1

THE CO-EVOLUTION OF INNOVATION, DEMAND AND GROWTH*

January 2013

Pier Paolo Saviotti, INRA-GAEL, Université Pierre Mendès-France, BP 47, 38040 Grenoble, France E-mail: pier-paolo.saviotti@wanadoo.fr

Andreas Pyka University of Hohenheim, Economics Institute, Wollgrasweg 23, D-70599

Stuttgart, Germany, E-Mail: a.pyka@uni-hohenheim.de

Abstract In order to explain long-run economic development we analyse in this paper the interplay

between supply-side and demand-side processes. On the supply-side three different

innovation processes are observed and interact: (i) growing productive efficiency, (ii) the

emergence of new sectors and (iii) the increasing quality and differentiation of existing

products. On the demand-side we analyse the meaning of disposable income and varying

preference systems. The analysis is undertaken with the help of a numerical model of

economic growth by the emergence of new industries. Our results show that the time path

of economic development which we observe could not have been generated by taking into

account a supply-side based view on innovations alone. Without making reference to the

formation of an adequate demand, development processes cannot be explained. The three

processes need to be combined because each one individually would not suffice to generate

long run economic development. However, only with the formation of an adequate demand

long run economic development becomes sustainable.

1) INTRODUCTION

Innovation is increasingly recognized as one of the most important factors which contributed

to economic development, at least since the time of the industrial revolution. Although a

very large number of papers studied the relationship between innovation and economic

development, almost all of them focused exclusively on the supply side. Yet it seems obvious

* The research leading to these results has received funding from the European Union Seventh Framework

Programme FP7/2007-2013 under grant agreement n° SSH-CT-2010-266959; project PICK-ME.

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that if there had been no demand for the innovations created since the beginning of the

industrial revolution, such innovations could not have contributed to economic

development. Rosenberg and Mowery (1978) stated „ … rather than viewing either the

existence of a market demand or the existence of a technological opportunity as each

representing a sufficient condition for innovation to occur, one should consider them each as

necessary, but not sufficient, for innovation to result; both must exist simultaneously.“ While

the completely static nature of demand theory - which students still learn in economics

textbooks – together with the absolute indifference to the nature of the goods and services

which in different periods are the objects of consumer choice, represented considerable

obstacles to the analysis of long range patterns of economic development, these faults are

no excuse for the absence of an adequate demand theory, especially within evolutionary

economics. To be fair, some pioneering papers started analyzing the problem of demand.

Reference to some of these will be made in the following sections. However, and in spite of

the value of these pioneering efforts, the construction of a demand theory adequate to

explain the dynamics of an economic system, the growth of which is driven by innovation

and structural change is at its very beginning. In this paper we focus on a number of

problems which are at the heart of such emerging demand theory, especially of a theory

focusing on long range economic development. We are going to analyze the problem at

three different levels:

(i) no innovation could have had an impact on economic growth if nobody had purchased it.

This means that consumers and or users needed to have (a) a high enough income to

purchase the innovation and (b) a preference system compatible with the purchase of the

given innovation;

(ii) the relative dynamics of demand and of process efficiency have an important impact on

the process of economic development. Saturation of demand and of markets can play a

powerful role in affecting the dynamics of the economic system;

(iii) finally, the role of demand is not separable from that of supply. In an innovative

economy search activities affect demand, which in turn affects future search activities and

thus demand in the following periods. This situation can be adequately described as the co-

evolution of demand, innovation and supply.

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Each of these points will now be analyzed separately. We carry out the analysis by means of

our TEVECON model of economic development by the creation of new sectors (Saviotti and

Pyka 2004a, 2004b).

2) HISTORICAL PATTERNS AND CONCEPTUAL BACKGROUND

Evolutionary economics owed its origin to the difficulties encountered when attempting to

use neoclassical economic theory to explain the nature and impact of innovation on

economic development. Given this beginning it is not surprising that until the present most

of the work in evolutionary economics focused on the supply side. On the one hand, this lack

of attention for demand is shared with recent developments in endogenous growth theory

(see for example Romer 1990; Aghion and Howitt 1992; Grossman and Helpman 2001). On

the other hand, models which focus on demand tend to stress structural change and to

belong to a neo-Keynesian approach (Kaldor 1957; Pasinetti 1981; Aoki and Yoshikawa 2002)

without considering long term effects of innovation.

