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Technological Change, Dynamic Efficiency, and Market Structure

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New Perspectives on Industrial Organization

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Abstract

To this point, most of our discussion about economic performance has focused on static efficiency and assumed that technology is fixed. Yet economic growth requires that we make investments today to develop better products or new processes that lower the cost of production. Persistent long-run economic growth has led to a continued rise in our standard of living. For example, Elwell (2006) documents that from 1980 to 2004 that output per capita grew by about 2.3% per year in Great Britain and by about 2.0% in the USA, Japan, and other major European countries (Germany, France, Italy, and the Netherlands). Although these growth rates may seem inconsequential, a small increase in the growth rate can have a sizable cumulative effect. To illustrate, a 2% growth rate will double the standard of living in approximately 35 years, while a 3% growth rate doubles it in only about 23.5 years.

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Notes

  1. 1.

    The “rule of 72” provides an approximation. That is, if the annual growth rate is x%, then the standard of living will double in approximately 72/x years.

  2. 2.

    Vaudeville was live theater by circus entertainers, comedians, dancers, and musicians.

  3. 3.

    For a review of the evidence, see Cohen and Levin (1989), Mankiw et al. (1992), Jorgenson and Stiroh (2000), DeLong et al. (2003), and Elwell (2006).

  4. 4.

    Percentages exceed 100% because other factors, such as an increase in government regulation and a shorter average work week, have reduced economic growth. Early studies by authors such as Denison (1985) gave an even higher contribution to technological change (at over 60%).

  5. 5.

    The US Patents and Trademark Office publishes patent information by country, industry, and company at http://www.uspto.gov.

  6. 6.

    As with most economic problems, this involves tradeoffs because research and development is costly and technological change can have undesirable consequences. For example, new technologies have made mass killing more efficient and have sometimes increased the level of pollution and market power. As we discussed in Chap. 1, equity, fairness, a clean environment, and macrostability are also important to social welfare. In this chapter, we focus on technological change that is beneficial and postpone discussion of these broader concerns to Chaps. 19 and 20.

  7. 7.

    An isoquant maps out the minimum combinations of L and K that will produce a given level of output (\( \bar{q} \)). An isocost function maps out all combinations of L and K that produce a given total cost (\( \bar{C} \)). For further discussion, see Varian (2010).

  8. 8.

    For further discussion, see the Committee on Science, Engineering, and Public Policy (1999).

  9. 9.

    The data are available at http://www.nsf.gov/statistics/nsf10314/content.cfm?pub_id=4000&id=1.

  10. 10.

    See Scherer (1965) and Jewkes et al. (1969).

  11. 11.

    Rogers actually divided individuals into five categories: innovators, early adopters, early majority, late majority, and laggards.

  12. 12.

    Given the problem with imitation, Keller (2002) suggests that permitting joint ventures and cooperation in R&D may also increase inventive activity.

  13. 13.

    This property rights issue also motivates our copyright legislation, which gives creators ownership of their artistic expression, and trademark laws, which protect a company’s words or symbols used to identify a firm’s particular brand or identity. Because these encourage creativity much like a patent, we focus primarily on patents in this chapter. You can learn more about patent, copyright, and trademark law from the Web page of the US Patent and Trademark Office at http://www.uspto.gov.

  14. 14.

    For a more complete description of the patent process, see Merges et al. (1997).

  15. 15.

    One example is Amazon.com’s one-click method of placing an order on the internet.

  16. 16.

    For an early discussion of this issue, see Nordhaus (1969).

  17. 17.

    That is, ∂q/∂R&D > 0 and ∂2 q/∂R&D2 < 0. This last condition assures that the firm’s second-order condition of profit maximization is met. To simplify the analysis, we let R&D affect demand or costs directly. That is, its effect on technology (T) is assumed to be 1 (i.e., ∂T/∂R&D = 1).

  18. 18.

