What is the term used to describe the level of output of a plant at which most plant level scale economies are exhausted?

Economies of Scale and Density in Transmission and Distribution

Some studies estimated the economies of scale for transmission and distribution elements, such as Huettner and Landon (1977), who found the minimum efficient scale occurred at around 2600 MW capacity. Kaserman and Mayo (1991) also found specific economies of scale for these phases and situated the minimum efficient scale at around 5 GWh. Greer (2003) found that none of the rural electric cooperatives distributed anywhere near the minimum efficient scale in 1996.

The network elements and the costs involved in these activities can be studied in greater depth by studying economies of density. This concept explains the evolution of average costs when production is increased and when some of the characteristics that define the product are maintained constant, for example, the size of the service area or the number of consumers.

2.6 Economies of Scale and Density in Transmission and Distribution

Some studies estimated the Economies of Scale for the transmission and distribution elements, like Huettner and Landon (1977), who found that the Minimum Efficient Scale occurred at around 2600 MW capacity. Kaserman and Mayo (1991) also found specific Economies of Scale for these phases, and they situate the Minimum Efficient Scale at around 5 GWh. And Greer (2003) found that none of the Rural Electric Cooperatives distributed anywhere near the Minimum Efficient Scale in 1996.

The network elements and the costs involved in these activities can be studied in greater depth by studying Economies of Density. This concept explains the evolution of Average Costs when production is increased and some of the characteristics that define the product are maintained constant, for example, the size of the service area or the number of consumers.

Minimum Efficient Scale

Geometrically, Figure 4.3 displays the relevant regions of an average cost curve. As output is expanded, cost increases at a decreasing rate until average cost is at its minimum. Known as the minimum-efficient scale, this point indicates the optimal level of output for a firm (or firms) to produce. After this, diminishing marginal returns set in (i.e., marginal cost begins to rise, thus causing average cost to increase at an increasing rate). This is displayed in Figure 4.3.

This concept is extremely important because it is an important factor in determining the optimal size and number firms in an industry. As such, it can have major implications for public policy, and regulatory considerations.

Minimum Efficient Scale

Geometrically, Figure 4.3 displays the relevant regions of an Average-Cost Curve. As output is expanded, cost increases at a decreasing rate until Average Cost is at its minimum. Known as the Minimum Efficient Scale (MES), this point indicates the optimal level of output for a firm (or firms) to produce. After this, diminishing marginal returns set in (i.e., Marginal Cost begins to rise, thus causing Average Cost to increase at an increasing rate). This is displayed in Figure 4.3.

This concept is extremely important since it is an important factor in determining the optimal size and equilibrium number of firms in an industry. As such, it can have major implications for public policy, particularly where they lead to the development of Natural Monopolies, or where monopolies that are not Natural Monopolies claim that they are in order to try to prevent government attempts to break them up.

5.1. Industry Structure

Geographic deregulation released a binding constraint on the size of banking companies wishing to grow larger, and advances in financial and information technologies provided a potentially attractive business model (transactions banking) that could be exploited by large banks. The fastest way for commercial banks to take advantage of these opportunities was to acquire other existing banks. On average, 500 commercial banks were acquired each year between 1990 and 2000, a substantial number in an industry that began the decade with a little over 12,000 banks.

This wave of bank mergers and acquisitions had two effects on the number and size distribution of U.S. banks. First, the number of banks (measured by the number of active federal and state bank charters) has declined dramatically, from around 14,000 banks—a number that had remained remarkably stable since the 1950s—to fewer than 8,000 banks today. Note that this decline in total numbers is a net figure that understates the impact of mergers and acquisitions. The overall number of banks is bolstered by the more than 3,000 new banking charters issued by state and federal banking authorities during the 1980s, 1990s, and 2000s. Strong anecdotal evidence, as well as systematic empirical evidence, indicates that these new, or “de novo,” banks tended to start up in the same local markets in which established banks had been acquired (Berger, Bonime et al. 2004, Keeton 2000). On the one hand, the overall number of banks is depressed by the 2,000-plus bank failures displayed in Figure 1.

