Quantitative Techniques for Competition and Antitrust Analysis_17 ppt

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Quantitative Techniques for Competition and Antitrust Analysis_17 ppt

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548 10. Quantitative Assessment of Vertical Restraints and Integration if they believe that once they’ve built up the product some downtown store will take the business away by advertising it at a lower price. We cannot afford to become a target for stores which base their promotional appeal on someone else’s name, the best known name they can lay their hands on. 41 Clearly, Corning’s view was that RPM in this case was geared toward reducing horizontal externalities between retailers of the form that led to bad outcomes for the manufacturer. In particular, the incentive to free-ride on rivals’ provision of service combines poorly with the lack of incentive to take into account the effects on rival’s sales if I undercut their prices.Absent theservice dimension, the horizontal pricing externality between competitors is the main force we think of as driving good outcomes for consumers. On the other hand, with the service dimension added, providing a second horizontal externality between retailers, the net effects of the externalities on overall welfare are less clear cut. Finally, the manufacturer, Corning, will clearly be affected by such decisions being made downstream so there are important vertical externalities here. The timeline of events was as follows. On October 8, 1971, the FTC announced a “price fixing” challenge to Corning’s RPM policy. On January 16, 1973 the FTC issued a press release saying that an administrative law judge (ALJ), the FTC’s hearing examiner, had ruled in Corning’s favor on all counts. This was subsequently appealed by the FTC complaint counsel. On June 17, 1973 the full FTC announced their appeal decision, which reversed the administrative law judge’s initial decision on the central RPM issue. On January 29, 1975, the U.S. Court of Appeals upheld the FTC decision. Ippolito and Overstreet argue that stock market evidence may have the power to distinguish between a number of basic hypotheses about the role of RPM in this market. (i) If the resale price maintenance was a device to cartelize the market at the retail level, a prohibition of RPM would increase the profits of all glass houseware producers. (ii) An increasein retail competition (downstream) would increase the total profits of all manufacturers (upstream). If on the other hand RPM was an attempt to cartelize the industry at the manufacturer level, the prohibition of the practice would cause profits for all manufacturers to decrease. (iii) Finally, if, as Corning claimed, the practice was only trying to elicit services from retailers, the end of RPM would hurt the profits of Corning as well as that of competitors that were using RPM. It would either have a zero or a positive effect on competitors that were not using RPM. This was the case of Anchor Hocking, Corning’s closest competitor. 41 Quoted in Ippolito and Overstreet (1996, p. 291). 10.2. Measuring the Effect of Vertical Restraints 549 Table 10.6. Predicted effect of eliminating Corning’s use of RPM. Economic theory Corning Anchor Hocking Other competitors Dealer collusion/ anticompetitive pricing C 0orC 0orC Manufacturer collusion/ anticompetitive pricing   Principal–agent theories  0orCif using RPM C if not using RPM Source: Ippolito and Overstreet (1996). The table below shows Ippolito and Overstreet’s predicted effects of a successful FTC case on stock values under alternative theories of resale price maintenance. In reality, the prediction of the elimination of RPM on competitors in the case where RPM induces promotional and sales effort is not so obvious. For example, it could be that promotional efforts to promote Corning glassware increase the total demand for glassware positively, affecting Anchor Hocking’s sales in the process. In such cases, where the marginal consumer reacting to the promotion is more the person who does not buy glassware as opposed to the person who is already a glassware customer from another brand, Corning’s close competitors might be hurt by the end of the practice and the promotional effort it elicited. The effect of an end to RPM on competitors can therefore be ambiguous depending on the distribution of consumer preferences and the relative importance and effect of the price and advertisement efforts. Finally, if Corning andAnchor Hocking are branded substitutes, the decrease in the price of one of them afterthe elimination of RPM may trigger the decrease of the price of the other since the two goods will be strategic complements. This is another reason why we might in truth expect to see close competitors be hurt by the elimination of RPM. Such concerns around the identification of harm (or otherwise) from RPM are serious and it is not immediately clear that the identification strategy always (or even often) works to