what do chicago, paris and los angeles have in common?

What do Chicago, Paris and Los Angeles have in common?

Alex Anas

Professor of Economics

State University of New York at Buffalo

Public Lecture

New Economic School

Moscow, Russia

February 18, 2013

• Chicago, Paris, L.A.

have developed differently

because of history and initial

conditions

• But they are shaped by the

same economic processes

• The same economic model can be

used to study all three places

• A Computable General Equilibrium model

based on theory and econometrics can be

applied to any metropolitan area

• To use these models, we just have to

recognize that the different areas are

shaped by the same processes

The RELU-TRAN Model (Regional Economy Land Use

and Transportation)

• There is a working version for the Chicago, MSA and the Greater Paris Region

• There is a current project underway that will

apply the model to the Greater Los Angeles Region.

RELU RELU LOOPS CONVERGED

RELU TRIPS

TRAN TRAN ITERATIONS CONVERGED

STARTING POINT

p, w, R,V,S G, g

Update

G and g

for next

cycle

RELU-TRAN CYCLE

Cyclical linking of the RELU and TRAN

algorithms in RELU-TRAN

G and g converged?

p, w, R, V converged?

Excess demands, profits

converged?

YES

RELU-TRAN CYCLES

CONVERGED

PRICES, p

( w, R ) p

OUTPUTS, X

( p, w, R, S,V ) X

WAGES, w

( p, X, R,S,V )w

RENTS, R

(p, X, w, S,V) R

VALUES, V

RV

STOCKS, S

VS

START POINT

p, w, R, V, S, G, g

The RELU algorithm

RELU LOOP

p, w, R, V converged?

Excess demands converged?

Economic profits converged?

RELU loops converged

NO YES

Update

p, w, R, V

for next loop

RELU TRIPS

ZONE-TO-ZONE

EXPECTED TIMES & COSTS

G and g

ROUTE CHOICE & NETWORK

EQUILIBRIUM FLOW

The TRAN Algorithm

ITERATIONS CONVERGED

AUTO MODE CHOICE

PROBABILITIES

CONGESTED HIGHWAY LINK

TRAVEL TIMES

TRAN

Decisions

Workplace- residence

locations Voluntary

unemployment

• Labor supply / leisure

• Commuting mode choice / vehicle choice

• Housing (quantity / type)

• Vehicle ownership (quantity / type)

• Discretionary travel pattern to obtain goods and services

Where to go ? Where not to go ?

How many trips per period ?

How much to spend ?

Mode choice / vehicle choice on each trip

Decisions are hierarchically linked and involve discrete as well as continuous choices

All choices on left

apply except those

in red

Consumer

Enter labor market Stay out of labor market

Discrete choice of Working/not working

(i,j,k)

Discrete choice of triplet: i: residence zone j: workplace zone k: type of housing

Auto Transit

Discrete choice of mode for commuting

Continuous variables •Floor space of type k in residence zone I •Labor hours of work supplied to place of work at j • Number of non-work trips and their destinations and modes • Quantity of goods purchased on non-work trips

A mix of discrete and continuous choices

FIRMS

PRODUCTION FUNCTION OUTPUT

LABOR TYPES

BUILDING

TYPES

INTERMEDIATE INPUTS FROM OTHER INDUSTRIES

AGRICULTURE MANUFACTURING

BUSINESS SERVICES

RETAIL TRADE

CONSUMER

INTER-INDUSTRY STRUCTURE

Congestion and urban development

• Many issues can be studied using a model such as RELU-TRAN

• Today I will focus on one issue mainly:

• How does urban development respond to increases in traffic congestion in Chicago,

Paris, Los Angeles

Congestion’s effect

on urban development depends strongly on:

• 1. How much public transit is available

• 2. How spread out geographically are

the jobs in the urban arae

• 3. How decentralized trips are

1. Use of public transit varies

• Los Angeles 2%

•USA (average) 4.9%

•Chicago 13%

•Greater Paris 50%

2. Job concentration varies

• Greater Paris 50% in the core

(City of Paris & CDTs)

• Chicago 30% in 4 job centers

• Los Angeles 30% in 30 job centers

3. Trips are decentralized and getting more so

• Most travel occurs in the suburbs

• Suburban to suburban travel is the most rapidly increasing

• This effect is bigger when public transit is less available

United States Canada

Residence Workplace 2000 Census (%) 2001

Census(%)

