The patterns of induced diffusion: Evidence from the international diffusion of wind energy

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Abstract

Recent years have seen growing academic interest in the concept of induced diffusion as efforts to address concerns about energy security and climate change have intensified. Research on induced diffusion explores whether policy tools or interventions can incentivise the diffusion of innovations. This body of literature has explored the effectiveness and efficiency of various policy interventions and as such has been mainly concerned with the determinants of diffusion. This paper is, by way of contrast, concerned with the patterns of diffusion when diffusion is induced. Drawing on the Bass and Davies models of innovation diffusion we develop a number of propositions that suggest that the patterns of diffusion are different when policy plays a role in the diffusion process. These propositions are then econometrically tested in the context of the international diffusion of wind energy in 25 OECD countries. We find that, as predicted, without effective and strong policy interventions, countries will have conventional logistic diffusion with very similar speeds of diffusion. However, as expected the patterns of diffusion take on a different functional form (Bass curve) when there is a strong policy inducement. We conclude by discussing the implications and limitations of these results and suggesting avenues for further research.

Research highlights

► Induced diffusion explores whether policy can incentivise innovation diffusion. ► This paper explores the patterns of induced diffusion. ► We do an econometric analysis of the diffusion of wind energy in 25 OECD countries. ► Without strong policy interventions diffusion is a conventional logistic shape. ► However, a Bass curve is evident when there is a strong policy inducement.

Introduction

Recent years have seen growing academic interest in the concept of induced diffusion as efforts to address concerns about energy security and climate change have intensified (see [1], [2]). Research on induced diffusion explores whether policy tools or interventions can incentivise the diffusion of, inter alia, environmental innovations. This body of literature has explored the effectiveness and efficiency of various policy interventions and as such has been concerned with the determinants of diffusion. This paper is, by way of contrast, concerned with the patterns of diffusion when it is induced.1 The paper, therefore, explores the question of whether the patterns of induced diffusion are different to the conventional patterns observed when diffusion is unaffected by policy interventions. We do so by examining the international diffusion of wind energy in 25 OECD countries.

Examining the patterns (time paths) of wind diffusion allows us to test established theory on innovation diffusion in the context of induced diffusion. This is because even though wind energy is on a cost basis in the same order of magnitude as incumbent electricity generation technologies, for it to diffuse sufficiently widely to reflect social objectives, externalities such as pollutants should be internalised into the prevailing regulatory regime (see Section 1.1, below). However, if wind diffusion requires policy designed to internalise these externalities, then it is not a ‘natural’/unfettered market process. This raises the question of whether this alters the pattern of innovation diffusion? Drawing on the Davies [5] and Bass [6] models of innovation diffusion we develop a number of propositions that suggest that the patterns of diffusion are indeed different when policy plays a role in the diffusion process.

If the patterns of induced diffusion are found to be considerably different to when there are no policy interventions this would imply that policies to induce diffusion do work. This in turn would contrast with assertions by some that interventions have little or no impact on diffusion [7] and would be broadly in line with the preponderance of the evidence that diffusion can be induced [1]. Prior to exploring in more detail the two literatures which this paper draws on and seeks to develop (on induced diffusion and on the pattern of diffusion), it is useful to provide some more sectoral and policy contextual background.

As the most viable large scale ‘new’ renewable generating technology, wind energy is at the centre of the energy policy debate in a large number of countries. Proponents of wind energy argue that it offers the potential to meet environmental goals, such as those of the Kyoto Protocol, whilst at the same time helping to assuage security of supply concerns by reducing reliance on imported fossil fuels from unstable regions of the world. Detractors of wind energy point to a myriad of issues to argue that its wide spread diffusion will run counter to energy policy goals of having affordable and secure energy supplies. These include: intermittency, low load factor, high cost, visual intrusion, noise disturbance and concerns about the public's acceptance of projects, such as ‘Not In My Backyard’ (NIMBY) objections.

There is a great deal of evidence showing that, even before accounting for diversification effects [8], [9], energy security concerns and environmental externalities, wind generation, on a cost basis, has been over the past decade in the same order of magnitude as more conventional generating technologies [10], [11]. Indeed, the cost of electricity generation from wind energy has declined dramatically over the last few decades (Fig. 1). There are numerous factors for this cost decline including:

  • Scale economies: Substantial economies of scale have been derived from ever larger turbines. Turbines in the 1980s tended to be 15 m tall whereas by 2006 they had reached up to 150 m in size [12]. Fig. 1 shows the effect of larger turbines in Denmark has been to increase the generating capacity of individual turbines twenty fold between 1987 and 2006.

  • Technological advances: There have been considerable technological advances in a range of areas including materials and blade and generator design [12]. These developments have played an important role in enabling ever larger and more efficient turbines (Fig. 1).

  • ‘Learning By Doing’: Numerous studies have shown that ‘learning by doing’ has also played an important role in these cost reductions with most studies reporting progress ratios between 80% and 95% [13], [14].

The decreasing cost of electricity generating from wind energy, as well as higher fossil fuel prices from around 2003 onwards, has made wind energy increasingly competitive with the most economic forms of generation (gas or coal). As a result wind energy is increasingly seen as a cost effective alternative. For instance, Dale et al. [11] estimate that having 20% of generation from wind energy in the UK would add 5% to the average electricity bill.

