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Economies of Scale: Basic Concepts and Empirical Evidence

Introduction

Economies of scale widely imply the cost-related benefits a firm realizes from an increased level of output. The benefits usually occur from the inverse relationship between unit fixed cost and total output. The rationale is that as more units are produced, the fixed value attributable to each segment diminishes since a fixed figure is distributed over a growing number of items. If the reverse occurred, for example, prices surge as more units are produced, then it would reflect diseconomies of scale (Athanassiou, 2015). Economies of scale usually are obtainable through expansion, which allows a business to increase its productivity or efficiency, improving production processes. Through efficiency attained from features such as specialization, organizations can produce via the least-cost model hence realizing a diminishing average cost. EOS can be achieved within several industries such as banking and medicine through research and innovation

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Theoretical Outline: Basic Concepts

Classification of Economies of Scale

Economies of scale (EOS) are widely categorized into two classes: internal and external, and they both arise from the level of aggregation experienced by a business. If the company is the item of emphasis, then the internal EOS would imply the industrial characteristics while the region would form the external EOS (Athanassiou, 2015). However, when the focus is on a firm or specific business, the internal EOS would constitute its elements. Simultaneously, the external EOS would entail every other influential item outside the individual business controls and regulations.

Within both internal and external environments, some economists further isolate the EOS in two main categories: static and dynamic. Static EOS decreases unit costs for the business through an increase of its output at a particular point of measurement. It is more prevalent if cost responsiveness to output is more elastic and this typically implies that the unit cost declines with a rising output at any point in measurement due to a diminishing marginal cost. Dynamic EOS sometimes referred to as learning effects, underscores the declining business unit costs attained from a cumulative production and is measurable over a long period of intervals as production accumulates. For instance, as the organization continues its production procedure, it may attain higher productivity through improved skills, effectively diminishing fixed costs over production time.

Sources of Economies of Scale

EOS is realizable from various areas, often categorized as full capacity economies, by-product recycling and waste management, economies of reserved stocks or inventory, economies of product multiple, economies of technical and human resource efficiency, and monetary economies. Full capacity economies and economies of expansion are mainly realizable from the indivisibility of factors of production, especially physical capitalization such as production equipment. As the units of production from equipment increase, the cost of production capital is diminished from increased revenues attained with more units.

Economies of technological and managerial changes are those attainable from improved processes and specialization. As the business grows, it may enhance its technical production process through innovation or improve its efficiencies through its workforce and labor divisions’ specialization ((Baumers et al., 2016, p. 193). As these processes increase production with efficiency and cost-effectiveness, the cost attributable to the production of a unit declines as it is divisible over many factors.

Economies of product multiple originate from a balance of productive capacities of each factor. When a production process involves the integration of multiple factors such as machines, labor, and plant, it is cost-effective to balance the productive capacity of each element through the improvement of cooperation levels between the items (Hernandez-Villafuerte et al., 2017). When the optimal productivity of a factor is not attained, inefficiency is realizable relative to factor costs. Usually, the realization of optimality is hypothesized to come from dividing the aggregate factor costs by units produced from their integrated processes.

Empirical Evidence of EOS

EOS and Scope in Health and Medical Researches

Funders of medical research usually desire to attain high-quality form innovations and often face investment decisions regarding research and development. Since funders need to account for the investor funds, mostly if they are publicly sourced, it is critical to evaluate which option would be economically viable in terms of investment costing, concentrated investment, or diversification (Hernandez-Villafuerte et al., 2017). As with industrial production, in research investment, the EOS is realizable through the average cost model. As presented by Hernandez-Villafuerte et al. (2017), economies of scale for researches are attainable when the average unit cost for a single output is less than the cumulative quantity produced at a time. For instance, an MRI scan cost diminishes as the number of times the scanner is used increases cumulatively.

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In such a model, economies of scope are attained. Economies of scope are realizable when performing two activities concurrently or at the same place yields a greater output for each unit of expenditure than when both activities are undertaken in isolation, for instance, conducting diagnostic and researches on medicine at the same time (Hernandez-Villafuerte et al., 2017; Obure et al., 2016). In health and medical researches, economies of scale would yield higher-quality results if conducted in institutions with either several researchers or studies taking place simultaneously. Economies of scale would be attainable through improved efficiency that would generate more quality, survivability over a long time, thereby diminishing investment cost attained through several outcomes.