2.1) LITERATURE REVIEW: EVOLUTIONARY DEMAND THEORY

Recently a growing attention has been paid to demand in models of economic growth, both

orthodox (Murphy, Shleifer and Vishny, 1989; Matsuyama ,2002; Foellmi and Zweimuller,

2006) and evolutionary (Bianchi, 1998; Andersen, 2001, 2007; Aversi et al ,1999; Metcalfe,

2001; Saviotti, 2001; Witt, 2001, Ciarli et al 2010). A very recent paper by Nelson and Consoli

(2010) makes the brave attempt to sketch a broad outline of such a demand theory. They

start from the need to reject the neoclassical assumption of perfect and complete

knowledge and, following Simon and March (Simon 1954, 1955; March and Simon 1958),

propose to replace it with a form of bounded rationality similar to the one used to explain

the behaviour of firms. Consumers would then not optimize but construct consumption

routines which guide their choices. In this approach the mechanism whereby routines are

constructed are of crucial importance. In demand as in supply innovation creates

uncertainty. Thus, consumers' knowledge is not just likely to be imperfect but to become

more so when new types of goods and services completely unknown to them are introduced

into the economic system. Especially at the beginning of the life cycle of the emerging goods

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and services very few consumers are likely to be able to overcome this uncertainty. In fact, in

these circumstances also consumers can be expected to act as innovators but to require a

threshold level of human capital to do so (Saviotti 2001). Furthermore, the role of lead

consumers (Malerba et al. 2007), patterns of imitation and differentiation (Saviotti 2001),

routines, user-friendly technologies can be expected to help overcoming the uncertainty

inherent in the emergence of new goods and services. Imitation patterns of lead consumers

can reduce such uncertainty but they are unlikely to lead to a complete homogeneity of a

consumer population. In fact, some consumers wish to imitate those who are better off than

themselves but other will want to distance themselves from most of the others, thus giving

rise to a segmentation of a consumer population (Granovetter and Soong 1986). Another

very important mechanism by means of which consumers can overcome the knowledge

barrier that they face to use new products and services consists of the development of user-

friendly technologies. Such technologies are designed to drastically reduce the amount of

knowledge required on the consumers’ side. For example, the development by Apple,

subsequently imitated by Microsoft, of the visual representation of operations which

secretaries and typists had been using for a very long time and which were very familiar to

them, drastically reduced the knowledge barrier which the average consumer needed to

overcome to be able to use computers to do text processing. This is just one of many

possible examples. The general underlying principle is that if all consumers needed to

understand well how cars, televisions, portable telephones, photographic cameras etc.

function, the markets for all these products would be much smaller than the ones we can

observe. Such general principle can be expressed by means of the twin characteristics

representation of product technology (Saviotti and Metcalfe 1984) by saying that

technologies become user friendly when their use requires only or predominantly

knowledge of the service characteristics of a given technology and not of its internal

structure.

2.2) THE ROLE OF PREFERENCES AND WANTS

All the previous considerations imply that the construction of consumption routines occurs

by means of social interactions, be they within imitation or learning patterns or through the

intermediation of firms in the construction of user-friendly technologies. While this seems

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quite a logical and realistic observation, it could have problematic implications for a theory

of consumer preferences. Routines are not identical to preferences but we cannot expect

the former to be incompatible with the latter. Thus, the social interaction component of

routines, which is likely to be translated into a social interaction component of preferences,

which contradicts the neoclassical assumption that utility functions are based solely on the

resources of each individual. That utility functions could be affected by social interactions

had been noted long time ago by Georgescu-Roegen (1965, 1970, 1976) and by Hirsch

(1976). According to the former the choice function of a peasant in a village depends on

both the quantity of goods/services owned by the individual and by the village institutions.

However, it is not obvious that this non-independence assumption applies only to peasant

villages and that it becomes irrelevant for modern industrialized societies. According to

Hirsch (1976) with increasing affluence people do not feel better off unless they are

relatively better off.