Despite the improved cost performance of wind energy relative to other generating technologies, it is broadly acknowledged that for it to diffuse sufficiently widely to satisfy environmental concerns, these environmental externalities, most notably CO2, need to be internalised so as to induce sufficiently rapid diffusion. Accordingly a whole range of policies have been developed to provide investment support for renewable energy projects, including the EU Emission Trading Scheme, tax breaks, the Kyoto Clean Development Mechanisms, Feed In Tariffs (FIT) and Green Certificate Markets (GCM). There has been a good deal of debate about the efficacy and efficiency of the two main policy options used in practice to support renewables investment, namely FIT and GCM (see [15], [16]). In this debate surprisingly few contributions have been framed within a formal diffusion framework. One exception is Soderholm and Klaassen [17] (see Section 2 for a discussion of this paper).

The increasingly favourable cost attributes of wind energy, rising fossil fuel prices and heightened concern about global warming and energy security mean that wind energy is growing into a substantial global industry. Up to recent years the industry has been dominated by European manufacturers such as Vestas, Gamesa, Enercon and Siemens reflecting the fact the preponderance of the diffusion of wind energy had happened in Europe. In 2002 European manufacturers accounted for approximately 90% of the capacity sold worldwide [18, p. 125]. Further, Beise and Rennings [19] observe that the ‘lead market’ effect of the early use of strict regulations (FIT) in Denmark meant that high wind energy penetration rates translated into industrial policy benefits, namely; a large export market in wind turbines. The last few years have, however, seen the turbine manufacturers from other parts of the world, most notably GE Energy from the US, Suzlon Energy from India and Goldwind from China, becoming increasingly important in the sector. This trend reflects a rapid acceleration of wind energy diffusion in the rest of the world, with approximately equal amounts of wind energy being installed in 2008 in Asia (8579 MW), Europe (8877 MW) and North America (8884 MW) [20].

The remainder of the paper is structured as follows. Section 2 reviews the literatures on induced diffusion and on the pattern of diffusion curves. Section 3 outlines the theoretical framework taken in the paper in the form of four propositions. Section 4 discusses research design and the data used, whilst Section 5 reports and Section 6 discusses the results of the econometric modelling. Section 7 concludes by discussing the implication and limitations of these results and suggesting avenues for further research.

Section snippets

Literature review

In this section we review the literatures on induced diffusion and on the pattern of diffusion. The origins of the concept of induced diffusion can be traced back to Hicks' [21] ‘induced innovation’ hypothesis that proposed that a change in the relative prices of the factors of production would by itself engender invention or innovation to economise the use of a factor which has become relatively expensive. A considerable literature has developed since, using the induced innovation hypothesis

Theoretical model

This section develops the theoretical model (Section 3.1) and related propositions on the patterns of induced diffusion (Section 3.2). Following the Davies model [5], it is proposed that, because industrial scale wind energy technology exhibits the characteristics of a Type B innovation (relatively expensive to adopt, significant and sustained learning by both manufacturers and generators, see Section 1.1), a symmetric S shaped diffusion curve might be expected, ceteris paribus. However, as

Design: estimation and data

This section describes the method by which the propositions are tested, describes the data used, and explains how diffusion and market saturation are measured in the context of wind energy.

Empirical analysis

This section presents the empirical findings. Section 5.1 provides a descriptive analysis of international wind diffusion; Section 5.2 reports the results of the econometric analysis.

Discussion

The results presented here have a number of policy implications. Most obviously, we have confirmed that diffusion is not, of course, instantaneous, but is typically S shaped. In itself, this has immediate implications for the setting of policy targets. For instance, in the UK a policy targets is that renewables should reach 10% diffusion by 2010 and 20% by 2020 [37], but this implies a linear deployment process. This is inconsistent with historical patterns of diffusion and the results we

Conclusions

This paper has sought to understand the patterns of diffusion when diffusion is, in part, induced. Drawing on the Bass and Davies models of innovation diffusion, we develop a number of propositions that suggest that the patterns of diffusion are different when policy plays an important role in the diffusion process. These propositions are econometrically tested in the context of the international diffusion of wind energy in 25 OECD countries using datasets from BTM and the IEA. We find that, as

Acknowledgements

This paper develops work from the corresponding author's doctoral thesis. Some of the work on this paper was undertaken whilst the corresponding author was a Jean Monnet Fellow at the Robert Schuman Centre for Advanced Studies, European University Institute. We would like to thank Catherine Waddams and the two anonymous reviewers for the helpful and constructive suggestions which we believe have greatly enhanced the paper. Lorcan Lyons (IEA) and Birger T. Madsen (BTM Consult) provided

Stephen W. Davies is Professor of Economics and also one of the four founders of the ESRC Centre for Competition Policy at UEA. He has been the General Editor of the Journal of Industrial Economics and is currently an academic adviser to the UK's Office of Fair Trading. Most of his recent research has been in Industrial Organisation in general and Competition Economics in particular, in which he has published thirteen books and over 50 refereed academic articles in leading journals. In his

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  • Cited by (0)

    Stephen W. Davies is Professor of Economics and also one of the four founders of the ESRC Centre for Competition Policy at UEA. He has been the General Editor of the Journal of Industrial Economics and is currently an academic adviser to the UK's Office of Fair Trading. Most of his recent research has been in Industrial Organisation in general and Competition Economics in particular, in which he has published thirteen books and over 50 refereed academic articles in leading journals. In his early research, he made seminal contributions to the theoretical and empirical understanding of the diffusion of process innovations, on which he published a research monograph and articles in leading journals such as the European Economic Review and Regional Studies.

    Ivan Diaz-Rainey is a Lecturer in Environmental Finance at Norwich Business School, University of East Anglia. He is the co-ordinator of the Environmental and Energy Finance Group (EEFG) and also an Affiliate Member of the ESRC Centre for Competition Policy and has previously been a Jean Monnet Fellow attached to the Florence School of Regulation at the European University Institute (EUI), Florence, Italy. Ivan's interdisciplinary policy-focused research applies concepts from finance theory and innovation research to energy and environmental policy.

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