Returns to Scale

At this new exchange rate, Japan’s labor costs per unit of output (converted into dollars) become 500/125 $4 and 1,250/125 $10 for the respective goods. With the appreciation of the dollar, Japanese goods become less costly (after converting into dollars). The U.S. cost advantage in pharmaceuticals has narrowed significantly ($3.75 versus $4.00), whereas the Japanese cost advantage in watches has widened. Accordingly, U.S. pharmaceutical exports should decline; these exports simply are not as attractive to Japanese consumers as before. In turn, a more expensive dollar (a cheaper yen) makes Japanese watch exports more attractive to U.S. consumers.

To sum up, relative productivities, relative wages, and the prevailing exchange rate combine to determine the pattern of cost advantage and trade. With respect to the exchange rate, depreciation of a country’s currency increases its exports and decreases its imports. A currency appreciation has exactly the opposite effect.

RETURNS TO SCALE AND SCOPE

Returns to Scale

Returns to scale are important because they directly determine the shape of long-run average cost. They also are crucial for answering such questions as Are large firms more efficient producers than small firms? Would a 50 percent increase in size reduce average cost per unit? Although the exact nature of returns to scale varies widely across industries, a representative description is useful. Figure 6.4 depicts a long-run average cost curve that is U-shaped. This reflects increasing returns to scale (and falling LAC) for low output levels and decreasing returns (increasing LAC) for high levels. In the figure, the minimum level of long-run average cost is achieved at output level Qmin. As in Figure 6.3, SAC curves for three plants are shown. Thus, output Qmin is produced using the medium-sized plant. If the costs of all possible plants were depicted, the lower “envelope” of the many SAC curves would trace out the figure’s LAC curve. To sum up, if the firm is free to use any size plant, its average production cost is exactly LAC.

As noted in Chapter 5, a number of factors influence returns to scale and, therefore, the shape of long-run average cost. First, constant average cost (due to constant returns to scale) occurs when a firm’s production process can be replicated easily. For instance, the electronics repair firm may find it can double its rate of finished repair jobs simply by replicating its current plant and labor force—that is, by building an identical repair facility beside the existing one and proportionally increasing its labor force. By duplication, the firm could supply twice the level of service at an unchanged average cost per job.

Second, declining average cost stems from a number of factors, including capital-intensive mass production techniques, automation, labor specialization,

FIGURE 6.4

U-Shaped, Long-Run Average Cost

The U shape is due to increasing returns at small outputs and decreasing returns at large outputs. Long-Run Average Cost

SAC1

SMC1

LMC SAC2

SMC2 LMC

SAC3

SMC3 LAC

Qmin

Output

advertising, and distribution. By increasing scale, the firm may be able to use new production methods that were infeasible at smaller outputs. It also may find it advantageous to exploit specialization of labor at the larger scale. The result of either kind of production innovation is a reduction in long-run average cost.

Fundamental engineering relationships may have the same effect. For instance, in 2011, Royal Caribbean International boasted the world’s largest cruise liner, costing $1.1 billion, with capacity for 6,400 passengers and 2,300 crew. The largest cruise ships take full advantage of scale economies. At twice the tonnage, a super-cruise liner can carry significantly more than twice the number of passengers while requiring only a relatively modest increase in crew. Accordingly, the cost per passenger declines markedly.

Declining average cost also may be due to the presence of a variety of fixed expenses. Frequently, significant portions of a firm’s advertising, promotional, and distributional expenses are fixed or (at least) vary little with the firm’s level

of output. (For instance, a 30-second television advertisement represents the same fixed cost to a large fast-food chain and a small chain alike. But this expense constitutes a much lower average cost per burger for the large chain.) Similarly, the costs to firms of many government regulations are (in the main) fixed. Accordingly, they represent a smaller average cost for the large firm. The U.S. automobile industry, perhaps the most highly regulated sector in the world, is a case in point.

Finally, increasing average cost is explained by the problems of organization, information, and control in very large firms. As the firm’s scale increases, so do the difficulties of coordinating and monitoring its many management functions. The result is inefficiency, increased costs, and organizational overload.6

A great many studies have investigated the shape of average cost curves for different industries in both the short and long runs. Almost all of these studies use regression techniques to generate equations that explain total cost as a function of output and other relevant explanatory variables (such as wages and other input prices). The data for this analysis can come from either a time series (the same firm over a number of months or years) or a cross section (a cost comparison of different firms within a single time period). Despite difficulties in estimating costs from accounting data and controlling for changing inputs (especially capital), technology, and product characteristics, these studies have produced valuable information about costs.

