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Core competencies, matching and the structure of foreign direct investment
Author(s) -
Díez Federico J.,
Spearot Alan C.
Publication year - 2014
Publication title -
canadian journal of economics/revue canadienne d'économique
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 69
eISSN - 1540-5982
pISSN - 0008-4085
DOI - 10.1111/caje.12097
Subject(s) - multinational corporation , foreign direct investment , matching (statistics) , business , greenfield project , industrial organization , investment (military) , core competency , core (optical fiber) , space (punctuation) , fixed cost , revenue , microeconomics , economics , marketing , finance , computer science , telecommunications , statistics , mathematics , politics , political science , law , macroeconomics , operating system
We develop a matching model of foreign direct investment to study how multinational firms choose between greenfield investment, acquisitions and joint ownership. Firms must invest in a continuum of tasks to bring a product to market. Each firm possesses a core competency in the task space, but the firms are otherwise identical. For acquisitions and joint ownership, a multinational enterprise (MNE) must match with a local partner that may provide complementary expertise within the task space. However, under joint ownership, investment in tasks is shared by multiple owners and, hence, is subject to a holdup problem that varies with contract intensity. In equilibrium, ex ante identical multinationals enter the local matching market, and, ex post, three different types of heterogeneous firms arise. Specifically, the worst matches are forgone and the MNEs invest greenfield; the middle matches operate under joint ownership; and the best matches integrate via full acquisition. We link the firm‐level model to cross‐country and industry predictions and find that a greater share of full acquisitions occur between more proximate markets, in hosts with greater revenue potential and within contract‐intensive industries. Using data on partial and full acquisitions across industries and countries, we find robust support for these predictions.