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Estimating Differential Dynamic Merger Effects on Market Structure and Entry in Related Markets

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Abstract

The U.S. and EU merger guidelines emphasize “ease of entry” arguments but little is known about the dynamic impact of realized mergers on market structure. This study provides insights on this topic with the use of detailed firm-level data on the memory chip market. Our estimation results provide evidence for differential merger effects on market structure. These effects depend on whether the mergers are dominated by market-power or efficiency gains. While efficiency-dominated mergers cause exit, market-power-dominated mergers attract entrants, and these effects are increasing over time. We also find that market-power mergers have a larger effect on entry than efficiency mergers have on exit. Our results show that mergers can reduce the number of potential entrants into related product markets and serve as an instrument to “reduce the likelihood of entry”.

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Notes

  1. See Section  7 of the Clayton Act (as amended by the Celler-Kefauver Act) and the EU Merger Regulation (EC) No. 139/2004.

  2. The potential market-power effect is inherent in a merger, since it eliminates an incumbent firm from the market, which potentially results in higher post-merger prices. The efficiency effect relates to synergy effects that are gained by the merging parties, which can reduce prices (see also Roeller et al. 2006; Gugler and Szuecs 2016; Siebert 2019).

  3. For example, Baumol et al. (1982) highlight that low entry barriers facilitate entry and enforce competitive market outcomes.

  4. Carlton (2007) notes that “...by focusing only on efficiencies that influence price over a short period, a government antitrust agency risks failing to credit the future efficiencies [via changes in market structure] that will benefit consumers in the long-run.”

  5. The entry section in the 1992 Horizontal Merger Guidelines was subsequently substantially revised; see Baker (2003) and Shapiro (2010) for more details.

  6. Potential entry defense arguments have led to the approval of mergers in airlines, supermarkets, film processing, and oil services (see, e.g., Bergman 2003).

  7. While this study distinguishes between entry of new and existing firms, this distinction is less relevant for DRAM firms, since entry requires specific types of production machinery, and any other market activity (such as microprocessors) would not cause a production advantage for producing dynamic random access memory chips.

  8. In our case, the concentration on the number of firms as the dependent variable is beneficial, as it helps avoid endogeneity problems, which we will explain later.

  9. Memory chip fabrication plants are highly specific to memory chip generations as every memory generation requires specialized production machinery. See Liu et al. (2018) for further information on entry into memory chip generations.

  10. We concentrate on horizontal mergers, as this allows us to relate closely to the horizontal merger guidelines.

  11. The patent information is contained in the National Bureau of Economic Research (NBER) patent database. A large name-matching effort was undertaken to match the names of patenting organizations and the names of manufacturing firms, including 30, 000 of their subsidiaries (obtained from the Who Owns Whom directory). The U.S. is the world’s largest technology market, and non-U.S.-based firms also frequently file for patents in the U.S.

  12. The USPTO has developed a highly elaborate classification system consisting of about 400 main (three-digit) patent classes to categorize the patented inventions. Patent examiners from the USPTO provided the technological classes that refer to DRAM-related patents.

  13. The superscript D refers to the DRAM market.

  14. We do not have to rely on aggregate sales data at the overall firm level, which are often taken from firms’ financial statements. These usually result in a broad definition of product markets, which can be problematic in our case.

  15. Note that the number of firms in column \(N^{D}\) in a given year is explained by the net effect of entry and exit occurrences during that year and the number of firms from the previous year.

  16. Note that DRAM and flash memory chips are distinct with regard to fundamental data information storage capabilities, and they are not considered substitutes. Therefore, the chips serve different purposes and characterize separate product markets.

  17. A merger is defined as horizontal when the acquiring and target firms are both active in the same product or memory market.

  18. Given the highly disaggregate product market level on which we concentrate, we are able to consider a relatively large number of mergers.

  19. Gugler and Siebert (2007) have shown that this relationship is robust to any degree of product differentiation.

  20. To establish the same reference point of time for different groups of firms, \(t_{m}\) refers to the time period when a merger took place. The market shares of nonmerging firms refer to the same period when the merger event occurred.

  21. In order to facilitate the interpretation of the parameter estimates, we replace the log of the number of firms plus one with the number of firms. Robustness checks confirm that the transformation of the left-hand side variable does not alter the statistical and economic impact of the estimation results.

