This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

The Rise of the Creative Class

Economics Of Discrimination

Economists have long puzzled over the astounding differences in productivity between firms and countries. For example, looking at disaggregated data on U.S. manufacturing industries, Syverson (2004a) found that plants at the 90th percentile produced four times as much as the plant in the 10th percentile on a per-employee basis. Only half of this difference in labor productivity could be accounted for by differential inputs, such as capital intensity. Syverson looked at industries defined at the four-digit level in the Standard Industrial Classification (SIC) system (now the North American Industry Classification System or NAICS) like 'Bakeries and Tortilla Manufacturing' or 'Plastics Product Manufacturing.' Foster, Haltiwanger, and Syverson (2008) show large differences in total factor productivity even within very homogeneous goods industries such as boxes and block ice. Some of these productivity differences across firms and plants are temporary, but in large part they persist over time. At the country level, Hall and Jones (1999) and Jones and Romer (2009) show how the stark differences in productivity across countries account for a substantial fraction of the differences in average per capita income. Both at the plant level and at the national level, differences in productivity are typically calculated as a residual-that is, productivity is inferred as the gap between output and inputs that cannot be accounted for by conventionally measured inputs.

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Why Do Management Practices Differ across Firms and Countries

We propose an independence criterion based on the eigen-spectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. First, the empirical estimate is simpler than any other kernel dependence test, and requires no user-defined regularisation. Second, there is a clearly defined population quantity which the empirical estimate approaches in the large sample limit, with exponential convergence guaranteed between the two: this ensures that independence tests based on HSIC do not suffer from slow learning rates. Finally, we show in the context of independent component analysis (ICA) that the performance of HSIC is competitive with that of previously published kernel-based criteria, and of other recently published ICA methods.

Measuring statistical dependence with Hilbert-Schmidt norms

Complicated neoclassical models predict that if investment is sensitive to current financial performance, this is a sign that something is "wrong" and is to be regarded as a problem for policy. Evolutionary theory, on the other hand, refers to the principle of "growth of the fitter" to explain investment-cash flow sensitivities as the workings of a healthy economy. In particular, I attack the neoclassical assumption of managers maximizing shareholder-value. Such an assumption is not a helpful starting point for empirical studies into firm growth. one caricature of neoclassical theory could be "Assume firms are perfectly efficient. Why aren't they getting enoug funding ?", whereas evolutionary theory considers that firms are forever struggling to grow. This essay highlights how policy guidelines can be framed by the initial modelling assumptions, even though these latter are often chosen with analytical tractability in mind rather than realism.

Neoclassical vs evolutionary theories of financial constraints: critique and prospectus

Despite the importance of high technology firms to the global economy, relatively little is known about factors contributing to these firms’ long-run growth. We examine these factors using a unique longitudinal dataset combining two waves of detailed surveys of 345 UK high tech firms with performance data from UK official datasets. Overall we conclude that the early strategic decisions made by firms have long-run impacts on their subsequent growth, and we suggest that policy measures targeted at shortfalls faced by these firms may have positive long-term consequences.

Long-run drivers of growth for UK high technology firms

In this paper a
comparison is made 
between data on
the US S
mall 
B
usiness 
I
nnovation 
R
esearch 
programme (SBIR)
and UK 
Small Business Research Initiative (
SBRI
)
(Tredgett & Coad 2013). 
Quantitative data on the first three y
ears of the UK SBRI (2009 
–
2013
) was compared to 
data on 
the first three y
ears of the US SBIR (1983 
–
1987
) from the US Small Business Administration. 
The data includes numbers of competitions, applicants and mo
ney spent on research contracts
. 
Some key differences in implementation of the two 
initiatives are identified and discussed in 
relation to the quantitative data. Quantitative data shows that while the US SBIR had steady 
growth, the UK SBRI has had a shaky start. Possible explanations for these results are suggested. 
Further work to stren
gthen the data and improve the validity of the evaluation is then outlined.

/pdf/the-shaky-start-of-the-uk-small-business-research-initiative-56pzvb4vrl.pdf

The shaky start of the UK Small Business Research Initiative (SBRI) in comparison to the US Small Business Innovation Research Programme (SBIR)

High Growth Firms (HGFs) make a considerable contribution to economic growth, and in recent years they have received increasing interest from entrepreneurship scholars. By analysing recent findings in the literature of high growth firms, this study identifies some stylized facts, as well as contradictory findings, and also some unknowns regarding the determinants and internal strategies of HGFs, particularly on the persistence of their superior growth performance and the implications of recent findings for economic policy.

/pdf/high-growth-firms-stylized-facts-and-conflicting-results-pl0h5223qn.pdf

High-Growth Firms: Stylized Facts and Conflicting Results

The issue of technological unemployment receives perennial popular attention. Although there are previous empirical investigations that have focused on the relationship between innovation and employment, the originality of our approach lies in our choice of method. We focus on four 2-digit manufacturing industries that are known for their high patenting activity. We then use Principal Components Analysis to generate a firm- and year-specific ‘innovativeness’ index by extracting the common variance in a firm’s patenting and R&D expenditure histories. To begin with, we explore the heterogeneity of firms by using semi-parametric quantile regression. Whilst some firms may reduce employment levels after innovating, others increase employment. We then move on to a weighted least squares (WLS) analysis, which explicitly takes into account the dierent job-creating potential of firms of dierent sizes. As a result, we focus on the eect of innovation on total number of jobs, whereas previous studies have focused on the eect of innovation on firm behavior. Indeed, previous studies have typically taken the firm as the unit of analysis, implicitly weighting each firm equally according to the principle of ‘one firm equals one observation’. Our results suggest that firm-level innovative activity leads to employment creation that may have been underestimated in previous studies. L’innovation des entreprises et croissance de l’emploi

https://halshs.archives-ouvertes.fr/halshs-00175042/document

Alex Coad

Papers

Neoclassical vs evolutionary theories of financial constraints: critique and prospectus

Long-run drivers of growth for UK high technology firms

The shaky start of the UK Small Business Research Initiative (SBRI) in comparison to the US Small Business Innovation Research Programme (SBIR)

High-Growth Firms: Stylized Facts and Conflicting Results

The employment effects of innovation