1.0  INTRODUCTION

 

1.1  Introduction

Public transportation has been  and continues to be an important instrument in the development of American communities.  Every day people use buses, advanced rail systems, minibuses, vans, and other modes of public transportation to face the challenges of daily survival.  In some cases, public transportation is used to reduce traffic congestion, parking problems, and air pollution by decreasing the number of cars used by urban travelers. 

Public transit systems also help promote the economic growth of a community and supply its riders with increased mobility and independence by transporting individuals to work and other necessary activities.  Particularly for individuals who are unable to afford or use cars, transportation to work, medical facilities, shopping areas, and social services is vital in order for them to maintain healthy and full lives.  This is especially true for rural areas which are generally made up of elderly and low income populations.  Therefore, public transportation enhances the quality of life for those who may use them. 

Despite its importance to the communities and citizens, public transit system are suffering because of cutbacks in federal funding.  A decrease in financial support will cause some transit providers to reduce or discontinue their services.  If this happens, the individuals who would be most affected are the handicapped, elderly, young, and low income; more specifically, rural communities.

Rural public transit is an indispensable public service which is vital to the economic and social well-being of the rural community and its citizens. This study documents the linkages between public transportation and economic activities in rural areas of Arkansas, estimates the impacts of rural public transportation in the state of Arkansas and in the local communities, and develops new and augments current methodologies for estimating the economic impacts of Arkansas rural public transportation.  


 

In Arkansas, rural public transportation contributes to the enhancement of the quality of life for those individuals living in and around small towns.  Not only is it important for the economic health of those using it to commute to work, but it also provides for a means of transportation for patrons traveling to shopping centers, medical facilities, and social services.

Although the qualitative aspects of providing public transportation services in rural areas has been recognized, the quantitative data which represents the economic impacts of such services has not been fully explored.  The heart of this study focuses on the development of a conceptual framework for identifying and analyzing the tangible and intangible benefits of rural transit systems.  It is believed that this type of data will provide rural transit providers with an opportunity to link the economic strength of a region and the rural public transportation system which serves it.  This study will address the quantitative deficiencies that currently exist by estimating the economic impacts of Arkansas rural public transit systems.


 

2.0  REVIEW  OF RELATIVE  LITERATURE

2.1 Overview of Public Transportation

In order to understand the importance of public transportation, both historical and current issues related to public transit were examined.  The following sections outlines various topics covered in the literature that are related to this study. 

2.1.1  Past 

One of the earliest modes of public transportation was the omnibus line of Paris.  This horse-drawn wagon was operated by Pascal, the mathematician, in 1662.  During the initial period of operation, the omnibus line offered free services and was very successful in attracting passengers.  However, later when the fare was changed, the patrons rebelled and the drop in support caused Pascal to discontinue the services [27].  Despite the failure of this system, Pascal's omnibus gave birth to many public transportation services all across the world.

In 1831, the United States installed it's first major omnibus system in New York city [27].  Although expensive to ride, the omnibus was believed to have "strengthened the central business district of cities," by making "the central area the focal point for internal travel" [27,71].  According to Sam Warner's study of the growth in Boston between 1870 and 1900, the physical plan of metropolitan Boston depended on the development of urban transportation [71].  Other city omnibus services were setup, but only in large cities. 

The next mode of public transit introduced in the United States was the horse-drawn streetcar.  This vehicle, which had metal wheels operating on a metal rail, was larger and faster than the omnibus [27].  Streetcars offered a large variety of boarding and exiting stops, thus giving the patrons different options of destinations [71].  It also continued to magnify the strength of the central business district by carrying more people to their traveling destinations.  Streetcar systems were started in many cities of various sizes and the fare cost depended on the distance traveled [27].


 

Although their business was successful at this time, transportation managers wanted to eliminate the use of horses.  Specifically, for Boston, the streets were too narrow to carry all of the cars needed and the four mile street extending out from city hall was long and tedious for some riders [43].  In 1873, the first cable car was installed in San Francisco.  This system was drawn by a cable which ran continuously between the rails beneath the street.  The car had a mechanism that would grip the cable to move and release it in order to stop.  The cable car mode of transportation spread quickly, but it could only be used in relatively flat land areas [27]. 

During the mid 1880's, electric railway cars were being developed [27,70,71].  At first there were problems in getting the car to run smoothly on the rails, but in 1888 Frank Sprague installed a smooth running electric railway system in Richmond, Virginia.  Because of the faster speed, the electric rail cars enabled street railways to be extended farther out from the central business districts and allowed people to travel to work or to shopping areas within a half hour [27].  Particularly for Boston, the electric streetcar brought convenient transportation to a range extending six miles from the city hall.  This extension caused the rate of building and settlement to become so rapid that the physical plan of Boston was reconstructed [71].   "By the time of World War I, the electric streetcar had had a major impact on the growth and structure of cities" [27].  Since services were good and fare prices were relatively cheap, the electric transit system became the basic mode of transportation before the introduction of the automobile [27].

Also, during the introduction of the electric railway systems, public commuter services were being developed.  Commuting was believed to permit "persons of ordinary means the opportunity to find good housing and, perhaps a more favorable environment than was available in the major city center" [27].  One type of commuter service was the public ferryboat.  These systems allowed citizens, bound by water barriers, to travel to better jobs, markets, and other services.   Another type of commuter service was the public railroads.  Originally the traditional railroads were only used for freight deliveries, but later they transported people to cities and towns which were not within walking distance.  The railroad was a major link for many small communities which helped them to obtain social and economic growth [27,71]. 


 

By the mid 20th century the street railway business became bankrupt and the motor bus was introduced [27,70].  At first there were numerous motor problems and the buses were not very dependable.  As auto technology advanced, the motor bus became the ultimate mode of transportation in the United States.  Although these buses were not very comfortable to ride they were capable of transporting 50 or more seated passengers.   This helped to deal with the increased traffic congestion in growing urban communities.  The greatest advantage of the motor bus was its flexibility.  It could travel to different locations without the need to reconstruct or develop a railing system [27,70].  This flexibility enabled citizens living or working in non-centralized  areas (areas outside central business districts)  to travel to various locations.

2.1.2  Present 

It is believed, even from the beginning, that public transportation has been an important tool  "in the economic health and quality of life of an individual" [35].  In an article written by David Raphael, it was estimated that 75 million people are unable to provide or afford their own transportation and must rely on others for their mobility [53].  Of the 75 million, 26 million were older Americans, 24 million were people with disabilities, and 25 million were adults and children in poor families [53].  Public transportation becomes the link that helps people to maintain healthy and independent lives by transporting people to work, shopping centers, and social services [21,35,4972].

After World War II, there was an increased dependence on personal automobiles [27].  This dependence is stated to have the three following disadvantages:  restricts the mobility of those who are unable to afford cars, "causes inordinate energy consumption and is environmentally destructive", and many areas lack the space and money to accommodate an increase in auto traffic [27].  Therefore,  public transportation can be used to help reduce traffic congestion, parking problems, and air pollution by transporting car owners from one place to another [27,31,42,70,73].  Today buses, advanced rail systems, minibuses, taxis, and other modes of transportation are used to help citizens and communities handle the challenges of daily survival.


 

2.2  Types of Public Transportation Systems

There are two main types of public transportation systems: fixed-route and demand-response [27,28,47,70].  Extending from these two systems are numerous forms of public transportation systems and services.  A selected list of transit systems are discussed in the following sections.

2.2.1    Fixed Route Systems 

The conventional fixed-route systems usually consists of large capacity buses that run on a specified route and allow the loading or unloading of passengers at designated locations. This type of system is generally used in urban and suburban areas were the passenger supply is high and relatively constant [27,47,70].  Since there is a high demand for service, the fare cost is low and affordable for most patrons [27,47]. The sources of funding for these systems includes federal and state governments aids, fare box and contracted revenues, and state and local subsides [5,27,47,70,74].

Fixed-route systems are the most widely used transit service and are helpful in the efforts to control traffic congestion.  In many urban areas, transit operators include a "park and ride" route [27,47,70].  This route allows patrons to park their cars in a specific location outside of downtown area and enables them to ride the bus to their needed destination.  By parking cars away from the inner city, park and ride services helps to reduce the flow of traffic in and out of the central city [27,47,70].

2.2.2    Demand-Response Systems 

In a demand-response system, transportation services are catered to specific needs or requests of the passengers [21,27,28,47,61].  Although there are demand response systems in urban and rural areas, this type of system operates well in communities which have small populations and low travel demands [26,27,28,60].  Several authors believed that demand response systems help provide a high degree of mobility to those who might otherwise be unable to travel [20,27,28].  


 

Most demand response systems offer door-to-door services, particularly for patrons who are handicapped and elderly [20].  The dial-a-ride service is one type of demand-response system.  In a typical dial-a-ride service, pickups are scheduled upon the request of the rider [20,26,46,69].  The passenger calls the transit office 24 hours in advance and requests a ride.   After the dispatcher receives the origin, destination, and the time of travel, he or she then schedules the passenger to be transported to the desired locations.  

Since demand-response often require movement through narrow areas, transit operators use vans, minibuses, cars or any other type of small vehicle to service the special needs of citizens [26,46].  Funding for these services are also received from fare and contracted revenues, state and federal governments, and state and local subsidies [26,60,69].  However, since demand response systems usually cater to patrons who have lower incomes, demand response systems rely more heavily on funding received from the federal, state, and local authorities [60].

2.2.3    Paratransit System

A paratransit system is referred to as a demand response system [69].  This type of system is usually marketed toward certain social groups such as: elderly, handicapped, and children.  For example, a paratransit van may pick up a handicapped patron and transport him to a medical facility.  Thus, a paratransit system is a demand response system [26,69]. 

2.2.4    Hybrid System 

A hybrid system, is a combination of fixed-route and flexible route characteristics [26,69].  One type of hybrid system is a fixed route with deviations.  In these fixed route systems, the transit authorities may alter their fixed route in order to service a patron desiring special needs [20,34].  In other words, the transit vehicle (usually a mini-bus or van) will normally operate on a fixed route.  When a special request is called in, the transit vehicle will detour from the scheduled route in order to pick up or drop off patrons [26].  After the task is completed, the transit vehicle will return to its normal fixed route schedule [27,70].  Hybrid services often work well in rural areas were the population is not very dense. 


 

2.3  Transportation in Rural Areas

The availability of transportation in rural areas is usually lower than in urban areas.  One major reason for the lack of transportation in a rural area is the low population density.  These communities often do not have the population size, adequate road development, or the financial income needed to support a stable public transit system [49].

2.3.1  The rural communities 

In the 1990  United States Census, the Census Bureau defines rural areas as places with populations of less than 2,500 citizens [64].  These  rural areas have been described as having scattered populations which mainly consist of elderly and low income citizens [27,36,61]. 

Knowles [35] suggested that rural citizens may need public services which are located in far away business centers.  In a health dependency study conducted by Krout,  it was discovered that health care services and facilities are less accessible in rural areas and that citizens must often travel long distances to receive the needed services [36].  This restrictive range of health opportunities may cause citizens to delay health services until a health condition becomes severe (resulting in more expensive health care), or until they are not able to take care of themselves.  In addition not only are health facilities difficult to access, but jobs, shopping areas, and social services are also located in distant locations [36,49,54].

To describe the geographic make up of rural communities, the Resource Management Corporation (RMC) stated that rural areas have long distances and rough terrain.  This means that most rural communities lack adequate land and road development [49,54].  For example in the article published by the Mass Transit Magazine, the Endless Mountain Transit System provides transportation over a large area which lacks road development [49]  The unknown author stated that most of the two lane roads are narrow and that some of the roads leading to resident homes are gravel and dirt roads [49].  These conditions make transportation both difficult and long [27,49]


 

Since a considerable portion of the rural population will not be able to afford or have access to private transportation [27,49,61], they must depend on public transportation as their sole means of conveyance [47].  If public transportation is not available rural citizens would be devastated because they would not be able to afford or obtain other options of transportation [61]. Unlike urban areas which have many other accessible transit modes (such as advanced rail systems, taxis, private transit systems), rural areas are limited in the number of available public transportation options [54].  Therefore, transportation is an important tool which affects the social and economic growth of rural communities [35,54,61].

2.3.2    Rural Transit Issues 

The primary concerns of rural public transportation operators are with providing services for the transit-dependent groups (elderly, youth, low income, handicapped, etc.) rather than with reducing traffic congestion [15,49,54].   According to David Raphael [52], in 1995, almost 1,200 small transit systems were established to meet the needs of 900 rural American counties.

Rural transit providers strive to serve the needs of the community in the most efficient way and with the least cost [27,28,70].  Since rural areas contain low density populations and widely dispersed travel ranges, it  is difficult and expensive to operate a fixed-route system [27,35].  Therefore, the smaller compact vehicles of demand-response systems are used to handle the smaller passenger load and the longer travel distances at a lower cost [27,28,35].   Demand-response systems are often used in rural areas because of the large number of elderly and low income populations who have specific transportation needs [27,28,33,54].

In some situations the demand for transit services are overwhelming and fixed-route systems have to be implemented in order to handle the load [61].  Also, fixed routes with deviations (hybrid services) may be installed in order to cut cost and to maintain some of the "demand response"  needs of patrons [27].  System alterations such as these are common,  particularly when a rural community is experiencing steady growth in population and area development [61]. 

 


 

2.3.3    Benefits of Rural Public Transportation 

There are many benefits which can be received by both the users and the community from the provision of rural public transportation.  The benefits for the transit users are: increased mobility for non drivers, increased flexibility in travel arrangements, improved accessibility to other areas, travel cost savings, and life style benefits [21,22,27,28,29,35,42,47,54,72].  These benefits can be experienced in rural areas where public transportation is adequate and accessible [21,49,54,72].

Benefits for the whole community include: increased employment, increases in jobs, educational, medical service, cultural and recreational opportunities, widened employment market for businesses, environmental impacts, and land use impacts [5,21,25,27,34,41,42,44,47,50,54, 61,72].   Therefore, "for many Americans, public transportation means opportunities to remain independent and self-sufficient and to participate fully in the life of the community" [52].

2.4  Financing Public Transportation

Transit systems receive funding from the local (community) governments, state government, the federal government, fares, and from private donations. These financial sources help public transit providers to service and meet the needs of growing communities.

2.4.1    Federal sources

In the United States, federal financial assistance for public transportation was regulated by the Urban Mass Transportation Act (UMTA) of 1964 [27,70].  This Act gave guidelines for the amount of money given to an urban transportation system.  Over the years many amendments and titles have been written and added in order to assist transportation operators in providing transit services.  Federal funding sources that have been available for public transit services are listed below.


 

C     The Urban Mass Transportation Assistance Act of 1970  was the first long-term commitment of federal funds.  This Act supplied an expenditure of at least $10 billion over a 12-year period for continuous local planning and flexible administration programs.  The 1970 Act also authorized that 2% of the capital grant and 1.5% of the research funds be allocated to financially support aid programs for elderly and handicapped persons [5,27,70].

C     The Federal-Aid Highway Act of 1973 contained two provisions which increased the use of highway funds for urban mass transportation.  One provision was that "federal-aid system funds can be used for capital expenditures on urban mass transportation projects" [27].  The other provision was that "funds for interstate highway projects can be relinquished and replaced by an equivalent amount from the general fund and spent on mass transportation projects" [27]. This Act also had other provisions: increased matching federal shares for mass transit projects from 66.67% to 80%; increased the amount of funds under the UMTA capital grant program from $3.1 billion to $6.1 billion; and allowed the spending of highway funds for bus-related public transportation facilities [5, 23,27]

C     The National Mass Transportation Assistance Act of 1974 was the first act that allocated federal funding for transit operating assistance.  It authorized $11.8 billion over a period of six years.  About $4 billion, derived by a formula based on population data, could be used for either capital projects or operating assistance [5,27,30,70].  Of the remaining funds, "$7.3 billion was made available for capital assistance at the discretion of the Secretary of Transportation" and $.5 billion was given to rural mass transportation [27,70].

C     The Federal Public Transportation Act of 1978 was established under Title III of the Surface Transportation Assistance Act of 1978.  This Act divided the formula grant into categories such as: capital grants for bus purchase; and additional operating grants for fixed guideway systems and places outside of urbanized areas [5,24].

C     AThe Omnibus Budget Reconciliation Act of 1993 raised to $0.02 the portion of the Highway Trust Fund tax on motor fuels to be placed in the Mass Transit Account, effective October 1, 1995@ [5].