tell apart a use of RPM that serves as a manufacturer’s collusive mechanism from the use of RPM that has the simple purpose of increasing retailer’s sales effort. On the other hand, as will be clear from our discussion at numerous points in this book, unambiguous identification results are rare and generally empir- ical exercises can be useful to undertake even if in order to place evidential weight on the results they need to be complemented with other pieces of evidence. Here, for example, we note that the extent of advertising spillovers is quantifiable and so that explanation of the results can be tested or at least a qualitative judgement made. Ippolito and Overstreet (1996) estimate whether firms had an abnormal return around the day of events that ruled for or against resale price maintenance. They run 550 10. Quantitative Assessment of Vertical Restraints and Integration the following regression: R it D a i C b i R mt C c i D t C e it ; where a i is a firm-specific effect, R it is the percentage return of firm i on day t, R mt is the percentage return of a value-weighted portfolio of the New York Stock Exchange (NYSE) and American Stock Exchange (ASE) stocks on day t, D t is a dummy variable that takes the value 1 for the days in the event window and 0 otherwise, and e it is a random error term for firm i on day t. The event window covers three to four days before and after the actual event. The motivation for this equation can be found in the capital asset pricing models (CAPMs) described in most finance books and we do not reiterate that here (see, for example, Campbell et al. 1997). Note that the coefficient c i is the average per day of abnormal returns. With this specification, cumulative abnormal returns are calculated using CAR t D c i Days in event window t : The regression results on the effect of the events on the value of the Corning stock are presented in table 10.7. There is a negative effect on the valuation of the com- pany after the FTC’s announcement of the investigation. The interim reversal had a very small positive effect. The FTC reversal and upholding of the case had another negative effect on the firm valuation and the decision of the Seventh Circuit Appeals Court had no particular effect on the stock prices. The cumulative abnormal return is a negative 12% in the five days before the announcement of the FTC investigation. Trading volumes presented in the paper do show abnormal activity right before the FTC announcement which, in the absence of other news at the time, appears to be highly suggestive that some traders were operating basedon insideinformation. In the case of the second event, the CAR show a positive effect on the benefits of Corning, which the authors report is particularly marked after the decision to dismiss the charges was published in the Wall Street Journal. The event study using Corning stock data indicates that investors in Corning value RPM as having a positive impact on the profits of Corning. However, such an observationis consistent witheither RPM acting tofacilitate downstreamprice fixing (reduction in intrabrand competition) or simply solving the free-rider problem in service provision. In order to attempt to discriminate between these stories we need to (at least) look at what happens to the expected profits of competitors. A positive effect of the demise of RPM on Corning’s competitors could be consistent with the principal–agent theory. On the other hand, a negative effect of the elimination of RPM could be consistent with either a price-fixing world (or perhaps a situation in which competitors derive positive externalities from Corning’s investment in services and promotion). The results (reported in table 10.8) indicate that RPM by Corning was perceived to also favor its nearest competitor Anchor Hocking. The FTC reversal of the ALJ 10.2. Measuring the Effect of Vertical Restraints 551 Table 10.7. Changes in Corning stock value at events in FTC case. Cumulative abnormal return 1-day 3-day 5-day 10-day 1. FTC announces complaint: a Press release B 0.016 0.049  0.122  0.160  (October 8, 1971) (1.17) (2.09) (4.13) (3.74) 2. ALJ dismisses case: Decision filed A 0.032  0.018 0.012 0.068  (December 27, 1972) (2.68) (0.86) (0.42) (1.73) Wall Street Journal story B 0.001 0.006 0.034 0.064 (January 17, 1973) b (0.08) (0.29) (1.23) (1.62) 3. FTC reverses ALJ: Decision filed B 0.014 0.017 0.055  0.110  (June 5, 1973) (1.05) (0.776) (1.86) (2.62) Wall Street Journal story B 0.003 0.015 0.008 0.014 (June 18, 1973) b (0.25) (0.64) (0.26) (0.31) One day after Journal 0.023  Journal story (1.74) 4. Seventh Circuit upholds FTC: Decision date A 0.021 0.015 0.042 0.021 (January 29, 1975) c (0.79) (0.32) 0.72 (0.25) Notes: t-statisticsarein parentheses. FTC, Federal Trade Commission;ALJ,Administrative Law Judge. “B” indicates that the window for the cumulative average return begins the required number of days before the event and ends with the event day. “A” indicates windows beginning at the event day with the required number of days after the event. a The Washington Star carried the story on Friday afternoon, and the Wall Street Journal on Monday, October 11. b Federal Trade Commission press releases were issued on theday before theWall Street Journal stories. c There was no Wall Street Journal story for this event.  