Girardi, Gherardo Gino Giuseppe
(2004)
The positive effect of entry of rivals on incumbents' profits: The see-saw effect.
PhD thesis, London School of Economics and Political Science.
Abstract
The thesis is a theoretical study of different mechanisms by which an increase in the number of rival firms leads to an increase in profits of an incumbent. Consequently, an incumbent may find it profitable to invite rivals, as is sometimes observed, for example in the semiconductor industry. Chapter 2: We expand the work by Farrell and Gallini (1988), in which a monopoly invites rivals to commit in period1 to low prices in period 2. Instead of assuming Bertrand competition as Farrell and Gallini do, we assume Cournot competition, and find the optimal number of rivals from an incumbent's point of view. Furthermore, the incumbent may invite rivals to enter already in period 1 so as to 'share' any losses incurred in the first period of production. Chapter 3: We propose a new mechanism by which an incumbent firm may want to invite rivals, based on the existence of capacity constraints, which we model as decreasing returns to scale. An incumbent may attract rivals in period 2 to increase consumer surplus in the same period above the level which it finds cost-effective to achieve on its own, enabling consumers to tolerate a higher price in period 1. Chapter 4: A multinational which trains workers may enjoy higher profits when more of its workers are poached by rival firms if it is compensated by a sufficiently lower wage during training. More workers are poached when there are more non-training firms and when training is more general. The result depends on the assumption of decreasing returns to scale, so that an increase in the number of poaching firms, or training that is more general, expands worker surplus beyond the level that the multinational could achieve on its own. The multinational can then pay trainees a lower wage.
Actions (login required)
 |
Record administration - authorised staff only |
Download statistics
Download statistics