EJ-Dosi-1997-OpportunitiesPatternsTechChange-2957752

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Opportunities, Incentives and the Collective Patterns of Technological Change
Author(s): Giovanni Dosi
Source: The Economic Journal, Vol. 107, No. 444 (Sep., 1997), pp. 1530-1547
Published by: Wiley on behalf of the Royal Economic Society
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 The Economic Journal, 107 (September), I530-I547. (C Royal Economic Society I997. Published by Blackwell
 Publishers, io8 Cowley Road, Oxford OX4 iJF, UK and 350 Main Street, Malden, MA 02I48, USA.
 OPPORTUNITIES, INCENTIVES
 AND THE COLLECTIVE PATTERNS OF
 TECHNOLOGICAL CHANGE*
 Giovanni Dosi
 In a few pages, in the introductory article for this debate, Vernon Ruttan
 succeeds in the unlikely task of flagging many issues at the core of the economic
 interpretation of technological change (and by doing so he implicitly addresses
 also a few sensitive spots for the economic discipline at large). Here I will not
 attempt to provide any thorough view of what I consider the achievements and
 limitations of the current state-of-the-art (see, however, Freeman (I 994) for a
 critical survey which I largely share). Rather, I shall put forward a series of
 remarks which, hopefully, could be seen as part of a much wider, and still
 largely unexplored, research programme.
 As a premise, just note that some form of attention to technology-related
 phenomena has spread over the last 20-30 years from small enclaves of
 heterodox economists and economic historians to become an important
 concern even for quite mainstream theories of e.g. the firm, industrial
 organisation, macroeconomics, trade, growth, etc. From 'patent races' all the
 way to 'New Trade' and 'New Growth' theories and even Real Business Cycle
 macro models, technical change has drawn a consideration which is less by
 default than it was, say, in Robert Solow's original growth models orJoe Bain's
 barriers-to-entry views on industrial structures. And, in parallel, empirical
 studies - at the levels of specific technologies, firms, sectors and countries -
 have boomed (for overviews cf. Dosi (I988), Nelson (I993), Freeman (I982,
 I 994), Cohen (I 995) and Granstrand (I 994), among others). So, at least in this
 sense, those 'decreasing returns' to the economics of technical change suggested
 by Ruttan do not seem to have set in. However, Ruttan's paper raises also
 substantive questions about the relative success of three interpretative
 perspectives - which he calls 'induced', 'evolutionary' and 'path-dependent'.
 In the following I shall argue that an evolutionary perspective, broadly
 defined, can easily accommodate both inducement effects and path-dependent
 patterns of technical change.
 Let me start from what I consider the major building blocks of an
 * Support to the research by the International Institute of Applied Systems Analysis (IIASA),
 Laxenburg, Austria and the Italian National Research Council (CNR) is gratefully acknowledged.
 Comments by Vernon Ruttan and Huw Dixon (Editor) and discussions with Andrea Bassanini, Valerie
 Revest, and Marco Valente have contributed to mould the paper to the present shape. The usual caveats
 apply.
 [I530
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 [SEPTEMBER I997] TECHNOLOGICAL CHANGE I53I
 evolutionary theory (admittedly in its maximal form: most models and
 empirical analysis cited below share only a subset of these features).'
 I. EVOLUTIONARY THEORIES OF ECONOMIC CHANGE
 i. As Sidney Winter used to summarise it, the methodological imperative of
 evolutionary theories is dynamicsfirst! That is, the explanation to why something
 exists intimately rests on how it became what it is. Or putting it in terms of
 negative prescriptions: never take as a good 'explanation' either an existence
 theorem or a purely functionalist claim (entity x exists because it performs
 function y ... ).
 2. Theories are explicitly microfounded, in the sense that they must involve or at
 least be consistent with a story of what agents do and why they do it.2
 3. Agents have at best an imperfect understanding of the environment they live
 in, and, even more so, of what the future will deliver. Hence, 'bounded
 rationality' in a very broad sense is generally assumed.
 4. Imperfect understanding and imperfect, path-dependent, learning entails
 persistent heterogeneity among agents, even when facing identical information
 and identical notional opportunities.
 5. Agents are always capable of discovering new technologies, new
 behavioural patterns, new organisational set-ups. Hence, also the continuous
 appearance of various forms of novelty in the system.
 6. Relatedly, while (imperfect) adaptation and discovery generate variety
 (possibly in seemingly random fashions), collective interactions within and
 outside markets, perform as selection mechanisms, yielding also differential growth
 (and possibly also disappearance) of different entities which are so to speak
 'carriers' of diverse technologies, routines, strategies, etc.
 7. As a result of all this, aggregate phenomena (e.g. regularities in the
 growth process or in industrial structures, etc.) are 'explained' as emergent
 properties. They are the collective outcome offar-from-equilibrium interactions and
 heterogeneous learning. Finally, they often have a metastable nature, in the sense
 that while persistent on a time-scale longer than the processes generating them,
 tend to disappear with probability one as time goes to infinity.3
 This is not the place to review the growing number of contributions which
 share some or all of these seven broad methodological building blocks.4 For the
 purposes of these comments it will suffice to mention the flourishing number of
 formal models and historical interpretations of economic growth as an
 evolutionary process propelled by technical change which have followed the
 1 More detailed discussions of evolutionary theories, following the seminal work of Nelson and Winter
 (I982), are in e.g. Coriat and Dosi (995), Hodgson (993), Dosi and Nelson (I994), Nelson (995),
 Silverberg and Verspagen (I995).
 2 Note, however, that there are a few 'aggregate' (i.e. non-microfounded) models which are nonetheless
 'evolutionary' in spirit (for a survey, Silverberg and Verspagen (I995)).
 3 On the notions of 'emergence' and 'metastability' cf. the discussion in Lane (I993). (The most
 noticeable exception to 'metastable' properties are irreversible lock-in phenomena, taken literally, so that
 collective regularities are limit properties of adaptation/learning process: see also below.)
