Download Economic Characteristics of the Joint Infrastructure Provision: The

Economic Characteristics of the Joint Infrastructure Provision: The Case of Electricity and
Natural Gas Distribution
Muzeyyen Anil Senyel1, Jean-Michel Guldmann2
Urban infrastructures are characterized by considerably high investment costs, which make them
almost irreversible. Once the construction is completed, it is very difficult and expensive to
modify the systems. Therefore a detailed cost analysis should be carried out in advance, to
prevent unprecedented future charges and to provide reliable infrastructure services. This study
aims to reveal the economic characteristics of urban energy (electricity and natural gas)
distribution costs, with a particular focus on the economies of scope (EoS). Both total and
underground distribution costs are modeled to see the effect of site-specific variables in a detailed
way.
Urban utilities provide either a single service (electricity, natural gas, water, telecommunications,
etc.) or multiple services in different possible combinations. It is expected for multi-utilities
having economic incentives to provide joint services, such as the efficient use of resources and
savings from the joint capital infrastructure and labor. However, under some conditions such
advantages may turn into disadvantages. EoS measure the level of cost advantage/disadvantage
arises from the joint provision of services, and eventually to decide either consolidation or
unbundling is more rational for a utility.
Infrastructure utility costs are substantially determined by outputs; such as sales, number of
customers and input prices. Site-specific urban and geographic conditions are likely to impact
costs, particularly capital infrastructure costs. In the literature, however, very few EoS studies
include urban and geographic factors in energy distribution cost modeling. Indeed, the only
considered site-specific variable has been density (Sing, 1987 and Farsi et al., 2008). Moreover,
the existing literature on EoS uses aggregate and company level data, which tends to disregard
the site-specific level characteristics. The studies indicate that economies/diseconomies of scope
are highly dependent on the selected functional form. Most of them suggest that EoS decrease
with increasing firm size, which implies that small firms should consolidate, whereas unbundling
may be the better strategy for very large firms.
Neo-classical economic theory assuming a firm producing outputs with a given set of inputs
constitutes the basis of the methodological approach of this study. The production function
concept is extended to multi-product and multi-dimensional industries by using the
transformation function concept (Eq. 1). The multi-utility firm considered here provides two
outputs (Q1, Q2): electricity and natural gas, which is characterized by a transformation function
that summarizes the feasible substitutions between these outputs and input prices (capital, PK,
labor, PL, and energy; PE). In addition to the input-output variables, urban and geographic factors
are included in cost model, in terms of a vector of site specific variables (ST). Because there is no
agreed-upon theory regarding the functional form of the capital cost function, Box-Cox
1
PhD, Department of City and Regional Planning, Middle East Technical University, Ankara, Turkey. [email protected]
Professor Emeritus, Department of City and Regional Planning, The Ohio State University, Columbus, OH, USA.
[email protected]
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regression, which is itself a flexible form allowing for the endogenous determination of the
parameters, is considered.
CK = fK(Q, PK, PL, PE, ST)
(Eq.1)
Once the cost function is estimated, the extent of EoS can be assessed. Such economies take
place if the joint provision of outputs is cheaper than the separate provision through two distinct
utilities (Eq. 2).
C(Q1, Q2, PK, PL, PE, ST) < C(0, Q2, PK, PL, PE, ST) + C(Q1, 0, PK, PL, PE, ST)
(Eq. 2)
The database includes four electricity and natural gas distribution companies (Central Hudson
Gas and Electric Company, Long Island Lighting Company, Niagara Mohawk Power Company,
and Orange and Rockland Companies) serving customers in the state of New York, census of
population, and geographic data, which are all available at the tax district (city, village or town)
level. Although census of population and geographic data are available for the all 1619 tax
districts in the State, company data is available for 246 tax districts. While only 15% of the tax
districts are included, the data cover almost all highly populated areas (except New York City),
with almost 32% of NYS population. Indeed, New York City is intentionally excluded, which
tends to reflect an outlier position, and should be analyzed by its own or together with
comparable urban areas in terms of population size and density. In 186 districts electricity and
gas are jointly served, while in 60 districts electricity is served by a single company. Almost all
natural gas investment is underground, whereas electricity can be delivered through overhead or
underground conductors. As a result, the tax district sample size is smaller (234) regarding
underground investments, with 48 districts having only electricity data and 186 districts having
both electricity and natural gas data. Census data cover almost all types of demographic and
housing factors, and site specific data include land-use, soil, slope, and street variables.
The regression results show total cost is a function of total electricity sales in kWh, total gas sales
in mcf, electricity fuel price, natural gas fuel price, number of street intersections, and the share
of old housing units (40 years and more). Output variables (electricity and natural gas sales) are
significant with a positive sign as expected. Higher fuel prices also increase costs. The number of
street intersections is significant, which can be interpreted as the effect of urban form on costs.
Increasing number of street intersections makes the distribution network more complicated,
which increases costs. Old housing stock can be considered as a proxy for the central highdensity neighborhoods, which may require special pavement in worn and narrow streets, and
more maintenance. Underground cost function has the same variables, with an addition of the
steel corrosivity of the soil. It is plausible for corrosivity has a statistically significant effect on
underground capital costs, since corrosion calls for special precautions and extra coating.
EoS analysis shows that, joint provision of electricity and natural gas is more cost efficient than
to serve them separately. Scope scores are calculated for different levels of electricity and natural
gas outputs, as well as different levels of price and site specific variables, which do not turn into
diseconomies in any output or variable combinations. Scores tend to decrease with increasing
outputs, while the number of street intersections turns out to have the greatest impact.
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As a result, not only output levels and input prices but also urban and geographic factors are
influential on the electricity and natural gas capital investments. EoS exist in both total and
underground investments, which make joint provision economically more feasible than the
separate provision.
References:
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Evidence from Gas, Water and Electricity Combinations. Applied Economics, vol. 36, pp.
2045-2057.
Mayo, J. W. 1984. Multiproduct Monopoly, Regulation, and Firm Costs. Southern Economic
Journal, vol. 52, pp. 208-218.
Ottoz, E. and M. Di Giacomo. 2012. Diversification Strategies and Scope Economies: Evidence
from a Sample of Italian Regional Bus Transport Providers. Applied Economics, vol. 44,
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Sing, M. 1987. Are Combination Gas and Electric Utilities Multiproduct Natural Monopolies?
The Review of Economics and Statistics, vol. 69, no. 3, pp. 392-398.
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