  22. Further information on autocorrelation and autoregressive processes is provided later.

  23. The information is published by the OECD and the Bureau of Labor Statistics. Monetary amounts are deflated to 1985 dollars, which is the initial year of our dataset.

  24. To control for industry marginal costs, we take advantage of an institutional feature of the DRAM industry. As mentioned in the industry description, the DRAM industry is characterized by learning-by-doing effects, which significantly reduce the unit cost of production. The industry learning effects are measured by \(\sum \nolimits _{s=1}^{t-1}Q^{D}_{s}\), where \(Q^{D}_{s}\) represents the DRAM industry output in period s. The industry marginal costs is proxies by using the inverse of industry-wide learning-by-doing effects.

  25. The research and development expenses and the interest rates used are as published by the OECD and the Bureau of Labor Statistics.

  26. As mentioned earlier, we use U.S. patent information procured from the U.S. Patent and Trademark Office. The concentration on U.S. patents is appropriate in our case since U.S. and non-U.S.-based firms frequently file for patents in the U.S.

  27. The formulation of a dummy variable is appropriate in our context since usually no more than one merger occurs per quarter.

  28. For robustness reasons, we also evaluate a third-year post-merger impact.

  29. The superscript Fl refer to the flash market.

  30. We will conduct robustness checks with regard to firm heterogeneities later.

  31. Note that we lagged the merger variable from four to 12 periods, which further diminishes any potential contemporaneous correlation issue with the industry-wide shock.

  32. The assumption that firms set quantities is useful and common practice for the semiconductor industry. It is also consistent with other studies in the engineering, management, and economics areas.

  33. We employ the assumption that firms are symmetric in c, which is consistent with standard entry models that concentrate primarily on the equilibrium number of firms. Later, we perform robustness checks and allow for firm heterogeneity.

  34. Note that we use symmetry in F across firms to be able to derive the equilibrium number of firms. This type of equilibrium is satisfied by many models of competition in industrial organization.

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Acknowledgements

I would like to thank Dennis Carlton, Sebastian Linde, Stephen Martin, Sam Peltzman, Susana Restrepo, Lars-Hendrik Roeller, Lawrence J. White, and seminar participants for their helpful discussions and valuable suggestions. All errors are my own.

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Correspondence to Ralph B. Siebert.

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Appendix: Theoretical Motivation

Appendix: Theoretical Motivation

We consider a simple oligopoly framework that is characterized by free entry to derive the equilibrium number of firms. The inverse demand is given by \(P(Q)=a-bQ\), where: P is price; Q is market output; a embodies the effects of all factors other than quantity that affect price (we refer to this as “market size”); and b is the slope of the inverse demand: \(P^{\prime }(Q)<0\). A firm \(i=1,\ldots ,N\) faces a constant unit cost or marginal cost c and a cost F that is independent of output.

We consider a simple two-stage game in which firms are profit-maximizers: In the first stage, firms decide to enter a market. A firm operates in the market if its profit covers the cost F such that:

$$\pi _{i}= (P(Q) -c_{i}) q_{i} - F_{i} \ge 0.$$

In the second stage, firms simultaneously determine their output.Footnote 32 Taking the first-order condition with respect to each firm’s output, using symmetry, and solving for a firm’s equilibrium output, we obtain:Footnote 33

$$\begin{aligned} q=\frac{(a-c)}{b(N+1)}. \end{aligned}$$
(7)

In equilibrium, a firm produces more output if: the market size increases; marginal costs decrease; and/or the inverse demand becomes more elastic. Importantly, the model shows that a larger number of firms increases industry output and competition, and the larger number of firms reduces firm-level output, profits, and price. Since profits decline in the number of firms, the number of firms is constrained.

Turning to the first stage, using symmetry in setup costs and solving for the equilibrium number of firms N, we obtain:Footnote 34

$$\begin{aligned} N = \frac{(a - c)}{\sqrt{bF}}-1. \end{aligned}$$
(8)

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Siebert, R.B. Estimating Differential Dynamic Merger Effects on Market Structure and Entry in Related Markets. Rev Ind Organ 55, 431–458 (2019). https://doi.org/10.1007/s11151-019-09709-2

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