 4 Note that, given the above quite broad definition of the 'evolutionary research programme', it may well
 cover also the contributions of authors who would not call themselves 'evolutionist' in any strict sense.
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 I1532 THE ECONOMIC JOURNAL [SEPTEMBER
 work of Nelson and Winter (1 982). (See among others Dosi et al. (i 988), Day
 and Eliasson (i 986), Silverberg and Verspagen (I 994), Conlisk (1 989),
 Chiaromonte and Dosi (I993), Silverbergand Soete (I993) and the discussion
 in Nelson (I 995) Coriat and Dosi (I 995) and Silverberg and Verspagen
 (I995).)
 Formal models have gone together with a rapidly growing number of
 empirical studies - inspired to different degree by evolutionary ideas - aimed
 at the understanding of the processes by which knowledge is produced, diffused
 and economically exploited. Since the characteristics of these processes bear
 major consequences also in terms of possible 'inducement' mechanisms and
 path-dependency, let me consider them at some length.
 II. SOURCES AND DRIVERS OF TECHNICAL CHANGE: WHAT HAVE WE
 OBSERVED INSIDE THE BLACK BOX ?
 In order to assess better what one has found so far 'inside the blackbox' of
 technological change,5 it is useful to distinguish between four (albeit
 interrelated) objects of analysis, namely, first, (the changes in) innovative
 opportunities (strictly speaking, the 'sources' of technical change pertain to this
 domain); secondly, the incentives to exploit those opportunities themselves;
 thirdly, the capabilities of the agents to achieve whatever they try to do,
 conditional on their perceptions of both opportunities and incentives, and,
 fourthly, the organisational arrangements and mechanisms through which tech-
 nological advances are searched for and implemented.
 Telegraphically,
 'the picture which emerges from numerous studies of innovation in firms
 is one of continuous interactive learning. Firms learn both from their own
 experience of design, development, production and marketing ... and from
 a wide variety of external sources at home and abroad - their customers,
 their supplies, their contractors..., and from many other organisations -
 universities, governments laboratories and agencies, consultants, licensors,
 licencees and others' (Freeman (I994), p. 470).
 Complementarity between sources internal and external to the firm is the
 general property (cf. for example Cohen and Levinthal (1 989), Malerba (I 992)
 and the overview in Freeman 0994)). And in fact a good deal of empirical
 work has gone into the understanding of the inter-sectoral and inter-
 technological differences in the relative importance of these various forms of
 opportunities - including, of course, those provided by scientific advances (cf.
 Klevorick et al. (I 993), Rosenberg (1 982), Freeman (1 982)). I shall turn below
 to modeling-related issues. However, note already that the evidence here is
 quite far from any view of exogenous shift in the opportunity set. (In fact, it is
 sometimes the case that even scientific advances are triggered by firm-
 sponsored technological developments and not the other way round, cf.
 Rosenberg (1994) and Freeman (I982).)
 5 Inside the Blackbox is the title of an influential book by Nathan Rosenberg (I982).
 C) Royal Economic Society I997
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Aulus
Destacar
Aulus
Destacar
 1997] TECHNOLOGICAL CHANGE 1533
 Relatedly, one observes a variety of learning processes, ranging from
 institutionalised search processes formally placed in R & D labs all the way to
 much more informal procedures of 'learning-by-interacting' with customers
 and suppliers (Lundvall, I992; Freeman, I994): again one is beginning to
 draw up sectoral maps of the typical learning patterns, conditional on their
 knowledge bases.
 Another robust 'stylised fact' emerging from studies on innovation and
 diffusion is the persistent heterogeneity in the knowledge and problem-solving
 capabilities that firms embody, their relative stickiness over time, together with
 wide asymmetries in performances, highlighted also by the persistence of
 'inferior' techniques and product characteristics - given the prevailing relative
 prices and demand patterns - and of significant profitability differentials.
 (More on these points in Dosi (I988) and Dosi et al. (I995), Nelson (I98I),
 Winter (I987), Malerba and Orsenigo (I996).)6
 Regarding incentives to innovate, a lot (in my view possibly even too much!)
 attention has been given to the conditions of appropriability of the rent streams
 coming from successful innovations. (An extensive intersectoral analysis of the
 various appropriation mechanism in the US industry from patents to secrecy,
 etc. - is in Levin et al. (I987).) While it is straightforward that some expected
 differential profitability is a necessary condition for private actors to undertake
 expensive and uncertain search efforts, to my knowledge, one lacks any
 convincing evidence that the intensity of search grows monotonically with the
 expected value of the rent streams: on the contrary, it seems, inter-sectoral and
 inter-temporal differences in the propensity of innovating are better accounted
 for, in a first approximation, by differences in opportunities and firm-specific
 capabilities rather than fine variations in profitability incentives (above a
 minimum threshold).
 Finally, one often observes relatively ordered patterns of technical change in
 both spaces of input coefficients and product characteristics (i.e. what I have
 called elsewhere technological trajectories) grounded in rather invariant,
 incrementally augmenting, knowledge bases (i.e. technological paradigms),
 every now and then intertwined by major discontinuities in both the sources of
 knowledge and the directions of change (Dosi, I982, I 988).
 How can these findings, together with the evolutionary perspective sketched
 above, help in explaining also possible inducement mechanisms on the rates
 and directions of technological change?
 III. INDUCEMENTS, SEARCH AND EVOLUTION
 The classic inducement story, recalled in Ruttan's article, had the pioneering
 merit of trying to provide some analytical link between today's prevailing
 economic conditions (be they relative prices or demand patterns), allocative
 6 Incidentally note also that technology-focused studies have recently found fruitful interchanges with
 firm-focused ones highlighting organisation-specific problem-solving capabilities as part of the answer to the
 questions of (i) why firms exist, (ii) why do they have the boundaries which one observes, and (iii) why are
 they different in behaviours and performances. See, among others, the special issue of Industrial and Corporate
 Change, no. I, I 994, on 'Dynamic Capabilities' edited by David Teece and Gary Pisano; Teece et al. (I 994);
 Montgomery (I 995) .