Significant at the 90% level of confidence.  Significant at the 95% level of confidence. Source: Ippolito and Overstreet (1996). decision in favor of Corning (i.e., a finding against RPM) is associated with a 7.6% decline in returns for Anchor Hocking. Such a result is inconsistent with Corning’s RPM only benefiting Corning. To help tell apart the potential explana- tions for this finding, Ippolito and Overstreet present another interesting piece of evidence. Specifically, they show that after the Appeals Court decision in 1975 declaring Corning’s RPM activities illegal, Corning sharply increased its adver- tising expenses. That response is consistent with a story where RPM was serving to provide demand-enhancing services that were replaced with advertisement fol- lowing the judgment. Rather strikingly, Anchor Hocking’s advertisement activities remained largely unchanged. 552 10. Quantitative Assessment of Vertical Restraints and Integration Table 10.8. Results of the event study regression on Anchor Hocking stock. Cumulative abnormal return 1-day 3-day 5-day 10-day 1. FTC announces complaint: a Press release B 0.001 0.033 0.032 0.077 (October 8, 1971) (0.09) (1.32) (0.99) (1.64) 2. ALJ dismisses case: Decision filed A 0.015 0.03 0.041 0.063 (December 27, 1972) (1.08) (1.24) (1.32) (1.41) Wall Street Journal story B 0.016 0.008 0.026 0.041 (January 17, 1973) b (1.16) (0.34) (0.85) (0.92) 3. FTC reverses ALJ: Decision filed B 0.013 0.075  0.076  0.053 (June 5, 1973) (0.76) (2.62) (2.02) (0.99) Wall Street Journal story B 0.007 0.004 0.020 0.042 (June 18, 1973) (0.41) (0.12) (0.49) (0.72) One day after Wall Street 0.012 Journal story (0.64) 4. Seventh Circuit upholds FTC b : Decision date A 0.037 0.023 0.010 0.071 (January 29, 1975) (1.69)  (0.60) 0.19 (1.01) Notes: t-statistics are in parentheses. FTC, Federal Trade Commission;ALJ,Administrative Law Judge. “B” indicates that the window for the cumulative average return begins the required number of days before the event and ends with the event day. “A” indicates windows beginning at the event day with the required number of days after the event. a Except as reported for the Seventh Circuit Decision, no other events related to Anchor Hocking were reported in the Wall Street Journal or the New York Times near the case events. b On February 28, 1975, Anchor Hocking agreed to acquire Amerock Corp., which was reported by the Wall Street Journal on March 5. This event may confound the interpretation of the Seventh Circuit Appeals decision.  Significant at the 90% level of confidence.  Significant at the 95% level of confidence. Source: Ippolito and Overstreet (1996). 10.2.6 Discussion This chapter has examined a relatively small number of recent or classic pieces of empirical work in the arena of vertical restraints and vertical integration. While our review has necessarily been a focused one, the literature on vertical restraints is neither large nor comprehensive at this point. Our aim has been to provide enough substance and detail about a small number of papers to help investigators move from these empirical examples to both the rest of the literature and perhaps more importantly toward designing and undertaking such analyses for bespoke projects. 10.3. Conclusions 553 Doing so is by no means an easy task. We hope that the material in this chapter (i) helps the reader to understand the kinds of approaches will be useful in evaluating vertical restrictions, (ii) provides sufficient introduction to encourage case handlers that there are helpful contributions available from the academic and case literature, and (iii) that there is certainly some exciting research in this area yet to come (e.g., around empirical effects of vertical integration on service provision or the appropriate approach to resale price maintenance, exclusive territories, or exclusive dealing). Lafontaine and Slade (2005) provide a complementary review of the current empirical literature on vertical restraints. While we have focused on the empirical tools that have proven useful in a range of papers, they provide an important contri- bution by pulling together the limited evidence currently available in the literature. They argue that, at least in industries where academics have undertaken work— mostly the beer, gasoline, and auto-distribution industries—the empirical evidence from the academic literature suggests that vertical restraints are generally associated with positive net welfare effects. 