Three decades of research on innovation and inequality: Causal scenarios, explanatory factors and suggestions

• DOI: https://doi.org/10.13169/prometheus.38.2.0147
• Published date: 30 August 2022
• Date: 30 August 2022
• Pages: 147-193
• Author: Thanos Fragkandreas

Thanos Fragkandreas147

RESEARCH PAPER

Three decades of research on innovation and inequality:

Causal scenarios, explanatory factors and suggestions

Thanos Fragkandreas

Westminster Business School, University of Westminster, and Centre for Innovation Management Research,

Birkbeck, University of London

ABSTRACT

Prompted by rising income inequality (in short, inequality) in advanced economies, a rapidly grow-

ing number of studies across various fields and disciplines of social science have, since the 1990s,

sought to find out how innovation (as the main engine of economic progress) affects the distribu-

tion of income in modern-day capitalist societies. Using the systematic literature review method,

this paper provides the first critical review of 166 studies on innovation and inequality published

in 114 journals in the last three decades (1990–2019). It is shown that, while the great majority of

studies under review concur that innovation induces inequality, this finding is subject to the disci-

plinary origins of research (e.g., development studies, economics, geography, innovation studies,

etc.) and the country under investigation. Furthermore, guided by an original causally holistic ana-

lytical framework, the analysis demonstrates that the relationship between innovation and

inequality is significantly more causally complex than the most popular theoretical perspective

(i.e., skill-biased technological change account) has let us believe; in particular, it is subject to five

causal scenarios and a range of explanatory factors (i.e., skill premiums, technological unemploy-

ment, international trade, declining union membership, spatial aspects, changing employment

conditions, policy, horizontal inequalities, sectoral composition and types of innovation). The

paper ends by discussing findings, policy implications and knowledge gaps, one of which concerns

the following under-researched question: how, and under what conditions do publicly funded

innovation policies reduce (or increase) inequality?

Introduction

What do the contributions of notable thinkers – such as Adam Smith (1776/1982), David Ricardo

(1891), Karl Marx (1999), Thorstein Veblen (1899/2009), Joseph Schumpeter (1934, 1944) and

Werner Sombart (1967) – have in common other than their obvious significance for contemporary

socioeconomic thought? In a nutshell, the classics of socioeconomic thought are replete with pas-

sages demonstrating that innovation1 is (bi-)causally related to inequality2 in capitalist societies.

Despite this, innovation scholars had, for several decades of the twentieth century, examined mainly

the positive side of the story, particularly the relationship between innovation, employment crea-

tion, competitiveness and growth (Fagerberg, 1994; Pianta, 2005; Antonelli, 2009). The question of

1In this paper, innovation is defined as the development of novel and socioeconomically significant combinations

of resources, which can take the form of new products, services, institutions and organizational models

(Edquist, 2005; Fragkandreas, 2017).

2Broadly defined as the unequal distribution of income (Tilly, 1998; Dorling, 2019).

CONTACT: kfrag01@mail.bbk.ac.uk

ACCEPTING EDITOR: Hans-Jürgen Engelbrecht

DOI:10.13169/prometheus.38.2.0147

Prometheus 148

inequality was largely ignored. Today, however, there exists a sustained interest in innovation and

inequality in various fields of social science. For instance, economists (e.g., Acemoglu, 2002; Van

Reenen, 2011), economic geographers (e.g., Breau et al., 2014; Lee, 2016), development scholars

(e.g., Hilbert, 2010), industrial relations scholars (e.g., Belman and Monaco, 2001), innovation

scholars (e.g., Cozzens and Kaplinsky, 2009; Lazonick and Mazzucato, 2013), sociologists (e.g.,

Fernandez, 2001) and political scientists (e.g., Hope and Martelli, 2019) have all examined the rela-

tionship between (technological) innovation and inequality.

Despite such a discipline-diverse interest, our knowledge of this rapidly expanding literature

has, to date, been overshadowed by the work of mainstream labour economists (Ashenfelter and

Card, 2010), particularly by research informed by the skill-biased technological change (SBTC)

account.3 Thanks to a few literature reviews on SBTC research (e.g., Acemoglu, 2002; Acemoglu

and Autor, 2011; Bogliacino, 2014; Goos, 2018), we know a great deal about the work of mainstream

economists on innovation and inequality, but much too little about the work, for instance, of

development studies scholars, heterodox economists, employment relations scholars, innovation

scholars, geographers and sociologists.

This ‘disciplinary parochialist’ (Sayer, 2000a) perspective has several important

ramifications for research and policy. First, it limits the cross-fertilization of knowledge, including

the formation of interdisciplinary research synergies and projects, among like-minded scholars in

the social sciences. Secondly, and as will be shown in this paper, it propagates assumptions about

innovation and inequality that have long been found to be fundamentally misleading and fallacious

in another field of study. Finally, a disciplinary perspective reduces the knowledge variety – a

necessary element in designing a new generation of inequality-sensitive and inclusive innovation

policies (Perez, 2013; Zehavi and Breznitz, 2017; Schot and Steinmueller, 2018; Edquist, 2019).