One general finding is that, for most goods and services, there are significant economies of scale at low output levels, followed by a wide region of constant returns at higher levels. In short, for a great many industries, long-run average cost tends to be L-shaped, as depicted in Figure 6.5b. This is in contrast to the usual textbook depiction of U-shaped LAC shown in Figure 6.5a. A small number of products display continuously declining average costs. This case usually is described under the term natural monopoly and includes many (but not all) local utilities, local telephone service, and cable television. Figure 6.5c shows this case.

A useful way to summarize the degree of scale economies across industries is provided by the notion of efficient scale. Minimum efficient scale (MES) is the lowest output at which minimum average cost can be achieved. In parts (a) and (b) of Figure 6.5, minimum efficient scale is designated by Qmin. In part (b), this occurs where the average cost curve first achieves a minimum. In part (c), there is no minimum efficient scale because LAC continuously declines.

Minimum efficient scale is important in determining how many firms a particular market can support. For example, suppose market demand is 10 million units per year. If minimum efficient scale for the typical firm occurs at 100,000 units per year, the market can support 100 firms, each producing at

6For many goods and services, transportation costs are an important factor in explaining increasing LAC. At a small scale, the firm can efficiently serve a local market. But delivering its good or service to a geographically far-flung market becomes increasingly expensive.

FIGURE 6.5

Three Examples of LongRun Average Cost

Long-Run Average Cost

Qmin

Long-Run Average Cost (a)

Qmin

Long-Run Average Cost (b)

(c) Output

Output

Output

minimum efficient scale. In contrast, if minimum efficient scale is 5 million units, the market can support only two firms producing efficiently. Finally, if average cost declines for all outputs (up to 10 million units), the market may be able to support only one firm efficiently.

As one might expect, estimates of MES vary widely across industries.7 For instance, in the production of sulfuric acid (a standard chemical), the MES for a plant is about 4 percent of total U.S. consumption. The average cost disadvantage of producing at one-half of MES is only 1 percent. The clear implication is that there is ample room in the market for as many as 25 (1/.04) firms. By comparison, the MES for electric motors is about 15 percent of U.S. consumption, and the cost disadvantage at one-half of MES is 15 percent. For production of commercial aircraft, MES is 10 percent of the U.S. market, and the cost disadvantage at one-half of MES is 20 percent. This suggests that the industry could support as many as 10 manufacturers. Economies of scale would not seem to explain why Boeing and Airbus dominate the worldwide market. Rather, the rise of these two aviation giants and the demise of Lockheed and McDonnell-Douglas more aptly are attributed to differences in the companies’ management strategies and technological capabilities.

As noted in Chapter 3, the Internet and the emergence of e-commerce have significant impacts on the structure of firm costs.8 A wide-ranging research study by Washington’s Brookings Institution estimated that across the whole of the U.S. economy, the adoption of information technology and e-commerce methods was producing total annual cost savings of a magnitude equivalent to about 1 percent of annual gross domestic product. Increased efficiency stemmed from reengineering the firm’s supply chain and from reducing transactions costs of all kinds. The greatest potential savings emerged in informationintensive industries such as health care, financial services, education, and public-sector operations.

Recall that the hallmark of information economics is the presence of high fixed costs accompanied by low or negligible marginal costs. As a result, average costs decline sharply with output. The fixed costs of business capital investments are increasingly found in computers, computing systems such as

7Estimates of plant-level economies of scale for different industries are collected in W. Shepherd and J. M. Shepherd, The Economics of Industrial Organization (Upper Saddle River, NJ: Prentice Hall, 2003). 8For discussions of e-commerce and cost economies, see G. Ellison and S. F. Ellison, “Lessons about Markets from the Internet,” Journal of Economic Perspectives (Spring 2005): 139–158; S. Borenstein and G. Saloner, “Economics and Electronic Commerce,” Journal of Economic Perspectives (Winter 2001): 3–12; and R. E. Litan and A. M. Rivlin, “Projecting the Economic Impact of the Internet, American Economic Review, Papers and Proceedings (May 2001): 313–317.

E-Commerce and Cost Economies