HOW DO LAND USE TRENDS AFFECT CBA OUTCOME?

Peter Almström

Svante Berglund

Maria Börjesson

Daniel Jonsson

27 november 2009, 1

Background

• CBA - number of assumptions about input factors • population, land-use, economic growth, vehicle

characteristics, fuel prices and public transport ticket prices

• Induces uncertainty in the outcome. • Assumed influence on relative ranking of road and rail

is often controversial. • CBA questioned by some practitioners/policy-makers.• Specifically, we concentrate on land-use assumptions.

27 november 2009, 2

Backgrund II

• Does new investment tend to "create its own demand" through long-term land use effects. • Rail investments - structured land use patterns • Road investments - increase the risk of urban sprawl.

• Underestimation of benefits of rail investments?

27 november 2009, 3

Purpose of the study

• How future land-use policy affect uncertainty in CBA outcome.

• Uncertainty can mean many things. We concentrate one the ranking of rail and road projects.

• A second purpose: how the ranking is affected by the fact that investments tend to create its own demand through land use changes.

27 november 2009, 4

Method

• Large-scale integrated land-use and transport model calibrated for the Stockholm region

• Ranking of the CBA outcome • Six rail and road investments • Three general land use scenarios for the period 2006-

2030: • a trend scenario, a central scenario and a periphery

scenario. • We investigate also how the demand induced by changes

in location patterns affects the relative ranking.

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Investments

27 november 2009, 6

Land-use scenarios

27 november 2009, 7

Central• 78 % of the population

growth in multi family housing

• The tolerance for high population and work place density is considerable

• Accessibility by public transport is important for localization of new housing and work places

Perifer• 27 % of the population

growth in multi family housing, single family houses are built in the same pace as in the 70’s

• Low tolerance for high density, considerable exploitation of unused land

• Accessibility by car is important for localization of new housing and work places

Trend• 58 % of the population

growth in multi family housing, the same as the trend during the last 30 years

• The tolerance for density is such that the current development structure is preserved

• Accessibility by public transport is important for localization of new multi family housing, accessibility by car is important for localization of new single family housing

Compared to what?

Land use 2030

Trend Central Perifer

Investments

Base

E4L

FÖR

ROS…

Car [vkm] and Transit [pkm]

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

JA JA2 E4L STL NAC SYD FÖR ROS

14500

15000

15500

16000

16500

17000

17500

18000

15802

16494

17125

15795

16484

17122

15897

16550

17179

15778

16466

17102

15785

16471

17106

15793

16492

17125

16369

17075

17734

15786

16482

17113

Travel distance, car [mill vkm/year]

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

Centr

al

Tre

nd

Peri

fer

JA JA2 E4L STL NAC SYD FÖR ROS

15200

15400

15600

15800

16000

16200

16400

16049

15779

15584

16123

15845

15650

16091

15832

15643

16140

15864

15663

16216

15945

15747

16088

15807

15615

16024

15768

15573

16201

15931

15739

Passenger kilometers [mill pkm]

Consumer surplus

Central Trend Perifer Central Trend Perifer Central Trend Perifer Central Trend Perifer Central Trend Perifer Central Trend PeriferE4L STL NAC SYD FÖR ROS

0

500

1000

1500

2000

2500

3000

3500

435366 398

48 64 81202 220 181

68 45 59

2896 2955 2996

144 153 128

Sum of benefits

Net present value ratio

FÖR

ROS

E4L

STL

NAC

SYD

-2.50 -2.00 -1.50 -1.00 -0.50 0.00 0.50 1.00

PeriferTrendCentral

User benefits in LUTI models

Land use 2030

Base Adj. to investment

Investments Base

Some investment

Land use and consumer surplus

Base Adj FOR Adj Base & FOR

Base Adj FOR Adj Base & FOR

Base Adj FOR Adj Base & FOR

Trend Central Perifer

0

500

1000

1500

2000

2500

3000

3500

569 595 595 562 563 560 593 594 610

126 127 129 108 109 108 138 145 147

429 430 431407 407 406

444 442 434

152 157 157152 153 152

152 152 156258 259 259

250 251 251253 254 255

1421 1438 14341415 1412 1405

1416 1418 1419

Time, Driver Cost, Driver Toll, Driver Total, Passenger Total, Transit Total, Goods

