Structural estimation of takeover contests

Sacchetto, S (2010) Structural estimation of takeover contests. Doctoral thesis, University of London: London Business School.

Abstract

The main focus of this dissertation is on the strategic interactions between potential buyers and target companies in takeovers. The first chapter provides an empirical analysis of two possible sources of high takeover premia: preemptive bidding and target resistance. I study an auction model of takeover contests with costly sequential entry by bidders. The parameters of the model are estimated using a structural approach for a sample of US target firms between 1988 and 2006. The results show that takeover premia are mainly determined by target resistance rather than preemptive bidding. In the second chapter, I formulate an alternative model of target resistance in takeover battles and develop a structural estimation procedure based on Maximum Simulated Likelihood. The chapter also discusses a methodological extension to the empirical framework aimed at explaining the sources of bidder heterogeneity. The third chapter studies the private takeover process that precedes the first public bid for the target. Using a hand-collected dataset, I identify the initiator of the takeover contest; classify the takeover process as an auction or a negotiation, depending on the number of participating bidders; and study the choice of the sales procedure and the determinants of o{THORN}er premia. I find that bidder-initiated contests are associated with a lower probability that an auction among bidders takes place, and a higher price offered to the target. In the fourth chapter, I formulate a theoretical framework to analyze the impact of stock-based compensation on managerial decisions, such as taking over another company. I show that managers may disregard private information about profitable investment opportunities in order to cater to the opinion of investors in the stock market and increase the share price in the short term. Using data on CEO compensation, I provide evidence on the association between stock price-based compensation and firm performance.