 

C     The Section 5 formula grant of the  Urban Mass Transportation Act was initiated in 1974.  It provides grants for urban areas with a population above 50,000.  The amount allocated is based on 50% of the total population and 50% of the population density [74].  The Section 5 grant can be used to pay 80% of the capital project or cover up to 50% of the operating deficit [29,74].  Section 5 recipients must provide reduced fares to the elderly and handicapped during the off-peak periods [29].

C     Section 18 formula grant of the Urban Mass Transportation Act of 1964, was amended in 1978.  This grant was constructed for areas that are non-urbanized. About 15% of UMTA funds could be used for technical assistance, such as project planning, management development, and program development [27].  The objectives of this program are to improve or initiate public transit programs by providing financial assistance for both capital and operation expenses [27,70].  The section 18 grant is developed to improve the "access of people in rural areas to health care, shopping, education, recreation, and employment as well as public services" [15].

C     Section 16(b)(2)  of the Urban Mass Transportation Act is to be allocated toward the planning and design of mass transportation facilities to meet special needs of elderly persons and persons with disabilities [27,51,70].  This section of the Urban Mass Transportation Act of 1964 was to provide additional funding for transit vehicles to meet the needs of elderly and handicapped [27,51]. This program provided $21 million in grants in 1975, from which 2000 vehicles were purchased [27,70]. Since many citizens, such as the elderly and handicapped, suffer the most if public transportation is not supplied, this grant helps transit providers to meet the needs of transit dependent [27].

C     In the Section 9 Grant Formula Program of the Urban Mass Transportation Act, urban and small urban areas are eligible to receive funding to operate transportation system in municipalities with a population of more than 50,000.  These funds can be used for buses, terminal construction or rental, office furnishing, and equipment, including computer equipment [51,74,70].


 

C     The Section 3 Program of the Urban Mass Transportation Act of 1964 provides grants to pay for up to 80% of the cost of the construction of new services and the extension of existing transit systems [5,74].  Funding can be allocated toward vehicle replacement and maintenance.  Allocations can also be made toward the modernization of existing fixed guide-way systems called ARail Modernization@ [5].  This grant was created for public and private non-profit transit providers in order to increase vehicle efficiency, decrease maintenance costs, and increase safety [51,74].

C     The Vocational Rehabilitation Act of 1973 allocated funding for services that provide for employment training and related transportation for those who qualify [29].

C     Titles XX of the Social Security Act  supplies social services to low income residents in each state.  This act provides free transport services to those whose income level does not exceed 80% of the state's median income [29].

C     Title XIX of the Social Security Act (Medicaid) states that state transportation plans must provide necessary transportation for recipients to and from medical facilities [29]. 

C     The Federal Highway Administration's Rural Public Transportation Demonstration Program (Section 147) of the Federal-Aid Highway Act of 1973 was developed to aid in the selection, routing, and scheduling of vehicles in rural areas [29].  This program enhances access of rural populations to employment, health care, retail centers, education, and public services [29].

Over time federal funds have been adjusted and revised in order to supply transit systems with necessary funding.  Listed below are some of the latest Federal funding regulations. 

C     Major Capital Investment, 49 USC 5309 (formerly Section 3, which was mentioned earlier in this section) was created for state or local public bodies and agencies.  Authorizing legislation designates 40% of the funds for new starts, 40% for rail modernization, and 20% for Bus Capital [5].


 

C     Urbanized Area Formula (UAF), 49 USC  5307 and 5336 (formerly Section 9) was to be received directly by urbanized areas with over a population of 200,000 and through state governors for urbanized areas under a population of 200,000 [5].  For operating assistance, about 50% is received from federal and 50% from state and local.  Allocations of 80% from federal and 20% from state and local, are received for capital assistance [5]. 

C     Elderly and Disabled Persons, 49 USC 5310 (formerly Section 16(b)) is allocated for capital equipment, contracted service, and state administrative costs.  The 5310 grant can be received by private, nonprofit corporations and associations providing mass transportation  services for the elderly and disabled or  to public bodies coordinating such service or providing service where no non-profit service is available [5]. 

C     Rural Area Formula (RAF), 49 USC 5311 (formerly Section 18) authorizes funding through FY 1997 [5].  These funds are available for mass transportation providers which operate outside of urbanized areas [5].  For operating assistance 50% comes from federal and 50% comes from state and local.  For capital assistance, about 80% comes from federal and 20% comes from state and local [5].

C     Rural Transit Assistance Program, 49 USC 5311 (b)(2) (formerly Section 18(h)) was established by the FMT Act of 1987 to provide research, technical assistance, and training grants and related support services to non-urbanized areas [5].

2.4.2  State and Local Sources 

Funding for public transportation is also received from state and local sources.  Sources such as tax based support, sales tax, utilities tax, gasoline tax, and lotteries are used to support public transportation systems at the state and local levels [27,70,74]. 

Some states  provide operating subsidies to the local transit systems.  In  Baltimore, the state funds the transit system's operating deficits that are not covered by federal financial aid [74].  California and Illinois provide operating subsidies to transit systems on the basis of the states sales tax revenues that are collected in that particular transit service area [74].


 

Financial support from local governments for public transportation is mainly generated from residential taxes.  In Cincinnati, a 0.3% income earnings tax is dedicated to the support of the local public transportation systems.  In New York and San Francisco, subsidies from bridge and tunnel tolls are collected to help public transportation [74]. 

2.4.3    Revenue sources & Private Donations 

Revenues are generated from "fare box" collections and from private charters for special events [27]  Fare for most demand response systems are based on the distance traveled by the patron [21,28].  Private donations are sometimes received to aid transit systems in developing communities. 

2.4.4    Decrease in Funding  

Presently, transit providers are dealing with greater demands and smaller amounts of federal funding [61].  The government, in efforts to create a workable budget, is making large cuts in the money that is allocated for public transportation [52,61].  With the increased cost of operating transit systems, a decrease in the budget will and has to be devastating [61]. 

In several articles, many transit providers expressed a need for more money to handle vehicle maintenance cost, technical equipment costs, vehicle replacement costs, and all other operating cost [61,73].  Although public transportation is important to the communities and the people, the lack of funding will probably cause many transit systems to discontinue their services [61]. 

Fares usually cover less than 40% of the operating cost [27].  Therefore, the funding received from the government compensates for most of the public transportation cost [61].

2.4.5    Alternatives for Funding Cuts

Many transit agencies have reduced services in an effort to handle funding cuts [53,61].  Some transit operators stated that they would have to offer fewer services and restrict the hours of travel due to funding cut.  Transit providers operating smaller services stated that they would have to create deviated fixed-route services instead of pure demand-response systems in order to continue services [53].

 

 


 

2.5  Previous Studies on Economic Impacts

Several types of economic impact studies have been conducted in the past.  The following sections summarizes those studies.

 

2.5.1 AMarket Opportunity Analysis for Short-Range Public Transportation

          Planning: Economic, Energy, and Environmental Impacts@

The Transportation Research Board published a report which discussed and presented the benefits of public transportation and the economic, energy, and environmental impacts of public transit systems.  This report is a part of the National Cooperative Highway Research Program Report (NCHRP) Project 8-16, "Guidelines for Public Transportation levels of Service and Evaluation".  This project information  is to be used as a tool in the development of improved methodology for short-range public transportation programs in urban areas with a population range of 50,000 to 500,000 [72].

Several benefits resulting from the provision of public transportation were presented and are listed in Figure 2-1.  These benefits (categorized as either direct economic benefits, quantitative benefits, or non-quantitative benefits), were derived  from the improvement of transit services in a medium-sized city and are stratified into three groups:

1)   User benefits  -  includes benefits experienced by current transit users that have increased mobility and reduced travel costs.

2)   Special group benefits - includes special treatment that is given to groups or institutions, such as large employment densities and business owners that exist near a transit station.

3)   Community at large benefits - includes benefits experienced by the whole community such as increased property values, reduced traffic congestion, and reduced energy conservation. 

Figure 2-1:  Categorization of Alleged Benefits from Improved Transit Systems

 

 

 

 

 

 [Source: Wilburn Smith and Associates, Inc., Community Benefits Resulting from an Improved Transit Program in the Sacramento Region, prepared for the Sacramento Regional Area Planning Commission, Sacramento, California, March 1971]


 

2.5.1.1  Economic benefits of public transportation.  In the economic impact portion of this report, the authors review the effects of decreased public transportation services upon its economic environment.  Major emphasis is placed on patronage (user effects), employment, and business development.  Since it is difficult to analyze impacts resulting from increased transit, the analysis was based on describing the impacts resulting from the temporary removal (strikes) of transit services.

The authors reviewed past cases of strikes to determine the changes in travel behavior and economic loss resulting from temporary transit interruption.  Although strikes were not permanent, it is believed that the results can help to assess the intensity of economic benefits supplied by public transportation.

There were several limitations associated with this approach.  A major problem encountered was the lack of research and uniform analysis within the field.  Another problem was that the population size and the availability of transit alternatives varied in each strike community.  In addition, each transit system resumed service immediately after the strike.  Therefore, all impacts were temporary, which only presents a basis for short-term reasoning.  The alleged benefits could be revealed in the magnitude of economic dislocations resulting from a strike.

2.5.1.2  Effects on transit patrons.   In the National Cooperative Study, the mass transit market was broken into three basic user market segments:

1)   Transit dependent riders (captive riders).  Individuals are dependent on mass transit for their transportation.  Individuals such as the elderly, the young, the handicapped, and the low-income families.

2)   Semi-dependent riders (semi-captive riders).  Individuals who use the transit system, but are able to travel by another transportation mode.  These usually consisted of  members of a one-car family in which there are two or more drivers.

3)   Independent Riders (choice riders). Individuals who have cars (or other definite alternative  transportation mode) immediately available for use.


 

In the strike cases studied, the transit interruptions lasted between 12 and 120 days.  Each strike reviewed resulted in increased traffic congestion and longer travel time as most transit patrons temporarily pursued another form of transportation.  In some situations, individuals were unable to adjust their transportation methods; therefore, many trips were suppressed.  The level of travel suppression depends on whether or not the rider was able to afford or obtain other transit modes operating in the same area.  The author suggests that the shifting of modes and extent of travel suppression stimulate the economic impact and that the scope of activities (such as shopping, medical care, etc.) determines the dimensions of impact. 

It is noted that all user segments will experience a loss of flexibility and convenience, but the greatest impact will be felt by the transit dependent, the individual who lacks alternative transportation options. The semi-dependent and independent riders were able to obtain other modes of transportation;  thus travel suppression was minimal.

In order to trace the economic impacts, the authors suggest that it is necessary to acknowledge the number of individuals falling under the definitions of captive, semi-captive, and  choice riders.  Also, that the available alternative modes of transportation services be determined.  From this information, the impacts are determined on the basis of how individuals make adjustments.


 

2.5.1.3  Suppression of travel.  In 1974 Alameda-Contra Costa (California) experienced a transit strike, there was a trip suppression rate (the percentage of the trips discontinued) of 50 to 60 percent for the elderly and the young, which was about twice the average trip suppression rates for all other transit users.  In San Bernardino, twenty-five percent of the dependent  riders ceased their travel during the 1974 Southern California Rapid Transit strike.  In contrast, only 4% of the semi-dependent patrons eliminated travel.  During the 1966 New York City Transit strike, 60% of the dependent riders discontinued trips during the strike, compared to 15% of the semi-dependent.  In Knoxville, Tenn., it was discovered that elderly captive riders had suppressed their travel at twice the rate of the elderly non-captive riders.  The impact of the strike was felt most dramatically by the elderly living in senior citizens housing.  The trips most frequently suppressed were  discretionary trip such as trips for religious purposes, visiting friends and relatives, leisure and recreational trips, and personal business.  In spite of the loss in transit service, non-discretionary travel continued to be made for shopping, medical appointments, and work trips.  The author stated that the most commonly used alternative mode was the car (carpooling, relatives, and personal).

2.5.1.4  Effects of travel suppression on employment.  One benefit commonly associated with mass transit is increased job opportunities for lower income residents because of available mobility.  It is thought that the transit dependent rider, which includes low-income individuals, is most likely to suffer from a transit interruption, since the access to the job site is interrupted.  However, strike statistics did not show this to be the case. 

The 1974 Southern California Rapid Transit District strike showed that few people were affected by the strike.  A large number of people were slightly inconvenienced (traffic tie-ups, etc.) and only a small number were hurt directly because of missed non-discretionary trips.  Of the 316 people interviewed, only 4% stated that they lost their jobs because of the transportation strike.   In November, the comparative statistic of new unemployment applications for Los Angeles County and the state of California recorded no statistical evidence that unemployment occurred because of lack of transportation.

The Connecticut cities went without bus services for 121 days in the fall and winter of 1972 and 1973.  Yet, the cities did not experience any serious dislocations in economic or social activities because of lack of service.  Similarly, in Knoxville, there was no noticeable increase in community unemployment resulting from the 6- week strike.  Major industrial firms and employment centers, except for the downtown retail merchants, all reported no difficulty in having employees reach work sites.


 

This general observation has also been seen in the studies of large metropolitan areas (Los Angeles and Houston, Texas.) and small cities (Hartford, New Haven and Stanford).  The effects of these transit strikes are not evident within the county's statistical unemployment records.  There were some jobs lost due to transit strikes, but the number was so low that it was not detectable within the over-all statistics.

In another case, a St. Louis, Missouri sponsor reported that many  patrons who used the bus to find jobs bought automobiles quickly thereafter and  discontinued using the public transit buses.  It was assessed that the over-all impact of bus services on  the unemployment status was minimal.  In the cases studied, individuals endured hardships in order to continue making "vital' or necessary trips.  Therefore, the authors of this report question the idea that mass transit is vital for individuals to reach job markets.

2.5.1.5  Mode shifts as a result of travel suppression.  In a study to identify consumer behavior during a strike, Bigelo-Crain Associates conducted a survey of 270 riders of the Southern California Rapid Transit District.  It was discovered that the private automobile met the needs of 60% of the usual transit patronage.  Taxi providers in the Los Angeles area experienced an over-all increase in revenues of 26%. (However, many who used taxis reduced their amount of travel because of the rider cost). 

In the Knoxville transit strike, other modes of transportation did not experience revenue or patronage increases (This excludes the transit services which were provided for students at the University of Tennessee).   Local cab companies reported no significant increase in revenues during or after the transit strike. 

The authors stated that most impacts that result from the provision of transportation depends up on the community in which it serves.  The studies revealed that the choice rider used different modes of transportation during a transit system interruption and that most of the captive transit riders, who did not own automobiles, relied on friends and family for transportation needs. 


 

2.5.1.6  Effects of travel suppression on retail businesses.  Changes in travel patterns can have an impact on retail trade. (For evaluation purposes, the businesses are classified by the transit market segments which they primarily serve.)  In Los Angeles, retail establishments experienced a 10 to 50 percent reduction in sales during a transit strike.  This Los Angeles study proved that the reduction in sale resulted from the recession and loss of transit patrons.

In Knoxville, retail stores experienced a 10 to 80 percent reduction in sales.  The businesses selling smaller and lower priced items were affected more than larger, more expensive stores.  For example, Knoxville's downtown specialty stores ( clothing and shoe stores, food/drug/variety stores, and restaurants), which depend on patron access, were hit the hardest during the strike. 

The author suggest that retail stores and small specialty shops receive the most adverse impact for a public transit strike.  Although these studies were distributed between medium-sized and major metro areas and strikes lasted 12 to 120 days, they provide good insight into the dislocations that result for the loss of public transportation.

2.5.1.7  Conclusions.    As the authors expected, the strikes mostly affected portions of the population that directly rely on public transportation as a principal means of mobility.  However, in most cases transit dependent riders were able to find alternative travel arrangements for essential travel.  Therefore most of the shopping, work, school, and medical trips continued.  The discretionary trips, such as religious and visitation trip, were reduced or discontinued. 

In retail sales, the small low priced retail facilities experienced more sales reduction during the interruption of public transportation.  Most of the CBD (central business district)  establishments and expensive retail stores felt only minor repercussions of losses, about 5 to 10 percent.

The authors suggest that the actual benefit experience for a public transportation system depends on the number of transit riders; the number of riders categorized as  captive, semi-captive, and  choice; the number of available substitute modes of transportation; the level of social opportunity that is affordable to the citizens; and the commitment to the economic vitality of the downtown area.  On the basis of the studies in this report, it was concluded that public transit alone is neither necessary nor sufficient for the economic vitality in a small-to-medium sized city.


 

2.5.2 SEPTA System

Research was conducted on the economic impacts of the Southeastern Pennsylvania Transportation Authority (SEPTA) on the regional and state economy.  The study, funded by a grant from the Urban Mass Transportation Administration, was commissioned by the Delaware Valley Regional Planning Commission [18].

