Fördelningseffekter av trängselavgifter Metodik och en fallstudie för Stockholm Jonas Eliasson Transek AB
Syfte Utveckla metodik för beräkning av fördelningseffekter inkomst, kön, geografi, hushållstyper Utveckla informativa, begripliga presentationsmått Tillämpa på Stockholmssystemet vissa skillnader gentemot dagens Stockholmssystem
Problem med standardmodeller 1. Tar inte tillräcklig hänsyn till socioekonomiska skillnader i beteende 2. Destinationsval okänsligt för inkomst, utbildning, bransch 3. Implementationen introducerar aggregation bias dataunderlaget speglar inte olika gruppers resförutsättningar t ex försummar man korrelation bilinnehav - inkomst 1+2) löses med nyestimerade modeller med mer socioekonomi 3) löses med sample enumeration... men sample enumeration räcker inte för att beräkna trafikflöden
SAMPERS + GR-modellen Standardmodellen SAMPERS + sample enumeration-baserad modell för Gruppers Resande Charges Socioeconomics Socioeconomics SAMPERS travel demand model Travel times GR : SE travel demand model Trip matrices Socioeconomic trip list EMME/2 Link flows
GR-modellen Separata modeller för män och kvinnor Tids- och kostnadskänslighet beror på inkomst tidsvärdet beror m a o på kön och inkomst Socioeconomiska vikter för olika OD-relationer t ex högre sannolikhet för män med hög inkomst att arbeta i city Ung. 4000 individer Sample enumeration + viktning för att reproducera befolkningstotal Modellbaserade (individspecifika) tidsvärden används Kalkylen omfattar enbart konsumentöverskott
Fallstudie: Stockholms trängselavgifter Ring + snitt 1.5 per crossing (peak) 1 per crossing (between peaks) Real scheme (aug 2005): 2 /crossing (peak) fine-tuning of time variation no belt, only cordon
Calculated congestion reduction Without charges With charges
Hur presentera fördelningseffekter Lätt att förstå ------------------------ Korrekt Använde referensgrupp som försökskaniner för begriplighet i begränsningen visar sig mästaren Lättbegripliga mått: För varje grupp presenterades Effekter på resandet: Alla färdmedel: Reslängdsförändring, antal resor till innerstaden, antal resor norr-söder Bilresor: förändrat antal resor Reskostnader: Procentuell förändring av total reskostnad Andel av intäkterna från olika grupper
Welfare effect explained as sum of four components 800 600 Avgift Anpassning Restid Lika återbäring Netto Charges Travel change Travel times Revenue use Net effect Benefits Vinster 400 200 0-200 -400-600 Förluster Costs -800
Four components of net effect W = j T 1 jb d jb 1 2 j ( 0 1 ) ( 0 1 T T d + T + T )( 0 1 θ t t ) jb jb jb 1 2 j jb jb jb jb paid charges value of reduced travel value of reduced travel times travellers surplus through Rule-of-a-half + revenue distribution scheme (share of) revenues
Men vs. women: Men s trips change more 0% -1% -2% Men Women -3% -4% -5% -6% -7% -8% Men drive more car, esp. to city center. Mean trip length No. trips city center Their travel is affected more although they are less cost sensitive! No. N-S trips Reason: more men have good alternatives that they don t use
Men vs. women: Men pay more Men Women Men pay almost twice as much charges as women In the most-paying quintiles, men pay four times as much as women 35% 65% Men have higher travel costs from the beginning and this difference increases (men s travel costs +19%, women s travel costs +15%) 7000 Men, charges/year 6000 Women, charges/year 5000 4000 3000 2000 1000 0 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Men vs. women: Net effects before revenue redistribution 600 400 200 0-200 -400-600 -800 Charges Reduced travel Travel times Net effect Men lose around 50% than women; value of time gains not enough to offset losses -1000 Men Women
Net effects: it s all about revenue use! 450 400 350 300 250 Men Women Lump sum transfer and transit improvements women win more than men 200 150 100 Tax cuts net effect roughly equal 50 0 Net - lump sum Net - transit Net - tax cuts
Income groups: Rich people change more 0% -1% -2% Poor Medium Rich -3% -4% -5% -6% -7% -8% Three equal-sized income groups. Mean trip length High income groups reduce their travel the most even measured relatively! No. trips city center No. N-S trips Richest third stands for 44% of traffic reduction poorest third for 20%.
Income groups: Rich people pay more Richest third pay 60% of the charges; poorest third pay 13%. In the most-paying quintile, richest third pay 6 times as much as poorest third. 59% Poor Medium Rich 13% 28% 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Income groups: net effect before revenue redistribution 1000 Charges Reduced travel Travel times Net effect 500 0-500 -1000-1500 Poor Medium Rich
Once again it s all about the revenue use! 700 600 500 400 300 200 100 0-100 -200-300 Poor Medium Rich Net - lump sum Net - transit Net - tax cuts
Household types & employment status 600 500 400 300 200 100 1 adult 1 ad+ ch 2 ad. 2 ad + ch Worker Retired Student Unemployed 1000 800 600 400 200 0-200 0 Net - lump sum Net - transit Net - tax cuts -400 Net - lump sum Net - transit Net - tax cuts
Geographical effects 800 600 400 200 0-200 -400 Yttre norrort Inre norrort Norra innerstaden North Center South Södra Innerstaden Inre söderort Yttre söderort Central parts of the region lose Northern part benefits more (larger share of employment) Difference north/south decreases if belt is removed -600 Netto effects om lika återbäring lump sum transfer
Conclusions Differences in travel patterns matter more than differences in cost sensitivity for the distributional impact Revenue use is the most important question; this determines net effects All groups can be winners -although hardly all individuals Mens trips and costs are more affected than womens Rich people s trips and costs are more affected than poor people No large difference between household types Employed are more affected than other groups City center and innermost south suburbs more affected
Do the conclusions apply to other cities? Stockholm characteristics: good transit supply and large transit share fairly high car ownership rich living near the center, poor in outer suburbs Revenue use is the deciding factor likely to hold anywhere Crucial issues: available alternatives to paying the charges? (transit, time switching...) car ownership & use in different segments If these are similar to Stockholm then probably yes