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 I534 THE ECONOMIC JOURNAL [SEPTEMBER
 decisions by the economic agents and tomorrow's technological possibilities.7
 However, it does so with pitfalls already mentioned by Ruttan and others. It
 blackboxes notional opportunities of innovation into the rather farfetched
 notion of an Innovation Possibility Frontier (IPF). It is rather cavalier on the
 ways relative prices (or demand patterns) affect incentives to search in
 particular factor-saving directions (unless one introduces quite ad hoc
 hypotheses on the shape of the IPF, on elasticities of substitutions, etc.). It is
 rather shaky in its microfoundations. And, finally, by folding together sources
 and incentives to innovate, it implicitly assumes a smooth response of
 knowledge-creation to market-signals.8
 Conversely, there is an evolutionary story of 'inducement' which, in my
 view, sounds much more convincing. It runs more or less as follows.
 Abandon the idea that there is any well defined IPF anywhere. Rather, each
 body of knowledge specific of particular technologies (each 'paradigm')
 determines the notional opportunities of future technical advance and also the
 boundaries of the set of input coefficients which are feasible on the grounds of
 that knowledge base. So, for example, the semiconductor-based paradigm in
 microelectronics orthe oil-based paradigm in organic chemicals broadly
 determine the scope and directions of technical progress - i.e. the 'trajectories'
 in both product and process technologies (for example, miniaturisation and
 increasing chip density in semiconductors; polymerisation techniques in
 organic chemicals, etc.). Together, technological paradigms bind the scope for
 dynamic interfactoral substitution (so that, for example, irrespectively of the
 relative price of energy, it is difficult to imagine, given our current knowledge
 base, a technology for the production of hyperpure silicon which would not be
 very energy-intensive...).
 It follows also from the foregoing remarks that the ways opportunities are
 tapped and the degrees of success in doing so depend to a good extent upon the
 capabilities and past achievements of economic agents. So, more technically,
 think of 'opportunities' as some measure on the set of input coefficients which
 are reachable at time t, with positive probability, conditional on the vector x>(t)
 of coefficients that agentj (j = i, ..., n) masters at t. And, straightforwardly,
 capabilities can be seen as the transition probabilities, specific to eachj for any
 given search effort.9 'Inducement', lato sensu, can work in four ways.10
 First, changes in relative prices and demand or supply conditions may well
 affect search heuristics. This is what Rosenberg (I976) has called focusing
 devices, and historically documented in a few cases of supply shocks and
 technological bottlenecks, from the continental blockade during Napoleonic
 7 In a different fashion, the endogenisation of technical advances resulting from explicit investment in
 knowledge-augmentation is of course also a central theme of New Growth theories, but its simpler (one-
 dimensional) account of technical progress cannot address the question of the directions of change.
 8 For a thorough critique of that particular version of inducement theories which treat innovation as
 'demand-pulled', cf. Mowery and Rosenberg (979). See also below.
 9 This to make things simple: in a more complicated but realistic account, allowing for imitation,
 transition probabilities of each j should depend also on the states achieved but all other agents and some
 metrics on their distances (cf. Nelson and Winter (I982) and Chiaromonte and Dosi (I993)).
 10 Most elements of this basic story can be found in Nelson and Winter (1982), Chapter 7.
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 I997] TECHNOLOGICAL CHANGE I535
 wars to late nineteenth century history of mechanical technologies ... (Bounded
 rationality and lack of 'rational' technological expectations stand behind the
 relevance of these behaviourally-mediated inducements effects. But, of course,
 evolutionary theories - quite in tune with empirical evidence - are at ease with
 these assumptions, see also below.)
 In this case, 'inducement' stands for the influences that the perception of
 environmental conditions exert upon the problem-solving activities which
 agents decide to undertake.
 Formally, it is like saying that market shocks induce different partitions of
 the notional search space attainable at t, and focus search in those regions
 where one is more likely to find, say, savings on the inputs which are perceived
 as scarce and more expensive. Note that, for example, part of the (highly
 convincing) interpretation of inducements to mechanisation in the American
 nineteenth century economy suggested by Paul David (I 975) can be rephrased
 in this way without any analytical loss, except the dubious commitments to
 rational choice with reference to a mysterious IPF.
 The earlier caveat that knowledge bases constrain the directions of search is
 crucial as well, and this applies to both single technologies and broad
 technological systems (or 'techno-economic paradigms' in the sense of Freeman
 and Perez (i 988)) which dominate in the economy over particular phases of
 development (e.g. steam power, electricity and electromechanical technologies,
 microelectronics and information technologies, etc.). Consider for example,
 Moses Abramovitz's proposition that 'in the nineteenth century, technological
 progress was heavily biased in a physical capital-using direction [and] it could
 be incorporated into production only by agency of a large expansion in physical
 capital per worker... [while] ... in the twentieth century... the bias weakened
 [and] may have disappeared all together' (Abramovitz, I993, p. 224). As I
 read it, it is a proposition on the nature of the knowledge available at a certain
 time -in the society and the ways it constrains its economic exploitation,
 irrespectively of relative prices. That is, the proposition concerns the boundaries
 of the opportunity set attainable on the grounds of the available paradigms"
 and the limits to possible 'inducement effects'.
 Second, inducement may take the form of an influence of market conditions
 upon the relative allocation of search efforts to different technologies or
 products. Note that while the former inducement process concerned the
 directions of search (e.g. in the input space), this second form regards the
 intensity of search and, other things being equal, the rates of advance. In the
 literature, it has come to be known as 'Schmookler's hypothesis' (Schmookler,
 I966), suggesting that cross-product differences in the rates of innovation (as
 measured by patenting) could be explained by differences in the relative rates
 of growth of demand. While it is no a priori reason why the perception of
 demand opportunities should not influence the allocation of technological
 efforts, the general idea of 'demand-led' innovation has been criticised at its
 11 A pale image of all that appear even after blackboxing the whole process into aggregate production
 functions, via different elasticities of substitution and factor saving biases. A pertinent discussion is the cited
 work by Abramovitz (I993). Relatedly see also Nelson (I98I).
