Distributional Impacts of Congestion Pricing

04/21/23 US DOT/Volpe Center 1

Distributional Impacts of Congestion Pricing

Douglass B. Lee, Jr.

International Symposium on Road Pricing

Key Biscayne, FL

November 2003


Purpose

Efficiency versus Equity

Equity

– horizontal

– vertical

Objective Measurement (vs. eye of beholder)

– direct impact (as a tax)

– relative to current financing methods (recycling)

– after behavioral response (incidence)


Two Major Dimensions of Equity Horizontal

– treat equals equally

Vertical

– impact on the distribution of income: reduce disparity (progressive), increase disparity (regressive), or neutral

– impact on income class proportional to income is neutral

– not everything is regressive


Conclusions

Vertical equity impacts of peak pricing are not bad, not enough to be an obstacle to efficiency

– true before revenue recycling; revenues can easily correct equity impacts (and also kill efficiency gains)

Alternative instruments are also not that bad, e.g., gasoline excise tax, property tax

Earmarking may be politically useful but is economically dubious if revenues are fungible (e.g., gambling revenues for education)


1. Direct Impact

Definition of income

– household, family, consumer unit, per capita

– money, earned income, before tax, after transfers, permanent income, wealth

Method of Measurement

– tax returns

– expenditures

– self-reported (c. 15% no response for NPTS)

– categories, quantiles, density function


Example Raw Income Data

income class


1999 Household Income

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

$2,5

00

$7,4

99

$12,

499

$17,

499

$22,

499

$27,

499

$32,

499

$37,

499

$42,

499

$47,

499

$52,

499

$57,

499

$62,

499

$67,

499

$72,

499

$77,

499

$82,

499

$87,

499

$92,

499

$97,

499

$100

,000

Household Income

freq

uen

cy

source: 2000 Current Population Survey, Census Bureau


NPTS 1995

6,22313,712

18,91925,326

29,72936,663

44,20852,918

66,898

117,033

$0

$20

$40

$60

$80

$100

$120

$140

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

HH income deciles

av

era

ge

HH

in

co

me

(0

00

)

source: NPTS (1995)


Shares of Income by Decile

1.5%3.3%

4.6%6.2%

7.2%8.9%

10.7%

12.9%

16.3%

28.4%

6.2 13.7 18.9 25.3 29.7 36.7 44.2 52.9 66.9 117.0

HH income deciles

sh

are

of

tota

l in

co

me

source: NPTS (1995)


Peak Congested Trips Selected NPTS trips

– mode = auto, SUV, van, or pickup

– start time = 6:30 to 9:30 AM or 3:30 to 7:00 PM

– travel day = weekday

– place = urban, suburban, or second city (not town or rural or undetermined)

– n= 52,000 out of 409,000 trips

Ignores– peak direction

– trip length

– degree of congestion (demand vs. capacity)

– occupancy


Tax on Peak Trips

Each trip charged a fixed amount

– same amount (“toll”) for each trip

“Tax” is borne entirely by any person currently driving in the peak

– whether they stay or change is not considered (yet)


Distribution of Peak Trips

4.0%

6.0%6.9%

8.5% 9.0%

10.3%

11.8%12.7%

14.4%

16.4%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

HH income deciles

sh

are

of

pe

ak

tri

ps


Peak Trips versus Income

share of household

income

share of peak highway trips

0%

5%

10%

15%

20%

25%

30%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

HH income deciles

sh

are

of

inc

om

e,

pe

ak

tri

ps

(%

)

source: NPTS (1995)


Distributional Analysis

Restate impact of policy as a percent of income for each income class

Horizontal line is neutral; falling (tax) is regressive


Peak Trips as Percent of Income

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

HH income deciles

pe

ak

tri

ps

as

% o

f in

co

me

source: NPTS (1995)


Observations

Tax impact generally rises with income, but not as rapidly

A tax per trip on existing peak travelers is mildly regressive, according to these data