Second, as illustrated in Figure 4, the size distribution of banks has changed. The population of medium-sized and larger banks has remained relatively stable since 1980, each varying between 300 and 500 banks. The reduction in the number of banks has occurred exclusively among banks with assets of less than $500 million. Three phenomena account for the decline: The vast majority of failed banks since 1980 have been small banks; most of the acquisition targets since 1980 have been small banks; and some small banks grew up and out of this size group by merging with other small banks.

Figure 4 is a crude version of a survival analysis (Stigler 1958). The figure suggests that economically meaningful scale savings can be captured by growing up to $500 million in assets but that growing beyond $500 million—at least for community banks—yields far less substantial gains. The literature on bank scale economies is large and has produced differing estimates of minimum efficient scale over the years.10 The earliest studies concluded that scale economies were fully exhausted by relatively small banks; most of these studies estimated minimum efficient scale for banks to be less than $1 billion of assets (2001 dollars). More recent studies have yielded somewhat different insights; many of these studies conclude that scale economies are available for large regional and even superregional banks. The stark differences between these two sets of results may be due to the inferior (though state-of-the-art at that time) methodologies used by the earlier studies, but the more likely explanation is the implementation of high-volume bank production technologies that were not available in past decades.

Efficient scale is likely to be quite different for transactions banks as well as banks that employ other nontraditional banking business models. As noted earlier, Rossi (1998) shows that even very large mortgage banks (which use a classic transactions banking approach) face increasing returns to scale. Hughes et al. (1996) conclude that even the largest commercial bank holding companies (in which product volume is often dominated by transactions banking activities) also exhibit increasing returns to scale. And DeYoung (2005) argues that Internet-only banks (again, banks that use a pure transactions banking strategy) exhibit larger scale economies than similar-sized banks that have branches.

Geographic expansion by merger has eliminated thousands of banking charters and has created very large banking companies. For example, just before the passage of the Riegle-Neal Interstate Banking Act in 1994, only four banks had more than $100 billion in assets; a decade later 10 banks were that large, with two of these banks approaching $1 trillion in assets. This industrywide consolidation has had little effect on the structure of local markets—by definition, a geographic expansion merger leaves the target market shares unchanged—but the nature of the competitive rivalry in the target market can change. Studies have shown improved cost efficiency at small local banks following market entry by large out-of-market banks, presumably because of competitive pressure (DeYoung, Hasan, and Kirchhoff 1998; Evanoff and Ors forthcoming). Other studies have shown that outside entrants with stronger “brand images” are able to expand their local market shares more quickly (Berger and Dick, forthcoming), consistent with the idea that perceived differentiation can be an effective tool for large banks that sell financial commodity products.

Geographic expansion mergers have also increased the distances within banking organizations and may have created internal management problems. Berger and DeYoung (2001, 2006) find that banking affiliates located farther away from the headquarters bank were less operationally efficient. While improvements in communications and information technologies have proved helpful in reducing these long-distance management problems, such organizational inefficiencies are one reason that small, locally focused banks may continue to be financially viable in competition with large banks. Distances between banks and their loan clientele have also increased over time. This phenomenon is mainly technology driven: automated, credit–scored lending models allow banks to make consumer, mortgage, credit card, and even some small business loans to borrowers they have never met in person, and asset securitization and credit derivatives allow banks to manage the risk associated with this type of lending (Petersen and Rajan 2002, DeYoung, Glennon, and Nigro 2006).

It is important to understand that the reduction in banking companies over the past two decades has not necessarily increased the distances between borrowers and lenders, because banks have simultaneously increased the size of their branching networks. There are about 70,000 commercial bank branches in the United States today, compared to only about 40,000 in 1990. This explosion in bank branches has been largely strategic in nature. For example, in some markets (such as Chicago), large banking companies are “packing the map” with branches in order to establish market presence and to limit entry by competitors. By increasing the size and scope of its branch network, a bank can position itself closer to both its current clients and its rivals’ customers. This strategy can be especially important for large, transactions banks; although it is difficult for these banks to offer personalized banking services, they can offer high levels of customer convenience by locating close by. This higher level of convenience may explain why retail customers appear willing to pay higher deposit-related fees at large banks. Finally, physical branches located in prominent places also serve as an important advertising vehicle, especially in markets into which a bank has just expanded.