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 I536 THE ECONOMIC JOURNAL [SEPTEMBER
 foundations for its theoretical ambiguities (does one talk about observed
 demand? expected demand? and how are these expectations formed?)
 (Mowery and Rosenberg, I989). The empirical evidence is mixed. The review
 in Freeman (I 994) concludes that 'the majority of innovation characterized as
 "demand led" ... were actually relatively minor innovations along established
 trajectories", while as shown by Walsh (I984) and Fleck (I988), "counter-
 Schmookler"-type patterns was [the] characteristic of the early stage of
 innovation in synthetic material, drugs, dyestuff...', and robotics (Freeman,
 I 984, p. 480).
 As emphasised by Freeman himself and by Kline and Rosenberg (1 986), the
 major step forward here is the abandonment of any 'linear' model of
 innovation (no matter whether driven by demand or technological shocks) and
 the acknowledgement of a co-evolutionary view embodying persistent feedback
 loops between innovation, diffusion and endogenous generation of further
 opportunities of advancement (see the empirical remarks above).
 Both mechanisms of 'inducement' discussed so far ultimately rest on the
 ways changing market conditions influence incentives, and in turn, the way the
 latter affect behavioural patterns - either in terms of search heuristics or
 allocation rules. However, changing relative prices can easily 'induce' changes
 in the directions of technical change, even holding search behaviour constant,
 via the selection of the (stochastic) outcomes of search itself. This is the third
 inducement process that I shall consider. Let me illustrate it by recalling the
 very basics of the Markov model of factor substitutionfrom Nelson and Winter
 (I982, pp. I75-92).
 It has been mentioned earlier that 'innovative opportunities', when talking
 about process innovations, can be seen as the (bounded) set of states in the
 space of inputs (per unit of output) attainable starting from an arbitrary
 technique in use at time t. Suppose that search is a random process invariant
 in t (this implies that one excludes both decreasing returns to innovative efforts
 and those inducement effects upon search rules, discussed earlier). When a new
 technique is drawn, it is compared with the one currently in use, given the
 prevailing input prices, and the minimum cost one is obviously chosen. The
 sequence of factor ratios displayed by a firm can be described by a Markov
 process characterised by the transition probability matrix F = [ffk] wherefik
 is the probability that state i follows state k.V2 Note that the transition matrix
 is time invariant but transition probabilities depend on relative input prices.
 This is because of the 'comparison check': holding constant the initial
 technique and the one drawn, whether the latter will be adopted or not might
 depend on relative prices,13 and that choice will set different initial conditions
 for the next draw, etc. The intuition on dynamic-choice-of-technique
 inducement suggests that if the relative price of some input increases, the
 12 Nelson and Winter, quite in tune with the general idea that there are 'paradigm-based' constraints to
 the scope of factor substitution, assume that factor ratios can assume only N possible values; thus
 i,k= I,...N.
 13 It obviously does not whenever the newly discovered technique is more efficient in terms of every input
 - a case which evolutionary theories easily allow.
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 I997] TECHNOLOGICAL CHANGE I537
 transition probabilities, loosely speaking, of 'getting away' from the techniques
 which intensively use that input will also increase. And in fact, Nelson and
 Winter (i982, pp. I80-92) establish the result, in a two-input case, that, with
 the appropriate ordering in terms of relative input intensities, the transition
 matrix F (based on the new relative prices) stochastically dominates the 'old'
 one, F. It is an appealing result, resting so far on many formal qualifications,
 but certainly worth further exploration.'4 The bottom line is the following.
 Even if opportunities do not change and agents do not perceive variations in
 relative prices as incentives to change their search rules, it is enough that
 relative prices enter into the criteria of choice between what has been found by
 search and what is already in use, in order to determine - in probability -
 'induced' changes in the patterns of factor use, at the level of individual firms
 and whole industries.'5
 Fourth, and complementarily, assume that agents are totally inertial in their
 production routines (i.e. in fact there is no innovative search): even in this
 extreme case, market selection will increase the frequency in supply - i.e. the
 market shares of agents who happen to embody the 'better' techniques,
 conditional on prevailing prices - via their differential ability to invest in
 production capacity.
 It is revealing to compare the foregoing interpretation of 'inducement' with
 the more conventional ones, reviewed in Ruttan's article (in this issue of this
 JOURNAL). In the evolutionary view, to summarise, one tries to disentangle
 three sources of 'inducement' related to (a) changes in microeconomic rules of
 search, affecting the direction of exploration in the notional opportunity space;
 (b) changes in the allocation of resources to search efforts (irrespectively of its
 'directions'); and (c) market-induced changes in the selection criteria by
 which some techniques or products are compared with alternative varieties.
 And, (d) it does that in ways that easily allow for endogenous interactions (i.e.
 ' co-evolution') between the incentive structure (stemming from relative prices
 and demand patterns), on the one hand, and learning capabilities, on the
 other. In this respect, the article by Gavin Wright, in this issue of this JOURNAL
 is an excellent illustration of the point. Even in the case of mineral resources
 -i.e. the nearest one can get to a 'naturally' determined opportunity set -
 Wright shows opportunities themselves have been the outcome of both public
 and private search efforts (see also David and Wright (I 997)). Conversely,
 more conventional views of inducement, by making stronger commitments to
 both optimising rationality and equilibrium, obscure - in my opinion - the
 distinctions between behavioural effects and system level ('selection') effects,
 and, together, render very difficult any account of the sector-specific and
 14 Among other points, the clarity of representation in terms of a time-invariant finite-state Markov
 process has its inevitable downside in that, - taking seriously the question of 'what happens as time goes to
 infinity?' -all persistent states return infinitely often in the limit (see also below on path-dependency).
 However, it should not be formally impossible to make transition probabilities phase-space dependent, thus
 giving also more persistence to the weight of past 'inducements'.