Land use and NPVR

Förbifart Förbifart MA Förbifart JA MA

Förbifart Förbifart MA Förbifart JA MA

Förbifart Förbifart MA Förbifart JA MA

Trend Central Perifer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.31

0.35 0.34

0.30 0.29 0.29

0.330.32

0.36

Sometimes

Land use

Central Trend Perifer

Investments

Base

Big transit

Big road

LUTI adjusted

LUTI adjusted

LUTI adjusted

LUTI adjusted

LUTI adjusted

LUTI adjusted

Conclusions• Land-use scenario effects are small in the time- perspective on

10-30 years. Has limited impact on CBA outcome.

• It is not obvious how the relative merits of rail and road investments are influenced by planning policy.

• The benefit of a large road investment, Förbifart Stockholm, increases with more sprawl.

Conclusions• Consistent with Zhao and Kockelman (2001) Pradhan and

Kockelman (2002) -larger impact on land-use than on transport patterns. In the transport network differences smooth out.

• Induced demand: • The consumer benefit (on the transport market) increases

if the land-use is adjusted to the investment – but the benefit of induced demand is small in the time perspective of 10-30 years.

• Does not translate directly to NPVR

• Conclusions apply to Stockholm, where the public transport system is well structured/developed.

Thank you

User benefits in LUTI models• If the land-use/transport model was an integrated

nested logit model (if models calculate rents clearing the market):

• But• No explicit land-use prices in the land-use model. • The land-use choice does not use the total benefits

appearing in the transport model. • We calculate only benefits in the transport market• Land use adjusts to accessibility with investment built

Model system

Accessibility Total population by type of housing and zone

Exogenous data: Transport networkAggregated population forecast, share of house typesEconomic development

Transport model

Demand/mode (5)

/destination/trip purpose

Assignment/peak/low

/car/transit

PopulationForecast

Population by: age, sex and zone

Land-use model

Demand/type of housing

Supply of land

Model for car ownership

and license holding

Data

Models

Literature • De Jong et al. (2007) finds that uncertainty due to input factors are larger than uncertainty due to model errors.

• That uncertain socioeconomic forecasts are a significant source of uncertainty in the model outcome (Rodier and Johnston, 2001; Thompson et al, 1997; Harvey and Deakin, 1995).

• Zhao and Kockelman (2001) Pradhan and Kockleman (2002).

• Rodier (2000; 2005) show that land use changes induced by highway investments accounts for about 50 percent of the increases in travel demand due to the investments. Marshal and Grady (2002) find, on the contrary, that land use impact have little effect on travel.

• Land-use density has an impact on travel and emissions - if combined with appropriate transit investments and auto pricing policies (Ewing and Cervero, 2001; Cervero 2001, Kenworthy and Newman, 1989; Rodier et al. 2002; Wegener and Fürst, 1999; Cervero and Kockelman, 1997; Ferdman 2005; Rodier et al. 2002; Rodier and Johnston 1997; Jonston and Ceerla, 1995; Rodier and Johnstson 2002).

27 november 2009, 24

Model characteristics• Transport model

• Lutrans (Land use Transport Model) is a simplified version of the national transport model Sampers.

• Simplified with regard to the number of trip types 2 – Work and other• Lutrans was developed and used for the regional plan for Stockholm – Mälardalen

• Car ownership model • Sensitive to land use characteristics in the zone i.e. the share of single family houses and

density. • We also have ”the usual variables” age structure, income (square root).

• Population forecast or population disaggregation model• Uses the age of the houses and share of single/multi family houses in a zone to calculate

the disaggregated population forecast• Land-use model

• Allocates a fixed number of inhabitants/workplaces to county• Accessibility, density• By single/multi family houses• Special model for conversion of summerhouses to permanent housing