The Market for Electricity

This same thinking is now being applied to the deregulation of electricity. However, unlike Telephony where there does not seem to have been any testing for Economies of Vertical Integration, those in electricity have been well established. The fact that the majority of the Electric Utilities in the United States are vertically integrated attests to this.

Until recently, no one questioned that the production of electricity was in fact a Natural Monopoly, since, like Telephony, what is required here is a network: a complex, interactive, interdependent connection of wires (by which end-use customers are connected to their local distribution company (LDC), which is connected to the transmission grid). This network represents an irreversible investment, which is characterized by both Economies of Scale and those of network planning, and as such yields a Natural Monopoly.

Because this network leads to externalities (one of which is the presence or creation of bottlenecks), Vertical Integration is the most efficient organization of the industry, especially for larger firms. But it is due to the vertical nature of electricity production that questions have arisen concerning whether any aspect of the production process may not be a Natural Monopoly. And, if this is the case, the question then becomes: Would the market be better served by allowing competition into that component, and would the gains from competition exceed the lost vertical economies that would result? And this is the critical element that needs to be explored. And this is one parallel that can be drawn, and hence lessons can be learned, from the deregulation of telecommunications.

Economies of Scope (Horizontal Production) Applied to Electricity

As an extension to their testing for vertical economies, both Kaserman and Mayo (1991) and Gilsdorf (1994, 1995) employ a Multiproduct-Cost Function to determine whether Vertical Integration and Economies of Scale together constitute a Natural Monopoly. In fact, the former tests for multistage economies between Generation and Transmission/Distribution. As previously stated, they too reject the Separability of inputs and outputs (what is generated is an input to what is transmitted/distributed) in the cost function. It is important to note that Separability is not the same thing as Economies of Vertical Integration, whereby it is output-output interactions that matter.

The use of a Multiproduct-Cost Function implies that it is Economies of Scope and Cost Complementarity that are relevant here. With this said, Economies of Scope can arise for either of two reasons:

1.

The cost function may have some indivisible input used in the production of both goods. For example, let F represent the cost of the indivisible input, and G and D are outputs in the production process (where G and D are, respectively, generated and distributed electricity). Then the cost of production is given by:

(5.12)C=F+G+D

which is characterized by Economies of Scope since separate production of any G, D > 0 would entail duplication of F.

2.

The cost function may exhibit Cost Complementarity, which means that there exists a cost interaction between the two outputs in the production process.

As an example, let the cost function be given by:

(5.13)C=G+D −G⁎D

Since G*D equals zero for separate production for either G or D > 0, the negative sign implies that joint production is cheaper by the amount of the interaction term.

Hence, in the distribution of electricity, Scope Economies occur via the transmission/distribution grid (and the access to), an indivisible input. You may recall that this creates a bottleneck, which is an argument for Vertical Integration. Economies of Vertical Integration are a straightforward extension of this:

Again, let C (G, D) be the cost of production for a vertically integrated firm. If this is less than the sum of the cost of separate production by a pure generator and the cost by a pure distributor, that is:

(5.14)CGD<CG0+C 0D

then it is said that there exist Economies of Vertical Integration.

This is equivalent to Eq. (5.10), which, as shown, is mathematically equivalent to Eq. (5.11). As such, this establishes that Economies of Vertical Integration are a necessary condition for Natural Monopoly. QED.

As stated earlier, a sufficient condition is also required. For this, a slight modification of the definition of Cost Complementarity will suffice. As defined in Chapter 2, Eq. (2.31), Cost Complementarity exists when:

(5.15)∂2CY/∂Yi∂Yj<0

for i ≠ j.

However, in this case, the outputs Yi and Yj represent the different stages of production.

If the above is satisfied, then the cost function exhibits Cost Complementarity, which is a sufficient condition for Subadditivity in a Multiproduct-Cost Function. Again from Chapter 2, a market is said to be a Natural Monopoly if, over the entire relevant range of outputs, the firm's cost function is subadditive.

