The impact of ownership on the cost of bus service provision: an example from Italy

TL;DR: In this article, the authors examined the potential impact of ownership on the cost of bus service provision for a sample of 65 private and 12 public companies providing local public transit (LPT) in Piedmont (Italy) from 1998 to 2002.

Abstract: This article examines the potential impact of ownership on the cost of bus service provision for a sample of 65 private and 12 public companies providing local public transit (LPT) in Piedmont (Italy) from 1998 to 2002. A translog cost frontier is estimated using the model in Battese and Coelli (1995) where inefficiency scores are allowed to vary across firms and over time. A public ownership dummy is included in the inefficiency model and it is always positive and significant. Density and scale economies and cost inefficiencies are then computed. Private companies seem to experience higher density and scale economies than public ones. Cost inefficiencies appear higher in the public sample.

Summary

1 Introduction

• The aim of this paper is to investigate the influence of ownership on the cost characteristics of a sample of bus companies operating local public transport (LPT) in Piedmont, a North Western region of Italy, and to draw some policy conclusions from such evidence.
• A translog cost frontier is estimated using the model in Battese and Coelli (1995) and the public ownership dummy, included in the inefficiency model, is always positive and significant pointing to higher inefficiencies for public companies.

2.1 Measuring inefficiency

• The aim of the paper is to give some evidence on the role of ownership on the efficiency of LPT firms.
• While c(.) is the deterministic cost structure, exp(v) represents the effect of exogenous shocks and exp(u) is the inefficiency.
• In a fixed effects model (firstly proposed by Schmidt and Sickles, 1984, in a frontier context) no distributional assumptions are imposed on the inefficiency term while since Pitt and Lee (1981) seminal contribution, random effects estimators are based on the imposition of a particular distribution on the inefficiencyii .
• Under the assumption of no correlation among the error terms and the regressors, distributional assumptions are imposed to both v and u terms.
• In their empirical application the authors decided: (a) to impose the influence of a set of external factors on the mean value of the truncated distribution of the inefficiency term and (b) to test the validity of the inclusion of another set of external factors into the cost technology.

2.2 The translog cost function

• A total cost function is estimated: TC = c(Y, N, pL, pM, pK, τ, Type of service) where total cost TC is a function of output Y, network dimension N, input prices for labour, other variable inputs and capital respectively (pL, pM, pK) and a time trend which approximates technology, τ.
• Summing up public firms are characterised by larger size and mixed urban and intercity services, while private firms mainly supply intercity services and they are smaller in terms of number of employees, vehicles and supplied bus-kilometres.

4.2 Density and scale economies in the bus industry

• They may produce interesting results as an automatic byproduct.
• Input prices are held fixed at the mean value of the whole sample.
• The number of vehicle-kilometres is much lower for intercity transport firms and this evidence allows for the existence of higher economies of density, that cannot be exploited as long as the type of service does not change and is constrained by a low level of demand.
• They present an inefficiency score of 1.033, whereas public firms in the range 150-250 employees, have an inefficiency score of 1.30.
• Xii Public companies show on average small economies of scale (1.072) while for private firms economies of scale are more relevant (1.151).

4.3 Inefficiency indicators

• Table 5 reports the estimates of the mean cost-inefficiency for the whole sample and separately for the two groups of public and private firms by different size classes to examine the possible correlations between firm size and inefficiency.
• The methodology itself is different as Fraquelli et al. compute the long run scale economies using the total number of places offered times km run as output variable and network size is not included.
• Characterised by particularly low levels of inefficiencies are excluded, (1.21 vs. 1.30, see footnote xiv)xv.
• Estimated inefficiencies are much higher under specification 1 (mean inefficiency 18%) but this result is not surprising as long as the two specifications give different measures of inefficiency.
• The influence of ownership on the provision of local public transport appears to be a relevant issue for policy makers, with particular attention to efficiency and economies of scale of the two groups, which should be carefully taken into account in the design of a transport policy.

Acknowledgments

• The authors wish to thank Luca Sanlorenzo for excellent assistance on the data and Massimo Filippini and Massimiliano Piacenza for helpful comments.
• The authors are also grateful to the participants to the Hermes Workshop on Local Public Transit, Moncalieri, July 18, 2005 and to the 4th North American Productivity Workshop (NAPW), New York, June 27-30.
• Financial support from Hermes (Higher Education and Research on Mobility Regulation and the Economics of Local Services) Research Centre is acknowledged.