 15 I do not dare extend this conjecture to whole economies, since no evolutionary model has so far
 adventured seriously into the exploration of multi-sectoral systems, linked by input-output relations,
 checking also the empirical plausibility of phenomena like reswitching of techniques, etc. - which appeared
 prominently in the theoretical debates in the I970S and disappeared by magic later on.
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 I538 THE ECONOMIC JOURNAL [SEPTEMBER
 period specific patterns of knowledge accumulation. The blackboxing under
 unobservable constructs like IPF's, 'elasticities of substitution', etc. just helps
 to rationalise the dynamic outcome while obscuring the processes driving it.
 IV. PATH-DEPENDENCIES
 In the broadest sense, one should expect path-dependency whenever in
 presence of nonlinearities and increasing returns of some kind. And, indeed, an
 evolutionary world characterising the endogenous generation of innovative
 opportunities is inevitably rich in positive feedbacks.16
 The very possibility that agents can access new information and knowledge17
 through their own actions already entails the possibility of some form of
 increasing returns. It is a point repeatedly emphasised by Kenneth Arrow
 (I962, i I987) and it has become one of the starting point of New Growth
 Theories (cf. Romer (I986, 1990, I994); Grossman and Helpman (i99i)).
 Briefly, this is because the main cost of acquisition of information is upfront, but
 thereafter information can be utilised at any scale of output, it is not used up
 through production itself (but if anything increased through phenomena like
 learning-by-doing) and it has non-rival use (if I use it, this does not prevent you
 from using it too...).
 Other (related) sources of increasing returns have been recognised since the
 origin of the economic discipline, like the famous proposition by Adam Smith,
 revisited by A. Young and neglected for another fifty years, on the positive
 feedback between size of the market, division of labour and specialisation-
 driven increases in productivity.18 Moreover, classic contributors to growth
 and development theories, including Gerschenkron, Hirschman, Kaldor, and
 Myrdal when suggesting processes of 'cumulative causation' and 'virtuous' or
 'vicious cycles', clearly had self-reinforcing dynamics in mind.
 Contemporary analyses of the patterns of technological change add other
 potential sources of increasing returns, associated,for example, with what have
 been called the 'cumulativeness' of technological advances (i.e. the probability
 of future discovery being positively influenced by past realisations), network
 externalities, learning-by-using, etc.
 In brief, one is at last acknowledging a wide set of positive feedbacks (and,
 thus, nonlinearities, and, thus, path-dependencies) in economics in general,
 and in particular in the domain of technical change.'9 How important they are
 and what form they take is primarily an empirical question (and the answer is
 likely to be conditional on particular sectors, technologies, etc.). However, one
 16 Note that evolutionary worlds (in the earlier definition) are almost by necessity nonlinear, but the
 converse does not hold (for example putting spaghetti to boil involves highly nonlinear dynamics, path-
 dependencies in the ways bubbles form in the water, phase-transitions, etc., but one would hardly call it an
 evolutionary process!).
 17 I discuss the difference between the two in Dosi (I995).
 18 It should be clear that increasing-returns phenomena may well be (and often are) quite distinct from
 sheer economies of scale. The example of division of labour is a good case to the point.
 9 As known, non-linear dynamics (with the related dependence on initial conditions) have been found
 to be a frequent occurrence also in otherwise highly orthodox models in macroeconomics, international
 trade, etc., but in these short notes it is impossible to discuss in general how far one can stretch standard
 neoclassical models in order to account for history.
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Aulus
Destacar
 I997] TECHNOLOGICAL CHANGE I539
 would like to have some 'theoretical tales' - as George Akerlof would put it -
 providing some guidance on the nature of the processes involved, and also
 helping in answering questions like: how important path-dependency itself is?
 Does it involve phenomena of irreversible lock-in? What are the consequences
 in terms of efficiency? And, moreover, can one reconcile path-dependency/
 positive feedbacks with individual forward-looking rationality?
 At a first glance, the ways evolutionary models a la Nelson-Winter treat
 increasing returns to knowledge appear to be quite different from the story on
 path-dependency that emerges, say, from Arthur et al. (I987), Arthur (I989)
 or David (I985). The interpretation that I want to suggest here, however,
 is that the two basic stories are to a good extent complementary, and that
 the remaining differences highlight major theoretical issues worth further
 exploration.
 In the barebone Nelson-Winter (NW) story (and in many others, cited
 above), heterogenous agents are so to speak 'carriers' of different behavioural
 and technological traits and interact in some collective environment, typically
 a market which rewards or penalises them on the grounds of some revealed
 performance, ultimately related to their profitabilities. In turn, the latter
 influence the ability of each agent to grow and its survival probabilities. In the
 discrete time formulation, next 'period', each agent may well search again for
 new technologies and new behavioural rules, undertakes production, and,
 again, faces its competitors in the market. And so on.20 In the last resort,
 dynamics rests on some learning processes (search, innovation, imitation by
 individual agents), on the one hand, and some selection mechanism on the
 other. Within the philosophy of the story (although not always in models that
 have been already implemented), path-dependency can arise at least at three
 levels. First, it may regard the patterns of technological learning of individual
 agents. Secondly, it may concern their behavioural' rules.21 Thirdly, path-
 dependency may be a collective property of the time profile of aggregate rates
 of growth of output, average productivities, factor intensities, product
 characteristics, etc.
 Conversely, take what I shall call in a shorthand the Arthur-David (AD)
 story.22 It is essentially a story of diffusion (although in the background there
 are implicitly incremental innovation of the products or technologies candidates
 to be adopted). In its simplest version, multiple producers offer two or n
 alternative technologies and the adoption choices feedback upon the incentive
 of the next adopter via (a) sheer imitation effects and endogenous preferences;
 (b) network externalities; or (c) learning 'induced' upon the producers of the
 chosen technology which then improve their quality and/or price.
 Said like that, one can see a nice complementarity between behaviourally
 20 The story can in principle be extended by allowing, for example, for multiple selection environments,
 e.g. both product- and financial markets; enlarging the dimensionality of the selection space, e.g. by
 introducing diverse output characteristics; testing for different interaction mechanisms ....
