Simulating the Effects of Railroad Mergers.

• Author: Park, Joon Je

Joon Je Park [*]

Michael W. Babcock [+]

Kenneth Lemke [++]

Dennis L. Weisman [ss]

The purpose of this paper is to add to the empirical literature regarding merger simulation analysis by examining the effect of railroad mergers on railroad market power. This is done by measuring railroad profits and revenue/variable cost ratios corresponding to different degrees of intrarailroad competition for movements of Kansas export wheat to Houston, Texas.

Two models are developed to achieve the objectives of the study. A network model of the wheat logistics system is used to identify the least cost transportation routes from the Kansas study area to the market at Houston. A profit improvement algorithm, which identifies Nash equilibrium prices, is developed to measure the amount by which railroads can profitably raise their prices above variable cost.

The results of the study have implications for U.S. railroad merger policy. The paper indicates that railroad mergers do not necessarily increase railroad market power or make railroad shippers worse off. Instead, the study demonstrates that the impact of railroad mergers on shippers and railroads depends on factors that vary geographically, such as the degree of intrarailroad and intermodal competition in the area.

1. Introduction

   The operating performance problems of class I railroads after the mergers of recent years have raised the issue of the impacts of railroad mergers on railroad shippers. Although most of the public's attention has been focused on service problems such as equipment supply and on-time reliability, the effect of recent class I railroad mergers on railroad market power and prices is a matter of policy concern.

   Conventional economic theory argues that an increase in intrarailroad competition will result in a decrease in railroad price. There is substantial empirical support for this hypothesis. For example, Levin (1981b) found that hypothetical railroad price increases resulting from railroad deregulation are quite modest in the presence of a moderate degree of intrarailroad competition. [1] Levin (1981a) discovered that for various assumptions regarding railroad demand elasticity and railroad revenue/variable cost ratios, the social benefit (net reduction in deadweight loss) of adding an equal-size railroad competitor to a monopoly railroad market ranges from 6.8% to 18.9% of revenues in that market. Adding a third railroad in a two-firm railroad market yields social benefits of 2.4%-6.8% of revenues in that market. MacDonald (1987) found that increased intrarailroad competition results in lower railroad grain prices. He found that a movement from a railroad monopoly to a duopoly with equal-size firms leads to an 1 8% decrease in railroad corn prices. A movement from duopoly to triopoly causes railroad corn prices to fall another 11%. Similar results are reported in MacDonald (1989). The Lemke and Babcock (1987) study of the impact of railroad mergers on western Kansas export wheat rail prices concluded that mergers do not significantly increase market power as long as some intrarailroad competition is maintained. However, mergers that produce regional monopolies result in substantial increases in railroad market power.

   The Staggers Rail Act of 1980 contained restrictions on railroad rate bureaus and permitted confidential railroad/shipper contracts. These provisions of the act fostered intrarailroad competition and several studies documented the decline in railroad grain prices resulting from increased railroad rivalry. [2]

   The purpose of this study is to add to the empirical literature concerning market power and competition between railroads. This is achieved through a case study of the transportation market for the export of Kansas wheat. However, the models, techniques, and general conclusions of the study can be applied to similarly situated regional transportation markets for homogeneous goods such as coal, ores, field crops, and lumber.

2. The Study Area

   The grain origin area of this study includes all of 57 counties and parts of 15 other counties in central and western Kansas that comprise about two-thirds of the Kansas land area. This area is divided into 342 production origins (12 X 12 square mile areas). In 1996, the area produced about 217 million bushels of wheat, which was 85% of the state's production. [3] The area also produced about 77% of total Kansas sorghum production and 81% of the state's corn production. [4]

   The area is served by four class I railroads including Burlington Northern (BN) (126 miles), Union Pacific (UP) (852 miles), Santa Fe (SF) (658 miles), and Southern Pacific (SP) (259 miles). In addition, there are five short lines serving the area, including Kyle Railroad (632 miles), Kansas Southwestern (KSW) (302 miles), Central Kansas Railroad (CKR) (882 miles), Cimmaron Valley (CV) (182 miles), and the Garden City Western (45 miles). Thus, the total miles of rail line in the study area is 3938. These railroads serve study area elevators with a total storage capacity of 670 million bushels.