The SEPTA system supplies services to a metropolitan area consisting of five counties in Pennsylvania (Bucks, Chester, Delaware, Montgomery, Philadelphia) and three counties in New Jersey (Camden, Gloucester, Burlington).  It is believed that the Southeastern transit system contributes to the role in supporting the health and growth of the metropolitan, Pennsylvania, and New Jersey economy.  However, the SEPTA system is in need of rehabilitation.  Aging facilities, such as buses, trains, track bridges, tunnels and viaducts, require constant and expensive capital investments to maintain an adequate level of service.  In previous years, before this study, the public transit system had not received the amount of funds needed to support "rehabilitation expenditures at levels consistent with continued long run maintenance of service" [18].  In addition, more funding was needed for  increasing operating and capital costs.

2.5.2.1  Purpose.  The study was done to evaluate whether the "transit rehabilitation programs would >pay off=  as investments" [18].   Since there was not sufficient funding for current rehabilitation, this study was done to provide an objective answer to the question of whether it is worth it to the state and the region to fund SEPTA=s program of rehabilitation at the level recommended by SEPTA and local officials for years 1992-2001.

2.5.2.2  The evaluating scenarios.  In order to evaluate the impacts of the transit system, the benefits and costs were compared in four different scenarios:

Rehabilitation Scenario - (Rehabilitation of SEPTA, and the continuation of SEPTA services): under this scenario the proposed rehabilitation projects and minor expansions would be adequately funded for the ten years (1992-2001) to improve transportation and service quality for all modes of transportation.


 

Immediate Shutdown Scenario - (An immediate permanent shutdown of all SEPTA services): this scenario assumes that SEPTA services would immediately close down  and that no public policy efforts would be made to start up services. 

C     Gradual Phaseout Scenario - (A gradual shutdown of all SEPTA services within ten years): under this scenario a public policy decision would be made that only the operating costs of SEPTA would be funded, and that the system would be allowed to go out of service as the number of riders diminished  and as services were eliminated.

$    Partial Reduction Scenario  (A 50 percent reduction of services within 5 years, and rehabilitation of the remainder of the system) : the partial reduction scenario is similar to gradual shutdown.  However, it is assumed that one-half the services would be maintained, and that the deterioration of services and ridership ends when SEPTA reaches about half its current size. 

2.5.2.3  The analysis.  The analysis process contained six steps. They are listed below. 

1.   Define Transportation  System Changes - The SEPTA Scenarios were defined in terms of transportation supply (capacity) and level-of-service (travel time) for public transit, car and truck travel, for each year over the period 1992 to 2020.

2.   Transportation Model - a computer model of regional transportation impacts is applied to estimate the impacts of transportation system changes on travelers, in terms of changes in operating costs, travel time costs, safety costs, and out-of-pocket costs and travel times incurred.  These are estimated separately by mode of travel (public transit, car and truck), for each year over the period 1992 to 2020.

3.   Economic Model- Economic simulation models for the Philadelphia metropolitan region and State of Pennsylvania are applied to estimate the impacts of travel cost and time changes on the economy, in terms of business sales, employment, income and population.  These impacts are estimated for each type of business and occupation group, for each year over the period 1992 to 2020


 

4.   Fiscal Model - fiscal models for the Pennsylvania state government and for the Philadelphia region's local governments are applied to estimate the impacts of business sales, employment, income and population changes on government revenues and expenditures.  These impacts are estimated in terms of net revenue changes for each year over the period 1992-2020.

5.   Energy and Air Pollution Estimation - Energy and emissions models are applied to estimate the impacts of changes in vehicle-miles of travel by public transit, car and truck on consumption of gasoline and emissions of air pollutants. These impacts are estimated for each year over the period 1992 to 2020.

6.   Interviews - findings from interviews with businesses, economic development professionals and representatives of elderly, handicapped, low income and minority groups are used to supplement the economic model analysis (Step 3, above), and to better distinguish the differential impacts on particular groups in the population.

2.5.2.4  Data Collection.  The data used for this study involved the information shown in Figure 2-2.

 

Figure 2-2:  Sources and Types of Data

 

 

 

 

 

 

 

 

 

 

Obtained from                                                            Data Collected                                            .

SEPTA                                                            transportation budgets, ridership and revenue

patterns

 

Delaware Valley Regional Planning                         population, employment, highway volumes,

Commission                                                    levels of service

 

Greater Philadelphia Economic                     regional economic competitiveness

Development Coalition

 

U.S. Dept. of Commerce                                local, state and national economic growth/

(Bureau of Economic Analysis)                     decline trends and national industry forecasts

 

Pennsylvania Dept. of Revenue &               local and state government revenues and

Pennsylvania Economy League                    expenditures

 

Interviews (businesses, social agencies       their dependence on, or sensitivity to, public

individuals, etc.)                                             transportation

Obtained from                                                            Data Collected                                            .

SEPTA                                                            transportation budgets, ridership and revenue

patterns

 

Delaware Valley Regional Planning                         population, employment, highway volumes,

Commission                                                    levels of service

 

Greater Philadelphia Economic                     regional economic competitiveness

Development Coalition

 

U.S. Dept. of Commerce                                local, state and national economic growth/

(Bureau of Economic Analysis)                     decline trends and national industry forecasts

 

Pennsylvania Dept. of Revenue &               local and state government revenues and

Pennsylvania Economy League                    expenditures

 

Interviews (businesses, social agencies       their dependence on, or sensitivity to, public

individuals, etc.)                                             transportation

  

 


 

2.5.2.5  Impacts.  This economic study analyzes the impacts of potential lack of rehabilitation of SEPTA's services relative to the necessary funding needed to keep the system in operation.  The impacts were addressed in several categories:

Transportation Impacts:   the additional travel cost and travel time incurred by the former riders of SEPTA who have to travel by car or other modes of transportation.  This also includes costs experienced by present automobile and truck users who have to contend with increased traffic congestion.

Regional and State Economic Impacts:  the changes resulting from the increase in local cost and expenditures for businesses and residents; such as, changes in business sales, population, employment and personal income.

Fiscal Impacts:  changes in local and state government costs and revenues that would occur resulting from population and employment losses.

Social Impacts:  specific segments of society that are affected by changes in mobility.

Environmental Impacts:  the changes in energy consumption and air quality resulting from increased car ownership and reliance.

Each category of impacts can be compared to the costs incurred by maintaining SEPTA services, or by the costs saved by reducing expenditures of SEPTA.

2.5.2.6 Transportation impact model.  For this model, there are two main user impacts of eliminating SEPTA services.  First, the increase of automobile transportation which can create a greater personal cost for former SEPTA users.  The other impact is the increase in traffic congestion, causing longer travel times and greater out-of-pocket operating costs for existing car and truck users.  These impacts will vary depending on the nature of the users travel.    

Some of the SEPTA users have access to cars or  some other mode of transportation but the other portion, who can not afford other alternatives, suffer greatly.  If trips to work can not be made a loss of income is experienced.  If social trips are restricted, there will be a loss of public welfare and independence. 


 

2.5.2.7  The computer model.  To estimate the changes, a computerized transportation impact model was developed for this study.   The model includes estimated cost of SEPTA users and highway users.  In the scenarios which involve the shutdown of SEPTA services, the former users are removed from the SEPTA system and their transit user cost are subtracted, and added to the highway system, with the highway user costs recalculated based upon the higher traffic volumes.

Since each scenario removes a portion of transit users and causes an increase in highway users, most of the impacts modeled are highway user impacts.  The increase highway cost are not only experienced by SEPTA users but by the present auto and truck users. 

The SEPTA user costs for this model were: in-vehicle travel times for SEPTA riders (SEPTA passenger miles at an average speed of 13.6 mph); highway costs (estimated from data of current traffic, forecaster population and employment); motor vehicle cost and travel times; accident costs; parking costs; and automobile ownership costs.

2.5.2.8  The economic model: overall regional impacts.  The impacts for eliminating or reducing SEPTA services are:

Increased cost of doing business in the region (increased delivery cost due to traffic congestion).

C     Decrease in the access to labor markets

C     Greater cost of living in the region due to the increase in out of pocket personal costs such as congested road travel cost and car ownership cost.

C     Loss of SEPTA employee jobs

C     Decrease in quality of life

C     Shift in personal spending (the increase in the purchase of cars causes increased spending on petroleum products, insurance, parking and repairs versus the amount that would have been spent on transit fares and other expenditures).

C     Reduced attraction of visitors.

 


 

2.5.2.9  The computerized economic model.  The magnitude of the economic impacts described above were estimated using a regional economic simulation model.  The REMI forecasting and simulation model, developed by Regional Economic Models, Inc., was specifically calibrated for two regions; 1) the 8-county Philadelphia metro area, and 2) the State of Pennsylvania excluding the Philadelphia area.

 The REMI Forecasting and Simulation Model includes all of the inter industry interaction among 49 private sectors in the economy.  It includes the trading flows by industry between the Philadelphia metro area and the rest of the state of Pennsylvania.  In addition to containing a complete inter-industry and trade flow structure, the model also includes key aspects of the economy that are regarded as important for policy evaluation. Key aspects such as the effect of industry location on the relative cost of doing business.  This relative cost of doing business is built up for each industry based on tax costs, fuel costs, wage costs, and the costs of all the intermediate inputs in the area.  The model includes a migration response to employment conditions in the area. 

The calibration starts with the detailed analysis of the economy at the level of 500 separate industries.  The model makes a forecast for over 2000 variables (including the Gross Regional Product by final demand sectors and by industries and employment and cost of doing business of 53 industries) with a complete history of forecast for all of these variables from 1969 through 2035.  Using any of over 700 policy variables it is possible to introduce changes that the region may experience due to policy initiatives.

The report describes the modeling and analysis process as being dynamic, due to the fact that transportation impact costs and overall economic impacts are modeled year-to-year for each scenario.  The two basic steps of the analysis are: 1) the transportation related cost are estimated for a particular year; then 2) these costs are used in the economic model to estimate the economic activity for the next year.  As a result, the changes in business sales, employment, personal income and population at the metropolitan and statewide levels are predicted.


 

2.5.2.10  Fiscal model.  The predictions derived from the economic model will affect the  revenues and expenditures for local and state governments.  Specifically, the decreases experienced in business sales, employment, and income will bring proportional reductions in some sources of government revenue.

To estimate the impacts of economic changes on local and state levels of government, the Pennsylvania Economy League (PEL) applied its Fiscal Impact Models.  These models were developed and maintained by PEL.  The models for the local and state governments are briefly discussed in the sections that follow. 

2.5.2.11  Local government impact.  The economic impacts represent the overall impact on all municipal governments within the metropolitan area.  It was constructed based on detailed analysis of revenues and expenditures of the city of Philadelphia and the communities in each county in the area.

The analysis of local government revenues takes into account the fact that there are great variations in taxes.  For the area outside of Philadelphia, the principle tax levied is the real estate tax for residents and companies.  However, principle taxes of the area within Philadelphia are non-property taxes which  include wage/occupation taxes, per capita taxes, mercantile or business privilege taxes and real estate transfer taxes.

2.5.2.12  State government impacts.  The model of state impacts indicates how state government revenues and expenditures would be affected by the reduction or elimination of SEPTA services.  The sources for state government revenues include:  personal income taxes, corporate profit taxes, sales tax, motor fuel tax, the lottery, and various fees. These revenues would change proportionally to changes in employment, personal income, and population.  (The four main changes of state government expenditures are: SEPTA, unemployment compensation, income maintenance programs, health and human service programs).


 

The government cost increases as greater numbers of jobs are lost, but decrease as some people eventually move out of the state.  "These changes in government expenditures are predicted by the fiscal impact model, based on regression studies of relationships of expenditures to changes in population, employment and income changes over time"[18].

2.5.2.13  Benefit/ cost analysis.  The report states that a benefit/cost analysis provides a means of assessing the net public benefits of SEPTA reduction alternatives, with respect to the rehabilitation and continuing of  SEPTA services. Each comparison is made in terms of the "net benefit" (benefits minus costs) and the benefit/cost ratio (benefits divided by costs).

The costs and benefits associated with SEPTA alternatives are defined by the fact that all of the alternatives are negative changes in transit services. Thus, the economic cost of reducing or eliminating SEPTA is "a loss of personal income due to contraction of the state economy as a result of the degraded transportation system"[18 ].  Therefore, the economic benefit of reducing or eliminating SEPTA is a savings in public spending that will subsidize the price of providing public transportation services.

The benefit/cost comparison effectively compares the benefit of money entering the  pockets of residents versus the costs of money leaving their pockets.  The reports suggest that this is a clear and straightforward way of assessing economic impacts on the state economy [18]. 

In order to evaluate each of the three SEPTA alternatives (relative to the rehabilitation case alternative), it is necessary to compare annual streams of cost and benefits estimated for the 30-year study period from 1991 - 2020.   Each future annual cost and benefit is estimated in terms of  constant 1990 dollars and it is then discounted to its equivalent present value.              Since a dollar available in the future has less present value than a dollar available right now, discounting helps to reflect the value of money over time.  The further into the future a cost or benefit occurs, the more heavily it is discounted and thus, the lower its equivalent present value.  Discounting is important because the attractiveness of one transit service alternative over another is determined by both the size and timing of its costs and benefits.


 

2.5.2 14  Results of economic impact study.  All three alternatives for the reduction or elimination of SEPTA services produced  a negative net benefit regardless of the discount rates.  The partial scenario is the smaller of the three, due to the fact that it has both a much smaller cost and a much smaller benefit.  

In terms of benefit/cost ratios, all three alternatives should be rejected.  In each case, the benefit/cost ratio is 0.35 or lower.  The ratio only considers the transportation cost, which means that the "benefits (in terms of public expenditures saved) are no more than one-third of the cost in terms of traveler impacts.  Considering all impacts on the economy of the state of Pennsylvania, the benefit/cost ratio of elimination or reduction of SEPTA resulted in values below 0.2.  This  means that the public expenditure benefits of not rehabilitating and continuing SEPTA services are less than 20% of the income losses incurred to the state economy.  The benefit/cost analysis clearly demonstrates that none of the reduction and elimination alternatives of SEPTA are cost-effective from the public point of view.

The report states that the cost/ benefit findings can also be viewed another way.  They indicate that public expenditures to continue SEPTA operations return $3 of transportation benefit to the region and the state for every dollar spent on SEPTA.  In terms of the economic impact, the return to the region and the state represents at least $5 of income for every dollar spent on SEPTA [18].

2.5.3 Summary Report: Economic Benefits of Transit in Indiana

 This study, conducted by the Indiana Transportation Association, evaluates the economic benefits of public transportation systems in Indiana.  There are 38 transit systems throughout the state which collectively serve an average of 27 million people per year.  The service area consists of thirty nine counties which represent 60% of Indiana=s population [31]. 

The impacts presented in this study were: economic, environmental, and social.  These impacts were analyzed by using data from annual reports written by the  Indiana Transportation Association, and by using a computerized model called the IMPLAN Input/Output Model.


 

2.5.3.1  Economic impact.  The economic impact category included employment impacts, sales impacts, and property value impacts due to the supply of public transportation.  The employment impact was divided into two categories:  changes in the number of employees hired or fired, and changes in unemployment compensations due to changes in employment.   The employment change category outlined three areas of employment scenarios.  They are:

C     Direct employment - the actual employment change in the transit industry due to any changes in transit serves.

C     Indirect employment - employment changes in other industries (industries such as transit vendors) which result from the purchases made by transit for expansion or reduction of the transit system.

C     Induced employment - employment increases due to the increase in household expenditures. (AThis expenditure change follows the change in incomes that result from the direct and indirect effects of the change in transit output@).

The direct, indirect, and induced employment changes were summed together to obtain the total change in employment. 

By using the IMPLAN input/output model, Indiana was able to estimate the changes in employment due to $1,000,000 change in transit expenditures.  The IMPLAN model determined that for every million dollar increase in transit output, there would be an employment impact of 40.6601 for direct employment, 4.0240 for indirect employment, and 21.9101 for induced employment.   This means that 41 new workers would be hired by the transit system, 4 workers hired by the transit supporting industries (indirect employment), and 22 new jobs created because of increases in household expenditures.   Thus, A the total employment effect of the initial $1 million change, then, is an increase of approximately 67 workers@ [31].


 

The IMPLAN model also generated two multipliers (Type I and Type III) that were used to estimate the changes in employment as a result of the change in transit expenditure.  The Type I multiplier was determined to be 1.0990, which represents the direct and indirect employment changes.  Type III multiplier was determined to be 1.6378 and it represents direct, indirect, and induced employment.   Therefore the Type III multiplier could be multiplied by the impact value and by the estimated change in transit expenditure to obtain the total employment change to the economy.  To demonstrate this application, an example is shown in Figure 2-3. 