    This derivative involves the use of the chain rule, which is discussed in the Mathematics and Econometrics Appendix at the end of the book. According to the chain rule, if y = f(x 1) and x 1 = f(x 2), then a change in x 2 causes a change in x 1 which causes y to change. That is, dy/dx 2 = (dy/dx 1)(dx 1/dx 2). In this case, because C = C(q) and q = q(R&D), ∂C/∂R&D = (∂C/∂q)(∂q/∂R&D).

  19. 19.

    This derivation is based on the fact that the Lerner index is ℒ ≡ (p − MC)/p = 1/η, where MC is the long-run marginal cost of production. Recall from Chaps. 6 and 12 that the Lerner index is derived from the firm’s first-order condition of profit maximization.

  20. 20.

    This is consistent with Spence (1975), who showed that the gains from improving product quality will be larger as the price elasticity of demand falls. However, Kamien and Schwartz (1970) find that the gains from reducing the cost of production are larger the more elastic is demand.

  21. 21.

    That is, ∂c/∂R&D < 0 and ∂2 c/∂R&D2 > 0. This is required for the firm’s second-order condition of profit maximization to hold.

  22. 22.

    The second-order condition is met, because ∂2 c/∂R&D2 > 0.

  23. 23.

    For simplicity, we have ignored the price of conducting research and development. Investment in R&D would also be expected to increase as the price of R&D falls.

  24. 24.

    Arrow actually compared monopoly with perfect competition (which is the same as the Bertrand outcome when the number of firms exceeds 1). In any case, Arrow’s main results are unaffected by assuming any market structure (such as Cournot) that produces an equilibrium level of market output that exceeds the cartel level of market output.

  25. 25.

    We discuss this fact in Chap. 2.

  26. 26.

    If the new technology lasted for many periods, its benefits would equal the present value of the gain in future gross profits. This simply complicates the analysis without providing important new insights.

  27. 27.

    Alternatively, we could assume that the firm owns the right to the new technology and licenses it out to existing firms for a royalty payment equal to MC − MC′. This produces the same result.

  28. 28.

    Even with patents, firms can sometimes circumvent them. Mansfield (1968) found that the time between the introduction of an innovation and when 60% of related products had imitated the innovation ranged from one month for simple production processes to several decades for more complex ones (e.g., steel production). As you might expect, Levin et al. (1987) found that it takes considerably longer to imitate a major new product that has been patented than one that has not been patented.

  29. 29.

    See Kamien and Schwartz (1982) and Reinganum (1989) for a more complete discussion.

  30. 30.

    This assumes that η is constant, an assumption that may not hold in reality. For further review of the theoretical literature, see Dasgupta (1988) and van Cayseele (1998).

  31. 31.

    Sutton argues that this is because the degree of substitutability between products is high in the vertical case.

  32. 32.

    See, for example, MacLaurin (1954), Scherer (1965), Pakes and Schankerman (1984), Jaffe (1986), Cohen and Levin (1989), Geroski (1990), and Blundell et al. (1999).

  33. 33.

    An explanation for this is provided by Nelson (1982a), who argues that advances in scientific knowledge increase technological opportunities by lowering the cost of applied research in scientific and technical fields.

  34. 34.

    For a review of the literature, see Kamien and Schwartz (1982), Cohen and Levin (1989), Geroski (1990), van Cayseele (1988), and Blundell et al. (1999).

  35. 35.

    The one exception is Gayle (2005), who attempted to control for the relative importance of a patent by using a citation-weighted patent count to measure innovative output. With this measure, Gayle found a stronger positive relationship between patent counts and industry concentration.

  36. 36.

    Again, this ignores the possible negative consequences of technological change, an issue that we address in Chaps. 19 and 20.

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Tremblay, V.J., Tremblay, C.H. (2012). Technological Change, Dynamic Efficiency, and Market Structure. In: New Perspectives on Industrial Organization. Springer Texts in Business and Economics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3241-8_17

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