According to the theory of demand presently studied in textbooks preferences can be

considered fixed and the only problem that should concern economists is the allocation of

resources under constraints. However, this assumption is at best valid as a short term

approximation. If our objective is to analyze long range patterns of economic development

the formation of preferences becomes a meaningful task. A fundamental question one

needs to raise here is whether consumers can have preferences for objects of consumption

of which they have never known the existence or the properties. Here we tend to think that

consumers can at best have very fuzzy preferences for these objects of consumption and

that such preferences can at best be related to the similarity of the service characteristics of

the new and of the pre-existing goods and services. Thus, the innovations which create

important knowledge discontinuities for producers are likely to significantly affect

uncertainty for consumers as well. However, an important asymmetry between consumers

and producers is the possibility already mentioned to create user-friendly technologies

which reduce the knowledge barrier the former need to use the new goods and services. In

spite of this possibility, consumers are increasingly required to act as innovators (Bianchi,

1998) by learning types of knowledge relevant for the use of new goods and services.

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Another concept that following Witt (2001) and Nelson and Consoli (2010) is regarded as

extremely important in the construction of an evolutionary theory of demand is that of

wants. Ulrich Witt is concerned among other aspects with the possible satiation of demand

and with the impact it could have on growth. In studying the potential impact of satiation on

growth Witt is following the suggestion by Pasinetti (1981) that demand can saturate and

thus induce a bottleneck in economic development, a suggestion to which we will return in

the next section. According to Witt, some wants correspond to basic physical needs, such as

the need for food, sleep etc. While these needs can quantitatively be saturated, they can be

satisfied in a wide and growing variety of forms. The increasing variety of foods available

today to the average consumer today is a case in point. However, this increasing internal

differentiation is not enough to explain the absence of satiation. Together with it, Witt

considers two other mechanisms which might have the same effect. First, the satisfaction of

these basic wants can be coupled with other services which are complementary to them,

such as the atmosphere in a restaurant created by decoration or music. Second, the

satisfaction of these basic wants can be coupled with physical tools, such as a fancy bed for

the want to sleep.

2.3) DEMAND SATURATION AND PRODUCT AND QUALITY DIFFERENTIATION

Demand saturation had been assumed by Pasinetti (1981) in his treatment of the

relationship between structural change and economic growth. Generalizing from Engel's law,

Pasinetti assumes that demand saturates in all sectors, thus leading to an imbalance

between demand and continuously growing productive efficiency. In turn this imbalance

leads to a bottleneck consisting of the possibility to supply all demanded output by a falling

percentage of the labour force and the other required resources. The bottleneck could be

overcome by means of the emergence of new sectors which allow for the compensation of

the falling ability of incumbent sectors to create employment. The earliest version of our

model (Saviotti and Pyka 2004b) shows that in presence of complete demand saturation the

emergence of new sectors would allow an economic system to overcome Pasinetti's trap. In

our subsequent work we study the possibility that demand saturation is not complete and

that emerging sectors do not produce homogeneous and unchanging outputs during their

life cycle. Recent empirical work by Chai and Moneta (2010) and modelling work by Saviotti

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and Pyka (2009) shows that complete saturation as a function of income rarely occurs. For

most goods and services, Engel's curves have rather irregular shapes, the most general but

not invariable feature of which can be a slowdown in the rate of growth of demand with

income as the sector matures. In our modelling work we show that complete demand

saturation occurs only when no new sectors emerge and when the demand curves of

different sectors are independent. These findings do not entirely invalidate Pasinetti's idea

that an imbalance would arise between continuously growing productive efficiency and

saturating demand. Such an imbalance would still occur provided that the rate of growth of

demand was lower than the rate of growth of productive efficiency during the mature phase

of industrial sectors. Furthermore, even if the bottleneck in economic development that

Pasinetti was referring to as a consequence of the above imbalance were not to occur,

increasing variety, increasing sectoral output quality and internal differentiation would still

provide mechanisms which would enhance the potential of economic development.

