Innovation‐Related Diversification and Firm Value

• Date: 01 June 2017
• Published date: 01 June 2017
• DOI: http://doi.org/10.1111/eufm.12110

Innovation-Related Diversification and

Firm Value

Zhao Rong

Research Institute of Economics and Management, Southwestern University of Finance and

Economics, 55 Guanghuacun Street, Chengdu, Sichuan, 610074, China

E-mail: zhaorong@swufe.edu.cn

Sheng Xiao

Bill and Vieve Gore Business School, Westminster College, 1840 S 1300 E, Salt Lake City,

UT 84105, USA

E-mail: sxiao@westminstercollege.edu

Abstract

We examine a novel determinant of corporate diversification and its valuation

effect: corporate innovations. We find consistent evidence that corporate

innovations increase the extent of diversification. To establish causality, we

estimate the firm fixed effects, 2SLS and GMM models. The 2SLS model uses the US

state-level R&D tax credits as an instrumental variable for corporate innovations.

We also find that a firm is more likely to diversify into an industry where it has

more applicable innovations. Further, such innovation-related diversification is

associated with significantly higher firm value. Our results are robust to various

measures of corporate innovations.

Keywords: innovation, diversification, firm value

JEL classification: G34, O32

1. Introduction

What motivates companies to pursue industrial diversification? Why do some

industrial diversification efforts enhance firm value while others lower firm value?

The authors thank John Doukas (Editor), three anonymous referees, as well as Kai Li,

Peter Thompson and Yoram Barzel for helpful comments. The authors also thank

participants of the EFMA Conference 2014 in Rome, Academy of Management Annual

Meeting 2014 in Philadelphia and Paris Financial Management Conference 2013 for

helpful discussions. Sheng Xiao gratefully acknowledges financial support from the

University of Minnesota’s single-semester leave fund, Westminster College’s Gore course

release fund and Naomi Fallentine Weyher Endowment. Zhao Rong gratefully acknowl-

edges financial support from Florida International University Dissertation Year Fellowship.

European Financial Management, Vol. 23, No. 3, 2017, 475–518

doi: 10.1111/eufm.12110

© 2016 John Wiley & Sons, Ltd.

These are arguably the two most important questions in industrial diversification

research (Montgomery, 1994). For example, for the motivation of diversification,

Khanna and Tice (2001) and Maksimovic and Phillips (2007) examine synergies

in internal capital markets, Tate and Yang (2015) study synergies in internal

labour markets, and Anjos and Fracassi (2015) scrutinise synergies in internal

information markets. For the valuation effect of diversification, Lang and Stulz

(1994), Berger and Ofek (1995), Lins and Servaes (1999) and Lamont and Polk

(2002) discover a ‘diversification discount’, while Whited (2001), Campa and Kedia

(2002), Villalonga (2004) and SColak (2010) find that the ‘diversification discount’

drops and sometimes even turns into a premium, after addressing measurement errors

or endogeneity.

We propose a novel determinant of industrial diversification and its valuation effect:

corporate innovations. Specifically, a firm’s innovative activities may result in

innovations that are not applicable to its existing business lines. To fully capture the

returns on these innovations, the firm may choose to diversify into an industry where

such innovations can be utilised. We therefore hypothesise that a firm’s innovations

have significant and positive effects on its extent of subsequent diversification. In

addition, we hypothesise that a diversifying firm is more likely to enter an industry where

its innovations are more applicable. Inspired by the models of Penrose (1959),

Matsusaka (2001), Maksimovic and Phillips (2002) and Gomes and Livdan (2004), we

regard diversification as a process to explore the opportunities for productivity

improvements. Since innovative firms continuously innovate, it is natural to expect that

these firms continuously search for good matches between their innovations and business

lines through diversification. Such innovation-related diversification is expected to

improve the match between a firm’s innovations and its business lines, resulting in a

more efficient allocation of resources. We thus hypothesise that when a diversifying firm

has more applicable innovations in the industry it enters, such a good match should

enhance its firm value.

3M, one of the largest 100 companies in the world, provides a case in point. It is a very

active innovator, and has diversified into a myriad of industries. It files about 500 new

patents per year, and produces over 55,000 products in multiple industries such as

aerospace, architecture, automotive, healthcare, electronics, food, beverages and

transportation, etc. As 3M states in a brochure titled A Culture of Innovation,‘3M’s

business model is to foster organic growth by inventing new products that previously did

not exist. This business model has led not only to new products, but also the creation of

new industries.’