42 Thus, the balance of work on vertical restraints and mergers does not suggest a general policy stance that is hostile toward them. At the same time, agencies will want to remain vigilant since we now have coherent economic theory suggesting that on occasion vertical restraints and vertical mergers may be welfare reducing. Competition policy conferences across the world, like Lafontaine and Slade, have in recent years noted that there are currently rather a small number of such studies, and that there is no doubt that there remains a great deal that we have yet to learn. In terms of the balance of evidence (and experience) we note somewhat of a difference between past antitrust intervention, where, in the round, agencies appear to have found problems with at least some vertical mergers and restraints and the message from Lafontaine and Slade summarizing the available academic literature. Wherever the debate eventually rests, we hope that the material in this chapter encourages more and better empirical work, some of which should occur within the context of casework or ex post reviews. 10.3 Conclusions  The effect of vertical restraints on the market may be captured using reduced- form regressions whenever there is enough relevant variation in the data to identify the effect. Natural experiments such as the prohibition of a practice can also provide good opportunities for useful regression analysis.  Structural estimation allows us to model a world without the practice even if that world does not currently exist, much as we do when estimating the 42 For a rare and very welcome examination of the relationship between vertical integration and productivity, see also Syverson and Hortascu (2007). 554 10. Quantitative Assessment of Vertical Restraints and Integration effect of anticipated horizontal mergers. Exactly the same caveats regarding the validity of the structural assumptions and the need for reality checks apply to the analysis of vertical mergers as those which apply to horizontal mergers. However, here generally the caseworker has far more work to do (multiple market definitions, someefficiency analysis (e.g.,the likely extent of reduction in double marginalization), as well as an evaluation of the effectiveness of giving a rival market power on driving sales to your downstream division). As a result, robustness checks in analysis may well need to be even more extensive.  Event studies focusing on the time when an investigation of a practice is announced may shed light on the markets’ appreciation of the profitability of the practice. Such studies may under specific assumptions be sufficient to discriminate between potential pro- and anticompetitive motivations for vertical restraints.  The theory of vertical restraints and/or vertical mergers suggests that there are many efficiency-based reasons to vertically integrate or use vertical restraints. Namely, such restrictions may decrease transaction costs or solve vertical or horizontal externality problems such as those caused by double marginaliza- tion or vertical service externalities or free-riding in the provision of service by retailers.  In many instances, different types of vertical restraints can be used to solve externality problems. Economic theory does not typically provide unambigu- ous predictions about whether a given vertical practice is likely to be good or bad for consumer welfare. Predictions about the impact of vertical mergers on prices, for example, are fundamentally ambiguous whenever own costs fall (say, because of a decline in transactions costs or double marginalization) but the opportunity of, for instance, using full or partial foreclosure strategies means there is a potential for vertically integrated firms to “raise rivals’costs.” This is a direct contrast in particular to the theoretical prediction about the price effect of a horizontal merger between firms producing substitutes. In casework, the ambiguity means that sometimes both pro- and anticompetitive explanations are consistent with the available evidence on the effect of a given vertical restraint and agencies may need to undertake a considerable amount of work to tell apart the two stories. Conclusion Since competition policy is now largely “effects” based, it is vital that the competi- tion policy and economics communities continue to develop ways in which we can empirically evaluate the actual effect of potentially anticompetitive but also poten- tially desirable practices. Throughout this book, we have attempted to carefully examine both of the two main approaches to undertaking such empirical work in economics. Along the way, and equally importantly, we have tried to provide a clear statement of the basis for each of the approaches that emerges from economic theory. The first general method we have looked at involves the estimation of reduced- form regressions of equilibrium market outcomes on factors that determine those equilibrium outcomes including some indicator variable fora practiceof interest.We have generally argued that reduced-form approaches are ideally informed by some kind of experiment in the data that constitutes an appropriate “natural experiment” for the issue being