6 References

• Battese G.E. and Coelli T.J., (1993), A Stochastic Frontier Production Function Incorporating a Model for Technical Inefficiency Effects, University of New England, Working Papers in Econometrics and Applied Statistics, n. 69.
• Coelli T. J. , Rao D. S. and Battese G.E., (1998), An introduction to efficiency and productivity analysis, Kluwer Academic Publisher, Boston.

Full text

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The impact of ownership on the cost of bus service
provision: an example from Italy
Ottoz, Elisabetta; Fornengo, Graziella; Di Giacomo, Marina
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www.peerproject.eu
Empfohlene Zitierung / Suggested Citation:
Ottoz, E., Fornengo, G., & Di Giacomo, M. (2009). The impact of ownership on the cost of bus service provision: an
example from Italy. Applied Economics, 41(3), 337-349. https://doi.org/10.1080/00036840601007260
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For Peer Review
The impact of ownership on the cost of bus service provision: an example
from Italy
Journal: Applied Economics
Manuscript ID: APE-06-0038.R1
Journal Selection: Applied Economics
JEL Code:
C23 - Models with Panel Data < C2 - Econometric Methods: Single
Equation Models < C - Mathematical and Quantitative Methods, L92
- Railroads and Other Surface Transport: Autos, Buses, etc. < L9 -
Industry Studies: Transportation and Utilities < L - Industrial
Organization, L33 - Public versus Private Enterprises; Privatization
< L3 - Nonprofit Organizations and Public Enterprise < L - Industrial
Organization
Keywords: local public transport, ownership, cost frontier
Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK
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1 Introduction
The aim of this paper is to investigate the influence of ownership on the cost
characteristics of a sample of bus companies operating local public transport (LPT) in
Piedmont, a North Western region of Italy, and to draw some policy conclusions from such
evidence.
The choice of a regional extent is consistent with the Italian regulatory framework
issued from the LPT reform process, started with Law 542/1997, which transferred
functions, tasks, goods, infrastructures, human, financial and organizational resources to the
local authorities corresponding to the Italian regional governments, making them
responsible for planning and policies relative to LPT in their territorial jurisdiction.
In particular local authorities are responsible for the competitive tendering procedure
introduced for the assignment of franchised monopolies in LPT services. Boundaries of the
service areas, which generally reflect the provinces and municipalities jurisdictional
boundaries, have been defined through transport plans obtained simply by adding up the
existing routes, without taking into account scale economies or diseconomies experienced
by bus companies or the fact that the area size determines which firm will be able to
compete for tenders.
The example of Piedmont. with the metropolitan area of Torino can be generalised to the
other Italian regions, being
one of the most important Italian areas both in terms of population
and economic relevance. Responsibility and financial resources for local public transport
have been here assigned by the regional government to the delegated authorities, identified
in 8 Provinces responsible for inter-city transport and in 16 large municipalities for urban
services. Single LTP firms, both publicly and privately owned, which previously had the
licence to provide bus service on the different lines, are now gathered in temporary groups
to supply local transport in a service area.
i
i
In order to allow the widest possible participation of small and medium firms in tenders, which because of
their technical, organisational and financial complexity would otherwise be beyond the possibility of a single
firm or small firms, the EU law maker explicitly admits that groups of economic operators may submit
tenders or put themselves forward as candidates.
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As both publicly and privately owned firms are involved in the LTP industry and in the
temporary groups recently created to take part in provincial tenders, the influence of
ownership on the provision of bus service appears to be a relevant issue for policy makers,
with particular attention to efficiency and economies of scale of the two groups, which
should be carefully taken into account in the design of a transport policy, aimed at
improving efficiency.
Many theoretical arguments suggest that privately owned firms should outperform
publicly owned ones: “the dominant positive model on the effect of ownership is the public
choice or property rights model.” (Boardman and Vining, 1989).
According to this view politicians, senior bureaucrats and tax-payers have attenuated
property rights, as compared to private owners, to the gains associated with improved
performance and, hence, lesser incentives to foster improvements; on the other hand public
sector managers have more incentives to act on their own self interest, pursuing goals other
than those of their agency.
These arguments have been challenged, though: both ownership and the degree of
competition faced by a firm are relevant when assessing its performance (Vickers and
Yarrow, 1989) and in a natural monopoly the presence of regulations, incomplete
information and transaction costs may hamper the role of markets, so that there might be
inefficiency from regulation of private firms (Hodge, 2000). Finally there is little evidence
that bureucrats effectively behave in a manner predicted by public choice theory (Martin
and Parker, 1997).
Many recent empirical studies, based on both parametric and non parametric
approaches, have recently tackled the problem of a different level of efficiency in private
and public companies, without reaching any conclusive evidence.
In the field of LPT Perry and Babitsky (1986) and Berechman (1993) find that private
companies are more efficient than public ones, although they attribute such a result to the
competing structure and not to ownership. For Chang and Kao (1992) and Kerstens (1996)
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private companies perform better in Taiwan and in France, whereas Viton (1997) doesn’t
find any significative difference in the U.S. market, just as Jorgensen et al. (1997), as well
as Odeck and Alkadi (2001) in their research on Norwegian buses. Finally Mizutani and
Urakami (2003) in the Japanese case and Roy and Billion (2005) in urban transport in
France, find that private firms are more efficient, whereas Filippini and Prioni (2003) reach
ambiguous results.
We deal with an unbalanced panel of 77 LPT companies operating over the period
1998-2002. The sample has the peculiarity of including both public and private companies,
whereas the preceding Italian studies were based on municipal companies only. A translog
cost frontier is estimated using the model in Battese and Coelli (1995) and the public
ownership dummy, included in the inefficiency model, is always positive and significant
pointing to higher inefficiencies for public companies. Inefficiencies are also increasing
with firm size for both public and private units. Density and scale economies are then
computed and private companies seem to experience higher density and scale economies
than public ones.
The paper is organized as follows. Section 2 sets forth the econometric model: the
flexible translog cost function is exploited in order to identify density, scale and cost
inefficiencies, comparing the different features of private and public companies. Section 3
describes the dataset. Section 4 discusses the main findings. The last section presents some
concluding remarks.
2 The empirical model
2.1 Measuring inefficiency
The aim of the paper is to give some evidence on the role of ownership on the
efficiency of LPT firms.
The panel structure of the data is exploited and the model in Battese and Coelli (1995),
which allows for the estimation of firm specific inefficiencies that vary over time, is thus
implemented (see Coelli et al., 1998 and Kumbhakar and Lovell, 2000, for a review of the
theoretical and empirical literature on productivity analysis; see Piacenza, 2001, for a
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Frequently asked questions

