capacity development in urban transport sector …...capacity development in urban transport sector...

Capacity development in urban transport sector

Metin Senbil2006.02.14

24th COE Seminar2

Background

• Environmental problems at various scales

• Energy considerations

• Transportation (problem) in developing countries– Future prospects

• Demand for transportation is increasing

• Developing countries

• Income ~ car ownership

– Space consumption

– Stronger Land Use and Transportation relationships

– Duality in space

– Transportation modes

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Background

Transportation (problem) in developing countries

Urbanization

CapacityAdministrative

Institutional

Physical

Individual

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Land use and transportation

Urban density

4003002001000

Dai

ly tr

ips

by f

oot p

er c

apit

a

1.2

1.0

.8

.6

.4

.2

0.0

Produced from Millennium Cities Database

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Urban density

4003002001000

Non

mot

oris

ed m

odes

per

cap

ita

1.6

1.4

1.2

1.0

.8

.6

.4

.2

0.0

-.2


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Proportion of jobs in CBD

806040200

Ave

rage

dis

tanc

e of

the

J-to

-W

30.0

20.0

10.0

0.0


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Proportion of jobs in CBD

806040200

Dis

tanc

e of

the

J-to

-W b

y m

echa

nise

d m

odes

30.0

20.0

10.0

0.0


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Transportation

Length of road per 1000 people

1000080006000400020000

Dai

ly tr

ips

by f

oot p

er c

apit

a

1.2

1.0

.8

.6

.4

.2

0.0


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Transportation

Length of freeway per 1000 people

3002001000

Ave

rage

dis

tanc

e of

the

J-to

-W

30.0

20.0

10.0

0.0


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Environment

Daily private transport trips per capita

543210

Tot

al e

mis

sion

s pe

r ur

ban

hect

are

30000.0

20000.0

10000.0

0.0


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Environment

Average time of a car trip

6050403020100

Tot

al e

mis

sion

s pe

r ur

ban

hect

are

30000.0

20000.0

10000.0

0.0


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Energy

Daily private transport trips per capita

543210

Ene

rgy

use

per

pass

enge

r km

5.0

4.0

3.0

2.0

1.0

0.0


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Energy

Average time of a car trip

6050403020100

Ene

rgy

use

per

pass

enge

r km

5.0

4.0

3.0

2.0

1.0

0.0


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Policy

Price of fuel per km

120010008006004002000

Pri

vate

tran

spor

t tri

ps p

er c

apit

a

5.0

4.0

3.0

2.0

1.0

0.0


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Policy

Average user cost of a car trip

3000200010000

Dai

ly p

riva

te tr

ansp

ort t

rips

per

cap

it

5.0

4.0

3.0

2.0

1.0

0.0


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Data and preliminary analysis

• PT surveys administered by JICA

• 11 developing cities around the world– Asia Pacific: Chengdu, Kuala Lumpur, Phnom

Penh, Jakarta

– Eastern Europe: Bucharest

– Middle East/North Africa: Tripoli, Damascus, Cairo

– South America: Belem, Managua

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Egypt

Syria

Romania

Lebanon

Cairo

Tripoli

Damascus

Bucharest

Manila

Jakarta

Chengdu

Phnom Penh

Kuala Lumpur

Brazil

Nicaragua

Belem

Managua

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JICA_11

City Population

Survey year

# of Households

# of Persons

# of Trips

Belem, Brazil 1,782,394 2000 6,889 24,043 59,529 Bucharest, Romania 2,150,000 1998 32,888 67,509 143,311 Cairo, Egypt 14,400,000 2001 41,962 136,070 268,360 Chengdu, China 3,090,000 2000 14,537 31,188 70,199 Damascus, Syria 3,078,190 1998 17,202 38,490 81,698 Jakarta, Indonesia 20,964,000 2000 100,864 425,237 1,083,280 Kuala Lumpur, Malaysia 1,390,800 1998 27,331 80,560 218,460 Managua, Nicaragua 1,200,000 1998 8,089 24,854 54,138 Manila, Philippines 9,454,000 1996 60,752 231,889 471,035 Phnom Penh, Cambodia 1,152,000 2000 6,446 18,664 40,369 Tripoli, Lebanon 330,900 2000 1,321 3,608 7,615

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JICA_11_trip modes

• Paratransit– Jakarta: Bajaj/Becak/Ojek

– Manila: Jeepney/Tricycle

• Motorcycles in Asia Pacific

• Age– Tripoli: 75 % of private vehicles are older than

10 years; 40% older than 20 years

– Damascus: 54% of private vehicles are older than 10 years; 22% older than 20 years

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JICA_11_Vehicle age- Tripoli

836 1.00 30.00 17.0730 6.11492

836 1.00 6.00 4.4007 1.16884

836 2 24 6.30 3.889

836

Vehicle age (first car)-dependent varia

Income

Household size

Valid N (listwise)

N Minimum Maximum Mean Std. Deviation

24.152 .812 29.743 .000

-1.925 .167 -.368 -11.514 .000

.221 .050 .141 4.399 .000

(Constant)

Income

Household Size

B Std. Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig.