Central

city

Central

city 27.5 46.1

Central

city Suburb 8.9 7.5

Suburb Central

city 20.2 16.2

Suburb Suburb 43.4 30.2

100.0 100.0

US & Canadian Commuting Patterns

Commute time increases

with city size in the US

Doubling population increases commute time by 10%

URBAN AREA WORKERS AVERAGE COMMUTE

LOUISVILLE 0.5 million 22.7 minutes

PITTSBURG 1.0 million 25.5 minutes

HOUSTON 2.0 million 28.8 minutes

CHICAGO 4.0 million 31.0 minutes

NEW YORK 8.0 million 34.0 minutes

• New York has 16 times more workers than Louisville

but only 50% higher commute time

Avoidance behavior: workers

• Workers avoid congestion by

1) Switching from driving to

public mass transit;

2) Relocating their homes closer

to their jobs;

3) Other

Avoidance behavior: firms

• Firms respond to congestion by

1) Paying higher wages to attract

workers;

2) Relocate closer to workers and

customers;

Combined effects of workers and firms

• Workers’ response increases

housing and job density in the

centers of cities

• Firms’ response spreads jobs to

less congested outlying areas and

makes more urban sprawl

Access to jobs/shops

Access to labor and

customers

Household Firm

Firm Household

Linkages between firms and households

Urban sprawl in the US

• One way in which an urban area reduces

congestion is by sprawling

• Because public transit is not plentiful

and easily accessible

• US urban areas have adjusted to congestion

by jobs moving out to suburbs

How much urban sprawl has happened in the US?

• 1972 to 1996: the U.S. urbanized land has sprawled at a rate of 2.48% per annum (2.5 times the 0.98% growth rate of urbanized population)

• An example follows about the Buffalo-Niagara Falls area in which I live

Chicago’s congestion

• How does congestion affect public transit, urban sprawl and travel behavior in Chicago?

• What would be the effects of a London type or Stockholm type cordon policy in Chicago?

1

Levels of network and zonal aggregation

CHICAGO 14+1 ZONE TEST VERSION Larger Chicago 111+6 zones

CITY

(5 zone)

SUBURBS

(9 zone)

Central Business District

Rest of City of Chicago

Inner ring suburbs

Outer ring suburbs

Exurban areaxban area

The Chicago

MSA

Lake

Michigan

Real Estate Growth (2000-2030)

Single family houses

Other buildings

Land available for

development

Change in Aggregate and Per Capita VMT

(Without Highway Capacity Additions )

Change in Aggregate and Per Capita VMT

(With Highway Capacity Additions)

Aggregate VMT

Per capita VMT

The Constancy of Commuting Time by Car Despite

Population Growth and Increasing Sprawl

Percent commuting

by car

Minutes of two way

commuting

Round-trip commuting by mode

Travel time per day

Driving-related aggregates

Non-work trips

Gasoline

VMT

Fuel Economy. MPG

Per-capita changes in driving-related variables

Non-work trips

Gasoline

VMT all trips

VMT in commuting

Effect of Growth on Job Sprawl

Other results from Chicago

• Do not add any road capacity more congestion, more sprawl, less VMT.

• Improve transit travel times (5% per decade)

less sprawl, less congestion but slightly,

more transit ridership, centralization.

• Stable gasoline prices

more intra-zonal trips, more

non-work trips, more sprawl

• Improve car fuel economy (4%

per decade)

Similar to gas price, but not as

strong.

How will rapid rail investments affect the Grand Paris Region

by 2035?

• The RELU-TRAN model was used for the “Ile de France” to model the effect of an estimated 35 billion Euros in planned rapid rail investments.

2

Population changes after projects

Job changes after projects

Rent increases after projects

What would be the effects of higher congestion in Los Angeles?

• 2% of the trips are by public transit

• 30% of the jobs are in 30 sub-centers

• It is the 2nd largest metro area in the US but has lower than expected travel times

3

Commute time increases

with city size in the US

Job sub-centers in the

Los Angeles MSA

Highways in the

Los Angeles MSA

Highways and job

centers in L.A.

Expected effects of higher congestion in L.A.

• Will new job sub-centers emerge?

• Will existing job sub-centers get bigger or smaller?

• How much will VMT per-capita decrease?