Cross-border Mergers and Acquisitions in Terms of Quantile Regression

The aim of this contribution is proposal of bilateral quantile regression models of relationship between log of volume of M&As (the total value of cross-border assets obtained through mergers and acquisitions by the source country in the target country) and its previous investigated three continuous predictors. These three predictors are (1st) log of the product of the two GDPs at date t, which restrict the elasticity to be the same for country i and country j; (2nd) log of market capitalization to GDP ratio of acquirer and target sectors used there as indicator of stock market development; (3rd) log of bilateral geographical distance between the capital towns of source and target country. It is shown that classical normal linear model truly holds on two of these three relationships, first and third one. But, on the second case the application of quantile regression provides a better description of the investigate relationship than a simple normal model with constant variance.