24th COE Seminar21

JICA_11_Commute Trip Mode

• Public vs. Private

.75 .25

.17 .83

.61 .39

.10 .90

.09 .91

.01 .99

.79 .21

.00 1.00

.47 .53

.12 .88

.04 .96

Tripoli

Phnom Penh

Damascus

Manila

Chengdu

Managua

Belem

Bucharest

Cairo

Jabotabek

Kuala Lumpur

Mean

PublicTransport

Mean

PrivateTransport

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JICA_11_Commute Trip Mode

SEX 0.223 0.011 20.742 1.250AGE 0.015 0.001 28.457 1.015Resident worker dummy (weighted) -0.001 0.000 -3.725 0.999

Tripoli -1.810 0.060 -30.315 0.164

Damascus -1.140 0.025 -45.353 0.320

Manila 1.564 0.022 71.308 4.776

Chengdu 1.660 0.082 20.192 5.262

Managua 4.177 0.128 32.739 65.144

Belem -2.014 0.037 -54.943 0.133

Cairo -0.138 0.011 -12.462 0.871

Jabotabek 1.383 0.019 73.567 3.989Kuala Lumpur 2.442 0.028 87.035 11.495

value Std. Error t Exp(B)

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Individual Capacity in urban transport_the case of Jabotabek

Min. Max. Mean Std. Deviation

Government policies: priority to transport policies 0 4 3.02 0.871Government policies: priory to environmental protection policies 0 4 2.77 0.846Transport policies: priority to road building 0 4 3.02 0.871Transport policies: priority to public transit 0 4 3.00 0.892Transport policies: priority to transportation management 0 4 3.00 1.106Transport policies: priority to environmental protection 0 4 3.02 0.877

Age 5 97 23.63 14.672Sex 0 1 0.51 0.500Middle Income 0 1 0.22 0.415High educated 0 1 0.21 0.408Employed 0 1 0.25 0.435Private motorized commute 0 1 0.15 0.361Pro-transit 0 1 0.62 0.485Pro-car 0 1 0.25 0.436Transport fee's Share more than 30% 0 1 0.20 0.402No. of Household Members 1 10 3.71 1.576Sample size 10,879

Explanatory variables

Dependent variables

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Ordered probit model

• Five ordered scales yi

• Latent Ui

• P(Ui is in the first range ) = Φ( β′X )• P(Ui is in the second range ) = Φ ( β′X + μ1) −

Φ( β′X )• P(Ui is in the third range ) = Φ ( β′X + μ2) −

Φ( β′X + μ1)• P(Ui is in the forth range ) = Φ ( β′X + μ3) − Φ

( β′X + μ2)• P(Ui is in the fifth range ) = 1 − Φ( β′X + μ3)

• LogL=∑NZjxlog(Pj)• Zj = 1 if individual chooses jth category,0 else.• GAUSS code

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Individual Capacity in urban transport_the case of Jabotabek_results of the ordered probit model_GOVERNMENTPOLICIES

• Demographic variables, i.e., age and sex, are insensitive to both transport and environment

• Middle income individuals attaches positive importance to both transport and environment

• High educated individuals are supportive for transport policies

• High household expenditures for transport cause sensitiveness to transport policies

• Both pro-transit and pro-car individuals attaches negative importance to environmental problems

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Individual Capacity in urban transport_the case of Jabotabek_results of the ordered probit model_TRANSPORTPOLICIES

• Pro-transit individuals strongly devalues policies on road building and transport management; as expected, values transit policies

• Pro-car individuals are supportive for both road building and transit policies

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Individual Capacity in urban transport_the case of Jabotabek_results of the ordered probit model

• Middle classes are supportive for all policies

• High educated are supportive for transport policies (however no conclusive result is obtained for road building)

• Individuals with bigger household sizes devalues all policies

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Structural Equations Model-basic structure

Attitudes

Socio-economic and demographic

Transportation

Land use

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Attitudes

Attitudes

Priority should be given to transport

policies

Priority should be given to transport management and

enforcement

Priority should be given to impacts of transportation on

environment

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Age

Income Household size

HouseholdIndividual

Sex

Education(highly educated)

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Land use

( )∑ ×−j

jj ppJ

log1

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Transportation

• Long-run– Private vehicle ownership

• Short run– Private vehicle use for commute trip

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Full model

Attitudes


policies


enforcement


environment

Soc

io-e

cono

mic

and

de

mog

raph

ic

Age

Inco

me

Hou

seho

ld

size

Hou

seho

ldIn

divi

dual

Sex

Edu

catio

n(h

ighl

y ed

ucat

ed)

=1

=1

=1

=1

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SEM model estimation and goodness-of-fit

• ADF Estimation

• Perform better than baseline models (saturated and independence models)

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Estimation Results-standardized

Attitudes


policies


enforcement


environment

0.246 0.038 0.948

0.186

0.936

0.236-0.0910.673

0.734

0.763

0.27

60.

948

-0.1

960.

308

0.567

0.969

-0.528

-0.040

0.332

0.582

0.542

0.11

3

0.288 0. 388

0.315

0.074-0.011

0.3620.074

capacity development in urban transport sector …...capacity development in urban transport sector...

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