nep-com New Economics Papers
on Industrial Competition
Issue of 2014‒10‒17
eight papers chosen by
Russell Pittman
United States Department of Justice

  1. Horizontal Mergers in the Presence of Capacity Constraints By Zhiqi Chen; Gang Li
  2. Application of the Proportionality-Calibrated AIDS Model to Predicting Potential Welfare Effects of Mergers between Fertilizer Sellers as Part of the Turkish Privatization Program By DALKIR Serdar; KALKAN Ekrem
  3. Consumer Learning on Social Networks and Retailer Digital Platform Strategies Access By Zheyin (Jane) Gu; Yunchuan Liu
  4. Quality Provision in the Presence of a Biased Intermediary By Alexandre de Cornière; Greg Taylor
  5. An Empirical Analysis of Search Costs and Price Dispersion By Avi Weiss; Joshua Sherman
  6. Is More Less? Propensity to diversify via M&A and market reactions By Abigail S. Hornstein; Zachary Nguyen
  7. A Reassessment of Competition in the Credit Card Market by Introducing Liquidity Cost Measures: Evidence from an Emerging Economy By Ahmet AYSAN; G. GULSUN AKIN; Denada BORICI; Levent YILDIRAN
  8. Competition in the Provision of Local Public Goods By Alexandra Petermann Reifschneider

  1. By: Zhiqi Chen (Department of Economics, Carleton University); Gang Li (School of Economics, Nanjing University)
    Abstract: We analyze the effects of a merger between two competitors in a Bertrand-Edgeworth model. The merger has no effect on equilibrium prices if a pure strategy equilibrium prevails both before and after the merger. Otherwise, the merger leads to higher prices. In the case where a mixed strategy equilibrium prevails before and after the merger, for example, the support of the price distributions shifts rightward after the merger and the post-merger price distribution of each firm stochastically dominates its pre-merger counterpart. The pre-merger capacity level of each firm plays a crucial role in determining the effects of the merger.
    Keywords: Merger, capacity constraints, Bertrand-Edgeworth model
    JEL: L13 L40
  2. By: DALKIR Serdar; KALKAN Ekrem
  3. By: Zheyin (Jane) Gu (University of Connecticut, School of Business, Marketing Department, 2100 Hillside Rd, Unit 1041, Storrs, CT, 06269.); Yunchuan Liu (University of Illinois, Urbana-Champaign, 415 Wohlers Hall, 1206 South Sixth Street, Champaign, IL, 61820, (217) 244-2749)
    Abstract: We model consumer social networks as information collection media and examine two major issues: first, how consumers construct product fit signals based on product feedbacks collected from their social connections to assist with their purchase decisions, and second, how a retailer can benefit from setting up a digital platform and helping consumers collect more product feedbacks on social networks. Our analysis identifies two important structure features of consumer social networks that affect the outcome of consumer social learning: social group inter-connectivity and overall social connectivity. In particular, when the consumer social network is not well-connected, characterized by low social group inter-connectivity and low overall social connectivity, with more product feedbacks collected on social networks consumers are more likely to form informative prior beliefs about which product has a good fit. In contrast, when the consumer social network is well-connected, characterized by either high social group inter-connectivity or high overall social connectivity, more product feedbacks collected on social networks are more likely to constitute uninformative product fit signals and leave consumers uncertain about which product has a good fit. Furthermore, our analysis shows that a retailer's incentive to set up a digital platform and help consumers collect more product feedbacks on social networks depends on the supplier market structure as well as the structure of consumer social networks. In particular, a big retailer that carries horizontally differentiated products offered by competing manufacturers has incentive to facilitate consumer social learning on well-connected social networks and when without retailer assistance consumers still collect product feedbacks from a good number of social connections. The big retailer's activity of facilitating consumer social learning can also enhance total channel surplus. In contrast, a small retailer that carries product(s) offered by a single manufacturer has incentive to facilitate consumer social learning only on social networks that are not well-connected and when without retailer assistance consumers only collect a small number of social feedbacks. And the total channel efficiency suffers when the small retailer withholds from facilitating consumer social learning. Our result highlights the unique motive of big retailers to embrace the digital era when internet, mobile networks, and social media have profoundly changed consumers' shopping habits as well as the unique contribution big retailers bring in channel efficiency through their efforts of facilitating consumer social learning.
    Keywords: Consumer Social Learning, Social Networks, Retailing, Game Theory
    JEL: M31
    Date: 2014–09
  4. By: Alexandre de Cornière (Department of Economics and Nuffield College, University of Oxford, 1 New Road, Oxford OX1 1NF); Greg Taylor (Oxford Internet Institute, University of Oxford, 1 St Giles, Oxford OX1 3JS)
    Abstract: In many industries, consumers rely on recommendations by an intermediary when choosing between competing products. In this paper, we look at how the existence of contracts between firms and intermediaries affects the quality of the advice received by consumers, and firms' incentives to invest in improving the quality of their products. We consider a model with one intermediary and two firms who decide how much to invest. Under a variety of contractual environments (vertical integration, ex post endorsement) we show that, even though the intermediary tends to endorse the best firm, contractual endorsement distorts firms' incentives to invest. Quality can then decrease or increase compared to an objective benchmark. We contrast our approach to a setup with fixed qualities and endogenous prices, under which contractual endorsement hurts consumers.
    Keywords: intermediary, quality, bias
    JEL: L1 L4 L86
    Date: 2014–09
  5. By: Avi Weiss (Bar-Ilan University); Joshua Sherman
    Abstract: We exploit cross-sectional and temporal differences in search intensity in order to examine the relationship between search costs and price dispersion using a hand-collected panel data set from Jerusalem’s Shuk Mahane Yehuda outdoor market. We present empirical evidence that price dispersion increases with the cost of search using several different measures of price dispersion, however, our interpretation of this finding is sensitive to the search proxy in question. We also address several acute difficulties facing empiricists seeking to test theoretical price-dispersion models in which consumers are heterogeneous in their search behavior.
    JEL: L11 L13
    Date: 2014–09
  6. By: Abigail S. Hornstein (Department of Economics, Wesleyan University); Zachary Nguyen (Charles River Associates)
    Abstract: Mergers and acquisitions (M&As) could lead to a firm diversifying into new industries, and the impact of this may be related to the firm's prior diversification. Using a panel of 1030 M&A transactions from 2000 to 2010, we find that previously diversified firms are more likely to pursue industrially diversifying M&As. Both previous and contemporary diversification measures are not associated with the firm's cumulative abnormal returns (CARs) at time of announcement but have a lasting effect on various performance measures up to two years later. We find evidence supporting both a diversification discount and premium, which can be predicted by the sign of the CAR at the time of announcement. This suggests that while diversification is necessary to explain firm value, it is not sufficient.
    Keywords: M&A, diversification, event study, operating performance
    JEL: G34 G32
    Date: 2014–03
  7. By: Ahmet AYSAN; G. GULSUN AKIN; Denada BORICI; Levent YILDIRAN
  8. By: Alexandra Petermann Reifschneider

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