   The study focuses on wheat because rail transportation is the dominant transportation mode for Kansas export wheat. This is not the case for corn or sorghum, the other major crops in the study area. For the 1992-1993 crop, small country elevators moved 52% of their wheat shipments by rail. The corresponding percentages for large country elevators and terminal elevators were 69% and 99%, respectively. [5]

   Most of the wheat grown on Kansas farms travels through a system of country elevators and inland terminal elevators to domestic flour mills or export terminals at coastal ports. Port terminals on the Gulf of Mexico have been the major destination for Kansas export wheat. During the 1992-1993 crop year, 62% of all Kansas wheat shipments were to the Gulf of Mexico ports.

   The wheat logistics system in Kansas is displayed in Figure 1. Trucks are used to ship wheat from farms to country elevators, inland terminal elevators, or subterminal elevators. Country elevators ship wheat to subterminals, inland terminals, domestic flour mills, or export ports (e.g., Houston) by truck or rail. Inland terminal elevators and subterminal elevators ship wheat by rail and by truck to other inland terminals or by rail to final markets. Inland terminal elevators have functioned as intermediate collection, storage, and routing points. Subterminals are designed for rapid loading of unit trains of wheat.

   In the study area, inland terminal elevators are located at Salina, Wichita, and Hutchinson, Kansas. Subterminals are located at Colby, Dodge City, Wakeeney, Liberal, and Ogallah, Kansas, and Enid, Oklahoma.

   Houston was selected as the only market in order to make the study more tractable. This assumption is not overly restrictive because in the 1992-1993 crop year, more than 60% of Kansas wheat shipments moved to Houston for export. [6]

3. Models and Procedures

   Two models are required to achieve the objectives of the study. A network model is required to identify the least cost transportation routes from the study area to Houston. The network model is a variation of the linear programming methodology. A model is also required to compute prices. We assume that oligopoly interaction is described by price-setting behavior in a homogeneous goods industry. Service differences (e.g., delivery times) between transportation modes are not important to shippers of products with a low value-to-weight ratio (e.g., wheat) who select transport modes on the basis of cost (Harper 1982, p. 16). Hence, we treat transportation in this model as a homogeneous service.

   A profit improvement algorithm is needed to measure the amount by which railroads can mark up their prices above variable cost in the face of changing market conditions. This approach is very much in the spirit of the merger simulation literature (Werden and Froeb 1994, 1996), albeit with homogeneous products, because the primary objective of the study is to simulate changes in market power postmerger. As Werden and Froeb point out, this approach can represent a marked improvement over the traditional structural methods for evaluating mergers.

   The Network Model

   With regard to the first of these models, the network includes 342 production origins (12 miles X 12 miles in area), 280 country elevators, 6 subterminals, 3 inland terminals, and one destination (Houston).

   In the network model, the initial movement of wheat is from a production origin to a country elevator, terminal elevator or a subterminal. A production origin may ship wheat to any country elevator that is within a 50-mile radius; it may ship to a subterminal if it is within a 70-mile radius. A production origin can ship to any terminal. Because one of the objectives of this study is to examine the ability of railroads to increase their market power and profits as intrarailroad competition is reduced, production origins must be allowed to deliver Kansas wheat farther than historical average mileages in order to identify transportation costs of alternative routes. [7]

   In the network model, wheat moves through the logistics system to the final demand point. After the wheat is assembled at country elevators or subterminals, the following types of shipment patterns may occur (Figure 1):

   (i) Multicar (15-car) rail shipments from country elevators to Houston.

   (ii) Multicar (15-car) rail shipments from country elevators to inland terminals or subterminals. This is followed by a 100-car-unit train movement from inland terminals or subterminals to Houston.

   (iii) Commercial truck movement from country elevators to inland terminals or subterminals. The subsequent movement is a unit train shipment of 100 cars from inland terminals or subterminals to Houston.

   (iv) Commercial truck movement from country elevators served by a given railroad to another country elevator served by a competing railroad(s). This is followed by multicar (15-car) shipments to...