 21 Organisational adaptation, inertia and lock-in is a theme widely discussed in organisational disciplines:
 for a suggestive discussion of the evolutionary roots of these phenomena cf. Levinthal (1992).
 22 That story also has many ancestors, in economic history and even in formal economic theory (cf.
 Atkinson and Stiglitz, I969).
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 1540 THE ECONOMIC JOURNAL [SEPTEMBER
 richer evolutionary models (the former) and sort of reduced-form ones (the
 latter), which, however, vividly highlight dynamic-increasing-return inter-
 actions between demand and supply of alternative technologies. And, with
 that, also (a) how 'history matters' (small initial fluctuations bear long-term
 macro effects); and (b) the possibility of lock-in into notionally inferior
 technologies. More subtle issues, however, differentiate the two stories, and
 disentangling them is the challenge that the evolutionary research programme
 ought to face urgently. Let me end by outlining some of them.
 V. MICROFOUNDATIONS AND PATH-DEPENDENCY
 It happens that evolutionary models in the NW model spell out a set of control
 variables which agents are in principle asked to master, together with some
 empirically-derived hypotheses on how they do it. The general acknow-
 ledgement of bounded rationality and heterogeneity comes as a natural
 corollary of the fact that even the sophisticated theorist would have
 overwhelming difficulties in finding out the appropriate intertemporal
 optimisation schedules, given the complexity of the problem. But, of course, the
 inevitable consequence is that the dynamics are not only path-dependent - in
 the sense of initial conditions and early stochastic fluctuations - but also
 behaviour-dependent - in the sense that the nature and distributions of agents'
 behaviour affects long-term outcomes, for identical initial conditions, oppor-
 tunities and incentives. Here come also the full challenge for evolutionary
 models to map classes of behaviours robustly into classes of collective long-term
 outcomes. (And this is also where an evolutionary perspective links with studies
 of organisational behaviour, on the one side, and analyses of economic
 institutions, on the other.) Works developed in the 'AD mode',23 on the
 contrary, are most agnostic on the behavioural foundations - a task made
 easier by the fact that generally the decision setting is simple enough as to make
 redundant any theoretical commitment on the degrees of 'rationality' of the
 agents ... (would you choose A or B, given that the majority of your sample has
 chosen A and it is convenient for you to choose with a majority/minority
 rule?...). So given the simplicity of the decision problem, decision rules can
 either be interpreted as based on some (stochastically perturbed)routine or
 alternatively as the outcome of (myopic) optimisation. But, beyond those
 simple set-ups, the type of chosen microfoundation matter, and, of course, the
 inclination of evolutionary theorists is that of setting them 'phenomenologi-
 cally' by abstracting some invariances from what agents actually do in
 circumstances similar to those purported by the model.24
 In this respect, note that the evolutionary story - based on heterogeneity of
 23 The fact that these are modelling styles and not deeper methodological commitments is shown, at least
 in the case of the author of these notes, by the fact that, according to the different objects of analysis, one
 has chosen either set of instruments: compare for example Chiaromonte and Dosi (I993), Silverberg et al.
 (I988), Dosi, Fabiani et al. (I994) with Dosi, Ermoliev and Kaniovski (I994), and Dosi and Kaniovski
 (I 994).
 24 More detailed discussion of decision and learning in evolutionary environments are in Nelson and
 Winter (I982), Winter (I 975), Dosi, Marengo and Fagiolo (I996).
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Aulus
Destacar
 I997] TECHNOLOGICAL CHANGE I54I
 expectations, competences and behaviours - and the alternative maximising
 agent/equilibrium story may often be rendered observationally equivalent at
 aggregate level by inventing the appropriate restrictions on opportunity sets,
 elasticities, risk-aversions, intertemporal preferences, etc. However, such
 observational equivalence breaks down at more micro-levels of analysis.
 To begin with, the 'stylised' facts, briefly mentioned above concerning
 persistent performances asymmetries across firms are, in my view, a robust
 circumstantial evidence against 'rational'/equilibrium microfoundations of
 technological search.25
 More direct computations of any assumption that agents involved in
 technological innovation/imitation are in some sense 'rational', and in
 particular hold 'rational technological expectations' are widespread in the
 applied literature, although not likely to convince the religious believers in
 ' rationality' - whatever that means in this context.26 For example, Rosenberg
 (i 996) - cited also in the companion article by Wright - highlights systematic
 mistakes of most major innovators in forecasting the economic impact of what
 they are doing. And, this is fully supported by many longitudinal case studies.
 For example, from what I have learned from the history of the semiconductor
 industry (Dosi (I984); see also Malerba (I985)), search efforts -in terms of
 both size of investments and direction of investigation - have been a far cry
 from what a rational (or, often even modestly reasonable) agent should have
 expected about outcomes. More generally, Freeman (I982) presents over-
 whelming evidence that grossly 'boundedly rational' criteria for evolution of
 R & D projects are often involving systematic underestimation of costs,
 cognitive path-dependencies, irresponsiveness to environmental feedbacks,
 etc.27
 Even more broadly, most of applied business economics insists that the very
 notion of 'strategy' is at best an ensemble of fuzzy and often contradictory
 heuristics (within an enormous literature, see for example, Starbuck (i989)).
 Havin,g said that, this should not be taken at all as a support for the idea that
 'outside full rationality anything goes...'. On the contrary, two complementary
 tasks are high on the evolutionary research agenda, namely first, a more precise
 identification of the empirical regularities regarding business behaviour in
 general and in particular with regard to innovative search; and, secondly, the
 25 Certainly, all this makes any 'representative agent' reduction of the underlying search dynamics utterly
 implausible. However, these are imaginative attempts to account together for heterogeneity in capabilities,
 individual forward-looking rationality and equilibrium. See, for example, Joranovic and MacDonald
 (I 994) -
 26 Notice incidentally that this is not meant as an outright objection to the usefulness in some
 circumstances, of sort of thought experiments grounded on fully 'rational' agents. For example, the way I
 understand the spirit of Paul Romer's exercises on endogenous growth is to show, among other things, that
 even if one had forward-looking representative agents, still one would get systematic divergences between
 endogenously generated and socially optional ratios of growth. And, a fortiori this applies when the
 underlying 'rationality' requirement is absent. All this, however, is quite different from taking seriously such
 microfoundations as descriptively pertinent.
