Diversification Strategies and Firm Performance: A Sample Selection Approach

Santarelli, Enrico ; Tran, Hien Thu (2013) Diversification Strategies and Firm Performance: A Sample Selection Approach. Bologna: Dipartimento di Scienze economiche DSE, p. 33. DOI 10.6092/unibo/amsacta/3845. In: Quaderni - Working Paper DSE (896). ISSN 2282-6483.
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Abstract

This paper is based upon the assumption that firm profitability is determined by its degree of diversification which in turn is strongly related to the antecedent decision to carry out diversification activities. This calls for an empirical approach that permits the joint analysis of the three interrelated and consecutive stages of the overall diversification process: diversification decision, degree of diversification, and outcome of diversification. We apply parametric and semiparametric approaches to control for sample selection and endogeneity of diversification decision in both static and dynamic models. After controlling for industry fixed-effects, empirical evidence from firm-level data shows that diversification has a curvilinear effect on profitability: it improves firms’ profit up to a point, after which a further increase in diversification is associated with declining performance. This implies that firms should consider optimal levels of product diversification when they expand product offerings beyond their core business. Other worth-noting findings include: (i) factors stimulating firms to diversify do not necessarily encourage them to extend their diversification strategy; (ii) firms which are endowed with highly skilled human capital are likely to successfully exploit diversification as an engine of growth; (iii) while industry performance does not influence profitability of firms, it impacts their diversification decision and degree.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Santarelli, Enrico
Tran, Hien Thu
Keywords
diversification, firm performance, panel data, sample selection, parametric and semiparametric models
Subjects
ISSN
2282-6483
DOI
Deposit date
08 Oct 2013 10:34
Last modified
18 Feb 2014 13:16
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