1

3M’s business model seems to have worked well. For example, its

share price rose by 223.96% between 31 December 1999 and 31 December 2015, while

the S&P 500 index gained only 40.15%. 3M’s case shows that when a firm diversifies

into a related industry after achieving proprietary innovations, its firm value may rise.

To examine whether 3M’s success is a general case that can be applied to other

companies, or just a special case that holds true only for a particular company, we

conduct a large-sample analysis. We first examine whether a firm’s innovations influence

1

Another relevant case is given by Kazuo Suzuki (1993), Chairman of Toppan Printing Co.

Ltd. in Japan, who describes how, through innovation-related diversification, his company

grew rapidly into a US$90 billion business with 19 offices overseas employing about 2,200

people in the US, Europe and Asia.

© 2016 John Wiley & Sons, Ltd.

476 Zhao Rong and Sheng Xiao

its extent of subsequent diversification. We measure a firm’s innovations by the number

of patents that the firm has accumulated, weighted by the number of citations that these

patents receive. Our main measure of a firm’s extent of diversification is the number of

industries (at the 4-digit SIC level) in which the firm is operating, but we also use other

measures for robustness checks. When we examine the effects of innovations on

diversification, endogeneity is a major concern. For example, a third variable may affect

both diversification and innovation. Also, reverse causality is possible. For example,

Seru (2014) finds that diversification significantly affects innovations. To tackle these

endogeneity issues, we utilise three main empirical strategies: (1) the firm fixed effects

model with one-year lagged innovations as the key independent variable; (2) the 2SLS

(two-stage-least-squares) model using the state-level R&D tax credits as the instrument

for innovations; and (3) the dynamic panel GMM (Generalised Method of Moments)

model. As a robustness check, we also use the Abadie-Imbens matching method.

Our firm fixed effects model successfully controls for the time-invariant firm-specific

factors that are correlated with both innovations and diversification. Furthermore, using

lagged innovations helps us mitigate the potential endogeneity issue to some degree. In

this model, we find that a firm’s innovations have significant and positive effects on the

extent of its subsequent diversification.

However, if innovations exhibit strong autocorrelation, using lagged innovations

would be less effective to mitigate potential endogeneity. To deal with endogeneity more

effectively, we resort to the 2SLS technique. Motivated by Wilson (2009), we use an

exogenous policy shock, i.e., the staggered implementation of state-level R&D tax

credits as the instrument for innovations. It is a valid instrument because the

implementation of R&D tax credits should affect firms’innovations, but it should not

directly affect firms’diversification decisions. Indeed, Wilson (2009) finds that the

implementation of state-level R&D tax credits significantly boosts firms’R&D

expenditures, and many studies document that higher R&D expenditures are associated

with more innovations (e.g., Fang et al., 2014). Using this exogeneous policy shock, our

2SLS estimation provides evidence on the positive causal effect of a firm’s innovations

on its subsequent diversification.

One potential problem with the above instrument is that it only varies at the state-year

level, so it may fail to address the possibility that the time-variant firm-specific

unobservables affect both innovations and diversification. To deal with this dynamic

endogeneity issue, we follow Acemoglu et al. (2008), Hoechle et al. (2012), Wintoki

et al. (2012), O’Connor and Rafferty (2012) and Flannery and Hankins (2013)’s methods

and estimate the dynamic panel GMM model. Doing so enables us to use firm-level

‘internal instruments’to tackle dynamic endogeneity. Our GMM estimation results

provide further evidence on the positive causal effect of innovations on diversification.

Thispositive relationshipbetween a firm’s innovationsand its subsequentdiversification

is consistent with the following two scenarios. Suppose a firm has some innovations

applicableto industry A but none of the firm’s innovations is applicableto industry B, and

both industriesare potential industriesthe firm may enter. Scenario (1) isthat the firm then

diversifiesinto industryA, while scenario (2) is thatthe firm then diversifies intoindustry B.

In both scenarios, the firm’s innovations are positively correlated with the extent of its

subsequent diversification. If scenario (1) is true, our hypotheses will receive strong

support. However, if scenario (2) is true, it will cast serious doubt on our hypotheses.

To distinguish between these two scenarios, we need to examine the following

question: given that a firm diversifies into one of these two industries (A or B), and that its

© 2016 John Wiley & Sons, Ltd.

Innovation-Related Diversification and Firm Value 477