastructure Planning in Sweden Johanna Jussila Hammes VTI, TEK-Stockholm
Background An explorative study Analyse data from two Swedish National Transport Infrastructure Plans, for 2004-2015 and for 2010-2021. What factors explain which projects get included in a Plan? Examine political economy explanations.
Hypotheses 1.There is a geographic-political aspect to the choice of infrastructure projects. 2.The preferred transport mode varies depending on government colour. 3.There is a rural-urban split in project choice depending on the colour of the government. 4.Lobbying affects the choice of which projects are included in a National Transport Infrastructure Plan.
Data VariableObsMeanStd.Dev.MinMax Nat. Plan 20042201011 Nat. Plan 20103890,450,49801 Government 199860955,217,8244,372,9 Government 200260954,595,8845,665,8 Government 200660947,018,3628,2960,46 Reg.-nat. congruence 19986090,490,501 Reg.-nat. congruence 20026090,490,501 Reg.-nat. congruence 20066090,510,501 Investment cost597896,152893,37030108,7 NBIR4070,892,01-2,19717 NBIR Assessed Positive6090,3960,4901 Rail6090,410,4901 Gothenburg area6090,0720,2601 Malmo area6090,0640,2501 Stockholm county6090,110,3101 Co-financing/IC, 20105790,0490,1701 NPV Freight/IC2870,2030,51-0,436,43
t-tests Mean (Std. Dev.) t Plan 2004-15Plan 2010-21Pr (|T|>|t|) Government 199854.2854.270.0125 (7.18)(7.74)(0.99) Government 200253.9553.840.1841 (5.57)(5.76)(0.85) Government 200647.8248.230.4274 (7.55)(8.48)(0.67) Reg.-nat. congruence 19980.460.430.4274 (0.50) (0.67) Reg.-nat. congruence 20020.460.450.2382 (0.50) (0.81) Reg.-nat. congruence 20060.540.57-0.4274 (0.50) (0.67) Rail0.620.52.1551 (0.49)(0.50)(0.032) Gothenburg0.0600.082-0.7712 (0.24)(0.28)(0.44) Malmö0.0690.0670.0707 (0.25) (0.94) Stockholm0.0920.17-2.0826 (0.29)(0.38)(0.038)
Conclusions The political variables get positive and statistically significant coefficients in the regression analysis. t-tests show no difference in the means of the variables between the two Plans. We consider the regression analysis to provide at least partial support for the first hypothesis. Rail investments get a positive and significant coefficient in the regression analysis. The mean value for Rail is greater for the 2004-15 Plan than for the 2010-21 Plan. Both governments favour rail investments over road but the left-wing government favours rail more.
Conclusions The regression coefficients for the big cities are insignificant. The mean value for Stockholm County is lower for the 2004-15 Plan than for the 2010-21 Plan. The left-wing government seems to have discriminated against the Stockholm County. The regression coefficients for Co-financing/IC are positive and significant. The coefficients for NPV Freight/IC are borderline significant and positive. Lobbying matters, especially lobbying by the municipalities through co-financing.