In the event there are limited finances to fund researches, quality from economies of scale would be attainable from undiversified investigations that are more focused. EOS in research and development may occur through other mechanisms such as the growth in scale of activities that efficiently utilize accrued items, equipment, and building or different location- concentrated fixed costs that are cheaper to solicit, such as an existing pool of experts (Hernandez-Villafuerte et al., 2017). However, the increase in research activities or factors may yield diseconomies of scale. Diseconomies of scale may come from coordinative complexities, divergent pressures to employ specific equipment or personnel, or from increased bureaucracies that can produce more costs.

Econometric Tools for Evaluating EOS in Healthcare and Medical Research

Evidence highlights three critical groups of econometric tools for assessing EOS; proxy variables, multi-product cost function, and multi-product production. Proxy variables analyses economies of scale through the use of proxies for ranking the research. These variables include cumulative innovative projects from a research pool, collective projects initiated by an institution, and the cumulative projects in progress of a particular set of researches at a point in time (Hernandez-Villafuerte et al., 2017). In the multi-product cost functions, the cost summation of attaining x outputs depends on the production for each unit and a group of control variables.

In the multi-product cost function model, two types of scale economies, ray economies of scale and product-specific economies of scale, are addressed. Ray economies of scale are the cost effects realized from a rise in the manufacturing of varied outputs by an equal proportion. On the other hand, product-specific economies of scale are the cost burdens of raising the quantitative production on one item while retaining other factors’ levels. The latter reflects the ratio of total costs of production for all outputs and the cumulative marginal cost of outputs. In case the total cost exceeds the marginal value, an overall rise in the production levels will yield a higher total cost representing diseconomies of scale. Product-specific economies of scale represent the ratio between the cost variations with and without producing an item I and the production of that item alone weighted by its marginal cost. Through these models, researchers are able to evaluate the overall cost impact of concentrating resources on individual research against employing the resources in isolated investigations at the same time.

Economies of Scale in the Banking Sector

Evidence prelude that interest rate spreads are high for bigger banks than their smaller counterparts. Perspectives hypothesize that bigger banks might be exploiting their market dominance to raise their loaning rates as they expand, improve efficiency, and become competitively dominant (Asongu and Odhiambo, 2019). Studies have also revealed that as banks expend beyond optimal limits, they begin to experience diseconomies of scale that arise from inefficacies. The standard or typical identifiable mechanisms used by banks to improve intermediation are raising loan portfolios or sizes of loans, lowering the cost of loans, interest rates, and fees, decreasing information flow between lenders and borrowers (Beccalli Anolli and Borello, 2015). However, broader evidence reveals that loan spread remains higher for bigger banks than the smaller ones, especially in the banking sector.

Big banks are presumed to attain economies of scale through smaller margins leveraged on their sizes. The leveraging capacity of bigger banks arguably should yield a lower funding cost relative to their smaller counterparts. Therefore, the hypothetical extension is that these efficiencies would trickle down to the bank customers through high returns on deposits and lower costs on borrowings. However, evidence point out that the banks do not retain this model. Paradoxically, big banks worldwide are continually more inefficient than smaller ones (Beccalli, Anolli, and Borello, 2015). As a result, there has been a growing concern on the role of economies of scale in improving banking sector efficiencies.

Two main arguments underpin this trend. First, it is hypothesized that as banks expand, improve efficiency, and minimize rivalry, they exploit the dominance by creating monopolistic features. Second, there is a perception that expansion beyond a certain optimum will yield economic disadvantages triggering inefficiencies. The second perspective points out that as banks grow, they experience increasing average costs that result in broader interest margins.

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Bank Size and Efficiency

Through the economic model, it is widely expected that as an organization grows, it will experience a corresponding improvement in efficiency through the workforce’s improved technical process and specialization. However, the increased process may always yield coordinative complexities, for instance, in the banking sector, this may be through an agency. In effect, smaller financial institutions with reduced technical complexities become more efficient by reducing increased activities that may yield higher marginal costs.

Using the Quiet Life Hypothesis (QLH), results prelude that firms exploit market power in the context of cost savings and foregone revenues to realize economies of scale. In this model, businesses with huge market shares focus less on price reductions and profit efficiencies. Instead of using their sizes to reduce costs and improve lending-borrowing efficiencies, larger financial institutions prefer to remain quiet (Asongu and Odhiambo, 2019). The economies of scale are realizable in the banking sector through five significant efficiencies; cost efficiency, revenue efficiency, captivity efficiency, and concentration efficiency.