An important trend in economic development occurring during the XXth century was the

growing quality and differentiation of goods and services. This trend is superimposed upon

the emergence of new sectors in such a way that product quality and differentiation grow

after the establishment of the new sector. In this process goods and services ceased to be

homogeneous. Many different attempts occurred to incorporate this heterogeneity in

demand theory (e.g. Wadman 2000). Finally, Ironmonger (1972) and Lancaster (1966, 1971)

assumed that consumers are not interested in products for their own sake but for their

characteristics. In our modelling work we use a version of Lancaster's theory (Saviotti and

Metcalfe 1984) in which a product is represented by two sets of characteristics describing

the internal structure of the technology and the services supplied to users and consumers

respectively. The two sets are called technical and service characteristics. Thus, we measure

product quality as an aggregator of service characteristics and product differentiation as the

range of services supplied. Clearly, the possibility of increasing product quality and

differentiation would not be conceivable without such a growingly heterogeneous nature of

products. Another departure we made from Pasinetti's work consists of taking into account

not only the emergence of new sectors but also the considerable increase in output quality

and differentiation internal to each sector.

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2.4) DEMAND DEVELOPMENT AND DISPOSABLE INCOME

The trend towards growing product quality and differentiation is historically recent.

Although we can find its origin during the industrial revolution, until the end of the XIXth

century most people spent almost all their income in what could be called necessities (e.g.

food, clothing, and housing). In this situation they could not be expected to purchase any

other (non-necessity) goods or services, given that by definition necessities cannot be

substituted by anything else. The possibility to purchase ‘higher’ goods and services required

the formation of what we call disposable income, an outcome which was necessarily

dependent on the growing efficiency of the processes producing necessities. This growing

efficiency started to create the required disposable income only at the beginning of the XXth

century, and even then only for the richest countries in the world (Hobsbawm 1968).

Important as it was, growing productive efficiency alone could not explain the phenomena

we observed during the XXth century. However efficient you make the production of bricks

and shoes, you cannot by that create cars or computers. Creativity, the capacity to give rise

to completely new objects of consumption is required in addition. The question then arises

of how creativity could be unleashed at a given time, let us say towards the end of the XIXth

century. A factor which contributed to the emergence of creativity is constituted by the

great progress made by science and technology during the XIXth century, progress which

allowed mankind to modify purposefully its external environment in an unprecedented way.

However, science and technology can give us the knowledge required to create new goods

and services but two conditions need to be satisfied for that to happen: (i) science,

technology and innovation require resources and (ii) consumers need to have a disposable

income to purchase the new goods and services.

The disposable income required for most consumers to be able to purchase goods and

services higher than necessities only became available at the end of the XIX century. This

happened by the combination of (i) the growing productive efficiency of all pre-existing

sectors, which reduced the cost of their output and the increasing income which would be

created by the new sectors, due to the relative investment and wages. All of these processes

required innovations creating the new goods and services in quantities, qualities and at

prices which could create a large enough demand for them to be produced.

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2.5) THE CO-EVOLUTION OF INNOVATION AND DEMAND

The dynamics of such a combination of supply- and demand-side processes cannot be

conceived as a set of independent events but as a co-evolutionary process of these different

and often complementary events. Co-evolution occurs when two variables influence each

other in such a way that as one of them grows or falls it induces a corresponding growth or

fall in the other one. In the economics of innovation attention has been focused on the co-

evolution of technologies and institutions (Nelson 1994), arguing that new technologies

require appropriate institutions and that the creation of such institutions can speed up the

development of new technologies and enhance their scope. The concept of techno-

economic paradigm (Perez 1983, 2007) describes with a different name the same process. In

our case the co-evolution occurs by the creation of an innovation, investment, creation of

employment and of income. Higher incomes can then induce the creation of higher quality

and of more differentiated products until the market corresponding to the new sector

eventually saturates inducing the emergence of newer sectors.

Here we propose a mechanism whereby different processes co-evolve giving rise to the

economic development patterns which we observe. The following stylized facts summarize

the previous discussion:

New sectors producing new goods and services are created by important innovations;

new markets emerge corresponding to these new sectors;

the internal quality and differentiation of these new sectors increases during their life

cycles and

the education levels of the population rise very rapidly and simultaneously with the

above processes.

