Pricing of Transport Networks, Redistribution, and Optimal Taxation

• Author: ANTONIO RUSSO
• Published date: 01 October 2015
• DOI: http://doi.org/10.1111/jpet.12103
• Date: 01 October 2015

PRICING OF TRANSPORT NETWORKS,REDISTRIBUTION,

AND OPTIMAL TAXATION

ANTONIO RUSSO

KOF Swiss Economic Institute

Abstract

The author studies optimal pricing of roads and public

transport in the presence of nonlinear income taxation. In-

dividuals are heterogeneous in unobservable earning abil-

ity. Optimal transport tariffs depend on time costs of travel

and work schedule adjustments (days and hours worked per

day) as a response to commuting costs. The author finds

that discounts for low-income individuals are optimal only

if the time cost of a trip is small enough. Lower travel time

costs facilitate screening; therefore, redistribution provides

an additional motive for congestion pricing. Finally, the

study investigates the desirability of means-testing of trans-

port tariffs.

1. Introduction

It is often argued that prices on urban transport networks should reflect

social costs of travel. As roads suffer from congestion externalities, economic

theory suggests that congestion pricing can increase efficiency. Clearly,

this may also have an impact on the distribution of welfare across society.

Indeed, policymakers often care about redistribution when designing

prices for publicly provided transport infrastructure. Concerns of a possible

regressive effect recently impeded the introduction of road pricing in

Antonio Russo, KOF ETH Zurich, Leonhardstrasse 21, 8092, Zurich, Switzerland

(russo@kof.ethz.ch).

I thank Georges Casamatta, Helmuth Cremer, Bruno De Borger, Philippe De Donder,

Jean-Marie Lozachmeur, Stef Proost, Emmanuel Thibault, the editor, and two anonymous

referees for useful comments and suggestions. All errors are mine.

Received June 26, 2013; Accepted July 11, 2013.

C2013 Wiley Periodicals, Inc.

Journal of Public Economic Theory, 17 (5), 2015, pp. 605–640.

605

606 Journal of Public Economic Theory

New York City and Paris.1Plans for a road pricing scheme in San Francisco

include a tariff discount to low-income drivers. Moreover, discounted public

transport fares are commonly granted to less affluent households. This is

the case, to make an example, of the “Forfaits Solidarit´

e Transport” in the

French Ile-de-France region. Furthermore, governments often subsidize

commuting expenditures (e.g., through tax exemptions) for reasons that

include helping disadvantaged workers.

Economic literature has looked at redistributive issues in pricing of trans-

portation infrastructure (Small and Verhoef 2007). However, it has done so

(with an important exception discussed later) ignoring the presence of in-

come taxation. This leaves open the question of whether such concerns are

actually relevant, as they could possibly be addressed with appropriately de-

signed income taxes. The main objective of this paper is to study such a

question. I consider the problem of a welfare-maximizing government that

designs both income taxes and tariffs for roads and public transportation.2

Individuals are heterogeneous in (exogenous) earning ability, which is as-

sumed to be private information, as is their labor supply. Thus, the govern-

ment faces self-selection constraints that may limit welfare redistribution. To

keep the setup as simple as possible, I use a model with only two types of

individuals (´

alaStiglitz 1982).

It is well established that nonlinear tariffs are a crucial ingredient of

efficient pricing policies in network industries (Wilson 1993). They are

drawing increasing interest also in transportation, although their potential

redistributive role (recognized in other regulated industries, such as en-

ergy or telecommunications) has not been explored.3This is why I con-

sider them in this paper. Nonetheless, nonlinear pricing of transport services

may not always be implementable (at least at reasonable costs).4Hence, I

also look at the case in which the government is constrained to use linear

tariffs.