Data are noisy, and noise tends to flatten the distribution (i.e., toward random)

Permanent income reduces regressiveness


Shares of SR-91 Users by Income Group

19%

23%

37%

21%

0%

5%

10%

15%

20%

25%

30%

35%

40%

% income < $40,000 % income < $60,000 % income < $100,000 % income >%100,000

income group

per

cen

t


Histogram of SR-91 Users by Income

21%

37%

23%

19%

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0 20 40 60 80 100 120 140

household income ($000)

freq

uen

cy


Histogram with Fitted Density Function

72.3

average income

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0 20 40 60 80 100 120 140 160 180 200

household income ($000)


Distribution Fitted to 1999 Household Income

calculated sample mean

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0 50 100 150 200 250

annual household income ($000)

rela

tive

fre

qu

ency


$72.3

average income

$83.154.842

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0 20 40 60 80 100 120 140 160 180 200

income ($000 per year)

freq

uen

cy


Relative Burden Function

constant distn. income

distn. toll

HH total classin HH of %income total class of income %

HH total classin HH of % tolls total classby paid tolls%

ncome$payments/i


Direct Burden for SR-91

SR91X

SR91

Poll Tax

0

1

2

3

4

5

6

0 20 40 60 80 100 120 140 160 180 200


2. Recycling of Revenues

Fuel excise tax, general sales tax, local property tax reduction

Consumption of gasoline and oil as percent of income/expenditures– excise tax is proportional to gallons,

not to dollar amount paid (i.e., not a sales tax)

Compare revenue-neutral policies


Distribution of Gas/Oil Expense

4.0%

5.4%6.2%

8.0%9.1%

10.5%

11.9%

13.4%14.6%

16.7%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%CU expenditure deciles

sh

are

of

ga

s/o

il e

xp

en

se

s

source: Consumer Expenditures in 1999 (BLS)


Gas and Oil Expenditures by Decile

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%CU expenditure decile

gas

olin

e/o

il as

% o

f ex

pen

dit

ure

s

source: Consumer Expenditures in 1999 (BLS)


Gasoline Expenditures as % of Income

0

0.5

1

1.5

2

2.5

3

3.5

$0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000

annual household income before taxes

per

cen

t o

f in

com

e sp

ent

on

gas

olin

e an

d o

il


Comparison of Two Taxes

peak highway trips

gas and oil expense

0%

1%

2%

3%

4%

5%

6%

7%

0% 20% 40% 60% 80% 100%

HH income deciles

trip

s,g

as

as

sh

are

of

inc

om

e


3. Shifting and Incidence Individuals who change behavior

reduce the burden of the tax/toll on themselves; those who stay and pay bear the full brunt

More careful analysis has been done for national tax instruments, but not for congestion tolls or “value pricing”

Behavioral responses can be estimated, but data are very few


Shifting the Burden

If employers pay commuting, burden is shifted to owners and customers

If costs are tax deductible, burden is diffused among taxpayers

Behavior changes to avoid the tax/toll cause some redistribution of the burden

Not zero-sum; delay is “deadweight” loss

e.g., tax on luxury (>100 feet) yachts


Supply-Demand Elasticities

S

S+tax

excise tax

Demand

q0q1

p0

ps

pcshare paidby consumers

share paidby suppliers


Behavior Changes No change

– high time-value travelers may prefer time savings with toll

Shift route

– increases time for traveler, impacts travelers on parallel routes

Shift to carpool or transit

– may leave traveler better off (cost plus time), impacts other modes

Shift time

– traveler worse off than before but less than paying the toll

Shift locations

– workplace or residence or other destination


Correcting Vertical Equity Impacts

Use of revenues from congestion pricing (Small rule)

– reduce general taxes or other user fees

– improve attractiveness of alternative transportation modes

– redistribute revenues according to income (low income receives largest compensation)

Documents

Distributional Impacts of Congestion Pricing