A pattern of interactions which could explain the observed events is as follows:

(i) Observing the important advances made by science and technology firms start

investing in industrial R&D, which becomes institutionalized (Freeman and

Soete 1997);

(ii) this gives rise to innovations which open up new markets;

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(iii) This also creates a growing demand for education at all levels;

(iv) as a consequence of (iii) the higher competencies required to produce the new

and higher quality goods and services become available and

(v) as a further consequence of (iii), the higher wages which are paid in exchange

for higher competencies contribute to create (a) the purchasing power required

to buy new as well as higher quality goods and services and (b) to fund the

demand for higher education.

In this paper we will not undertake the exploration of the full co-evolutionary pattern

outlined above. Here we will pursue a more limited exploration of the co-evolution of

demand, of productive efficiency, of the emergence of new sectors and of the increasing

quality and differentiation in these sectors.

As a consequence of the previous considerations we consider the growing efficiency of

productive processes, the increasing variety due to the emergence of new sectors and the

increasing quality and internal differentiation of incumbent sectors as conditions which are

jointly required to create the pattern of economic development which we observe.

In our paper we explore this situation by means of a demand function which includes the

contributions of price, product quality, product differentiation, and an income term. The

process of economic growth affects the income related term in ways which depend on a

number of parameters of the TEVECON model, thus affecting the rates of economic growth

in the following periods.

Assuming that consumers have a high enough income to purchase a new good or service

they must also value it positively. In other words, they must have positive preferences for it.

In this paper we will analyze this problem by inserting a preference related term into the

demand function. In absence of a theory of preference formation we will approach the

problem in the following ways: we will assume that consumers’ preferences are

systematically biased towards (a1) newer goods and services or towards (a2) older goods

and services. These ‘switching preference’ experiments will allow us to investigate the

extent to which preferences support or hinder the evolution of particular types of demand

even when an adequate income share is available.

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3) A MODEL OF ECONOMIC DEVELOPMENT BY THE CREATION OF NEW SECTORS

Our model of development has been developed over the past years and has already

undergone a number of modifications and extensions (see Saviotti and Pyka, 2004a, 2004b,

2008a, 2008b). We will give first a brief description of the model and then introduce the

equations most central for this study. For a description of the formal structure we refer to

the respective references. In Pyka and Saviotti (2010) a detailed description of the basic

mechanisms, the parameters applied, the model’s robustness as well as major outcomes are

summarized.

In the model each sector is generated by an important innovation. Such innovation creates a

potential market and gives rise to what we call an adjustment gap. The term adjustment gap

is due to the fact that as soon as a potential market it is created it is in fact empty: neither

the productive capacity nor the demand for the innovation is present. They are gradually

constructed during the life cycle of the new sector. As the new sector matures the

adjustment gap tends to fall: a productive capacity which in the end matches demand is

created. When this happens the sector enters its saturation phase. The productive capacity

is generated by Schumpeterian entrepreneurs establishing new firms initially induced by the

expectation of a temporary monopoly and of the related supra normal profits. The success

of the innovation gives rise to a band wagon of imitators. The number of firms in the new

sector gradually rises, but this also raises the intensity of competition in the sector, thus

gradually reducing the inducement to further entry. After the intensity of competition in the

new sector reaches levels comparable to those of established sectors the new sector is no

longer innovating but becomes part of the circular flow. When a sector achieves maturity in

the way described above an inducement exists for Schumpeterian entrepreneurs to set up a

new niche, which can eventually give rise to the emergence of a new industry. In other

words, the declining economic potential of maturing sectors induces the creation of newer

and more promising ones.

Competition plays a very important role in this process of creation of new industries.

Entrepreneurs are induced to establish new firms by the expectation of a temporary

monopoly, that is, by the absence of competition. However, the new sector would not

achieve its economic potential unless imitative entry took place. In this way the intensity of

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competition rises, thus reducing the inducement to further entry. An additional contribution

is made to the dynamics of our artificial economic system by inter-sector competition. Inter-

sector competition arises when two sectors produce comparable services. Inter-sector

competition is an important component of contestable markets (Baumol et al. 1982) and can

keep the overall intensity of competition of the economic system high even when each

sector achieves very high levels of industrial concentration.