Figure 2-3:  Multiplier Demonstration

Given: - a decrease of $87.7 million in transit expenditures,

- a direct impact value is 40.6601 (derived from the IMPLAN model), and a

            - Type III multiplier of 1.6378 (derived from the IMPLAN model)

The reduction in direct employment would be :

(87.7 * 40.6601)= 3566 reduction of employees for the transit system.

The reduction in direct, indirect, and induced employment would be:

(87.7*40.6601*1.6378) = 5,840 reduction of employees for entire state.

Given: - a decrease of $87.7 million in transit expenditures,

- a direct impact value is 40.6601 (derived from the IMPLAN model), and a

            - Type III multiplier of 1.6378 (derived from the IMPLAN model)

The reduction in direct employment would be :

(87.7 * 40.6601)= 3566 reduction of employees for the transit system.

The reduction in direct, indirect, and induced employment would be:

(87.7*40.6601*1.6378) = 5,840 reduction of employees for entire state.

  

The change in unemployment compensation expenditures was estimated by multiplying the number of  hired or fired employees by the average weekly unemployment compensation cost per person ($141.69 per week).  This calculation produces a dollar amount that would be saved or the amount of money that would be spent on unemployment because of a change in employment due to the change in transit expenditures.

The retail impacts determined by multiplying an average purchase amount (per transit rider) by one-half of the total number of round trips.  The average purchase amount was estimated to be $7.62 per round trip and was obtained from surveys given in Mobile, AL, Fr. Worth, TX, and Nashville, TN.  This amount represents the total impact of retail sales due to consumers traveling to buy goods and services [31]. 

At the State and local levels, the economic impacts were described as tax revenues brought about by public transit due to the increase in property values and increase in personal spending.  The multipliers for both personal income (employee compensation for direct and indirect employment) and total income (personal income plus incomes associated with proprietary income and other property income) were determined from the IMPLAN model.  The multiplier for property value was then obtained by taking the difference between the personal multiplier and the total multiplier.  This property value multiplier was then multiplied by the change in transit expenditures to get the property value impact [31]. 


 

The Indiana transit system was estimated to have an employment impact of 4,300.  This means that over four thousand people were employed due to the transit system.  If the transit system did not exist, the State would experience a $10.4 million increase in unemployment expenditures.  It was also discovered that the total annual retail sales associated with a person riding transit amounted to $104 million and that the tax revenues to the State and Local governments were estimated as $16.5 million, due to public transit.

Therefore the total economic impact of public transportation on Indiana was estimated to be $121.5 million per year based on the economic IMPLAN input-output model.   Thus for every $1.00 invested in public transportation, there would be a return of $1.38 or 38%.

2.5.3.2 Environmental impacts.  The environmental impacts category evaluated the effects of public transit on air pollution,  parking space construction (in central business locations), and vehicle accidents.  The impact of transit on air pollution was estimated by multiplying the total pollution emission rate per vehicle mile for a transit vehicle by the total number of transit vehicle miles.  The total emission rate was the sum of the three pollutant rates, shown below:

POLLUTANTS                                              RATE (grams per vehicle mile)

non-methane hydrocarbons (NMHC)           3.25

carbon monoxide (CO)                                   18.86

nitrous oxides (NOx)                                     15.91

The impact of transit on parking cost incurred by private automobile drivers was determined by first estimating the number of auto trips by dividing the total transit trips by the average auto occupancy.  Then the number of auto trips was divided by two to estimate the number of auto trip destinations for which new spaces would be needed if transit were eliminated.   To obtain the dollar value, specifically for Central Business Districts, the number of spaces needed was multiplied by the cost of one parking space (The parking space cost was estimated to be $5,000 per space).


 

The accident impacts for transit were estimated using the national statistics rates of accidents per rider.  The rates were:

TYPE                                                  RATE (per rider)

property damage                                .0000105

Personal injury                                   .0000072

fatalities                                              .000000019

It was estimated that if  public transit did not exist Aharmful air pollutants non-methane hydrocarbons (NMHC), carbon monoxide (CO), and nitrous oxides (NOx) would increase by four-hundred and sixty (460); three thousand three-hundred and eighty (3,880); and forty (40) tons, respectively.  The Indiana Transportation Association estimated that 6,900 parking spaces would have to be constructed if the transit system did not exist.  At a cost of $5,000 per single parking space, parking accommodations would cost almost $35,000,000 without public transportation.  An increase of $4.5 million  was estimated for vehicle accident costs, if the transit system did not exist [31]. 

2.5.3.3  Social Impacts.  Social impacts were viewed as the Aopportunity for people to travel economically@ and as an increase in Amobility for those who are too young, too old or too disadvantaged to own or operate a private vehicle@ [31].  The economic effect of using transit was determined by comparing the fare cost of transit to the cost of using other modes of transportation [31]. 

If transit did not exist, it was estimated that travel expenditures would increase by $18.2 million each year because transit riders would have to find alternative means of travel.  In reference to the disadvantaged, the following was estimated:

C     8% of Indiana households did not own an automobile

C     10% of the population was below the poverty level

C     4% of the population could not travel without mobility assistance.

C     23% of the population was too young to drive

C     13% of the population was 65 and older [31].

2.5.4 Transportation Cost Analysis: Techniques, Estimates and Implications


 

This cost analysis was conducted by Todd Litman of the Victoria Transport Policy Institute.  The report presents a Aframework estimating and comparing total roadway transportation costs, including internal and external, market and non-market costs@ [42].   Litman reviewed previous cost studies and outlined twenty cost estimates, which will be discussed in the following paragraphs.  These estimates were calculated for 11 modes of travel under various conditions (urban peak, urban off-peak, and rural travel).  The modes are as follows:

- Average automobile                        - Diesel bus                            - Bicycle

- Compact (fuel efficient) car             - Electric bus/ Trolley                        - Walk

- Electric car                                       - Motorcycle                           -Telecommute

- Van or light truck

2.5.4.1 Vehicle cost.  Vehicle cost were costs associated with owning and operating a vehicle.  These costs were separated into two categories:  Fixed vehicle ownership cost and variable vehicle operating costs.  Fixed costs included vehicle purchase or lease costs, insurance costs, and registration and vehicle tax costs.  The variable costs included maintenance and repair costs, fuel, fuel taxes, oil, paid parking, and toll costs.  Figure 2-4 and 2-5 show the estimated cost for fixed vehicle ownership costs and variable vehicle operating cost. 

Figure 2-4:  Fixed Vehicle Ownership Costs (1996 U.S. dollars/vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.206

0.206

0.206

0.206

Compact Car

0.181

0.181

0.181

0.181

Electric Car

0.258

0.258

0.258

0.258

Van/Light Truck

0.268

0.268

0.268

0.268

Rideshare Passenger

0

0

0

0

Diesel Bus

0

0

0

0

Electric Bus/ Trolley

0

0

0

0

Motorcycle

0.252

.252

0.252

0.252

Bicycle

0.05

0.05

0.05

0.05

Walk

0

0

0

0

Telecommute

0.2

0.2

0.2

0.2

 


 

Figure 2-5: Variable Vehicle Operating Cost 1996 U.S. dollars/vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.147

0.128

0.109

0.124

Compact Car

0.107

0.093

0.079

0.090

Electric Car

0.207

0.180

0.153

0.175

Van/Light Truck

0.207

0.180

0.153

0.175

Rideshare Passenger

0.003

0.003

0.002

0.002

Diesel Bus

3.75

0.750

0.75

1.35

Electric Bus/ Trolley

4.50

1.05

1.05

1.74

Motorcycle

0.062

0.054

0.05

0.054

Bicycle

0.020

0.020

0.020

0.020

Walk

0.040

0.040

0.040

0.04

Telecommute

0

0

0

0

 

2.5.4.2 Travel time costs.   Travel time cost is the value of travel time to the user.  Litman uses a value of $6.00 (50% of the national average wages of $12/hour) per hour to represent the value of time for automobile drivers and $4.20 per hour (35% of the national average wages of $12/hour) for the value of time for passengers.  In order to obtain the cost of time per vehicle mile, the time value per hour was multiplied by the average speed.  The urban peak speed was 30 mph plus a 16.5% congestion premium, urban off-peak and rural speeds were averaged to be 35 mph and 40 mph respectively with no congestion premium.  Litman=s estimates for user travel time costs are presented in Figure 2-6.

 

 

 

 

 


 

 

Figure 2-6: User Travel Time Costs (1996 U.S. dollars per Passenger Mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.23

0.17

0.15

0.174

Compact Car

0.23

0.17

0.15

0.174

Electric Car

0.23

0.17

0.15

0.174

Van/Light Truck

0.23

0.17

0.15

0.174

Rideshare Passenger

0.18

0.154

0.135

0.152

Diesel Bus

0.281

0.208

0.184

0.213

Electric Bus/ Trolley

0.281

0.208

0.184

0.213

Motorcycle

0.23

0.17

0.15

0.174

Bicycle

0.35

0.30

0.30

0.31

Walk

1.00

1.00

1.00

1.00

Telecommute

0

0

0

.0

 

2.5.4.3 Accident costs.  The automobile accident costs were defined as net insurance disbursement estimates.  These costs were divided into two categories:  internal and external costs.  Internal costs were vehicle damage deductibles and uncompensated injuries.  External costs were uncompensated damages, lost income, pain and grief.  The cost estimates for accident cost are displayed in Figure 2-7 and 2-8.

 

 

 

 

 

 

 


 

Figure 2-7:  Internal Accident Costs (1996 U.S. dollars per passenger mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.05

0.05

0.05

0.05

Compact Car

0.055

0.055

0.055

0.055

Electric Car

0.05

0.05

0.05

0.05

Van/Light Truck

0.05

0.05

0.05

0.05

Rideshare Passenger

0.05

0.05

0.05

0.05

Diesel Bus

0.003

0.003

0.003

0.003

Electric Bus/ Trolley

0.003

0.003

0.003

0.003

Motorcycle

0.437

0.437

0.437

0.437

Bicycle

0.05

0.05

0.05

0.05

Walk

0.05

0.05

0.05

0.05

Telecommute

0

0

0

0

Figure 2-8: External Accident Costs (1996 U.S. dollars per passenger mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

.035

.035

.035

.035

Compact Car

.033

.033

.033

.033

Electric Car

0.035

0.035

0.035

0.035

Van/Light Truck

0.035

0.035

0.035

0.035

Rideshare Passenger

0

0

0

0

Diesel Bus

0.02

0.02

0.02

0.02

Electric Bus/ Trolley

0.02

0.02

0.02

0.02

Motorcycle

0.077

0.077

0.077

0.077

Bicycle

0.002

0.002

0.002

0.002

Walk

0.002

0.002

0.002

0.002

Telecommute

0

0

0

0


 

2.5.4.4 Parking.  Parking cost consist of off-street parking costs.  Parking costs were separated into two categories:  internal and external.  Internal costs were estimated by dividing the non residential parking space costs ($600 per parking space) by the average number of miles driven per year (12,000 miles per year).  To make the adjustment for each vehicle class, various percentage savings of one mode over another mode were applied.  The external costs were estimated by converting the average cost of parking per day to an average cost of  parking per vehicle mile.  The internal and external parking cost are shown in Figures 2-9 and 2-10.

Figure 2-9:  Internal Parking costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.05

0.05

0.025

0.042

Compact Car

0.045

0.045

0.023

0.038

Electric Car

0.05

0.05

0.025

0.042

Van/Light Truck

0.05

0.05

0.025

0.042

Rideshare Passenger

0

0

0

0

Diesel Bus

0

0

0

0

Electric Bus/ Trolley

0

0

0

0

Motorcycle

0.04

0.04

0.020

0.033

Bicycle

0.003

0.003

0.001

0.002

Walk

0

0

0

0

Telecommute

0

0

0

0

 

 

 

 

 

 

 

 

 

 


 

Figure 2-10: External Parking Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.12

0.040

0.020

0.048

Compact Car

0.114

0.038

0.019

0.046

Electric Car

0.120

0.040

0.020

0.048

Van/Light Truck

0.120

0.040

0.020

0.048

Rideshare Passenger

0

0

0

0

Diesel Bus

0

0

0

0

Electric Bus/ Trolley

0

0

0

0

Motorcycle

0.090

0.030

0.015

0.036

Bicycle

0.006

0.002

0.001

0.002

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.5  Congestion.  Litman defined congestion as Aincremental costs resulting from interference among road users@.   Congestion costs for urban peak time were estimated by:

   ($100 billion in nation congestion cost)* (80% ) = $0.17 per mile

  (2,300 billion U.S. miles driven annually)*(20%)

The 80% represents the percentage of congestion costs and 20% represents the percentage of driving which occurs under urban peak conditions.  

The congestion cost for urban off-peak periods were calculated by:

($100 billion in nation congestion cost)* (20% )   = .02 per mile

(2,300 billion U.S. miles driven annually)*(40%)

The 20% represents the percentage of congestion costs and 40% represents the percentage of driving which occurs under urban peak conditions.   There is a zero congestion cost rate for rural areas because rural areas usually do not experience congestion.  Figure 2-11 displays the cost for congestion .

 

 


 

Figure 2-11:  Congestion Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.17

0.02

0

0.042

Compact Car

0.17

0.02

0

0.042

Electric Car

0.17

0.02

0

0.042

Van/Light Truck

0.17

0.02

0

0.042

Rideshare Passenger

0

0

0

0

Diesel Bus

0.34

0.04

0

0.084

Electric Bus/ Trolley

0.34

0.04

0

0.084

Motorcycle

0.17

0.02

0

0.042

Bicycle

0.009

0.001

0

0.002

Walk

0

0

0

0

Telecommute

0

0

0

0

 

2.5.4.6  Road facility external costs.  Roadway facility costs were defined as costs required for automobile use not borne by user fees.  This cost includes Aroad construction and maintenance, land acquisition, financing expenses, and the portion of roadway support facilities and programs required for automobile traffic@ [42].  The costs were allocated between different vehicle classes based on their use of road space and road damages.  The road facility costs are shown in Figure 2-12 [42].

 

 

 

 

 

 

 

 


 

Figure 2-12:  The Road Facility External Costs

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

.016

.016

.010

.014

Compact Car

.016

.016

.010

.014

Electric Car

0.038

0.038

0.023

0.032

Van/Light Truck

0.021

0.021

0.013

0.018

Rideshare Passenger

0

0

0

0

Diesel Bus

0.07

0.07

0.042

0.059

Electric Bus/ Trolley

0.07

0.07

0.042

0.059

Motorcycle

0.009

0.009

0.005

0.007

Bicycle

0.001

0.001

0

0.001

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.7 Roadway land value.  The roadway land value was defined as the opportunity costs of land used for roadways.  This cost includes the Avalue of land used for road rights-of-way and other public facilities dedicated for automobile use@ [42].   First to obtain the annual roadway cost, the roadway land worth of $75 billion is multiplied by 75%, which is the percentage of road way which represents right-of-ways.  This amount is then divided by the national average of vehicle miles (2,300 billion) to obtain the roadway land value per vehicle mile. The roadway land value costs are presented in Figure 2-13.

 

 

 

 

 

 

 

 


 

Figure 2-13:  Roadway Land Value Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.024

0.024

0.024

0.024

Compact Car

0.024

0.024

0.024

0.024

Electric Car

0.024

0.024

0.024

0.024

Van/Light Truck

0.024

0.024

0.024

0.024

Rideshare Passenger

0

0

0

0

Diesel Bus

0.024

0.024

0.024

0.024

Electric Bus/ Trolley

0.024

0.024

0.024

0.024

Motorcycle

0.024

0.024

0.024

0.024

Bicycle

0.001

0.001

0.001

0.001

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.8 Municipal services.  Municipal service costs are costs of public services for motor vehicles not funded by user fees.  This cost includes policing, emergency response, planning, courts, street lighting, parking enforcement, and driver training provided for motor vehicle use.  The cost of municipal services estimated by Litman are shown in Figure 2-14.

Figure 2-14:  Municipal Service costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.015

0.010

0.005

0.009

Compact Car

0.015

0.010

0.005

0.009

Electric Car

0.015

0.010

0.005

0.009

Van/Light Truck

0.015

0.010

0.005

0.009

Rideshare Passenger

0

0

0

0

Diesel Bus

0.015

0.010

0.005

0.009

Electric Bus/ Trolley

0.015

0.010

0.005

0.009

Motorcycle

0.015

0.010

0.005

0.009

Bicycle

0.002

0.001

0.