 27 In the same spirit, in Dosi and Lovallo (I 995), we argue that a good deal of evidence on corporate entry
 can be explained in terms of decision biases such as 'overconfidence' and 'illusion of control'.
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 1542 THE ECONOMIC JOURNAL [SEPTEMBER
 analysis of the statistical conditions under which a heterogenous and messy
 microeconomics yields nonetheless relatively stable aggregate properties.28
 VI. SELECTION DYNAMICS AND THE NOTION OF 'FITNESS
 I have already mentioned that an evolutionary interpretation of technical
 change (and more generally economic dynamics) has one of its building blocks
 in some selection process - whether it is done by markets or by other
 institutional arrangements (e.g. hospital authorities in the case of medical
 technologies, of defence ministries for military equipment...). Selection is
 important, of course, because agents are assumed to carry with them different
 technical and economic solutions to similar problems. Some of them turn out
 to 'get it right' and others to 'get it wrong'.
 But what does 'wrong' or 'right' mean? The question bears, more
 technically, on the dimensions of the selection landscape and its functional
 form. Take the simplest case (which is not very far from the first generation of
 models in the NW mode) where technological search is about producing a
 homogeneous output as cheaply as one can, given input prices. Therefore, costs
 (or better the difference between industry-level output prices and firm-specific
 costs) define the selection landscape, which determines also the 'fitness' (and
 relatedly the potential to grow, shrink or die) of individual entities, and of the
 techniques that they embody. Assuming that innovative opportunities are
 notionally unlimited, and with some further restriction on the shape of the
 demand curve, it is easy to construct a landscape which has no fitness
 maximum (with costs that go to zero as time goes to infinity).
 Note two things. First, at each arbitrary time the 'fitness' of individual
 entities or techniques is a contingent notion, because it depends on the
 distribution of all entities and techniques at that time, which in turn is the
 outcome of all the stochastic history of arrivals, plus selection, up to that time.
 Secondly, the implied idea of path-dependency is only a weak one, since one
 knows where the process will converge to in the limit, irrespectively of initial
 conditions. Moreover, given relative prices, one is able to say what is 'better'
 and what is 'worse' in a history-independent fashion (because that depends
 unequivocally on lower or higher costs of production).
 This basic story, however, can be refined and easily take on board more
 path-dependent phenomena. For example, on the grounds of the same basic
 process, the interaction between search patterns and relative prices can
 produce long-term path-dependencies, e.g. whenever some initial input prices
 'focus' search in a particular region of the technology space, which in turn
 affects search competences and probabilitiesof discovery the next round, etc.29
 In this example, and in many possible variations on the same theme, what can
 28 This links with the attempts of doing the same thing on the demand side: see the inspiring work by
 Hildebrand (I994).
 29 One cannot discuss here the formal issues involved in the different representations and their analytical
 tractability (for example the fact that the simpler dynamics described above can be sketched as a time-
 invariant Markov process, while time-invariancy is likely to be lost when accounting for many forms of path-
 dependent learning).
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 I997] TECHNOLOGICAL CHANGE I543
 generate path-dependent trajectories of innovation is the local and cumulative
 nature of learning, involving dynamic increasing returns to particular bodies of
 knowledge. Still, one can have path-dependency on the learning side together
 with path-independent attributes of the various technologies over which
 selection operate.
 The AD modelling style pushes path-dependency even further and implicitly
 suggests that both selection criteria and 'fitness landscapes' ought to be
 considered entirely endogenous: whether the technological winner turned out
 to be the internal combustion engine or the steam engine or the electrical car
 - so the story goes - depended primarily on a series of small events early on in
 the diffusion history, which got amplified by dynamic increasing returns. In
 these circumstances, of course, there is no way to define what is 'good' or 'bad',
 either for producers or adopters, without knowing the whole history of the
 process up to the time when the question is asked (and, even less so, ahead in
 time).
 VII. DETECTING PATH-DEPENDENCE
 How strong path-dependency is, to repeat, seems to me to be mainly an
 empirical question, and a major one for both economic historians and students
 of technology. There is, however, the tricky methodological issue of 'how do
 you recognise path-dependency when you see it?'. After all, we just observe one
 sample path, since we can only see the one history that actually occurred. And,
 of course, in order to know whether the occurrence of what you see now is path-
 dependent or not one ought to be able to 're-run history' repeatedly - which
 is very rarely the case in human affairs.30
 An extreme perspective on this issue is what I shall provocatively call Mr
 Pangloss' view. Its main claim is the analytical irrelevance of the nature of the
 process leading to the observed state s(t) of the system at t, in all circumstances
 when (a) that state is not remediable (in the sense that, at t, there is no state
 s'(t) which is preferable and can be achieved with a net welfare gain), and (b)
 agents made the best use of their information along the whole path leading to
 s(t). (A thorough presentation of the view is in Liebowitz and Margolis (I 995),
 but of course the basics are already in Voltaire's Candide.) In this perspective
 the two main tasks of theorists and historians are, first, the rationalisation of
 whatever one observes as an equilibrium, and secondly, the attribution of
 rational purposefulness to all actions which led to the present state.3'
 The evolutionary view in most respects is the opposite one: it tries to
 understand the processes which have led to whatever observed phenomenon
 30 Dosi and Metcalfe (I99I) discusses these issues at greater length.
 31 Note that even if one granted all that, path-dependency in the sense used in these notes cannot be ruled
 out at all: under conditions of network externalities, dynamic increasing returns, etc., individually purposeful
 decisions may collectively lead to both satisfactory outcomes or irremediable disasters.
 And, more generally, what does it mean to be individually 'rational' in a path-dependent world (except
 for omniscient beings who know with infinite precision initials conditions and the full sequence of choices that
 all other agents will make)?