Cost efficiency is underpinned around the model that size yields average cost reductions through efficiency, hence economies of scale. The perspective is that unavoidable operation costs such as marketing, regulatory expenses, and salaries are cushioned with increased revenue from higher business volumes. However, economies of scale fail to rise from size growth for the banking sector since big banks are most likely to implement more technical processes such as the banking software (Pruteanu-Podpiera, Weill, and Schobert, 2016). However, revenue efficiencies are reliant on bank-specific items instead of size.

Three perceptions fundamentally underscore how economies of scale are attained from revenue efficiencies by banks. First, giant corporations are likely to use banks they deem reliable and offer quality services. Such clients demand extensive benefits as conditions to remain customers and usually are very profitable. Second, the broader assumption is that banks with wide cross-border networks are more reliable and provide better services. These two items are broadly achievable by large banks, hence realizing increased revenue from higher business volumes. Third, the large financial institution can leverage risk diversification better than the smaller ones, which is often achievable through credit syndicates and numerous insurance mechanisms (Pruteanu-Podpiera, Weill, and Schobert, 2016). Hence, as banks become more prominent, they can enjoy economies of scale from increased business volumes sourced from more customers.

According to Beccalli, Anolli, and Borello (2015), Captivity efficiency results in economies of scale from ambitious efforts by large banks to raise their control over financial product distributions. While regulating investments in line with Undertakings for Collective Investment in Transferable Securities (UCITS), large banks may underwrite several structured products for their customers hence realizing improved revenues from increased transactions (Beccalli, Anolli, and Borello, 2015). Similarly, through these underwritings, large banks substantially minimize the conveyance of transparent information to the market, thus maintaining a competitive advantage and attaining economies of scale.

Conclusion

Economies of scale widely imply the benefits a business derives from diminishing costs. As the number of units produced rises, the fixed cost associated with generating each unit reduces since it is distributed over several segments. Economies of scale are either internal or external and can be dynamic or static depending on the point average cost reductions are realized as productions take place. EOS can be achieved within R&Ds and banking sectors through slightly different models, although in both areas, it entails declining average costs as production units increase.

In the banking sector, economies of scale may be realized from expansions, resulting in technical and managerial efficiencies. Through these efficiencies, large banks can enjoy increased business volumes from the increased customer base, hence retaining a competitive advantage. In research and development, economies of scale are realizable when the average cost of units produced through innovation results in a diminishing average cost related to generating more units over time. In R & D, EOS can be attained through a synergistic combination of factors to perform concurrent studies or recycled resources in new research to avoid incurring more costs during the research life cycle.

Reference List

Asongu, S.A. and Odhiambo, N.M., (2019) ‘Size, efficiency, market power, and economies of scale in the African banking sector’, Financial Innovation, 5, pp. 1-22.

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Athanassiou, M. (2015) Economies of scope: international management. Web. 

Baumers, M., Dickens, P., Tuck, C. and Hague, R. (2016) ‘The cost of additive manufacturing: machine productivity, economies of scale and technology-push’, Technological Forecasting and Social Change, 102, pp. 193-201.

Beccalli, E., Anolli, M. and Borello, G. (2015) ‘Are European banks too big? Evidence on economies of scale’, Journal of Banking & Finance, 58, pp. 232-246.

Hernandez-Villafuerte, K., Sussex, J., Robin, E., Guthrie, S., and Wooding, S. (2017) ‘Economies of scale and scope in publicly funded biomedical and health research: evidence from the literature’, Health research policy and systems, 15(1), pp. 1-17.

Obure, C.D., Guinness, L., Sweeney, S., Vassall, A. and Integra Initiative (2016) ‘Does integration of HIV and SRH services achieve economies of scale and scope in practice? A cost function analysis of the Integra Initiative’, Sexually transmitted infections, 92(2), pp.

Pruteanu-Podpiera, A., Weill, L. and Schobert, F., (2016) Banking competition and efficiency: a micro-data analysis on the Czech banking industry. In Global Banking Crises and Emerging Markets. London: Palgrave Macmillan, pp. 52-74

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