Previous public finance literature has studied how (if at all) a gov-

ernment that can use income taxes should deviate, due to distributional

1In a recent interview, New York State Assemblyman Richard L. Brodsky said he opposed

its introduction “for the reason that these schemes put the burden for paying the fees on

blue blood and blue collar alike” (see New York Times, “Congestion Pricing: Just Another

Regressive Tax?” http://www.nytimes.com)

2The term “tariff” should be given a broad interpretation here: since the government

controls taxes and prices, tariffs I describe may result not only from fares or tolls, but also

from commuting subsidies in the form of tax deductions.

3See Wang, Lindsey, and Yang(2011) for a study of nonlinear pricing of tolled roads and

Batarce and Ivaldi (2011) for public transportation. Cremer and Gahvari (2002) study

nonlinear pricing by a regulated firm in the presence of optimal income taxation.

4It is indeed quite demanding in informational terms, since observability of individual trip

quantities is necessary. This information is not rarely available though: for example, most

road pricing schemes involve the use of electronic tolling systems that keep track of indi-

vidual accesses to the tolled road. Moreover,governments often h ave accessto commuting

data collected by employers. I discuss feasibility issues at the end of Section 2.

Pricing of Transport Networks 607

concerns, from correcting externalities (Cremer, Gahvari, and Ladoux 1998,

Bovenberg and Goulder 2002, Kaplow 2006). However, it has disregarded

two relevant features for transportation, which are central in my analysis.

The first is that consumption of transport goods requires travel time.

Boadway and Gahvari (2006) and Gahvari (2007) consider time of consump-

tion in an optimal redistributive taxation framework. They do not consider

externalities.5Mayeres and Proost (1997) study optimal redistributive

taxation in the presence of congestion externalities, but restrict attention

to linear taxes. Using such an approach, pricing of transport infrastructure

may be a means to compensate for inappropriate tax instruments. I do not

impose restrictions on the design of income taxes (it is constrained only by

the available information).

A second key feature of my setup is that I explicitly model the relation

between travel and labor supply. Individuals can decide the number of

days at the workplace (which require commuting) and daily work effort,

measured by the length of working days (i.e., daily work hours). Although

employers may allow little flexibility in adjusting days and hours worked, in-

dividuals may choose between jobs offering different schedules: for instance,

a job with either a four-days-a-week schedule or a five-days-a-week one requir-

ing shorter daily shifts.6Intuitively, the presence of commuting costs may

encourage to choose the former.7However, productivity may diminish when

the length of working days increases. This is due to fatigue and difficulty in

scheduling more work activities in a single day. For example, opportunities

to interact with colleagues or customers might be diminished when working

at early or late hours. Hence, in my setup, substituting working days for

more daily effort implies a penalty in terms of hourly productivity.

While labor supply plays a central role in models of income taxation,

little attention has been dedicated to the impact of policies that affect com-

muting to work. Parry and Bento (2001) and Van Dender (2003) consider

5Cremer et al. (1998) and Kaplow (2006) studied environmental levies in the pres-

ence of nonlinear income taxation. They consider a model where commodities do not

require any time for consumption. Moreover, they focus on externalities that do not affect

the marginal cost of consuming goods, unlike traffic congestion. An optimal taxation

model with time as input for activities and congestion externalities is also studied in De

Borger (2011). He uses a representative agent framework.

6Looking at German data, Guti´

errez-i-Puigarnau and van Ommeren (2010) find that

about 16% of workers have changed the number of workdays over the period of observa-

tion (1997 to 2007). They also note that while the proportion of workers that work exactly

five days per week is high (83%), it is falling over time. Much greater variation is found in

daily hours. Similar evidence (for United States and Germany) is reported in Hamermesh

(1996). Both suggest that workers satisfy their demand for different schedules mostly by

changing jobs.

7Commuters may also have other margins of flexibility in responding to changes in travel

costs: they may change residence or shift travel to off-peak hours (Arnott, De Palma, and

Lindsey 1993). A discussion of their likely impact on my results is provided in the conclud-

ing remarks.