Capabilities, policy and institutions in the emergence of venture capital in the UK and US

Venture capital (VC) is widely perceived by UK policymakers to be a key requirement for the growth and development of successful and innovative early stage firms. This thesis examines how government policy has impacted the emergence of VC sectors in the UK and US. Using historical, qualitative and quantitative methods it argues that the public rationale behind UK policy has been largely framed in ways that underestimate the importance of capabilities, demand for capital, and institutional differences. The thesis examines venture capitalists’ key supply-demand relationships: with funded firms; with limited partners; and with the markets that allow exit via IPO. It argues that the US VC sector has developed unique capabilities enabling the assembly of complementary assets to bring firms to successful IPO. In the UK, policy aimed at addressing the ‘equity gap’ has focused on the provision of capital rather than developing the capabilities that have characterised the US sector. We perform quantitative analysis examining the effectiveness of recent UK schemes at providing VC funding to small firms. Drawing upon two proprietary datasets, including one new hand-collected dataset of all investments made under the Venture Capital Trust scheme, the thesis provides new quantitative evidence on the success of government policy interventions, demand for capital by firms, and investment exit opportunities. The thesis then compares principal-agent and evolutionary framing perspectives of the VC sector, arguing the evolutionary view explains some nuances more readily than a pure principal-agent view. It concludes by discussing the theoretical and policy implications of the research

How do we measure firm performance? A review of issues facing entrepreneurship researchers

This chapter aims to provide a succinct overview of the important challenges facing researchers seeking to perform firm-level research, along with an outline of the different data sources that may be used, and some techniques that can be employed to ensure that data are robust. An emphasis is put on the linked importance of research design and choice of data. We discuss quantitative data and, more specifically, the measures used to observe firm performance, and present different types of data sources that researchers may use when studying firm-level data, i.e. self-report data, official statistics, commercial data, combinations of data and big data. We examine potential problems with data, from measurement to respondent and researcher errors. Finally, some key points and some avenues for future research are briefly reviewed

Growth processes of high-growth firms as a four-dimensional chicken and egg

This article investigates whether high-growth firms grow in different ways from other firms. Specifically, we analyze how firms grow along several dimensions (growth of sales, employment, assets, and operating profits) using Structural Vector Autoregressions. Causal relations are identified by using information contained in the (non-Gaussian) growth rate distributions. For most firms, the growth process starts with employment growth, which is then followed by sales growth, then growth of operating profits, and finally growth of assets. In contrast, high growth firms put more emphasis on growth of operating profits driving other dimensions of growth, with employment growth occurring at the end

How unpredictable is research impact? Evidence from the UK's Research Excellence Framework

Although ex post evaluation of impact is increasingly common, the extent to which research impacts emerge largely as anticipated by researchers, or as the result of serendipitous and unpredictable processes, is not well understood. In this article, we explore whether predictions of impact made at the funding stage align with realized impact, using data from the UK’s Research Excellence Framework (REF). We exploit REF impact cases traced back to research funding applications, as a dataset of 2,194 case–grant pairs, to compare impact topics with funder remits. For 209 of those pairs, we directly compare their descriptions of ex ante and ex post impact. We find that impact claims in these case–grant pairs are often congruent with each other, with 76% showing alignment between anticipated impact at funding stage and the eventual claimed impact in the REF. Co-production of research, often perceived as a model for impactful research, was a feature of just over half of our cases. Our results show that, contrary to other preliminary studies of the REF, impact appears to be broadly predictable, although unpredictability remains important. We suggest that co-production is a reasonably good mechanism for addressing the balance of predictable and unpredictable impact outcomes

Skills combinations and firm performance

Creative skills, STEM(science, technology, engineering and mathematics) skills and management skills have all been positively associated with firm performance as well as regional growth. But do firms that combine these types of skills in their workforce grow more quickly than those that do not? We compare the impact of STEM, creative and management skills on their own, and in various combinations, on turnover growth. We use a longitudinal dataset of UK firms over the period 2008–2014 with lagged turnover data to explore whether the combination of skills used by a firm impacts its future turnover growth. Using fixed-effect panel and pooled OLS models, we find that the performance benefits associated with both STEM and creative skills materialize when they are combined with each other or with management skills rather than when they are deployed on their own

Non-founder human capital and the long-run growth and survival of high-tech ventures

This paper considers the impact of non-founder human capital on high-tech firms' long-run growth and survival. Drawing upon threshold theory, we explore how lack of access to complementary skills at different points in the life course impacts founders' thresholds for exit. We examine these factors using a unique longitudinal dataset tracking the performance and survival of a sample of UK high-tech firms over thirteen years as the firms move from youth into maturity. We find that firms that survive but do not grow are characterized by difficulty in accessing complementary managerial skills in youth, while firms that grow but subsequently exit are characterized by shortfalls of specialized complementary skills during adolescence. Firms that grow and survive do not report skills shortfalls. We discuss the implications of these resource constraints for entrepreneurs’ decisions to persist or exit through the life course

Long-run drivers of growth for UK high technology firms

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

How unpredictable is research impact? Evidence from the UK's Research Excellence Framework

Although ex post evaluation of impact is increasingly common, the extent to which research impacts emerge largely as anticipated by researchers, or as the result of serendipitous and unpredictable processes, is not well understood. In this article, we explore whether predictions of impact made at the funding stage align with realized impact, using data from the UK’s Research Excellence Framework (REF). We exploit REF impact cases traced back to research funding applications, as a dataset of 2,194 case–grant pairs, to compare impact topics with funder remits. For 209 of those pairs, we directly compare their descriptions of ex ante and ex post impact. We find that impact claims in these case–grant pairs are often congruent with each other, with 76% showing alignment between anticipated impact at funding stage and the eventual claimed impact in the REF. Co-production of research, often perceived as a model for impactful research, was a feature of just over half of our cases. Our results show that, contrary to other preliminary studies of the REF, impact appears to be broadly predictable, although unpredictability remains important. We suggest that co-production is a reasonably good mechanism for addressing the balance of predictable and unpredictable impact outcomes

The Spread of Retracted Research into Policy Literature

Retractions warn users against relying on problematic evidence. Until recently, it has not been possible to systematically examine the influence of retracted research on policy literature. Here, we use three databases to measure the extent of the phenomenon, and explore what it might tell us about the users of such evidence. We identify policy relevant documents that cite retracted research, we review and categorise the nature of citations, and we interview policy document authors. Overall, we find 2.3% of retracted research is policy cited. This seems higher than one might have expected, similar even to some notable benchmarks for ‘normal’ non-retracted research that is policy-cited. The phenomenon is also multifaceted. Firstly, certain types of retracted research (those with errors, types 1 and 4) are more likely to be policy-cited than other types (those without errors, types 2 and 3). Secondly, although some policy relevant documents cite retracted research negatively, positive citations are twice as common and frequently occur after retraction. Thirdly, certain types of policy organisations appear better at identifying problematic research, and are perhaps more discerning when selecting and evaluating research

The fusion effect: the economic returns to combining arts and science skills

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