Figure 5.2 displays the source of Economies of Scope within the vertical structures of Telephony and of electricity. For the former, it is in the “generation” of the voice, fax, or data that is an input into the subsequent stages that are displayed in Figure 5.1. In the case of the latter, Economies of Scope occur in stage three, the Distribution of electricity to various types of end user, or customer class, which are distinguished by voltage level, among other aspects (discussed in Chapter 2).

Figure 5.2. The horizontal structures of Telephony (vertical stage 1) and electricity (vertical stage 3).

(Source: MLGreer.)

The market for electricity

This same thinking is now being applied to the deregulation of electricity. However, unlike telephony, where there seems to have been no testing for economies of vertical integration, those in electricity have been well established. The fact that a majority of the electric utilities in the United States are vertically integrated attests to this.

Until recently, no one questioned that the production of electricity was in fact a natural monopoly, since, like telephony, what is required here is a network: a complex, interactive, interdependent connection of wires (by which end-use customers are connected to their local distribution company, which is connected to the transmission grid). This network represents an irreversible investment, which is characterized by both economies of scale and those of network planning, and as such yields a natural monopoly.

Because this network leads to externalities (one of which is the presence or creation of bottlenecks), vertical integration is the most efficient organization of the industry, especially for larger firms. But, due to the vertical nature of electricity production, questions have arisen concerning whether any aspect of the production process may not be a natural monopoly. And, if this is the case, the question then becomes: Would the market be better served by allowing competition into that component and would the gains from competition exceed the lost vertical economies that would result? This is the critical element that needs to be explored. And this is one parallel that can be drawn, and hence lessons can be learned, from the deregulation of telecommunications.

Economies of scope (horizontal production) applied to electricity

As an extension to their testing for vertical economies, both Kaserman and Mayo (1991) and Gilsdorf (1994, 1995) employ a multiproduct cost function to determine whether vertical integration and economies of scale together constitute a natural monopoly. In fact, the former tests for multistage economies between generation and transmission/distribution. As previously stated, they too reject the separability of inputs and outputs. It is important to note that separability is not the same thing as economies of vertical integration, whereby output-output interactions matter.

The use of a multiproduct cost function implies that economies of scope and cost complementarity are relevant here. With this said, economies of scope can arise for either of two reasons:

1.

The cost function may have some indivisible input used in the production of both goods. For example, let F represent the cost of the indivisible input, and G and D are outputs in the production process (where G and D are, respectively, generated and distributed electricity). Then the cost of production is given by

(5.12)C=F+G+D

which is characterized by economies of scope, since separate production of any G, D > 0 would entail duplication of F.

The cost function may exhibit cost complementarity, which means that there exists a cost interaction between the two outputs in the production process. As an example, let the cost function be given by

(5.13)C=G+D-G×D

Since G × D equals 0 for separate production of either G or D > 0, the negative sign implies that joint production is cheaper by the amount of the interaction term.

Hence, in the distribution of electricity, scope economies occur via the transmission/distribution grid (and the access to it), an indivisible input. You may recall that this creates a bottleneck, which is an argument for vertical integration. Economies of vertical integration are a straightforward extension of this.

Again, let C(G, D) be the cost of production for a vertically integrated firm. If this is less than the sum of the cost of separate production by a pure generator and the cost of a pure distributor, or,

(5.14)C(G ,D)<C(G,0)+C(0,D)

then it is said that there exist economies of vertical integration.

This is equivalent to equation (5.10), which, as shown, is mathematically equivalent to equation (5.11). As such, this establishes that economies of vertical integration are a necessary condition for natural monopoly. [QED]

As stated earlier (in Chapter 2), a sufficient condition is also required. For this, a slight modification of the definition of cost complementarity will suffice. As defined in Chapter 2, equation (2.30), cost complementarity exists when

(5.15)∂2C(Y)/ ∂Yi∂Yj<0,fori≠j

However, in this case, the outputs Yi and Yj represent the different stages of production.

