Firm size, market conditions and takeover likelihood - Tunyi Tunyi Abongeh (Review of Accounting and Finance, 2019)
Purpose: The firm size hypothesis – takeover likelihood (TALI) decreases with target firm size (SIZE) – has enjoyed little traction in the TALI modelling literature; hence, this paper aims to redevelop this hypothesis while taking account of prevailing market conditions – capital liquidity and market performance. Design/methodology/approach: The study uses a logit modelling framework to model TALI. Model performance is assessed using receiver operating characteristic (ROC) curve analysis. The empirical analysis is based on a UK sample of 34,661 firm-year observations drawn from 3,105 firms and 1,396 M&A deals over a 30-year period (1987-2016). Findings: While acquirers generally seek smaller targets because of transaction cost constraints, the paper shows that the documented negative relation between SIZE and TALI arises from sampling bias. Over a full sample, mid-sized firms are most at risk of takeovers. Additionally, market conditions moderate the SIZE–TALI relationship, with acquirers more inclined to pursue comparatively larger targets when financing costs are low and market growth or sentiment is high. The results are generally robust to endogeneity. Research limitations/implications: Sample truncation on the basis of SIZE leads to empirical misspecification of the TALI–SIZE relation. In an unbiased sample, an inverse U-shaped specification between TALI and SIZE sufficiently models the underlying relation and leads to improvements in the predictive ability of TALI models. Originality/value: This study advances a new firm size hypothesis which is consistent with classic M&A theories. The study also evidences market conditions as a moderator of the acquirer’s choice of target SIZE. A new model specification which recognises the non-linear relation between TALI and SIZE and accounts for the moderating effect of market conditions on the SIZE-TALI relationship leads to improvements in the performance of TALI prediction models.