0.001

Walk

0.002

0.001

0

0.001

Telecommute

0.002

0.001

0

0.001

 


 

Figure 2-15: Equity and option value costs (1996 U.S. Dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.005

0.005

0.005

0.005

Compact Car

0.005

0.005

0.005

0.005

Electric Car

0.005

0.005

0.005

0.005

Van/Light Truck

0.005

0.005

0.005

0.005

Rideshare Passenger

0

0

0

0

Diesel Bus

0

0

0

0

Electric Bus/ Trolley

0

0

0

0

Motorcycle

0.005

0.005

0.005

0.005

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

 

2.5.4.9 Transportation equity & option value.  Transportation equity is defined as the adequate transportation for people who are economically, socially, or physically disadvantaged.  Transportation option value was defined as the value of having a variety of transport choices. The equity and option values are affected by the transportation system, land use patterns, facility design, and social habits that affect travel requirements.   Litman notes that there is little research available for this cost and that its estimate is extremely uncertain.  The transportation equity and option values are displayed in Figure 2-15, above.  

2.5.4.10 Air pollution costs.  Air pollution costs are defined as air pollution caused by motor vehicle use.  The pollutants used for this study include: carbon monoxide (CO), particulate (PM), nitrogen oxides (NOx), volatile organic compound (VOC), sulfur oxides (SOx), carbon dioxide (CO2), methane (CH4), road dust, and toxic gases such as benzene.  Using previous studies and estimations of air pollution, Litman estimated the cost per vehicle mile for air pollution. The air pollution costs are presented in Figure 2-16.

 

 


 

Figure 2-16: Air Pollution Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.062

0.052

0.016

0.040

Compact Car

0.051

0.042

0.010

0.031

Electric Car

0.016

0.013

0.004

0.010

Van/Light Truck

0.112

0.094

0.029

0.071

Rideshare Passenger

0.002

0.002

0.001

0.001

Diesel Bus

0.185

0.16

0.070

0.129

Electric Bus/ Trolley

0.078

0.065

0.020

0.050

Motorcycle

0.106

0.086

0.014

0.061

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.11  Noise.  Noise was defined as unwanted sounds and vibrations produced by motor vehicle use.  Noise included traffic noise (engine acceleration, tire/road contact, braking, and horns) and vibrations included low frequency noise, which is produced by heavy vehicles. Using previous studies and estimations of noise pollution, Litman estimated the cost per vehicle mile for noise pollution.  Figure 2-17 displays cost for noise.

Figure 2-17: Noise costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.010

0.010

0.005

0.005

Compact Car

0.010

0.010

0.005

0.005

Electric Car

0.003

0.003

0.003

0.003

Van/Light Truck

0.010

0.010

0.005

0.008

Rideshare Passenger

0

0

0

0

Diesel Bus

0.050

0.050

0.025

0.04

Electric Bus/ Trolley

0.030

0.030

0.015

0.024

Motorcycle

0.100

0.1

0.050

0.08

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

 


 

2.5.4.12 External resource consumption costs.  External costs are costs of resources consumed by vehicle production and use.  It was estimated that the United States consumes 24% of aluminum, 30% of iron, 15% of steel, 76% of lead, 67% of rubber production, and over 50% of petroleum for automobile construction and usage.  Using these percentages and previous consumption studies, Litman estimated a cost of external resources per vehicle mile.  These costs are presented in Figure 2-18. 

Figure 2-18: External Resource Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.029

0.025

0.021

0.024

Compact Car

0.014

0.013

0.011

0.012

Electric Car

0.007

0.006

0.006

0.006

Van/Light Truck

0.039

0.033

0.028

0.032

Rideshare Passenger

0.001

0.001

0

0.001

Diesel Bus

0.152

0.131

0.110

0.127

Electric Bus/ Trolley

0.045

0.038

0.032

0.037

Motorcycle

0.012

0.010

0.009

0.010

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0.003

0.003

0.002

0.003

2.5.4.13  Barrier effects.  Barrier effects is defined as the Amotor traffic impacts on the mobility, security and comfort of pedestrians and cyclists, and its effect on their movement and activities@.   This cost is obtained from previous literature and imposes costs in terms of increased automobile dependency and use, and increased chauffeuring.  Figure 2-19 displays the barrier effect costs.   

 

 

 

 

 


 

Figure 2-19: Barrier Effect cost (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.015

0.010

0.005

0.009

Compact Car

0.015

0.010

0.005

0.009

Electric Car

0.015

0.010

0.005

0.009

Van/Light Truck

0.015

0.010

0.005

0.009

Rideshare Passenger

0

0

0

0

Diesel Bus

0.038

0.025

0.013

0.023

Electric Bus/ Trolley

0.038

0.025

0.013

0.023

Motorcycle

0.015

0.010

0.005

0.009

Bicycle

0.001

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.14 Land use impacts.  Land use impacts are defined as external costs of land use impacts caused by roads and automobile traffic.  Based upon previous studies Litman estimates land use costs for cars, trucks, motorcycles, and telecommuting (ridesharing, public transit, bicycling, and walking impose no land use impacts because they decrease road building requirements and encourage higher densities). Figure 2-20 displays the land use impact costs.

Figure 2-20: Land Use Impacts Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.070

0.070

0.035

0.056

Compact Car

0.070

0.070

0.035

0.056

Electric Car

0.070

0.070

0.035

0.056

Van/Light Truck

0.070

0.070

0.035

0.056

Rideshare Passenger

0

0

0

0

Diesel Bus

0

0

0

0

Electric Bus/ Trolley

0

0

0

0

Motorcycle

0.070

0.070

0.035

0.56

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0.070

0.070

0.035

0.056

 


 

2.5.4.15 Water pollution and hydrologic impacts.  Water pollution and hydrologic impacts are pollution and hydrologic effects from vehicles, roads, and parking usage.  Water pollution included: crankcase oil drips and disposal, road de-icing (salt) damage, roadside herbicides, leaking underground storage tanks and air pollution settlements.  Hydrologic impacts include: increased impervious surfaces, concentrated runoff and increased flooding, loss of wetlands, shoreline modifications, and construction activities along shorelines.   By dividing the estimated annual cost of water pollution ($29 billion) by the estimated number of vehicle miles per year (2,300 billion), the estimated cost of pollution is $0.13 per vehicle mile.  The cost of electric vehicles is estimated at half of this rate.  The water pollution costs are presented in Figure 2-21.

Figure 2-21:  Water Pollution Costs (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.013

0.013

0.013

0.013

Compact Car

0.013

0.013

0.013

0.013

Electric Car

0.007

0.007

0.007

0.007

Van/Light Truck

0.013

0.013

0.013

0.013

Rideshare Passenger

0

0

0

0

Diesel Bus

0.013

0.013

0.013

0.013

Electric Bus/ Trolley

0.007

0.007

0.007

0.007

Motorcycle

0.013

0.013

0.013

0.013

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

2.5.4.16  Waste disposal.  Waste disposal is defined as the external costs of automobile waste disposal.  This cost includes: disposal of used tires, batteries, junked cars, oil and other semi-hazardous materials resulting from motor vehicle production and maintenance.  The waste disposal cost are estimated by dividing the annual external motor vehicle waste cost ($4.2 billion per year) by the average number of annual vehicle miles (2,300 billion miles per year).  The waste disposal cost are shown in Figure 2-22.

 

 


 

Figure 2-22: Waste Disposal Costs  (1996 U.S. dollars per vehicle mile)

Vehicle Class

Urban peak

Urban off-peak

Rural

Average

Average Car

0.002

0.002

0.002

0.002

Compact Car

0.002

0.002

0.002

0.002

Electric Car

0.002

0.002

0.002

0.002

Van/Light Truck

0.002

0.002

0.002

0.002

Rideshare Passenger

0

0

0

0

Diesel Bus

0.002

0.002

0.002

0.002

Electric Bus/ Trolley

0.002

0.002

0.002

0.002

Motorcycle

0.0002

0.002

0.002

0.002

Bicycle

0

0

0

0

Walk

0

0

0

0

Telecommute

0

0

0

0

2.6 Other Transportation Studies

Other studies were conducted that are useful in estimating the economic impacts of public transportation.  They are discussed in the following sections.

 

2.6.1  Puget Sound:  Case Study

 

This case study was developed by ECONorthwest for the Puget Sound Regional Council and the U.S. Department of Transportation Federal Highway Administration.  The study focuses on the analytic approach to integrated transportation planing, specifically, Athe evaluation of long-term, large-scale system alternatives of the type contemplated in a metropolitan transportation plan@ [20].  ECONorthwest goals were to:

$    demonstrate the application of integrated transportation planning analysis methods to the analysis and evaluation of several hypothetical system-level transportation plans

C    identify short-term and long-term changes to current transportation data collection and modeling techniques that would support integrated transportation planning

$   identify further refinements to integrated transportation planning analysis and evaluation methods.

 


 

This study tests the application of integrated transportation planning by applying it to three hypothetical transportation system plans for the central Puget Sound region.  The hypothetical plans were: 1) additions to highway capacity, 2) major additions to transit capacity, and 3) economically efficient pricing of transportation facilities.  The form of each alternative was selected based on its similarity to a policy for which the Regional Council had already done most of the necessary modeling.  This analysis tested the Aapplication of integrated transportation planning across substantially different alternatives in order to reveal the strengths and weaknesses of the approach and the adequacy of the available data@ [20].

2.6.2   A Guidebook for Rural Public Transit Services

A study was conducted by the University of Oklahoma to estimate the ridership of Oklahoma's rural public transportation.  This study will be used as a tool in developing new transit systems for Oklahoma=s rural areas.  The estimation of ridership on public transit is a critical and difficult step in the planning process for any system.  This is due to the fact that ridership affects operational decisions such as vehicle size, type of service provided, and frequency of route provision [35].

A multivariate regression modeling approach was used because of the data available from Oklahoma rural transit systems.  This approach has the advantage of allowing for the consideration of many factors affecting transit usage. The details of the model are discussed in the following sections. 

2.6.2.1  Ridership model.  The model developed for estimating passenger trips is based on the theory that ridership depends on demographic characteristics, characteristic of the transit service, and the availability of other transit services.  It is recognized that transit systems might need different kinds of ridership estimates.  Operators who are attempting to establish a new transit system would want to look at ridership estimates for the entire system within a county.  Alternatively, an existing transit system may want to alter the type or extent of services offered and would only want to analyze ridership for a particular route or routes.  The following three models were developed:

C  County model - considers ridership in a county for an entire transit system.

C  Demand response model - examines ridership for intra-community demand-responsive services


 

C  Fixed route model - looks at inter-community fixed route use.

The data for this study was collected from six, Section 18, systems serving 19 counties in Oklahoma.  The transportation systems located in these areas consisted of various fixed route, demand response, and contractual services.  Data was collected on a monthly basis for 19 months.  The information gathered consisted of the following:

 

1. ridership

2. type and extent of service provision

3. fares

4. presence of other transit services in the area

5. population

6. income levels

7. vehicle registration

8.  population densities

 

2.6.2.2  The model variables.  The variables used in the model are listed and described in Figure 2-23 .

Figure 2-23: Variable Definitions

 

Variable Name

 

Description

 

County Model

 

 

 

SERPOP

 

sum of populations of incorporated places where the transit system picks up

riders.  Population of destinations are not included.  Estimated annually using

preliminary Census reports and projections.

 

INCHH

 

average 1979 income per household by county

 

AUTO

 

number of auto, pick-up, and farm truck registrations per household by county.

 

MILES

 

number of vehicle miles of transit service provided per month

 

FREQ

 

Frequency of service is proxied by the sum of the number of days each route is

run per month

 

OTHBUS

 

number of other public or human service agency transit vehicles operating

 in the service area

 

SUMMER

 

dummy variable, where 1 indicates the month of May, June, July, or August

and 0 indicates any non-summer  month.  Used to examine summer

observations versus non-summer observations

 

Demand Res. Model

 

 

 

POPSEC

 

Population of the incorporated place which is served.  Estimated annually

using preliminary Census reports and projections.

 

FREQ

 

number of days the route is provided per month

 

Fixed Route Model

 

 

 

POPDEST

 

population of city which is destination of route, estimated annually

 

DIST

 

Round trip mileage of route

 

PERMIL

 

percentage of total monthly vehicle miles provided by system which are  run

on the fixed route.

 

FREQ

 

number of days per month the route is run

[Elizabeth F. Knowles and Gerald A. Doeksen,  A Guidebook for Rural Public Transit Services, University of Oklahoma, November 1987].

 

 

 

 


 

2.6.2.3 County model.  One way passenger trips per month were calculated by the

 

equation below:

 

County Model =3196.7 + .0351(SERPOP) + .1408(MILES) + 7.5935(FREQ) - .1003(INCHH) - 325.428(OTHBUS) - 190.2434(SUMMER) - 824.6981(AUTO)                                         (2-1)

Calculation of county-wide ridership estimates were performed on a step-by-step basis.  First, the value of the model variable was calculated according to its definition.  Second, the product of the variable values and their respective parameter estimates were summed.  This sum is the estimate of total ridership per month. 

 

2.6.2.4  Demand response model.  One way passenger trips per month was described in the study by equation (2-2) below:

 

Demand Response Model = -156.8 + .0711(POPSEC) + 12.8973(FREQ)             (2-2)

 

The projection of rides per month for a demand responsive system in Community A was calculated by using the population of the sector served and the frequency of service. 

2.6.2.5  Fixed route model.  One way passenger trips per month was defined in the study by equation (2-3).

 

Fixed Route Model  = 15.4 + .0006(POPDEST) - .2720 (DIST) + 7.7072(FREQ) +

139.0134(PERMIL)                                                                           (2-3)

 

To calculate this estimate, the variable PERMIL was calculated and the variables population, distance, and frequency was provided.  PERMIL is calculated by  dividing the total monthly miles run per route by the total monthly miles run by the system. 

The authors states that, Athe success of these models may partially depend on how similar the community characteristics are to those on which the model was initially based@ [35].  The examination of the ridership estimates can lead to important decisions regarding fleet capacity and route scheduling.  Once a transit system has operated for several years it will have a history on which to base ridership  projections.  Models, such as those presented, may help transit operators to examine potential ridership in a community.

 

 


 

2.6.3  A Disaggregate Discrete Choice Model of Transportation Demand by Elderly and

          Disabled People in Rural Virginia

In the study undertaken by Steven Stern, a correlated multinomial and a Poisson regression model was used to measure the demand for public transportation (fixed-route buses and special paratransit) by the disabled and elderly people living in rural Virginia.  The disabled and elderly people in this study are referred to as the transportation-handicapped (TH) [60]. 

Data was obtained from a transit system located in Albemarle County SMSA of Charlottesville, Virginia.  This information included the characteristics of paratransit  (called JAUNT) and fixed-route transit used by elderly and disabled people.  The study attempts to determine how fare cost and location characteristics affect demand for paratransit and fixed-route transit.  The study also attempts to show how the existence of attractive paratransit and accessible fixed-route transit increases the TH opportunities outside of their homes.

The author reports that most previous discrete choice studies assume that an individual uses the same mode of transportation every trip.  However, TH people used many modes of transportation because they could not rely upon any one mode all of the time.  The study provided for each individual to use more than one mode.

 

2.6.3.1 Conclusions.  The author concluded the following:

C     That paratransit systems providing door-to-door service was highly valued by the transportation-handicapped populations. 

C     The taxi services was a potential mode of transportation, but was inferior due to its fare cost. 

C     Buses were estimated at being a poor alternative, especially in rural areas were distances between destinations is far apart.  

C     Buses that were handicapped  accessible showed a statistical significance, but had a small effect  on mode choice. 

C     The demand was price inelastic.

C     The total number of trips taken by TH were insensitive to the availability and characteristics of the transportation mode.


 

Therefore, based on these conclusions the author suggests that TH limit the number of trips they take and that most of the trips the TH take are necessary (such as trips to medical facilities ).

This chapter has summarized relevant literature related to the proposed research.  Some aspects of the work surveyed was used in this research.  The method of analysis used in this project is the subject of the chapter that follows. 


 

3.0  METHOD OF ANALYSIS

3.1  System Selection

 The first step of this study was to select and analyze the rural transportation systems. According to the United States Census, rural is defined as a place with a population of less than 2,500 [64].  Hence for this study, rural transportation is defined as public transportation which is supplied to areas with less than 2,500 people.  The project requirements for transit system selection were: that the system operates non-private services, that the transit supplies services to rural areas, and that the transit system received Section 18 funding for non-urbanized areas. 

