The economic performance of foreign controlled firms in Italy: a comparison between industrial and financial investors
DOI:
https://doi.org/10.71014/sieds.v80i1.574Keywords:
Foreign affiliates, international funds, MNEs, Labour productivityAbstract
It is well known from the theoretical and applied economic literature on industrial economics and international business that foreign control positively affects the economic performance of enterprises. This is motivated by the presence of a technological and managerial advantage that the multinational enterprise possesses, as an industrial investor, over domestic companies. On the other hand, the distinction between foreign direct investments and portfolio investments is consolidated both in official statistics and applied analysis as a factor that that discriminates between industrial from financial investment.
The growing relevance of foreign direct investments finalised to the control of resident companies and led by international financial investors, such as international investment funds and other types of institutional investors, calls into question this traditional approach, since this type of investor, although making acquisitions or greenfield investments with a majority stake, is classified as a financial and not an industrial operator. As a result, the presence of a positive effect on economic performance of companies under the control of an international investment is not yet clearly defined in the literature.
The aim of this work is to empirically test the presence of this effect – statistical significance, magnitude and direction – by using an innovative micro-level dataset in order to support further empirical and theoretical analyses in this field. In particular, the micro-level dataset is derived from the survey on foreign-controlled companies in Italy carried out by Istat, with respect to which financial investors are identified as a subset of foreign investors by manual profiling. The statistical model used is regression with robust estimators applied to this cross-section of micro data.
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