studied. We noted that reduced-form approaches to estimating the impact of a practice, in the last chapter a vertical practice, on equilibrium outcomes generally requires being able to compare outcomes in a situation with and without the practice. In addition we must be sure that there are no systematic differences between the two samples that we are comparing except for the difference in the conduct that we are assessing, or at least as sure as we can be. The chances of being able to do so are best when we have a natural experiment which exogenously imposes or eliminates a conduct and also probably some form of local markets. The second general method we have looked at involved a structural approach, building explicit models of consumer and/or firm behavior. One great advantage of structural modeling is that it enables us to develop predictions for what might hap- pen in a world not yet observed. That is the very essence of policymaking. However, we have also noted that structural models will typically rely heavily on assumptions which must be sound and justifiable, at least as reasonable approximations to behav- ior in the world, in order for the results of any prediction exercise to be credible. We also emphasized throughout that the use of structural models can only go hand in hand with a process of “reality checking” and model testing in order to carefully evaluate and ultimately ideally verify the performance of the model being used. The bottom line on structural modeling is perhaps unsurprising: (1) if a model is a poor approximation of the world, it will probably provide a poor basis for making fore- casts, and (2) modeling the world is what economists can and should do and while models are always approximations, the reality is that in industrial organization the models have improved substantially over the last few decades. 556 Conclusion Which methodologyto use will be a matter ofjudgment bythe economist on a case team, ideallyinformed byher colleagues about such things as potentially appropriate natural experiments. The best method will greatly depend on the details of the case, the data available, and the question(s) which must be answered. Attempting to undertake a sound empirical exercise will often be informative even if analysts do not get so far as to build a sophisticated economic model. We often learn far more about an industry by examining data sets carefully than we would by listening to anecdotes from a variety of commentators on that industry. In terms of the variety of evidence we receive during investigations, cold hard numbers are attractive for competition authorities and probably many authorities do not currently do as much as they could to fully exploit the useful information available from market-, firm-, and consumer-level data. We hope this book will provide at least a small contribution to encourage agencies to do more. References Abrantes-Metz, R. M., L. Froeb, J. Geweke, and C. Taylor. 2006. A variance screen for collusion. International Journal of Industrial Organization 24:467–86. Abreu, D. 1986. Extremal equilibria ofoligopolistic supergames. Journal of Economic Theory 39:191–225. Abreu, D., D. 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Diagnosing foreclosure due to exclusive dealing.Working Paper, Stern School of Business at NYU. Aslanbeigui, N., and M. Naples. 1997. Scissors or horizon: neoclassical debates about returns to scale, costs, and long-run supply, 1926–1942. Southern Economic Journal 64:1926–42. Athey, S., and P. Haile. 2002. Identification of standard auction models. Econometrica 70: 107–40. Bailey, E. 1981. Contestability and the design of regulatory and antitrust policy. American Economic Review 71:179–83. 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(NYSE) and American Stock Exchange (ASE) stocks on day t, D t is a dummy variable that takes the value 1 for the days in the event window and 0 otherwise, and e it is a random error term for firm

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  • Title

  • Copyright

  • Contents

  • Preface

  • Acknowledgments

  • 1 The Determinants of Market Outcomes

    • 1.1 Demand Functions and Demand Elasticities

    • 1.2 Technological Determinants of Market Structure

    • 1.3 Competitive Environments: Perfect Competition, Oligopoly, and Monopoly

    • 1.4 Conclusions

    • 2 Econometrics Review

      • 2.1 Multiple Regression

      • 2.2 Identification of Causal Effects

      • 2.3 Best Practice in Econometric Exercises

      • 2.4 Conclusions

      • 2.5 Annex: Introduction to the Theory of Identification

      • 3 Estimation of Cost Functions

        • 3.1 Accounting and Economic Revenue, Costs, and Profits

        • 3.2 Estimation of Production and Cost Functions

        • 3.3 Alternative Approaches

        • 3.4 Costs and Market Structure

        • 3.5 Conclusions

        • 4 Market Definition

          • 4.1 Basic Concepts in Market Definition

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