Under these requirements the following fourteen Arkansas Public Transit systems were selected:

 

Ozark Regional                                              Razorback Transit

Fort Smith Public Transit                               City of Siloam Springs

South Central Arkansas Transit                   East Central Arkansas E.D.C.

North Arkansas Transit System                   Pine Bluff City Transit

Southeastern Arkansas Transit                    City of Hot Springs

Central Arkansas Transit Authority             Eureka Springs Transit

Mid-Delta Community Services                   Black River Area Development

Razorback Transit, Central Arkansas Transit (CAT), and Pine Bluff City Transit receive Section 9 funding for urban and small urban areas, these three transit operators were added to this study due to their supply of services to surrounding rural areas.  Each transit system is considered to be a rural public transportation system. 

3.2  Data Collection


 

In order to determine the economic impacts of any rural transit operator, data concerning the transit system=s service area and the public transportation providers was collected.  This data was instrumental in outlining the benefits of public transportation and determining the impacts of each rural public transportation system.

3.2.1  Demographic Data 

Demographic data was collected on each of the public transit operator service area.  This information aided in understanding the social and economical structure of the area served by the public transit systems.  The analyst recognizes that many of the rural areas consist of more than one Arkansas county.  Therefore for the multi-county service areas, the demographic data from all of the counties of that particular service area were combined.  Demographic data included the following: 

C     names of the counties within each transit service area

C     characteristics of the citizens living in that area (the average number of elderly, poor, disabled, and youth),

C     the size and density of the population,

C     the average cost of living index,

C     the average amount of personal household income,

C     the average number of cars per household,

C     the average annual amount of consumer expenditures per county (spending on health care, personal goods, etc.),

C     the number of employers per county,

C     and the demographic information specifically on elderly populations (average income, percentage living in nursing homes, annual expenditures). 

This data was collected from various sources such as the United States Census-Arkansas,  Arkansas Statistical Abstracts, Arkansas Census of Retail Trade, Demographics USA- County Edition, and United States Statistical Abstracts [9,17,43,58,62,63,64,65,66,67].

3.2.2  Transit Operator Data & Survey  


 

It was necessary to  collect information regarding each public transit system and a survey was developed to obtain relevant transit system information.  Before sending the survey to all Arkansas transit systems, a preliminary run was conducted to test the feasibility of the survey.  The developed survey was delivered to a public transit operator, who confirmed that the answers to the survey questions could be gathered.  After a comprehensive discussion, the final changes and adjustments were made to the document.  Copies of the survey were sent with a cover letter which explained the contents and basis for the tool.  The survey was composed of two sections.  The first section sought information concerning the history of the transit system, types of services offered by the transit system (fixed-route, demand-responses, contractual services, etc.), the days and times transportation services are available, the transit fleet size, travel data (average number of miles per trip, average number of passengers per mile, average travel time per patron, average vehicle speed, average number of trips to medical facilities, etc.),  the general characteristics of patrons using the transit services (number of elderly riders, number of disabled patrons, etc.),  and other demographic data for the transit=s service area (tourist attractions, educational facilities, etc.).

The second section requested information concerning the financial aspects of the public transit system, such as: the average annual expenditures (maintenance and wage costs),  estimated annual revenues (rider fares and contracts), and other types of financial support received by the transit providers (formula grants and taxes).   The complete survey is presented in Figure 3-1. 

 


 

Figure 3-1: Survey

 

 


 

Figure 3-1: Survey (continued)

 


 

Figure 3-1: Survey (continued)


 

3.2.3  Data Obtained 

Summaries of the demographic data for each transit system is presented in Figures 3-2, and 3-3.  The counties serviced by each transit system and  demographic data such as the average household income, number of manufacturing businesses, total population, and total number of households per transit area are shown in Figure 3-2.   The percentage of the population in each transit area that is transit dependent is shown in Figure 3-3.  Transit dependents are defined as households that do not have personal transportation, households with low income, individuals who are sixty-five and older, and individuals with mobility limitations [21,29,53,61].

From the fourteen surveys that were sent to Arkansas transit systems there was a return rate of  92.86%.  After the documents were reviewed, a data sheet for each transit system was created and is contained in Appendix B.  A partial summary of each transit system is outlined in Figure 3-4.

There were three basic types of routing services among the Arkansas transit operators: fixed route, demand-response, and/or fixed routes with deviations (or scheduled routes with deviations).  The fixed route systems provided pick-up and drop-off locations along a specified route.  The demand-response services respond to or react upon the request of the patrons desiring transportation.  In the scheduled routes with deviation service, a transit vehicle operates on a scheduled route and will deviate from its course in order to supply services to patrons who may need transportation outside of the routing area.  The types of routes for each transit system are also displayed in Figure 3-4.

 


 

Figure 3-2:  Counties Served and Demographics per Public Transit System

 

Transit System

 

Counties serviced

 

Total population

 

Avg. household income ($/year)

 

Number of business establishments

 

Total Number of households

 

Ozark Regional

 

Washington, Benton, Carroll, Madison

 

241,130

 

27,231

 

6,441

 

87,504

 

Fort Smith Public Transit

 

Sebastian (City of Fort Smith)

 

99,590

 

30,865

 

 3,209

 

39,298

 

South Central Arkansas Transit

 

Clark, Hot Springs, Montgomery, Pike, Saline

 

129,662

 

22,998

 

2,406

 

48,007

 

North Arkansas Transit System (NATS)

 

Baxter, Boone, Carroll, Fulton, Izard, Marion, Newton, Searcy

 

127,046

 

22,469

 

3,077

 

51,766

 

Southeastern Arkansas Transit

 

Ashley, Bradley, Calhoun, Cleveland, Chicot, Dallas, Desha, Drew, Grant, Jefferson, Lincoln

 

222,338

 

27,231

 

4,302

 

78,677

 

Central Arkansas Transit Authority  (CAT)

 

Pulaski

 

349,660

 

34,770

 

11,158

 

137,209

 

Mid-Delta Community Services

 

Arkansas, Monroe, Phillips

 

49,681

 

20,204

 

1,032

 

18,205

 

Razorback Transit

 

Washington

 

113,409

 

30,010

 

3,168

 

43,372

 

City of Siloam Springs

 

Benton

 

97,449

 

31,722

 

2,478

 

37,550

 

East Central Arkansas E.D.C

 

Crittenden, Lee, St. Francis

 

91,489

 

21,884

 

1,643

 

31,656

 

Pine Bluff City Transit

 

Jefferson

 

85,487

 

27,246

 

1,750

 

30,001

 

City of Hot Springs

 

Hot Springs

 

26,115

 

23,290

 

2,266

 

30,836

 

Eureka Springs Transit

 

Carroll

 

18,654

 

24,928

 

636

 

7,550

 

Black River Area Development (BRAD)

 

Clay, Lawrence, Randolph

 

52,122

 

21,125

 

1,007

 

20,806


 

Figure 3-3: Percentage of Transit Dependent Populations per Transit system (1990 Census).

 

Transit system

 

 

Low income households

 

 

Population age 60+

 

Households without cars

 

Population with mobility limitations

 

Ozark Regional

 

18.3

 

14.7

 

5.85

 

3.4

 

Fort Smith Public Transit

 

18.4

 

18.1

 

6.4

 

3.9

 

South Central Arkansas Transit

 

21.1

 

18.9

 

7.8

 

4.9

 

North Arkansas Transit System (NATS)

 

25.1

 

21.9

 

7.7

 

5.2

 

Southeastern Arkansas Transit

 

16.5

 

14.1

 

13.2

 

4.4

 

Central Arkansas Transit Authority  (CAT)

 

16.7

 

15.5

 

10.8

 

3.4

 

Mid-Delta Community Services

 

22.8

 

20.9

 

6.37

 

5.6

 

Razorback Transit

 

19.1

 

14.9

 

5.7

 

3.2

 

City of Siloam Springs

 

13.4

 

23.1

 

6.4

 

3.5

 

Pine Bluff City Transit

 

26.9

 

17.7

 

13.2

 

4.0

 

City of Hot Springs

 

24.2

 

21.7

 

10.8

 

4.9

 

Eureka Springs Transit

 

20.9

 

24.7

 

6.1

 

3.9

 

Black River Area Development (BRAD)

 

11.6

 

24.5

 

6.37

 

6.5


 

Figure 3-4:  Transit System Summary

 

Transit system

 

Type of routings

 

Fleet Size

 

Ann. vehicle miles

 

Average Annual Ridership

 

Fare Cost

 

Age of the Transit System

 

Eureka Springs Transit

 

fixed route,

 

13

 

120,000

 

19,200

 

$3.00/person

 

14 years

 

North Arkansas Transportation

 

demand-response, fixed routes w/ deviations

 

28

 

300,000

 

165,120

 

$14.5/person/week

 

16 years

 

Hot Springs Intra-city

 

fixed

 

18

 

363,700

 

190,400

 

$1.00/person

 

16 years

 

Razorback Transit

 

fixed route, demand-response

 

24

 

271,040

 

 

 

free

 

17 years

 

Ozark Regional Transit

 

fixed route, demand-response

 

38

 

923,792

 

212,509

 

$1.25/person

 

19 years

 

Mid-Delta Transit

 

fixed route, demand-response

 

48

 

963,000

 

19,200

 

$3.50/person

 

14 years

 

BRAD Public Transit

 

demand-response

 

10

 

171,150

 

63,680

 

$1.00/person

 

22 years

 

Pine Bluff Transit

 

fixed route, demand response

 

13

 

200,000

 

138,240

 

$0.80/person

 

23 years

 

Southeast Arkansas

 

fixed route, demand response

 

54

 

77,500

 

169,258

 

varies

 

3 years

 

Fort Smith public Transit

 

fixed route

 

10

 

300,000

 

85,232

 

$1.00/person

 

1 year

 

Central Arkansas Transit

 

fixed route, demand-response

 

78

 

2,622,583

 

319,984

 

$0.90/person

 

11 years

 

South Central Arkansas Transit

 

fixed route, demand-response

 

63

 

638,240

 

254,720

 

$2.00/person

 

over 60 years

 

 


 

3.3   Benefits

A list of possible benefits derived from rural public transit were established utilizing demographic and transit operator data.  These benefits can be described as any economic/social advantage(s) that may be received by a state, community, or individual from the availability of public transportation.  Developing the list of benefits involved reviewing the different characteristics (demographics) and writing descriptions of how the public transit system could positively support or contribute to these characteristics.  For example, if an area has a large population of elderly citizens who are unable to drive, public transportation may help the elderly to maintain their independence by transporting them to shopping and medical facilities.  Also, if the ratio of car ownership per household is low in an area, businesses and industries may experience large turnover rates due to employees not being able to obtain dependable transportation to work.   In this case, public transportation could be contracted by employers to supply a dependable source of transportation for their employees, thus, decreasing the rate of turnovers for employers.  

The list of  benefits were then separated into two main categories:  individual and community benefits.  The benefits are shown in Figure 3-5 for each category.

 

 

 

 

 

 

 

 

 

 

 

 

 


 

Figure 3-5:  Benefits for the Transit User and Community

 

User benefits:

- increased mobility for non drivers

- increased flexibility in travel arrangements

- improved accessibility to other areas

- decreased cost in travel

- improved lifestyle

Community benefits:

- improved employment

- increased opportunities in medical services, educational advancement, and

  recreational activities

- increased employment market for businesses

- multiplier effect of expenditures

- improved environment

- increased land use

 

User benefits:

- increased mobility for non drivers

- increased flexibility in travel arrangements

- improved accessibility to other areas

- decreased cost in travel

- improved lifestyle

Community benefits:

- improved employment

- increased opportunities in medical services, educational advancement, and

  recreational activities

- increased employment market for businesses

- multiplier effect of expenditures

- improved environment

- increased land use

  

 

It was assumed that some of the benefits in the list would be of minimal importance to the rural communities evaluated and thus could be excluded from this study.   For example, the benefit of public transit being used to reduce traffic congestion, was unlikely to be an important issue for the rural areas in this study.  Since rural areas do not have dense populations, there are very few cases of traffic congestion problems.  Therefore, traffic reduction was not considered a viable benefit for most rural areas.

The next phase of this study involved establishing links between transit benefits, patrons currently riding transit, and the services provided by the public transit system.  The relationship among these three links were used to determine the impacts for this study.  The links analyzed in this study are displayed in a diagram in Figure 3-6.

 

 

3.4  Selecting Impacts


 

The objective of this study is to analyze the economic impacts of  Arkansas rural public transportation. An extensive review of  economic impacts was necessary in determining those applicable to the Arkansas transit systems.   The impacts reviewed from the literature are listed as follows:

C     Social - cost savings to the community and individual transit user

C     Employment - economic effects to employees and employers

C     Environmental - effects to the environmental area

C     Land use - development and usage of land

C     Retail sales - effects of retail sales on an area

C     Accident - costs of accidents

C     Elderly  - effects on elderly populations

C    Medical - effects on medical costs

C     Delivery - effects on delivery and commercial transportation

The impacts were selected by comparing the links established in the previous section to the characteristics of the available impacts.  The impacts which were similar in character to the links were selected.  Impact selection was also based upon the amount of data obtained from the data collection.  For example, if there was not enough data to support a quantitative estimation of an impact, it was not included.

The impacts selected were:  social, elderly, medical, employment, and retail.  (The environmental, land use, and accident impacts were included in the social cost estimations).  Each category is defined, discussed, and quantitatively represented in the following sections. 

The impacts were analyzed by one of two methods.  One method compared the quantitative estimates of using the existing transit versus estimates of the area without the public transit.  The other method was a cost-benefit analysis of the impact category. 

3.5  Parameters


 

The parameter I (the increase in the number of automobiles) was calculated for impacts which compared the cost of using the existing transit system to the cost of increased automobile usage due to the absence of the public transit system.  This parameter represents the increased number of automobiles that could be added to the transit service area if the public transportation system did not exist.  To calculate the increase in the number of automobiles to the area, the following equation was used:

I   =   ΣPAS                                                                                                    (3-1)

  N

 

where:

 

I           =  estimated increase in automobile if the transit system did not exist

PAS     =  passenger capacity per transit vehicle.

N         =  average number of persons per automobile

 

The variable PAS was obtained from the survey received from each transit system.  The variable N is equal to 1.2 persons per automobile and is the national average of persons per automobile [5].  Parameter I  will be utilized in the following sections.

3.6  Social Impacts

The social impact is the estimated cost savings for individuals and the community serviced by a public transportation system. In this analysis it is assumed that patrons will select the mode of transportation that is most economical for them.  Thus, the social impact for the individual was estimated by comparing the cost of using public transit verses the cost of using other modes of transportation.  Social impacts to the community were based on the savings in cost when public transit is supplied verses the estimated cost that would occur if the transit system did not exist.

3.6.1  Individual Cost Savings


 

            The cost savings received by a public transit user was estimated by comparing the usage or operation costs for various modes of transportation within a service area.  The modes of transportation used for comparison in this study were the personal automobile, taxi, and the public transit system. Based on information received from each transit system analyzed, the aforementioned modes are the most commonly used forms of transportation.  

The operating cost of each transportation mode was calculated in order to determine the savings or social impact (if any) to the individual using one mode of transportation over another.  The following equation was used to calculate the estimated annual individual social cost of using the automobile or taxi.

UX = [G*RX+ FEE]* D                                                                                   (3-2)

 

where:

 

UX        = estimated annual social cost per mode x (automobile or taxi) for individuals

G         = average number of miles traveled per day

RX       = average operation cost per vehicle mile for transportation mode x ( automobile or taxi)

FEE     = additional daily fees incurred by the selected mode (parking or base fees)

D         = average number of workdays per year (250 days)

 

The average operation cost for automobiles of $0.43 per vehicle mile was obtained from the United States Statistical Abstract [58].  The operation cost for taxi, $1.20 per vehicle mile, was averaged from taxi fare estimates received from taxi companies in Arkansas [14,56].  The parking fee for automobiles was obtained from the literature and estimated to average $3.00 per day [31,42]. The taxi base fee (taxi pick-up fee) was averaged to be $2.13 per pick up and was multiplied by two to represent the addition taxi fee cost per trip [14,56]. Therefore, the taxi fee was $4.26 per day.   The estimated annual social cost of public transit for individuals was calculated using the following equation:

YP= K*D                                                                                                                   (3-3)

 

where:

 

YP       = estimated annual social cost of public transit for individuals

K         = fare cost per unit of time ($/ day)

D         = number of workdays per year (250 days)


 

After estimating the annual cost for the public transit system, automobile and taxi, the cost difference of the public transit system and the automobile or taxi was determined.  This was done to determine the savings or increase in using one mode over another.  The results for each transit system are shown in Appendix A. 

