- Length: 16 pages
- Sources: 5
- Subject: Transportation
- Type: Term Paper
- Paper: #6894998
- Related Topics:
__Regression Analysis__,__White Noise__,__Fixed Costs__,__Variable__

Introduction

The study of the cost structure of the railway transportation industry has receives a considerable chunk of academic literature attention. For example Caves et al. 1980,1981a,1981b.1985;Freeman et al. 1985;Dodgson et al. 1985;Wunch 1996;Oum et al. 1999; Cantos et al. 1999.All these pieces of literature focused on the study of the running and operation of railway systems. Through the years, research work has demonstrated the very large variation in the cost efficiency or productivity that is usually present within a selected sample of railway companies. The factors underlining this variance have also been developed in terms of the cost and production function viewpoint.

In the rail way efficiency literature, it is noted that a prominent theme that is most discussed is the subject of return to scale (RTS).TRS is also referred to as return to density (RTD).Return to density is used to describe the correlation between all the aspects of inputs and the summation of all the firms operations. Such operations would normally include elements such as the total output and the entire network size. The RTS component is used in describing the relationship that exists between the input component of the railway network and the output components while the railway network itself is held fixed.Circumstancial evidence in the literature reveal that RTS are as a result of the existence of fixed costs in the railway business. It can also be attributed to the existence of a certain range of semi-fixed costs that do not bear a direct correlation with the industry's input. Several other less consistent evidence exists to support the notion of the existence of elements of economies of scale. However the running of a railway service is always undertaken under a constant return to scale.

The operation in the railway stations may provide a vital source of increasing the level of RDS in Metro operations. It is critical to ensure that the station is continuously staffed and in proper operation with all the energy and other elements running at all times. Several factors however may cause a variation in the running cost of one metro station to another. Such factors include the type of engineering, the station's depth, the size and the dimensions of station, the nature and degree of technology rolled and many other factors. The cost of a running a railway station can be conceived to be semifixed and can be considered to not to be varying proportionately with the system output. This fact makes the cost to be of paramount importance in the process of increasing the RTD.

In this paper, we come up with an econometric model to study and analyze all the variances in the cost of operating a metro station. An econometric model then becomes paramount in the process of determining the effects of certain characteristics of the station on its cost of running and other more factors that also affect the running cost in other ways. It is worth noting that it is almost impossible to deduce from historical data the effects of certain factor in the running of a metro station. We analyze data from a total of 83 stations and 13 metro systems from various cities of the world. From the analysis we try to zero in on the major drivers of cost by way of approximation. The result presented is then used in the estimation and the discussion of the model description.

Model description

The data used in our analysis describes the total sum of each metro station's operating cost and the various metro station characteristics that are unique to the 13 metro stations. The metro stations that were considered in this study include the following:Buernos Aires, Hong Kong MTR., Hong Kong KCR, Dublin, Lisbon, Montreal, London, Taipei, Singapore, Sao Paulo, Toronto, Glasgow and Naples. In the subsequent analysis, we consider a regression of the total cost of operating a metro station against the characteristics of the station in order to determine the role of these characteristics in the various variances in the cost of running the metros.

In this study we do not adopt the usual cost function approach in the analysis. The cost function cannot be determined in this study since we do not possess the data on the prices factor. The reason for dropping the cost factor is because the operating cost of an individual station cannot be used as the appropriate measure or unit against which the cost decisions are based. For example, the operation of the metro stations does not require factor inputs at the level of the station in relation to the costs and operations for the railway system in general.

In addition, it would be erroneous to associate any particular behavior to be peculiar to an individual station. Such behavior would include items or elements of cost minimizing behavior. It is usual for a metro system not to adopt a certain level of operational efficiency by allowing a certain controlled amount of discrepancies in efficiency in order to realize a broader goal and/or objective that is associated with a certain reasonable level of system output that is reflected in the subsequent overall cost of running the metro.

In light of the above mentioned factor, what is of real importance in our analysis is the way and the extent to which the metro station characteristics serve to bring an influence on the total overall costs. It is worth mentioning once again that there is an absence of the factor price data as this is definitely important in the determination of the station costs. In order to gain control over these omitted variables, we must estimate the operating costs of the metro station by use of certain set of dummy variables. These dummy variables must be representative of the 13 metro station systems. The assumption that we must hold with the use the deployment of these dummy variables is that they will aid in the capture of certain unobservable system-specific effects such as the factor prices.

In coming up with the model to represent the factors that influence the operating cost of a metro station, we use a log linear model below:

(1)

Where

Represent the total operating cost of a certain metro station

Represent a vector (kx1) that is for continuous explanatory variables in nature and utilized in the description of Station i's characteristics.

Represents a vector (mx1) used for the dummy variables that are associated with the metro stations

Represents white noise

Represents the yet to be estimated kx1 vector of parameters

Represents the yet to be estimated mx1 vector of parameters.

The analysis is based on a log linear scale since it reduces possibility of multicollinearity and therefore presents a more direct and straightforward parameter estimates for the present elesticities.In this analysis, the dependent variable is taken to be the annual operating cost of the metro station. This cost is made up of several other sub-costs that are either related to the money spent on the staff and other utilities such as water and electricity. Other forms of utilities that make up the cost are the costs associated with the repair of lifts, and the cost incurred in the maintenance of several other integral systems e.g air conditioning. Building maintainence, CCTV and the ticketing system.

The equation (1) will be used in coming up with two econometric models. The first model is estimated without the metro system-specific dummy variables and then the second econometric model is estimated using the metro system-specific dummies in order to have a direct control over the country-specific effects on the operating cost of the metro stations

The following is the list of the explanatory variables which are used in the description of the station's characteristics and the corresponding hypotheses that we seek to test with the variables.

Age of the metro station -- the age of the metro station is considered in terms of the number of years taken from the time the station was first opened. An average is taken in case the station was opened in different stages. The hypothesis drawn…