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«Recent advances in the measurement of productivity change have exposed a much clearer picture of the turbulent dynamics of restless capitalism. This ...»

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CREATIVE DESTRUCTION

AND THE MEASUREMENT

OF PRODUCTIVITY CHANGE*

J. Stanley Metcalfe and Ronnie Ramlogan

ESRC, University of Manchester, Manchester, United Kingdom

Recent advances in the measurement of productivity change have exposed a much

clearer picture of the turbulent dynamics of restless capitalism. This essay has two

objectives. First, to show that the population method drawn from evolutionary theory provides a coherent frame in which the various processes impinging on productivity change can be integrated. Secondly, to identify some of the puzzles and ambiguities that arise from decomposing any aggregate measure of productivity growth into innovation effects in firms and selection effects in markets. We shall also show that there is no unique way of making this decomposition. This is an important matter because the transmission process between innovation and changing resource allocation underpins the process of economic development in the broad sense.

JEL Classification: D24, E11, O30, O40.

Keywords: Productivity change and Evolutionary Population Dynamics, Fisher Price Theorems * The opportunity to present some of these ideas at the Druid Summer conference in Copenhagen in June, 2005 and at the Argentine Economic Association Annual conference in November, 2005 in Buenos Aires are gratefully acknowledged, as are comments from Esben Andersen, Thorbjern Knudsen, Omar Chisari, Dick Nelson and an anonymous referee. The stimulus provided by a reading of Baldwin and Gu (2005) is also acknowledged although we are entirely responsible for the interpretation provided here. A second draft of the ideas was developed at the University of Queensland in summer 2005. JSM is grateful to John Foster for the opportunity to work in this stimulating environment, and to Kurt Dopfer, Jason Potts and John Foster for extended discussion of the evolutionary background to the problem dissected here.

stan.metcalfe@man.ac.uk ronnie.ramlogan@man.ac.uk Revue OFCE June 2006 J. Stanley Metcalfe and Ronnie Ramlogan

1. Introduction Recent advances in the measurement of productivity change made possible by new micro data sets (Caves, 1998; Bartelsman and Doms, 2000;

Tybout, 2000), have exposed a much clearer picture of the turbulent dynamics of restless capitalism and by implication the connections between innovations and aggregate economic performance. That growth and development proceed hand in hand with changing structures of economic activity has been understood since the early days of economics as a di

–  –  –

experience within industries and economies, as scholars such as Nelson (1989) have carefully pointed out, and, therefore, acts as a barrier to a deeper understanding of the links between innovation and economic growth1. For example, the crucial concept of the aggregate production elasticity linking say labour input increase to output increase, frays in our hands in a multi sector economy for its magnitude will depend on how any increase in labour is allocated across the different industries. Thus it cannot be interpreted as a technology construct alone2. More importantly it loses sight of the fact that the evolution of the economic structure is itself a function of the diversity of productivity performance across the constituent firms and industries within it.

Most fundamentally of all a macro approach hides the central point that in the process of development some activities have to decline in absolute and relative importance and others must disappear; not everything can grow in a process of development and certainly no economy ever develops with all activities expanding at the same proportional rate— Von Neumann style. In short development requires the reallocation of resources and a changing composition of output and demand, consequences of the market process.

Yet more fundamentally it requires innovation, the application of knowledge to create the new productive opportunities to which the reallocation of resources is an adaptive response. The framework which brings together innovation and adaptation, we argue, is naturally evolutionary and takes as its frame the concept of a population of activities.

1.1. Population Analysis Population analysis is a standard reference concept in evolutionary thought, a device to emphasise the fundamental evolutionary categories of variety and the dynamic consequences of selection acting on differences between entities to produce evolutionary change. As such it stands in contradistinction to the concept of essentialism that phenomena are to be understood in terms of a few key, defining attributes around which discrepancies are abnormal irregularities. Within population analysis, by contrast, the focus is precisely on the significance of the ‘abnormalities’ simply because uniform populations are devoid of evolutionary potential. An economy in which all agents behave identically is simply an economy that cannot develop.

The concept of a population implies two contributing ideas: a set of differentiated entities or ‘individuals’, and a causal selection process that serves to identify the inclusion criteria for membership of the population and

1. See the more recent discussion in Harberger (1998) on micro diversity and aggregate productivity growth, pointing to the very uneven cross sector incidence of productivity change in the US economy.





2. Empirically minded scholars such as Massell (1960) clearly understood this point but the pursuit of macro fundamentalism soon buried the implications. Interestingly, careful theorists such as Hicks (1932) who did so much to promote a production function approach, were at pains to point out that the ‘production’ elasticities did reflect the composition of output and thus the composition of demand.