The present paper redresses the lack of an interdisciplinary assessment of the current stock

of knowledge on innovation and inequality. It does so by identifying and reviewing, in a critical

manner, 166 studies published in a broad range of journals (114) in the last three decades (1990-

2019). A major novelty of the present review is that, unlike previous reviews on the subject, which

are narrative and focus exclusively on research within only a single field (e.g., Acemoglu, 2002;

Acemoglu and Autor, 2011; Van Reenen, 2011; Bogliacino, 2014; Lee, 2016; Goos, 2018), the

analysis in this paper is cross-disciplinary (i.e., synthesizing knowledge from different fields),

systematic (i.e., based on the systematic literature review method) and causally holistic (i.e., utilizing

an original conceptual framework). All of this enables the review process to cross freely the

disciplinary boundaries of knowledge and identify several overlooked aspects of causality in the

relationship between innovation and inequality.

Several novel insights and critical observations emanate from the analysis. First, it is shown

that while, in quantitative terms, the extant research concurs that innovation induces inequality, one

needs to be extremely cautious about the validity of this finding. This is because the disciplinary

origins of research (e.g., economics, development studies, sociology, etc.) and the country under

investigation seem to affect the propensity of research to report that innovation induces inequality.

Secondly, against the STBC account, which rests upon a one-dimensional perspective on causality,

this review shows that there are five main causal possibilities through which innovation and inequality

are causally related. These are as follows: absence of causality (causal scenario 0); innovation induces

inequality (causal scenario I); inequality stimulates innovation (causal scenario II); innovation

3According to this account, innovation has – for much of the twentieth century – been complementary to skills

in general, and the labour productivity (and thus also wages) of the skilled labour force in particular (Card and

DiNardo, 2002; Acemoglu, 2002; Van Reenen, 2011). Innovation, as SBTC scholars argue, induces inequality

by increasing the wage gap between skilled and unskilled employees (Acemoglu, 2002; Van Reenen, 2011;

Bogliacino, 2014; Goos, 2018). At the macro-level, the SBTC account predicts that the more technologically

advanced the modern capitalist system becomes, the more polarizing the distribution of skills and wages among

workers tends to be (Autor et al., 1998; Krusell et al., 2000).

Thanos Fragkandreas149

ameliorates inequality (causal scenario III); inequality hampers innovation (causal scenario IV).

Thirdly, the analysis identifies numerous determinants (i.e., skill premiums, technological

unemployment, international trade, declining union membership, geographical aspects, changing

employment conditions, policy, horizontal inequalities, sectoral composition and types of innovation)

that appear to be shaping (in the form of causal mechanisms) the multidimensional direction and

strength of causality. Finally, and because of its critical outlook, the paper detects and challenges

several prevalent assumptions and methodological practices, such as the following:

1. The lack of a sophisticated understanding of innovation as a highly uncertain, collective

(multi-actor), organization-specific and sectorally differentiated activity;

2. The widely held theoretical assumption that income acquisition is being primarily shaped

by atomistic (human capital) attributes in labour markets, rather than being the primary

outcome of relationally created and maintained processes that occur mainly in concrete,

unequally structured organizations, such as the innovative firm;

3. The widely adopted methodological practice in which the identification of a few statistically

significant associations, including the absence of them, is treated as conclusive evidence of

operative causal mechanisms; and

4. The easy extrapolation of the research findings in the liberal market economies (e.g., the

US, the UK and Canada) to the other market economies (e.g., coordinated and mixed mar-

ket economies).

The analysis in this paper responds, albeit in a different manner than customary (e.g.,

concrete research), to recent calls made by innovation scholars (e.g., Soete, 2013; Martin, 2016;

Chaminade et al., 2018; Schot and Steinmueller, 2018; Coad et al., 2021) that inequality needs to

be placed much higher on the research agenda in the field of innovation studies.4 By offering an

up-to-date, causally holistic analysis of the extant multidisciplinary lines of research, the paper

transforms a highly fragmented body of research into a coherent guide to the current empirical stock

of knowledge on innovation and inequality while also suggesting several cross-disciplinary (yet

consistent with the theoretical core of the field of innovation studies) paths of research on a topic of

increasing scientific and policy relevance (Fagerberg et al., 2012; Martin, 2012; Lundvall, 2013).

The remainder of this paper consists of four sections. The second introduces key stylized

facts of inequality research, before spelling out the key dimensions of the analytical framework of

this review. The third discusses the key steps and procedures that this paper has followed to identify

and analyse, in a systematic manner, the extant research on innovation and inequality, whereas the

fourth provides a chronological review of the literature, focusing on bibliometric issues (e.g., prolific

authors, journals, disciplines and keyword developments), causal scenarios and explanatory themes.

The paper ends with a summary of key findings, knowledge gaps, policy implications and suggestions.

Innovation and inequality: theoretical background and review framework

Rising inequality: key trends and determinants

Over the past three decades, numerous studies have shown that inequality has been galloping in

both developed and developing economies (e.g., Stiglitz, 2012; Piketty, 2014; OECD, 2015; Lakner

4By innovation studies, this paper refers to the half-century-old, cross-disciplinary field of research whose primary

aim is to study, in a systematic manner, the nature, determinants, social and economic benefits and consequences

of innovation (Fagerberg et al., 2012; Lundvall, 2013). While diverse, much innovation studies research falls

into three main strands (Fagerberg et al., 2012; Lundvall, 2013): the economics of innovation strand (Fagerberg,

2003); the management and organization of innovation strand (Tidd and Bessant, 2018); and the socioeconomic

strand dealing mainly with the diffusion of innovation (Rogers, 1995), innovation (eco)systems (Edquist, 2005;

Granstrand and Holgersson, 2020) and sociotechnical systems and transitions (Geels, 2004).