Q1. What are the factors that are included in the efficiency scores?

Transaction costs, overhead costs, high wages obtained in large firms because of trade unions’ higher bargaining power are also included in efficiency scores. 

Q2. What are the contributions in this paper?

For more Information regarding the PEER-project see: http: //www. peerproject. 

Q3. What is the impact of ownership on the provision of local public transport?

The influence of ownership on the provision of local public transport appears to be a relevant issue for policy makers, with particular attention to efficiency and economies of scale of the two groups, which should be carefully taken into account in the design of a transport policy. 

Q4. What are the two sets of estimators for cost frontier functions?

In the empirical literature on stochastic frontier functions, where panel data are available, at least two sets of estimators have been proposed (see Sickles, 2005 and Greene, 2002, 2004 for recent surveys on panel estimators for parametric and non parametric frontiers): fixed effects and random effects estimators. 

Q5. How many employees does the dummy variable represent?

In order to control for the possibility of spurious relationships, the authors decided to include a set of dummy variables: SMALL, that equals one if the firm has less than 50 employees, MEDIUM, equal to one if the firm has more than 50 and less than 150 employees and LARGE that equals one if the firm has more than 150 employees. 

Q6. What is the main caution when using a set of different variables as external influences?

The authors are going to use a set of different variables as external influences, assuming thatthey all are exogenous (i.e. out of the firm control) at least in the five years of their panel. 

Q7. What is the significance of the interaction terms with PUBLIC dummies?

However the estimations for the interaction terms with PUBLIC*INTERCITY and PUBLIC*URBAN dummies are negative and bigger than 0.069 in absolute values. 

Q8. What is the dummy in the inefficiency model?

A translog cost frontier is estimated using the model in Battese and Coelli (1995) and the public ownership dummy, included in the inefficiency model, is always positive and significant pointing to higher inefficiencies for public companies. 

Q9. What are the results of the papers by Mizutani and Urakami?

The results are mixed: while Filippini and Prioni (2003) do not reach clear-cut outcomes, the papers by Mizutani and Urakami (2003) and Roy and Billion (2005) point to higher costs and higher inefficiencies respectively for publicly owned bus companies. 

Q10. What is the significance of the parameter estimates for PUBLIC dummy?

The parameter estimates for PUBLIC dummy is positive (0.069) indicating the presence of significant higher inefficiencies for publicly owned companies.