In our model the variety of the economic system plays an essential role. Economic variety is

approximated by the number of different sectors. By raising variety the creation of new

sectors provides the mechanism whereby economic development can keep occurring in the

long run. In this way the economic system can escape the trap generated by the imbalance

between rising productivity and saturating demand (Pasinetti 1981, 1993; Saviotti 1996)

which would occur in a system at constant composition. This also affects the macroeconomic

employment situation: In particular, this artificial economic system can keep generating

employment even when employment creation is falling within each sector (Saviotti and Pyka

2004b).

In order to illustrate qualitatively the developments generated by our model figure 1a shows

the development of the number of firms in a certain industry. Within a wide range of

conditions the number of firms in each sector grows initially, reaches a maximum and then

falls to low values. Within these conditions each sector seems to follow a life cycle, similar to

the ones detected by Klepper (1996), Klepper and Simons (2005), Jovanovic and MacDonald

(1994), Utterback and Suarez (1993). However, in our model this industry life cycle is created

by variables very different from those used by the previous authors who refer to increasing

returns to R&D, radical innovations or the emergence of dominant designs. In our case the

cyclical behaviour is caused only by the combined dynamics of competition and of demand.

We do not wish to say that cyclical behaviour cannot arise under the conditions identified by

the previous authors. We simply say that cyclical behaviour can arise also from the interplay

of competition and of demand. Figure 1b displays the development of the intensity of

competition and one clearly sees the impact of intra-industry dynamics as well as the

additional effect of inter-sector-competition after the emergence of new sectors.

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#

t

ICi

t

fig. 1a) number of firms fig. 1b) intensity of competition

In the following paragraphs we describe briefly the formal aspects of our model. The main

equation governing the dynamics of each sector in the model is:

t

i

t

i

t

i

t

i

t

iMAICAGFAkdN

1 (1)

where dNit is the change in the number of firms in sector i at time t, AGi

t is the adjustment

gap at time t, ICit is the intensity of competition at time t, and MAi

t is the number of mergers

and acquisitions at time t. Equation (1) represents the rates of entry (FAit · AGi

t) and exit (ICit,

MAit) into and out of sector i. Thus, dNi

t is the net entry of firms in sector i at time t. In this

equation co-evolution is represented by the term FAit · AGi

t.

The exit term ICit includes inter- and intra-industry competition (for a detailed description

see Saviotti and Pyka 2008a). The second exit term MAit includes besides exits via mergers

and acquisitions also failure and bankruptcy (see Saviotti, Pyka, and Krafft 2007).

t

ii

tt

iDDAG max (2)

The adjustment gap AGit (displayed in figure 2c) is very large right after the creation of the

sector, and later it decreases gradually, although not at all times. It is in fact possible for the

adjustment gap to grow during certain periods if innovations following the one creating the

sector improve either the performance of the product or the efficiency with which it is

produced, or both. In our model search activities affect both the maximum possible demand

(Dtmax,i) and the instant demand (Dt

i) in a sector i. If we consider that analytically the

adjustment gap (equation 2) is defined as the difference between these two types of

demand, we can understand that the time path of the adjustment gap depends on those of

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Dtmax,i (fig. 2b) and of Dt

i (fig. 2a). During particular periods it is possible for Dtmax,i to grow

more rapidly than Dti, thus enlarging the adjustment gap, or delaying the saturation of the

market. In the long run we expect the adjustment gap to be reduced to zero or to a low

constant value, i.e. the market to become saturated.

1 101 201 301 401

demand of sector i

t1 101 201 301 401

maximum demand of sector i

t 1 101 201 301 401 t

adjustment gap of sector i

fig. 2a) Demand fig. 2b) Maximum demand fig. 2c) Adjustment gap

FAit represents financial availability, the amount of money present in the economic system

that financial institutions are prepared to allocate to sector i at time t. Thus, FAit depends on

money as well as on the presence of financial institutions capable of judging the prospects of

growth and development of sector i at time t. It is in principle possible for an economic

system to have enough money but to lack the financial institutions capable of assessing the

potential of a new sector (Pyka and Saviotti, 2009). The role of financial institutions has been

crucial in the process of economic development and financial innovations have been

required several times to adapt these institutions to changes in the economic environment

(Perez 1983, 2002, 2007). AGit , the adjustment gap, is the size of the potential market of

sector i at time t. Co-evolution of the technology of sector i and of FAit occurs when FAi

t

grows with AGit and AGi

t grows with FAit .

