Spillover feedback loops and strategic complements in R&D

• Published date: 01 December 2019
• DOI: http://doi.org/10.1111/jpet.12397
• Author: Evangelia Chalioti
• Date: 01 December 2019

J Public Econ Theory. 2019;21:1126–1142.wileyonlinelibrary.com/journal/jpet1126

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© 2019 Wiley Periodicals, Inc.

Received: 23 July 2019

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Revised: 25 July 2019

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Accepted: 26 July 2019

DOI: 10.1111/jpet.12397

ORIGINAL ARTICLE

Spillover feedback loops and strategic

complements in R&D

Evangelia Chalioti

Department of Economics, Yale

University, New Haven, Connecticut

Correspondence

Evangelia Chalioti, Department of

Economics, Yale University, 30 Hillhouse

Avenue, Room 35, New Haven, CT 06511.

Email: evangelia.chalioti@yale.edu

Abstract

This paper studies, in a two‐period model, the effects of

knowledge spillovers among product market competi-

tors on R&D levels. It argues that when firms’R&D

decisions are strategic complements, in industries in

which spillovers increase the marginal productivity

of a firm’s R&D, both incoming and outgoing spillovers

spur R&D in equilibrium. Outgoing spillovers can foster

innovation even in a homogeneous‐product industry. In

these industries, the intellectual property law should be

such that facilitates knowledge diffusion. If firms have

power in deciding the level of knowledge spillovers, we

show that a firm will choose to disclose its knowledge to

its product market competitors.

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INTRODUCTION

Innovation in knowledge‐based industries and technological parks depends significantly on

technological interactions among research units and the intensity of knowledge diffusion. Levin

(1988) studies the effect of spillovers on R&D activity and states that there are differences in

technical advances in different high‐technology industries. He argues that innovation “stands

alone”and spillovers diminish the marginal productivity of a firm’s innovation in material and

drug industries before the revolution in genetic engineering. However, in pharmaceuticals and

electronics‐based industries, innovations are “building blocks”and spillovers increase the

marginal productivity of a firm’s R&D. Feldman (1999) also provides a survey of the empirical

literature and argues that knowledge spillovers across diverse firms within a region contribute

to higher rates of innovation and increased productivity. We study firms’incentives to innovate

in precisely these industries in which feedback is regenerative and argue that when a firm’s

R&D decision is a strategic complement, larger outgoing spillovers foster innovation. In these

industries, the intellectual property (IP) policies should facilitate knowledge diffusion rather

than putting limitations. If the spillover rates are assumed to be endogenous, firms will choose

to disclose their knowledge to their product market competitors.

In the regenerative feedback model (RF model, hereafter), spillovers make a firm’sown

R&D more productive. A researcher finds it cheaper to solve her technological problem by

accessing another researcher’s R&D output, which is disclosed by patents or publications.

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The other researcher can also build on this new innovation, facilitated by spillovers, and

further improve her own results.

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Using patent and citation data, Belenzon (2012) argues that

an R&D‐taking firm reabsorbs its spilled knowledge by recombining its own existing ideas

with external follow‐up developments in novel and unexpected ways. For example, Intel cites

a Microsoft patent that is in turn cited by another Microsoft patent. In this case, Intel’sfollow‐

up development of Microsoft’s original patent is internalized by Microsoft in its new

invention.

We study cost‐reducing R&D incentives in a two‐period model in which firms first

independently acquire R&D to improve their efficiency and, then, compete à la Cournot in the

product market. The analysis focuses on the equilibrium R&D incentives when cross‐firm

spillovers are large, making rivals’R&D decisions strategic complements: An increase in R&D

by one firm elicits increased R&D from the other. R. Amir (2000) and M. Amir, Amir, and Jin

(2000) study in depth the distinction between strategic complements and substitutes in R&D

and how this connects to spillovers. When a firm’s R&D decision is a strategic complement, the

firm’s objective is precisely to reduce the production cost; that is, a firm’s incentive to steal

business is weak relative to its stronger incentive to improve its own efficiency. If the feedback

is regenerative, by conducting more R&D, a firm contributes to another firm’s R&D output

through outgoing spillovers while indirectly improving its own‐R&D performance.

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This occurs

because incoming spillovers allow the innovative firm to internalize (at least) some share of the

provided benefit. The return to cost reduction increases with outgoing spillovers, as do the gains

from undertaking R&D. As outgoing spillovers intensify, a firm has stronger incentives to

acquire more R&D itself to produce more efficiently. Therefore, firms will profit more if the IP

protection is weak, allowing for larger spillovers.

We perform this analysis by considering linear demand and convex cost functions and

specify the conditions under which outgoing spillovers foster R&D in equilibrium. This analysis

establishes that the relationship between outgoing spillovers and firms’equilibrium R&D

depends on the nature of strategic interactions in the R&D stage: The innovative firm’s R&D

decision needs to be a strategic complement.

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Existing models with exogenous spillovers, based on D’Aspremont and Jacquemin (1988; AJ

model, hereafter) and Kamien, Muller, and Zang (1992), assume that firms autonomously invest

in R&D and there are no interactions during the R&D process. Spillovers have either no effect

or negative effects on the marginal productivity of a firm’s R&D. In these models, outgoing

spillovers always induce homogeneous‐product rivals to conduct less R&D in equilibrium.

Outgoing spillovers harm the innovative firm and decrease its optimal R&D. Rockett (2012)

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Spillovers are more likely to depend on R&D outputs than on R&D inputs, that is, a researcher’s effort. In a stochastic framework, a researcher benefits from

another’s research only if both succeed (inputs are irrelevant); that is, innovative results need to be successfully produced by both researchers, allowing them to

build thereon. Jaffe and Trajtenberg (2002) use patents and citations (R&D outputs) to infer patterns of knowledge diffusion.

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Spillovers are more intense within geographic areas and across firms with similar technologies and existing expertise (Feldman & Audretsch, 1999). They also

depend on the strictness of IP law and the stage of the R&D and commercialization process.

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When knowledge is more articulable, it is easily conveyed via journal articles, project reports, prototypes, and other tangible mediums. When knowledge is

more tacit in nature, it is transmitted via face‐to‐face interactions and direct communication. Feldman and Lichtenberg (2000) construct several indicators of

tacitness using data on publicly supported R&D projects in the European Union. Fershtman and Gandal (2011) study the spillovers that occur through the

interaction between researchers who contribute to the development of different open source software.

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We can show that it does not depend on the mode of competition in the product market: As long as firms’R&D best‐response curves are upward sloping,

outgoing spillovers can stimulate R&D in both Cournot and Bertrand settings.

CHALIOTI

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