 Note also that path-dependent worlds are likely to violate a notion much weaker than full forward-looking
 rationality, namely no-regret criteria: if I could go back (and, even more so, if we could collectively go back
 in time) would we have done something different? And the answer is possibly positive.
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 I544 THE ECONOMIC JOURNAL [SEPTEMBER
 (with much lower commitments to rationality of the actors involved along the
 path), and, also with the help of formal tales, attempt counterfactual
 experiments ('what would have happened if...'). In doing that it also tries to
 establish, from a normative point of view, the leverages and 'windows of
 opportunities' - as Paul David puts it - for individual and collective actors to
 influence the selection of future paths.
 VIII. SOME ISSUES AHEAD
 Contrary to the rather pessimistic tone of Ruttan's essay, my assessment of the
 current state-of-the-art is the beginning of a very promising interaction
 between empirical analyses, 'appreciative theories' and formal modelling
 which is possibly going to bear fruits well outside the domain of technological
 change.
 More than twenty years ago, when Chris Freeman was writing the first
 edition of his classic Economics of Industrial Innovation, he was correctly lamenting
 the poverty of empirical studies in the field. Now the situation is very different
 and, if anything, the bottlenecks are on the ability of the theory to digest
 observations and 'stylised facts'.
 An illustrative example is growth theory. Despite the nearly universal
 recognition that 'knowledge is important', the ways knowledge-generation is
 generally accounted for is strikingly at odds with the evidence I tried to
 summarise earlier. New Growth models attack the issue more directly, and
 current evolutionary models, in my biased view, go even further (at the expense
 of elegance and analytical tractability). But still there is a long way to go in
 order to incorporate path-dependent learning, micro-heterogeneity, out-of-
 equilibrium interactions, etc. into a robust aggregate story of trade, growth,
 international convergence, divergence, forging ahead and falling behind (more
 on this in Dosi, Freeman and Fabiani (I994)).
 Even more striking is macroeconomics (that area arbitrarily carved out of
 growth theory with the justification, in good Keynesian times, that it handled
 the 'short-term', and, nowadays, on the basic assumption that the future all the
 way to infinity is correctly understood by our representative agent). In this
 area, despite the general perceptions that technology (together with institu-
 tions) have a lot to do with the nature of macro adjustments - and vice versa,
 that macro variables influence the rates and directions of knowledge
 accumulation -, very little has been done so far to explore the implications of
 all that.
 Similar considerations apply to the theory of industrial organisation: one is
 often struck by conflict between the acknowledgement of the empirical
 evidence and the baroque attempts to force it within an equilibrium/forward-
 looking strategic-rationality framework.
 The list of examples is much longer. One of the points that I have tried to
 argue is that an interpretation of technological dynamics which significantly
 relaxes the commitments to equilibrium, rationality and inter-agent hom-
 ogeneity is straightforwardly born by the current evidence, and is also
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 I997] TECHNOLOGICAL CHANGE I545
 beginning to generate formalised theoretical tales - with implications well
 beyond technical change itself, addressingbasic issues like how the future is
 linked to the past, how individual (possibly mistaken-ridden) decisions
 aggregate into collective outcomes, and how problem-solving knowledge is
 accumulated in a society. I am not sure that nowadays younger generations of
 scientists have the 'Kuhnian' spirit of paradigm-subversion, the courage and
 the integrity to take up the challenge. But certainly there are enough empirical
 evidence and theoretical tools to begin with.
 University of Rome 'La Sapienza' and University of Sussex
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 ( Royal Economic Society I997
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	Contents
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	Issue Table of Contents
	The Economic Journal, Vol. 107, No. 444, Sep., 1997
	Front Matter
	Information and Incentives: The Economics of Carrots and Sticks [pp. 1311 - 1329]
	The Econometrics of Macroeconomic Forecasting [pp. 1330 - 1357]
	Bounded Rationality and Strategic Complementarity in a Macroeconomic Model: Policy Effects, Persistence and Multipliers [pp. 1358 - 1374]
	The Labour Supply, Unemployment and Participation of Lone Mothers in In- Work Transfer Programmes [pp. 1375 - 1390]
	Price Formation in an Open Economy: Theory and Evidence for the United Kingdom, 1951-1991 [pp. 1391 - 1404]
	Quantifying the Uruguay Round [pp. 1405 - 1430]
	An Experiment on the Pure Theory of Consumer's Behaviour [pp. 1431 - 1444]
	Credit Constraints in General Equilibrium: Experimental Results [pp. 1445 - 1464]
	A Laboratory Study in Group Polarisation in the Team Dictator Game [pp. 1465 - 1483]
	Policy Forum: Competitiveness and Competitiveness Policy
	Editorial Note [pp. 1484 - 1485]
	Competitiveness Policy in the 1990s [pp. 1486 - 1503]
	UK Competitiveness Policy vs. Japanese Industrial Policy [pp. 1504 - 1517]
	Controversy: The Source and Measurement of Technical Change
	Editorial Note [pp. 1518 - 1519]
	Induced Innovation, Evolutionary Theory and Path Dependence: Sources of Technical Change [pp. 1520 - 1529]
	Opportunities, Incentives and the Collective Patterns of Technological Change [pp. 1530 - 1547]
	Traditional Productivity Estimates are Asleep at the (Technological) Switch [pp. 1548 - 1559]
	Towards a More Historical Approach to Technological Change [pp. 1560 - 1566]
	Reviews
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	Corrigendum: Reviews [p. 1603]
	Software Reviews
	Introduction [p. 1604]
	PcGive Professional 9.0 for Windows [pp. 1604 - 1613]
	X-12-ARIMA (Beta VErsion 1.1a) [pp. 1613 - 1620]
	untitled [pp. 1620 - 1626]
	Book Notes [pp. 1627 - 1650]
	Books Received [pp. 1651 - 1654]
	Current Topics [pp. 1655 - 1656]
	Back Matter [pp. i - xii]