OFCE/June 2006 J. Stanley Metcalfe and Ronnie Ramlogan

–  –  –

the economic terms relevant for this discussion, the population could be a set of national economies, a set of industries within a given economy or a set of competing firms within a given industry or indeed submarket of an industry. If we now think of our entities as ‘firms’ in ‘industries’ there is an alternative way to distinguish the various change processes acting on the population, a way that emphasises the variation and selection basis for the population framework. From this evolutionary viewpoint the various possible changes can be subsumed under the general categories of

1) Selection processes (exit and differential growth of firms), and

2) Creative processes (innovation based changes in product and process characteristics in continuing firms, entry and recombination/fusion of firms). These are each markedly different in both their nature and their consequences for economic change. The conditions, for example, that drive an activity out of the industry population are not the same as those that generate differential growth and decline although both are related to profitability. Similarly, product innovation involves different issues from merger or divestiture and a full evolutionary economic theory would be sensitive to these differences.

OFCE/June 2006 J. Stanley Metcalfe and Ronnie Ramlogan

–  –  –

flows with sufficient accuracy add to the complications, but they are not our concern here. Rather, we shall explore how the empirical results look through the lens of population analysis.

The principal issue at stake is the relative contribution of the different elements outlined in figure 1, although no study to our knowledge has investigated the effects of recombination and fission on the productivity measures. If we consider a single industry the aim is to identify the relative contributions of within (innovation), between (selection) and net entry effects. Notice that the nested nature of population analysis allows the focus to be at higher or lower levels than the industry. Thus taking the population as a set of industries (an economy), we could apply the same accounting logic to assess the effects of productivity growth at industry level, a ‘within’ effect, and of structural change, the emergence of new industries and the disappearance of old industries, the ‘between’ effects. Of course, the ‘within’ effect for any one industry as a whole, is a mélange of the ‘within’ effects in firms and the ‘between’ firm and net entry effects in that industry. Similarly, we could take the multi plant firm as the population and measure within productivity effects at plant level together with the opening of new plants, closure of old plants and changing allocation of the firm’s output across continuing plants as the between effects.

The creation of micro data sets has greatly facilitated assessment at these different levels so that the manufacturing sector in a whole economy could be treated as a population of productive establishments. How does the empirical evidence turn out? Consider first the study by Olley and Pakes (1996) on plant level data for the telecommunications industry in the USA post deregulation, which identified the importance of firms reallocating output to more efficient plants, the expansion in the capacity of those plants and the exit of less efficient plants for industry productivity growth. In their view it was reallocation of capital resources and not increases in plant productivity that account for the improvement in industry performance. An early study by Bailey et al. (1992) measuring total factor productivity growth in US manufacturing plants in twenty-three industries for 1972-1987, concluded that entry and exit played only a minor role in changing industry productivity growth and that the growth in the relative output of high productivity plants, the ‘between’ effect, was very important to the growth of manufacturing productivity. Similarly, a study of three high-tech industries by Bartelsman and Dhrymes (1998) found that the reallocation of resources to more productive plants accounted for about 25% of total factor productivity growth between 1972 and 1986. Other scholars, however, have taken a different view on the evidence, privileging the ‘within’ effects much more than the ‘between’ effects. The OECD (2001a,b), for example, in a number of studies has argued to the effect that a large fraction of aggregate labour productivity growth is due to firm level ‘within’ effects alone and that while exit processes boost aggregate productivity, changes in market shares play a OFCE/June 2006 J. Stanley Metcalfe and Ronnie Ramlogan

–  –  –

6. Similar results are reported in Hazeldine (1985) and Foster et al. (2001).

7. A more recent study of productivity growth in Germany, pre and post unification, also finds good evidence for ‘between’ effects and notes that they vary considerably across different industries (Cantner and Kruger, 2004, 2005).

8. In his survey of industry dynamics processes in LDCs, Tybout (2000) discusses some limited empirical evidence in favour of relatively high rates of turnover in plants and employment, the finding that efficiency, compared to survivors, is lower in exiting plants and in entrant plants, and that these categories rarely account for more than 5% of total output in any year. Carlin et al., 2001 discuss productivity growth decompositions for the transition economies of Eastern Europe. This empirical literature provides striking empirical verification of the dynamic nature of competition and of the importance of distinguishing selection of activities in plants from selection of firms.

OFCE/June 2006

CREATIVE DESTRUCTION AND THE MEASUREMENT OF PRODUCTIVITY CHANGE

Clear cut conclusions cannot be drawn from the studies available but some lessons are clear. It matters greatly whether one is computing the effects on labour productivity growth or total factor productivity growth;

within effects seem to arise more significantly with respect to the latter than the former. Secondly, the precise decomposition method also matters very greatly in assigning different effects as explanations of productivity change at the population level. Thirdly, and hardly surprisingly, measurement across different populations leads to different outcomes.

Why does this matter?

Most fundamentally the resolution of the question is important for the light it throws on the dynamics of development under market capitalism and the role played by market forces in the process of creative destruction.



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