Starting from the behaviour of microeconomic variables we can also calculate the curves for

aggregate variables. Figure 3 shows the time path of aggregate employment, obtained by

aggregating the employment curves of individual sectors.

15

-

20

40

60

80

100

120

1 51 101 151 201 251 301 351 401 451 t

# aggregate employment and trend

fig. 3: Aggregate employment curve

As can be seen in figure 3, the aggregate employment curve, constituted by the

superposition of the individual sectors’ employment curves, can give rise to a constant or

growing employment even when the ability of each sector to create employment declines.

Using the number of sectors in the economic system as an approximate measure of variety it

can be seen that these results support the hypothesis that variety growth is a necessary,

although not sufficient, condition for the long term continuation of economic development

(Saviotti 1996). In the rest of the paper the slope of the quasi linear part of the aggregate

employment curve will be used as a measure of the performance of the economic system.

4) THE FORMATION OF DISPOSABLE INCOME

To explore how the emergence of innovations can give rise to the disposable income

required to purchase them we modify the demand function (4) which we had used in

previous versions of our TEVECON model to include an income related component:

i

iiiDispi

t

ip

YYDDD

,

0 (3)

Where Di0 is the initial demand for the output of the new sector i, Ddisp,i is the disposable

income which can be allocated to purchase the new good or service i, Yi and ΔYi are the level

of services supplied by the new product/service and the degree of product differentiation, pi

is the price of the new product/service. The disposable income Ddisp,i can be calculated by

subtracting from total income the expenditures on all previous goods or services. In the

TEVECON model such disposable income is created due to the combination of the growing

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productive efficiency of pre-existing sectors and of the increased output and employment

following the creation of a new sector based on an important innovation. The extent of the

increase in income thus generated depends on the size of the market for the new product or

service and on all the parameters affecting the demand equation (3).

In figures 4-6 we display the curves for the number of firms Nit, for income and for demand

obtained with the new demand function (4). These results correspond to what we call from

now on the standard scenario which is taken as the basis for our further explorations.

fig. 4: Development of the number of firms in the different industries

fig. 5: Income development

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fig. 6: Demand development in different sectors

The time path of the number of firms Nit (fig. 4) and of income (fig. 5) is qualitatively similar

to that obtained with the previous formulation of the demand equation (Saviotti and Pyka

2008). The number of firms rises first, reaches a maximum and then falls to a low value – in

other words the populations of firms describe a sequence of industry life cycles (ILCs). The

income generated (figure 5) keeps rising all the times. The emergence of each sector is

accompanied by an initial period of very fast increase in income followed by a period in

which income rises much more slowly. A similar tooth like shape is shown by consumption

and investment.

The demand curves for individual sectors obtained with demand function (3) displayed in

figure 6 differ from those which we had obtained in Saviotti and Pyka (2008) where the

disposable income was not considered. There, demand rose in the initial phases of a new

sector before reaching a level of saturation; also the sectorial demand curves where

independent of each other. With the new demand function (3) which includes explicitly

disposable income, sectorial demand curves interact. The interactions are of two types: the

emergence of a new sector raises income and as a consequence increases the demand for

older sectors giving rise to spikes in the demand curve since part of the higher income is

available also for the previous sectors; (ii) the fall in demand occurring in the mature phase

of a sector occurs because one way of purchasing new goods or services is to spend less on

pre-existing ones. On the whole we consider that our new demand function including an

income constraint is superior to the previous one because it represents not only what

consumers would like to purchase, as the previous one, but also what they can purchase.

