Oscar Diego JARA RAMIREZ will defend his thesis on Monday, July 1st at 11:00 am, Auditorium 4 & by ZOOM
Title: "Essays in Empirical Industrial Organization"
Supervisors: Mathias REYNAERT & Isis DURRMEYER
To attend the conference, please contact the secretariat Christelle Fotso Tatchum
Memberships are:
- Mathias REYNAERT : Professor in Economics, TSE, University of Toulouse Capitole, Supervisor
- Isis DURRMEYER : Professor in Economics, TSE, University of Toulouse Capitole, Co-supervisor
- Pierre DUBOIS : Professor in Economics, TSE, University of Toulouse Capitole, Président
- Claire CHAMBOLLE : Senior Researcher, INRAE/Paris Saclay Rapporteure
- Joel STIEBALE :Associate professor in Economics, DICE/Heinrich Heine University Rapporteur
- Morten SAETHRE : Associate professor in Economics, Norwegian School of Economics Examinateur
Abstract
The first two chapters focus on understanding the effect of market structure on equilibrium outputs like prices or product offerings in the markets of energy drink distribution and mobile telecommunications. The third chapter explores methodologies for measuring the effects of leniency programs on cartel formation.
In the first chapter, I develop a new structural model of bargaining to evaluate the impact on prices and welfare of a consolidation of upstream firms operating in different geographic markets. The model considers that upstream and downstream firms negotiate for market-specific wholesale prices for many markets simultaneously, instead of market by market independently. I call these two ways of bargaining multi and single market bargaining. A consolidation of upstream firms present in different geographic markets affects the negotiation process and, through multimarket bargaining (MMB), impacts downstream prices. I apply this model to a consolidation of regional distributors in the U.S. energy drinks market, where one of the leading brands transitioned from having two national distributors to only one. National retailers with stores in both affected and unaffected areas began negotiating with one distributor instead of two. The theoretical model predicts that under MMB, retail prices change in every region, not just those affected by the consolidation. Empirical evidence supports this prediction, showing that national retailers reduced their prices by 1.5% in regions directly affected by the consolidation and by 1.6% in indirectly affected regions. The structural model further reveals that when the regional distributors expand into new regions, their bargaining position relative to national retailers weakens. This results in better deals for national retailers, effectively lowering retail prices.
In the second chapter, jointly with Nicolas Martinez, we study the effects of firm entry and technological progress on product offerings and pricing in the Peruvian mobile telecommunications market. The chapter examines how the entry of two new firms and the introduction of 4G technology affected a market previously dominated by two incumbents. After the new firms entered the market, the incumbents began offering more plans with higher variation in data allowances. This change coincided with the introduction of 4G connectivity, which significantly altered consumers' valuation of data and thus demand patterns. Reduced form evidence shows that prices for prepaid tariffs decreased significantly, while postpaid plan prices remained constant or slightly increased. We then use a structural model of supply and demand to analyze the joint effects of competition and technological progress. The demand estimation shows a significant increase in consumer willingness to pay for data after the introduction of 4G, highlighting the crucial role of technological change. The findings indicate that both competition and technological advancements drive changes in market outcomes, with technological progress leading to higher consumer valuations for data and more varied product offerings from incumbents.
The third chapter addresses the challenges of prosecuting cartels due to their secretive nature and examines the effectiveness of leniency programs in detecting and deterring cartels. Leniency programs incentivize cartel members to come forward with evidence, aiming to destabilize existing cartels and deter the formation of new ones. However, measuring the efficacy of these programs is challenging because the full population of cartels is not observed. I propose using Hidden Markov Models (HMM) to estimate the effects of leniency programs, as HMMs can identify unobservable latent states by analyzing observable data that indirectly indicate underlying processes. This chapter emphasizes the importance of measuring the effects of leniency programs and that other policy changes should not disrupt their workings.
