Transportation Input and Agglomeration Economies

Isard (1956) simulated a condition where a firm is faced with more than one point of raw materials or input source and market points. This simulation shows the problem where a firm has to substitute a closer distance to one input source at the expense of longer distance to the other input source. If the firm decides to locate near the market, the firm also has to substitute closer distance to market at the expense of longer distance to raw material sources. The main objective of this simulation is to find the location that

3 There is trade-off between the investment in labor or land inputs for transport and the labor or land inputs for product cultivation.

minimizes the overall transport costs. Transportation cost is a function of distance and mass of the inputs or finished products.

It is important to note the elasticity of transport cost to distance, whereby the increase in transport cost from zero distance to a distance slightly more than zero (i.e.

from 0km to 0.1km) is significantly higher compared to the increase in transportation cost from distance more than zero to a slightly longer distance (i.e. from 1km to 1.1km).

Because of the elasticity of transportation cost to distance, Isard argued that the most efficient location is located in the corner of the polygon rather than the middle because it is always more efficient to have one of the inputs or outputs free of transport costs.

Isard (1956) also found that transport costs are the most important determinant of spatial structure. This finding was based on the analysis of relationship between three locational factors and the distance of settlements. The three locational factors are transportation and transfer costs, labor, utilities and financial service costs and factors that give rise to agglomeration and deglomeration. He found that only transport and transfer costs have regular variation with the distance of settlements, while the other two locational factors do not have any regular variation. This shows that transport costs are the main determinant in the formation of an economy’s spatial structure.

Nevertheless, this does not necessarily imply that agglomeration economies have no influence on the spatial structure of an economy. Isard explains how despite the lack of regular variation between spatial structure and the agglomeration economies, the factors of agglomeration can influence spatial structure. Hoover (1937) classified agglomeration factors into three categories, which are large-scale economies, localization economies and urbanization economies. Isard explains the relationship between the

factors of agglomeration and the creation of spatial structure. According to Isard, the relationship between large-scale economies as an aglomeration factor and the spatial structure of an economy, can be explained with reference to Losch’s (1938) hexagonal market area theory. Isard refers to the case of two different commodities with different marginal costs. The marginal cost of one of the commodities may increase sufficiently to allow for the division of market while the other commodity may have economies of scale extended over much larger range of products. In this case, for the commodity with economies of scale extended over much larger range of products, if the market area is enlarged, the gain in revenue outweighs the loss from incurring higher transportation costs. In contrast, the commodity with significant increase in marginal cost cannot have a larger market area since transport costs are higher. Therefore, a hierarchy of small and larger markets are created through a system of economies of scale, which conforms to Losch’s theory of market area hierarchy.

Isard refers to Weber’s (1909) theory on the reasons behind clustering of several firms or units, in explaining the relationship between localization economies and spatial structure. Weber sees the intersection of critical isodapanes’ between two or more firms as the condition for clustering. However, it is important that when clustered together, the unit can produce the requisite quantity in serving the combined market area efficiently.

An isodapane consists of points of equal transport costs from the point of distribution.

The critical isodapane is reached when savings in labor cost are just off-set by the increased transport costs (Pinto, 1977). When agglomeration takes place through clustering, the benefit of agglomeration economies that the firm gets is equivalent to the extra profit gained from serving the market beyond the critical isodapane.

According to Weber (1909), when two or more production activities have intersecting critical isodapanes, there lies a point where one larger unit of production can cover more than one of the production activities’ market areas. The point should have the lowest transport costs in relation to the total agglomerated output. However, Isard sees a possible weakness to Weber’s approach. Weber fails to explain the possible reluctance of firms to move to a new location, especially when the plants are already constructed. The significant opportunity costs in moving to a new location may create a strong bargaining power for existing plants so that new firms cluster around these existing plants. In addition, Isard argues that each production activity is reluctant to locate far away from its own optimum transport point. Thus, firms with greater bargaining power would be able to maintain their optimum transport point while those with less bargaining power would be forced to relocate near firms with greater bargaining power. However, Isard admits that Weber’s theory may be relevant for new development areas such as government-induced local actions, since bargaining power and existing preference of locations are not issues and can be altered through the government’s intervention. It is also important to note that transportation cost may not in all cases be an overriding factor for locational consideration, particularly when considering the contribution of transportation cost to the total cost that may vary from product to product.

Hoover’s (1937) third classification of agglomeration category, urbanization economies, involves the presence of localization economies or diseconomies. These localization economies or diseconomies include the larger pool of skilled labor, higher utilization of specialized and auxiliary industrial and repair facilities and large-scale buying and selling through brokers. Isard sees urbanization economies as playing a

significant role in determining the spatial structure. The localization economies encourage higher concentration or clustering of activities. However, localization diseconomies such as higher costs of living costs and congestions may limit the clustering of activities.

Weber’s isodapane approach can be used to explain how localization diseconomies and economies can influence the spatial structure. According to Isard, the use of isodapane is especially useful for development of new areas. Given the full knowledge of existing technology and possible changes to the technology, planners have an opportunity to plan the area based on the optimal spatial distribution and the hierarchy of cities with different sizes. However, isodapanes can also be used in existing land use if the objective is to alter the channels in the structure of the network to attain a situation closer to the optimum. Isard (1956) draws a graph that summarizes the economies and diseconomies in urban economic activities. This graph also shows the optimum urban population size for the respective economic activities to have efficient and feasible operations. Figure 2.1 shows Isard’s graph. Based on figure 2.1, the average optimum city size for all the urban economic activities is about 100,000 people. A later study by Fuguitt and Zuiches (1975) discovers that most of the residents living in rural areas prefer to be within 30 miles of a city over 50,000, which shows that the 100,000 people optimum city size standard in 1950 remains relevantly high if compared to the standard in the later years.

Figure 2.1. Economies of Scale for Urban Activities

Population

1,000 10,000 100,000 1,000,000

Annual net economies ($ million)

Education Economies Power Economies

Labor Economies Transportation Economies

Total economies

Source: (Isard, 1956, p.187)