In this paper, I investigate the influence of tax incentives on the financial structures of mergers and acquisitions (M&A) conducted by multinational entities (MNE). Previous research has already found evidence for tax avoidance by debt shifting. I analyze the importance of locating debt at holdings which own the operating firm. Placing debt at the level of the holding is more advantageous since it allows inter alia for debt financing up to the purchase price. Accordingly, by using firm-level data provided by the German Central Bank I show empirically that the probability that a firm is held by a holding in the same country increases with the tax rate in that country (though the effect is rather small). As a limitation, I find this effect only for a sample of all firms and no additional effect in case of M&As (denoted as M&A firms). Since this way of debt financing requires that interest payments of holdings are used to offset profits of the operating firms, I consolidate financial structures of holdings and the operating firms. I discuss theoretically and show with descriptive statistics that this consolidation – the major contribution of my paper – leads to a higher total debt ratio compared to the unconsolidated case. However, this effect can only be observed in particular for the subsample of those M&A firms which actually belong to such structures of holdings and operating firms and does not lead to an increase of the debt ratio in the sample of all M&A firms. Finally, I show that the tax sensitivity of external debt financing increases with the consolidation (though again with no additional effect in case of M&A firms). I conclude that those findings may be one explanation why previous studies have found relatively low effects of taxes on debt financing.

Harendt, Christoph (2018), Tax Influence on Financial Structures of M&As, ZEW Discussion Paper No. 18-004, Mannheim. Download


Corporate Taxation, Multinational Firms, Foreign Direct Investment, Capital structure, Mergers and acquisitions, Empirical Analysis, Firm-level data