3.6.2 Social Impact on the Community

  The social impacts to the community were determined by comparing the community social cost with the existing transit system to the social costs to the community if the current transit system did not exist.   It is assumed that if  the transit system were to disappear, there would be an increase in the number of automobiles for the transit area.  Thus, this increase in automobiles in the area would increase the social cost to the community.

Community social costs were calculated using cost variables from a study conducted by Todd Litman.  In Litman=s study, cost variables of various modes of transportation, area type (rural or urban), and time periods were presented [42].  It should be noted that the rural social cost variables were used for all transit systems, except for Central Arkansas Transit Authority and Pine Bluff City Transit.  The urban social cost variables were used for these systems due to their more urbanized transit service area.  The social cost variables are described as dollars per vehicle mile and are displayed in Figure 3-7.

The travel time variable was adjusted for each transit system, due to the availability of transit vehicle speeds and Arkansas=s average wage rate. The adjustment for each transit system was calculated using the following equation:

 

TIM = L * WAGE                                                                                                     (3-4)

       S

 

 


 

where:

 

TIM     = cost of travel time per vehicle mile for transit

L          = percentage of wage which represents the value of time per hour (0.35 or 0.5)

WAGE = average wage per hour ($10.41/hour)

S          = average speed of the transit vehicle (miles per hour)

 

The variable L (0.35 for rural bus and 0.5 for urban bus) was taken from Litman=s study, as the percentage of the hourly wages that is representative of the value of the transit rider=s time.   Litman=s study uses an average wage of $12 per hour [42].  The average wage for Arkansas was estimated by the Arkansas Economic Development Commission to be $10.41 per hour and the average speeds for the transit vehicle was obtained from surveys received from the transit systems [7]. Therefore, the TIM was calculated for each transit system and summed with the other cost variables (for transit) to obtain the total social cost per vehicle mile for transit (SCT).  The SCT variable is used later in this section to calculate the annual social cost to the community with the current transit system. 

Since the actual speeds for automobiles were unknown for the transit areas, the travel time variables for the urban- peak automobile and rural automobile were adjusted by using Arkansas=s average wage rate and Litman=s estimate of automobile speeds [42].  The adjustments for the travel time variable of urban-peak automobile and rural automobile are shown in Figure 3- 8.

The adjusted TIM variables, calculated in Figure 3-8, were used to represent the travel time variable for all urban-peak and rural automobiles ($0.202 per vehicle mile and $0.091 per vehicle mile, respectively).  The travel time variable for the automobile was summed with the other social cost variables (for automobiles) to obtain the total social cost per vehicle mile for automobile (SCA).  The SCA variable is used in the following sections to calculate the annual social cost to the community if the transit system did not exist.


 

Figure 3-7: Social Cost Variables

Cost Variables

Definition

Urban peak-bus

(transit)

Urban peak- auto

Rural  bus

(transit)

Rural auto

user cost  *

 

 

 

 

 

     fixed

Vehicle purchase or lease

------

------

-----

-----

     variable

Maint., repair, fuel cost, parking toll

------

------

-----

-----

Travel time  **

Value of travel time.

varies

.203

varies

.091

Accident cost

 

 

 

 

 

     internal

Cost for motor vehicle occupants

.003

.05

.003

.05

     external

Cost for non-occupants of motor vehicle

.20

.035

.20

.035

Parking

 

 

 

 

 

     internal

Opportunity cost of residential parking space

0

.05

0

.025

     external

Opportunity cost of non-residential parking space

0

.12

0

.020

Congestion

Incremental costs resulting from interference among road users.

.34

.17

0

0

Road costs

Roadway facility costs required for automobile use not borne by user fees.

.070

.016

.042

.010

Right-of-Way,  Land

Opportunity costs of land used for roadways

.024

.024

.024

.024

Public Services

Costs of public services for motor vehicles not funded by user

.015

.015

.005

.005

Trans. Equity, Option Value

Equity- adequate provision of transportation for disadvantage

Option value- value of having a variety of mode choices

0

.005

0

.005

Air pollution

Costs of air pollution caused by motor vehicle use

.185

.062

.07

.016

Noise

Unwanted sounds and vibrations produced by motor vehicle use

.050

.010

.025

.005

Resource Consumption

External costs of resources consumed by vehicle production and use.

.152

.029

.110

.021

Barrier Effect (severance)

Effect of motor vehicle on non-motorized transportation modes in public ways

.038

.015

.013

.005

Land use Impacts

External costs of land use impacts caused by roads and automobile traffic

0

.070

0

.035

Water Pollution

Water pollution & hydrologic impacts from vehicles, roads, and parking.

.013

.013

.013

.013

Waste Disposal

External costs of automobile waste disposal

.002

.002

.002

.002

*    The user cost variables were not used in this section due to the estimation of social cost estimations presented

       in the previous section.

**  The travel time variable was adjusted for the transit system and the automobile.


 

Figure 3-8: Adjusted Travel Time Variables for Automobiles

 

Urban-peak automobile                                             Rural automobile

    TIM = (.5)*($10.41 per hour)                                   TIM = (.35)*($10.41 per hour)

        30 miles per hour                                                       40 miles per hour

= $0.1735 per vehicle mile                                         = $0.0911 per vehicle mile

 

(Litman adds 16.5%  to the urban-peak automobile

to account for a congestion premium. Therefore, the

urban-peak automobile is $0.202 per vehicle mile) 

 

Urban-peak automobile                                             Rural automobile

    TIM = (.5)*($10.41 per hour)                                   TIM = (.35)*($10.41 per hour)

        30 miles per hour                                                       40 miles per hour

= $0.1735 per vehicle mile                                         = $0.0911 per vehicle mile

 

(Litman adds 16.5%  to the urban-peak automobile

to account for a congestion premium. Therefore, the

urban-peak automobile is $0.202 per vehicle mile) 

  

To calculate the social cost to the community, the appropriate cost variables (as listed in Figure 3-7) for each mode (transit and automobile) were summed to obtain a total social cost per vehicle mile (SCT for transit and SCA for automobiles).  After the totals were established, the estimated annual cost was calculated for each mode of transportation in a transit area.   The estimated annual cost for transit was calculated using the following equation:

SOT   =  MT*SCT + OM                                                                                           (3-5)

where:

 

SOT     = estimated annual social cost to the community with the transit system

MT      = average number of vehicle miles per year for transit system

SCT     = total social cost per vehicle mile for transit system (dollars per vehicle mile)

OM     = annual operating and maintenance cost for transit system

 

If the transit system did not exist, it was assumed that there would be an increase in automobile usage.  Therefore, the social cost for automobile usage to the community was calculated using the following equation:

SOA = MA*SCA*I                                                                                                    (3-6)

 

where:

 

SOA     = estimated annual social cost for the community without the transit system

MA     = estimated annual miles per automobile

SCA    = total social cost per vehicle mile for automobile

I           = increase in the number of automobiles if transit is not supplied.

 


 

It has been estimated that the average number of miles traveled per year by private automobile is 15,000 miles per year [58].  The parameter I was calculated for each transit service area using equations discussed in a previous section.  The results for each transit system are shown in Appendix A.

3.7  Retail Sales Impact

This section discusses the procedure used to estimate the effects of the existing transit system on the sales of local retail businesses.  In a study conducted by the American Public Transit Association (APTA), it was estimated that for every $1 invested in transportation, there would be an economic increase for industries located in the transit service area [4].   For example, the economic increase  (or multiplier) for textile manufacturing industries is 0.0361.  Therefore for one dollar spent by transit, the textile industries would experience a $0.0361 increase in revenues.   APTA estimated multipliers for thirty-eight industries by using an Input/Output model called the Regional Industrial Modeling System (RIMS II) [3,4].

To represent the effects of public transit on retail sales, APTA=s multipliers for retail trade and eating and drinking establishments, were added together to obtain the total retail multiplier.   The retail trade multiplier (estimated as 0.1534) represents any establishment which sells merchandise for personal or household consumption and renders services leading to the sale of goods [57].   The eating and drinking multiplier (estimated as 0.0757) represents retail establishments which sell prepared foods and beverages for personal consumption on the premises or for immediate consumption [57].   Thus, the combination of these two multipliers were used to represent the total retail multiplier for this study.

After obtaining the total retail multiplier, the retail sales impact was estimated using the following equation. 


 

RTI-=  Qr * OM                                                                                                         (3-7)

 

where:

 

RTI  = estimated annual increase in retail sales due to the supply of public transportation

Qr     =  total retail multiplier  per retail trade establishments (0.2291)

OM  = annual operation and maintenance cost for transit system

 

The retail sales results for each transit system is obtained in Appendix A.

3.8  Medical Impacts

It is believed that public transportation positively affects the physical health of the community by transporting patrons to medical facilities.  The analyst assumed that thirty  percent of the patrons traveling to medical facilities would not be able to receive regular medical attention, if the transit system did not exist.  Thus, to estimate the medical impacts of the transit system, the following equation was used.

MED = B*N*P                                                                                                          (3-8)

where:

 

MED  =  estimated medical impact per transit system

B         =  average cost of hospitalization

N         =  number of people traveling to medical facilities

P          = percentage of people who would be unable to receive regular medical attention if  the

   transit system did not exist (0.30)

 

The MED represents the increase in medical costs that would occur, if the public transit system did not exist.  The average hospitalization cost (B) was $8,181 per hospital trip and was obtained from a report produced by the Arkansas Department of Health [6].   N was obtained from the surveys received from each of the transit systems, assuming that the number of medical trips per week represents the number of people of people traveling to medical facilities.  The calculated results of the medical impacts for each transit system are presented in Appendix A.


 

3.9  Impacts on Elderly

 A large percentage of elderly people maintain their independence by using public transportation to travel to medical facilities, shopping areas, social services,  and etc.   According to Jahnigen and Binstock, the population of elderly Americans increases each year.  Jahnigen and Binstock reported that by the year 2000,  the elderly persons at ages 85 and older will represent thirteen percent of the total population and that persons between ages 65 and 84 will represent forty-eight percent [32].  Thus, with the steady growth of elderly populations, the demand for transportation services for the elderly will increase. 

If public transportation systems did not exist, portions of elderly transit riders may be forced to live in nursing homes because they have no other means of getting from one place to another.  In an article written by Joseph Stroud, several public transit directors responded to issues concerning federal funding cuts [61].  The article suggests that both elderly and low-income populations would suffer greatly if transit services were to diminish [61].  Taunya Kopke (former transit director of the Ozark Regional Transit) suggested that a loss in pubic transit services would be Akilling people=s freedom@.  Kopke believes that decreases in transit services would cause people, who are elderly or who need medical treatment,  to lose their freedom because the lack of transportation would force them to enter nursing homes in order to receive necessary care [61]. 


 

To determine the impact of public transit on the elderly population for this study, the number of elderly people who may be forced to enter the nursing home , if transit did not exist,  was estimated.  In a survey taken of 1,083 poor elderly people in Florida, it was discovered that 6.1 percent of these people could not receive regular medical attention because of the lack of transportation [55].  Therefore, it is assumed that the people who lacked transportation to medical services, were also unable to reach other services and places (such as social services, shopping, nutritional services, etc.).  Thus, the 6.1 percent was used as an adequate indicator of the percentage of elderly who would not be able to travel due to the lack of transportation. In another study conducted by Jahnigen and Binstock, it was reported that twenty-nine percent of persons aged 65 and older are living in nursing homes [32].  This percentage (29%) was used to determine the number of elderly persons who would enter the nursing home if the transit system did not exist.  The number of elderly persons who would have to enter a nursing home due to the lack of public transit was estimated using the equation below:

NUE = LT * ER * NH                                                                                                           (3-9)

 

where:

 

NUE    = number of elderly riders who would enter the nursing home if the transit

   system did not exist.

LT       = percentage of persons who would not be able to travel due to the lack of transportation 

   (0.061)

ER       = number of elderly riders per transit system

NH      = percentage of elderly persons who would enter the nursing home if transit did not exist

   (0.29)

 

The variable ER was obtained from the surveys received from each transit system, assuming that the number of elderly trips per week represents the number of elderly patrons.

To estimate the impact on elderly population in terms of annual dollars, the following equation was used:

ELD    =  NUE * (HCT - AVI)                                                                                   (3-10)

where:

ELD    = estimated impact on elderly per transit system

NUE    = number of elderly riders who would enter the nursing home if the transit

   system did not exist

HCT    = estimated annual cost to live in the nursing home

AVI     = average household income per transit area


 

The difference in the variables HCT and AVI estimates the additional amount of income that would be needed if a patron has to enter a nursing home.  The average annual income per transit area was obtained from the U. S. Census for Arkansas [67].  The Department of Human Services of Little Rock estimated the average cost of living in a nursing home at $4,000 per month [19].  Therefore, the estimated annual cost of living in the nursing home was $48,000 per year.  The results for each transit system is presented in Appendix A.

3.10  Employment

Public transportation directly effects employment within a community by transporting patrons to jobs daily.   Public transportation improves employment by connecting non-drivers/ non-car owners to jobs and supplying employers with a steady flow of employees.  Thus, patrons using transit for commuting to work receive a regular income and employers save money from less turnover which in turn results in less training cost and less administration cost (due to decreases in hiring, tardiness, and production downtime).

To estimate employment impacts,  multipliers outlined in a study conducted by the American Public Transit Association (APTA) were used.   APTA obtained multipliers for 38 industries by using an Input/Output model called the Regional Industrial Modeling System (RIMS II).   The RIMS II multipliers indicate that for every $ 1 spent on transit expenditures there is a certain dollar increase in the revenues of 38 industries [3,4].  The list of the industries and their multipliers are shown in Figure 3- 9.

 

 

 

 


 

Figure 3-9:  APTA=s Multipliers per Industry Due to Transit Expenditures [4]

 

Industry

 

multiplier

 

 

 

Industry

 

multiplier

 

Agriculture

 

0.0923

 

 

 

Electrical machinery

 

0.0668

 

Forestry and Fisheries

 

0.0027

 

 

 

Motor vehicles

 

0.0531

 

Coal mining

 

0.0055

 

 

 

Other transportation equipment

 

0.0071

 

Petroleum and natural gas mining

 

0.0255

 

 

 

Instrument

 

0.0085

 

Other mining

 

0.0088

 

 

 

Miscellaneous manufacturing

 

0.0137

 

New construction

 

0.0

 

 

 

Transportation

 

0.1012

 

Maintenance and repair

 

1.0353

 

 

 

Communication

 

0.0475

 

Food and kindred products

 

0.1630

 

 

 

Utilities

 

0.0671

 

Textiles

 

0.0361

 

 

 

Wholesale trade

 

0.1194

 

Apparel

 

0.0341

 

 

 

Finance

 

0.0554

 

Paper products

 

0.0308

 

 

 

Insurance

 

0.0548

 

Printing and publishing

 

0.0354

 

 

 

Real estate

 

0.1302

 

Chemicals

 

0.1282

 

 

 

Lodging and amusement

 

0.0277

 

Rubber and leather

 

0.0397

 

 

 

Personal services

 

0.0279

 

Lumber and Furniture

 

0.0358

 

 

 

Business Services

 

0.0846

 

Stone, clay and glass

 

0.0146

 

 

 

Health services

 

0.0639

 

Primary metals

 

0.0570

 

 

 

Other services

 

0.0882

 

Fabricated metals

 

0.0518

 

 

 

Households

 

1.2195

 

Non-electrical Machinery

 

0.0319

 

 

 

 

 

 

 

The retail trade and the eating and drinking multipliers were not included, since they were used to calculate the retail impact of the transit systems. 

In addition to the industrial multipliers,  APTA also generated a multiplier for the overall household income.  This multiplier represents the impact on household earning (wages and benefits) for the household sector of the transit area [3,4].   In other words, the overall income includes the wage and benefit incomes for all households of the transit service area.  Therefore, for one dollar spent on transit expenditures, there would be a $1.22 increase in the overall household income of the transit area.  The increase in the overall household income due to the supply of public transit was estimated using the following equation:

 

 


 

HOS  =  MUH * OM                                                                                                 (3-11)

 

where:

 

HOS    = estimated annual increase in the overall household income of the transit service area

MUH = multiplier for the overall household income per transit service area

OM     = average annual operating and maintenance cost for transit

 

This estimated annual increase in household income represents the personal employment impacts due to the supply of public transit.

To estimate the effect of public transit on employers of the community, it was assumed that increased transit spending would result in more patrons being attracted to the transit system.  Thus, the expenditures per transit system was used to estimate the increase in employment (employment impact) for industries serviced by the public transit system.  