If equation (5.15) is satisfied, then the cost function exhibits cost complementarity, which is a sufficient condition for subadditivity in a multiproduct cost function. Again from Chapter 2, a market is said to be a natural monopoly if, over the entire relevant range of outputs, the firm's cost function is subadditive.

Figure 5.2 displays the source of economies of scope within the vertical structures of telephony and of electricity. For the former, it is in the “generation” of the voice, fax, or data that is an input into the subsequent stages that were displayed in Figure 5.1. In the case of the latter, economies of scope occur in stage three, the distribution of electricity to various types of end users, or customer classes, which are distinguished by voltage level, among other aspects (this is discussed in Chapter 2.)

Figure 5.2. The horizontal structures of telephony (vertical stage 1) and electricity (vertical stage 3)

2.2.1 The restructuring context

The physical situation in a country provides a set of relatively “hard” constraints. A crucial element is the presence of indigenous energy resources, such as hydropower, coal, natural gas and oil, or – at the other end – dependence upon other countries for energy resources. Market size and degree of isolation matter too. Small isolated systems, in small countries or on islands, like Iceland, Malta, or in the Caribbean, cannot efficiently support multiple competing generating companies as a consequence of the relatively large minimum efficient scale of the several types of generation units. This also impedes the use of specific technologies or fuels, such as large-scale coal plants. The geographic distribution of demand also plays a role: in thinly populated areas or small, remote concentrations of electricity demand it may be difficult to create competition in supply (see also Weinmann and Bunn, 2004).

A second set of constraints relates to macro-economic characteristics such as the level of economic development, the rate of demand growth, and the availability of investment capital. These factors influence the acceptability of changes in tariffs or prices to different categories of users, the need for investment, and financing options for system expansion and/or rehabilitation. Three obvious categories of countries are, firstly, developing countries with a relatively stagnant economy; secondly, countries on the path of economic development and industrialization; and, thirdly, the OECD countries.

The third category of constraints derives from the institutional and socio-political environment of a power system. North (1990), Williamson (1998), Glachant and Finon (2000), and Finon (2003) explain how informal institutions such as culture, traditions, and values affect the development of formal institutions, such as property rights, legislation, regulation, and the role of the (federal) state in the economy. In De Vries and Correljé (2006) it was discussed how formal institutions can be divided into general institutions, such as the polity, the judiciary, and the bureaucracy, and sector-specific institutions, such as sector legislation and regulation and jurisprudence, which are the main tools of market design. Arguing that the freedom of action for those who are in control of the reform process and the need to coordinate different aspects of the reform process are essential to the success of a restructuring process, Glachant and Finon (2000) consider the power of the central government a key factor with respect to the success of market reform.

Table 2.1 provides an overview of the physical, macro-economic, and institutional constraints. Together they determine to a large extent the solution space that is available to governments that wish to restructure their power sectors. Within the context of these constraints, governments need to find a balance between their own multiple objectives and those of the energy sector and of consumers.

Table 2.1. Factors that determine the context of the restructuring process

Some confusion may arise with respect to the difference between variables and constraints, as the starting value of a variable itself may pose a constraint on the liberalization process. For instance, the fuel mix at the outset of liberalization influences the economic and environmental performance of the sector for many years after the reforms have been instituted. However, this should not be considered a constraint, but rather the beginning value of the variable “fuel mix,” which may change over time. Undeniably, “take-off” variables such as the fuel mix have a significant path-dependent impact, but analytically it is essential to make a clear distinction between fixed constraints, as factors that lie outside the control of the actors within our system, and variables that are (more or less) under their control. Market design variables will be discussed in Section 2.3.

Appendix

Table A1. Review of studies considering technical efficiency in the European context

Table A2. EU energy companies included in the sample

Note: The time frame includes years 2005–2016, except for the following companies: Enemalta (2005–2011; as of 2012, financial statements have not been available to the public), Essent Nederland B.V. (2005–2010; in 2010, RWE Power AG became a full owner of Essent), PGE Polska Grupa Energetyczna SA (2007–2015; financial reports for 2005 and 2006 are not available to the public).

Table A3. Pearson correlation coefficients

Note: * significant at the 0.05 significance level.