Predicting mergers and acquisitions in the food industry

Two logit models are estimated to explain merger and acquisition (M&A) activities in US food manufacturing using firm level data for public firms: a “target model” predicting the likelihood of a firm being targeted for M&A and a “takeover model” predicting the likelihood of a targeted firm being taken over. Target model results suggest the importance of firm liquidity, debt/leverage, profitability, growth in sales, stock earnings capacity, percentage of common stocks traded in the stock market, and market-to-book ratio. Activity or turnover ratio, firm size, and price–earnings ratio were not statistically significant. Takeover model results suggest the importance of degree of officer control, attitude surrounding the transaction, number of prior bids, existence of litigation during negotiations, and involvement of the bidder and/or target in other takeovers during negotiations. With predictive accuracy of 74.5 and 62.9%, respectively, these models suggest the systematic nature of M&A activities.