In order to estimate the community employment impacts, the types of industries located in the transit service area were determined so that the industrial multipliers for the system could be ascertained.  The industries existing in each transit area was found in the U. S. States County Business Patterns and U. S. Census of  Retail Trade publications [62,66]. The equation to estimate the employment impact for the community is shown below:

EMPI-= ( ΣQj) * OM                                                                                                            (3-12)

 

where:

 

EMPI              = estimated annual employment impact for the community due to transit spending

Qj        = industry j multiplier

OM     = annual operating and maintenance cost for transit system

 

The employment impact results for each system are presented in Appendix A.  The next chapter presents a numerical example of the methodology described. 


 

4.0  NUMERICAL  EXAMPLE

 

This section will demonstrate the mechanics of the methodology section by estimating impact obtained for one of the analyzed transit systems.  The public transit system used for this numerical example was the North Arkansas Transit System (NATS).  This system operates in the Northern section of Arkansas and serves six counties; Baxter, Boone, Carroll, Fulton, Izard, Marion, Newton, and Searcy.

Parameters & Variable Adjustment

 

Car increase estimations (I)

 

NATS reported that they had twenty-eight vehicles within their fleet, which consisted of  the following types of vehicles:  21 passenger buses, 17 passenger buses, 14 passenger buses, 15 passenger vans, 12 passenger buses and mini vans.  The following equation was used to calculate the estimated increase in automobiles, if the transit system did not exist:

I   =   ΣPAS

  N

 

where:

 

I           =  estimated increase in automobile if the transit system did not exist

PAS     =  passenger capacity per transit vehicle

N         =  average number of persons per automobile

 

Assuming that there are an equal number of each vehicle type, the sum of the passenger capacity for NATS was calculated below.

Given 28 vehicles within the fleet, it was assumed that NATS had the following transit vehicles:

 

five - 21 passenger buses

five - 17 passenger buses

five - 15 passenger buses

            five - 14 passenger vans

            four - 12 passenger buses


 

            four - 6  passenger mini vans

 

The passenger capacity for NATS was:

ΣPAS = (5*21) + (5*17) + (5*15) + (5*14) + (4*12) +(4*6) = 407 passenger capacity

Therefore the estimated increase of automobiles, if NATS did not exist, was:

 

         I =  ΣPAS_

        N

=    407

      1.2

= 339.166 or 339 automobiles would be introduced into the service area if NATS did not            

  exists.

 

Social Impacts:

Individual social impacts

The following equation was used to calculate the individual social cost for using the

automobile and the taxi.

Ux = [(G*Rx)+ FEE]* D                                                                                

where:

Ux        =  estimated annual social costs per mode x (automobile or taxi) for the individual

G         =  average of number of miles traveled per day

Rx        = operation cost per vehicle mile for a transportation mode x ( automobile or taxi)

FEE     = additional daily fees incurred by the selected mode (parking or base fees)

D         = average number of workdays per year (250 days)

 

The total estimated annual social cost per year for automobile and private taxi usage are as follows:

 

Ux = [(G*Rx)+FEE]* D                     

Ua =  [(25)($0.43) + $3.00] *250 = $3437.50 per year

Ut =  [(25)($1.14) + $4.26] *250  = $8190.00 per year

 

The estimated annual social cost for an individual using NATS is

YP= K*D

where:


 

YP       = estimated annual social cost of public transit for individuals

K         = average fare cost per day ($/ day)

D         = average number of workdays in a year (250 days)

 

Therefore the annual individual social cost for NATS was:

 

YP= K*D

     = ($2.90/day )(250 days)

     = $725.00 per year

 

Thus, taking the difference between automobile social cost and NATS social cost, the social cost savings to the individual was:

          3437.50 - 725  = $2712.50 per year in social cost savings when NATS is utilized instead of

    the automobile.

 

Taking the difference between taxi social costs and NATS social cost, the social cost savings for the individual was:

8190.00 - 725 = $7465 per year in social cost savings when NATS is utilized instead

   verses the taxi.

 

By using NATS, an individual could save between $2,712.50 to $6,932.50 per year in travel cost.

 

Community Social impacts

The travel time variable for each transit system was calculated.  The calculation for the travel time variable cost per vehicle mile is shown below:

TIM = L * WAGE    

       S

where:

 

TIM     = cost of travel time per vehicle mile for transit

L          = percentage of wage which represents the value of time per hour (0.35 or 0.5)

WAGE = average wage per hour ($10.41/hour)

S          = average speed of the transit vehicle (miles per hour)

 

The TIM for NATS was:

 

 

 


 

TIM =  L * WAGES

        S

         = (0.35 * 10.41)

   (50 mph)

         = $0.0728 per transit vehicle mile

 

This travel time cost variable for NATS was added to the other social cost variables, listed in Figure 3-7, to obtain the total social cost per vehicle mile for the transit system.  Thus, the total social cost per transit vehicle mile (SCT)  for NATS is $0.5699  The equation for estimating the annual social cost for the transit system is shown below:

SOT   =  MT*SCT + OM

where:

SOT     = estimated annual social cost to the community with the transit system

MT      = average number of vehicle miles per year for transit system

SCT     = total social cost per vehicle mile for transit system (dollars per vehicle mile)

OM     = annual operation and maintenance cost for transit system (maintenance + wage + other)

 

Therefore the social cost to the community with the presence of NATS was:

 

SOT   =  MT*SCT + OM

                      = (300,000)(0.5699) + (140,833 + 155,071 + 48,665)

          = $515,539 per year in social costs to the community

 

To estimate the social cost for automobile usage, the cost variables for automobiles (taken from Litman=s study) were added to obtain the total social cost per automobile vehicle mile.  Total social cost per mile per automobile usage (SCA) was $0.361.  The social cost to the community if the transit system did not exist was calculated as follows:

SOA = MA*SCA*I

where:

SOA     = estimated annual social cost to the community with out the transit system.

MA     = estimated annual miles per automobile

SCA    = total social cost per vehicle mile for automobile

I           = increase in the number of automobiles, if transit is not supplied.

 


 

The social cost to the community if NATS did not exist resulted in the following:

 

   SOA  = MA*SCA*I

  =  (15,000)(0.361)(339)

  =$1,835,685 per year in social costs to the community if NATS did not exist. 

 

These estimates show that the community social cost is less with the presence of NATS.  The community saves a total of  $1,320,155 ($1,835,685-515,530) per year in social cost due to the supply of NATS services.

Retail Sales Impact:

The impact for retail sales was estimated using the following equation

RTI-=  Qr* OM

 

where:

 

RTI  = estimated annual increase in retail sales due to the supply of public transportation

Qr     =  total retail multiplier  per retail trade establishments (0.2291)

OM  = annual operating and maintenance cost for transit system (maintenance + wage + other)

 

The impact on retail sales for NATS was as follows:

 

RTI =  Qr* OM

       = (0.2291) * (140,833 + 155,071 + 48,665)

       = $78,940.76 per year

 

NATS is estimated to be responsible for $78,940 in sales revenue per year for retail establishments in the NATS service area.  Hence, the continued spending and improvement of the transit system will continue to increase the sales of the retail trade establishments. 

Medical Impacts

 

Medical impacts were estimated using the following equation

 

 

 

 

 


 

MED = B*N*P

 

where:

 

MED  =  estimated medical impact per transit system

B         =  average cost of hospitalization

N         =  number of people traveling to medical facilities

P          = percentage of people who would be unable to receive regular medical attention if  the

   transit system did not exist (0.30)

 

The MED represents the increase in medical costs that would occur, if the public transit system did not exist.  Therefore, the medical impact if NATS did not exist was estimated as:

MED = B*N*P

          = ($8,181*50*0.3)

          =$122,715 increase in medical cost

 

There would be and increase of $122,715 in medical expenditure for the NATS transit area if the transit system did not exist.

Elderly Impacts

The impacts on the elderly population was calculated by estimating the number of elderly persons who would have to enter nursing homes if the transit system did not exist.  The following equation was used:

NUE = LT * ER * NH

 

where:

 

NUE    = number of elderly riders who would enter the nursing home, if the transit

   system did not exist.

LT       = percentage of elderly persons who would not be able to travel due to the lack of 

    transportation          

   (0.061)

ER       = number of elderly riders per transit system

NH      = percentage of elderly persons who would enter the nursing home if transit did not exist

   (0.29)

 

The number of elderly persons who would have to enter the nursing home if NATS did not exist

 


 

was:

NUE = LT * ER * NH

         = .061 * 65* .29

         = 1.131 or 2 elderly patrons would have to enter nursing homes if NATS did not

exist

 

To view the impacts on elderly in terms of annual dollars, the following equation was used:

 

ELD    =  NUE * (HCT - AVI)

 

where:

 

ELD    = estimated impact on elderly per transit system

NUE    = number of elderly riders who would enter the nursing home, if the transit

   system did not exist

HCT    = estimated annual cost to live in the nursing home

AVI     = average household income per transit area

 

Therefore, the impact on elderly in terms of dollars for NATS was:

 

ELD    =  NUE * (HCT - AVI)

= 2 * (48,000 - 22,469)

= $51,062 per year

 

Therefore, without the provision of the public transit, the elderly patrons (who would enter the nursing home) would need an increase of $51,062 per year in household income.     

Employment Impacts.

 

The employment impact on the overall household income of the NATS service area was

calculated as follows:

 

HOS  =  MUH * OM

 

where:

 

HOS    = estimated annual increase in the overall household income for the transit service area

MUH = multiplier for household income

OM     = average annual operating and maintenance cost for transit (maintenance + wages + other)

 

Thus, the amount of overall household income due to the annual spending on NATS was:

 

HOS  =  MUH * OM

          = (1.2195)* (140,833 + 155,071 + 48,665)


 

          = $265,630 per year of the overall household income is due to

  the existence of NATS

 

Therefore NATS contributes $265,630 per year to the household income of the its service area.

The NATS service area consists of the following industries (the multiplier for each industry is shown in parenthesis):

 

agriculture  (0.0923)                           electrical machinery(0.0668)                   lodg. & amusmt. (0.0277)

forestry and fisheries (0.0027)                      instruments (0.0085)                    personal services (0.0279)

construction (0)                                  misc. manufacturing (0.0137)                  business services (0.0846)

apparel (0.0361)                                 transportation (0.1012)                health services (0.0639)

paper products (0.0308)                     communication (0.0475)               other services (0.0882)

lumber and furniture (0.0358)                        utilities (0.0671)

printing and publishing (0.0354)        wholesale trade (0.1194)

rubber and leather (0.0397)               finance (0.0554)

primary metals (0.057)                       insurance (0.0548)

fabricated metal (0.0518)                   real estate (0.1302)

The total multiplier is 1.3385.   NATS reported an average annual maintenance cost $140,833 per year.  The employment impact of the NATS to the community was calculated as:

EMPI = (ΣQj) * OM

 

where:

 

EMPI = estimated annual employment impact for the community

Qj         = industry j multiplier

OM     = annual operating and maintenance cost for transit system (maintenance + wage + other)

 

EMPI-= (ΣQj) * OM

           = (1.3385)($344,569)

           = $461,205.60  increase in business sales per year due to the supply of transit

 

Therefore, a revenue increase of $461,205 for local industries is estimated due to NATS.

Conclusion for NATS


 

The social impact category showed that an individual using NATS saved between $2,713 to $7,465 per year in travel costs.  The social cost to the community with the existing transit system, was $1,320,155 less than the social cost to the community, if the transit system did not exist.  The amount of retail sales due to the annual NATS expenditures was $78,941 per year.  The medical savings due to the existence of NATS was estimated to be $122,715. 

For NATS, it was estimated that 2 elderly patrons would enter the nursing home if the transit system did not exist.  Elderly patrons living in nursing homes would experience an increase of  $51,062 per year in living expenses.  Therefore, NATS enables elderly patrons and their families to maintain their mobility and save money in living costs.

The employment impact of the household sector of NATS service area was estimated to be $420,202 per year.  This means that $420,202 of the overall household income of NATS service area was due to the annual amount spent on public transit expenditures.   There was a positive employment impact to the community for NATS.  Therefore, it was concluded that NATS positively affects the economic structure of the individuals and community it serves.


 

5.0  CONCLUSIONS AND RECOMMENDATIONS

Rural public transportation is vital to the economic and social well-being of the rural community and its citizens.  Rural areas generally have a high percentage of elderly and low income populations who may find it more difficult to obtain personal transportation.   Rural public transportation helps to enhance the quality of life for those who may use them.

Although the qualitative aspects of providing public transit services in rural areas has been recognized the quantitative data which represents the economic impact of such services has not been fully explored  The main objectives of this project were to document the linkages between public transportation and economic activities in the rural areas of Arkansas, estimate the impacts of rural public transportation in the state of Arkansas and in local communities, and develop new or augment current methodologies for estimating the economic impacts of Arkansas rural public transportation.  This data will provide rural transit providers with an opportunity to link the economic strength of a region(s) and the rural public transportation system which serves it.

From the extensive review of the literature, it was determined that both the individual and the community receive benefits from public transportation.  Individuals who use public transit experience increased mobility, flexibility in travel arrangements, improved accessibility to other areas, savings in travel costs, and improved lifestyles.  The benefits to the community include improved employment, larger employment market for businesses, and improved environment.


 

For the thirteen transit systems analyzed in this study, there were five impacts estimated:  social, retail sales, medical, elderly, and employment.  The calculated results of the social impacts showed that money is saved when the public transit system is used by the individual and the community.   The retail impacts calculated for each transit system had a positive impact on retail trade revenues.  Therefore the amount of money spent on transit expenditures contributes to the amount of revenue experienced by retail trade businesses of the transit service area.

For the medical impacts, it was determined that current transit patrons traveling to medical facilities would have to spend more money in medical cost (if the transit system did not exist).   The existence of transit also saves money for elderly patrons.  Since the elderly patrons have a dependable source of transportation, they do not have to obtain additional income to live in nursing homes. 

There was a positive employment impact on the overall household income and the industries located within the transit services area.  Thus, spending on annual transit expenditures contributes to the overall household income and the revenues of  local industries.    In reference to the calculated results of all impact categories, it is concluded that the thirteen Arkansas rural public transit systems positively affect the economic structure of the individuals and communities they serve.

Despite the economic significance of rural transit, public transit systems are suffering because of cutbacks in federal funding.  These cutbacks will cause transit providers to reduce or discontinue their services.  Thus, preventing some rural transit riders from maintaining their mobility and independence to travel to shopping areas, medical facilities, and jobs. 

The impact methodology developed in this research could be used to show the benefits derived by having a public transit system.  In an effort to obtain funds public transit operators may find it beneficial to show quantitatively how the transit system affects an area.  An extension of this research could be the development of a software tool that does the necessary calculations and provides the user with appropriate view graphs for such presentations. 


 

For the past couple of years, the government has tried to reduce spending and reshape the welfare structure in America.  One of the main objectives of the welfare reform is to help able bodied citizens to obtain work and establish a positive source of income for themselves.  This means that more people, who do not have private transportation, will have to depend on public transit for transportation to work or training and for transportation to child care facilities.   With the cutbacks in transportation funding, these welfare recipients may have a difficult time finding an adequate supply of public transportation to job sites.   In an article written by J. Stroud of Mass Transit Magazine, Maggie Franklin stated,

AThey=re wanting to cut welfare spending, and public transportation is a must for welfare recipients,@ she continues, AThey don=t have a car, and public transportation is what gets them back and forth to work.  So if they don=t have public transportation they can=t go to work @ [61].

The relationship between welfare reform and public transportation needs to be established.  An extension of this research could be an analysis to estimate and quantify the economic impact of welfare reform on public transportation. 


 

REFERENCES

1.            Administration on Aging, AOlder Persons with Mobility and Self-Care Limitations: 1990@, National Aging Information Center, January 8, 1996.

2.                         American Chamber of Commerce Research Association, ACost of Living Index@, 1997.

3.        American Public Transit Association,  Employment Impacts of Transit Capital Investment and Operating Expenditures,  Washington:  Government Printing Office, April 1, 1983.

4.        American Public Transit Association, ANational Impacts of Transit Capital and Operating Expenditures on Business Revenues@, Washington: Government Printing Office, 1983.

5.        American Public Transit Association, Transit Facts Book, Management Services Department, Washington: Government Printing Office, January 1996.

6.                          Arkansas Department of Health, AHealth Statistics@, Yahoo, Online, 1997.

7.        Arkansas Economic Development Commission, AArkansas as a Business Location@, Yahoo, Online, 1997.

8.