4.1) PRODUCTIVE EFFICIENCY, OUTPUT VARIETY, PRODUCT QUALITY AND SECTOR

INTERNAL DIFFERENTIATION

18

Growing productive efficiency, increasing output variety, product quality and sector internal

differentiation contribute jointly to economic development. To understand their role we

would need to be able to separate them. In past work (Saviotti and Pyka 2004c) we

approximated output variety by the number of sectors and used the informational entropy

function to calculate it. It is more difficult to separate productive efficiency from product

quality at the sectoral level because they are jointly produced. For example, during a given

period the output of a sector changes both in quantity and in quality. To take a typical

example, the cars produced today differ not only in numbers but also in quality from those

which were produced in the 1950s. In TEVECON product quality is explicitly present in the

demand function as Yi, the level of services supplied by a product. Yi can be considered an

aggregator of several product service characteristics (Saviotti, Metcalfe, 1984). To explore

the effect of changing product quality on economic development we modified the

parameters of the equations of Yi and of Yi, which represent product quality and product

differentiation respectively. We created two extreme cases, one in which there is no change

in product quality and product differentiation and one in which these changes are high. We

will call these two scenarios low quality and high quality respectively.

Figures 7-12 show the impact of on a number of model variables. To abstract from some

particularities of the first sector, in the graphs the development of the respective figures in

the second industry are displayed. Figure 7 shows the time path of product quality and of

product differentiation in the two cases. As it could be expected, in the low quality case

product quality does not change while in the latter case it grows. Figure 7 also shows that in

the high quality scenario it takes longer for new industries to emerge. Figures 13 and 14

show the development of disposable incomes in the low and high quality scenarios. as

Figures 15 and 16 illustrate the aggregate income and employment developments for the

low and high quality scenarios.

19

fig. 7: Product quality (yit) in the low quality (dark) and high quality (light) case

fig. 8: Sectorial demand (Dit) in the low quality (dark) and high quality (light) case

fig. 9: Sectorial output (qit) in the low quality (dark) and high quality (light) case

fig. 10. Sectorial wages (wit) in the low quality (dark) and high quality (light) case

fig. 11: Quantity of human capital (HCit) used in a sector in the low quality (dark) and high

quality (light) case

20

fig. 12: Quality of human capital (hit) in the low quality (dark) and high quality (light) case

fig. 13: Disposable income created in the economic system for the low quality case

fig. 14: Disposable income created in the economic system for the high quality case

fig. 15: Difference between employment development in the low and high quality scenario

21

fig. 16: Difference between income development in the low and high quality scenario

The changes induced by the increase in product quality during the life cycle of a sector can

be summarized as follows:

The difference of the two scenarios is best displayed in figure 7 where the immediate effect

of the switch from the low to the high quality scenario can be seen in the sharp increase of

the output quality variable Yit, which overtakes in the high quality scenario and reaches a

significantly higher value. At a sectorial level this affects demand Dit which remains almost

constant in the low quality case while it grows considerably in the high quality case (figure

8). Output qit only moderately increases in the first periods in order to decrease again in the

low quality case while it grows in the high quality case over the observed time interval

(figure 9). Also sectorial wages wit finally remain constant on a lower level in the low quality

case compared to increasing sectorial wages the high quality case (figure 10). This difference

in the development of sectorial wages is also reflected in the quantity of human capital (HCit)

which rises and falls more rapidly and subsequently settles on a lower value in the low

quality case with respect to the high quality case (figure 11) and in the quality of human

capital (hit) which falls gently in the low quality case while it grows in the high quality case

(figure 12). Improving product quality necessitates higher quantities and qualities of human

capital accompanied by higher wages.

Figures 13 and 14 display the development of the disposable income (Ddispo,it) for the two

scenarios. The disposable incomes to purchase goods and services from new industries grow

faster in the low quality scenario supporting the faster emergence of new industries. In the

high quality scenario the increasing disposable incomes generated from the emergence of

new industries is partly used to purchase higher quality and differentiated goods and

22

services in the mature industry. From this follows a positive feedback on wages and human

capital. This leads to a pronounced difference on the aggregate level of the artificial

economy. Figure 15 displays the difference in the aggregate employment development in

the two scenarios. It immediately can be seen that the employment figures in the low quality

scenario always are superior to the employment figures in the high quality scenario.

However, this is not the case with respect to the aggregate income. The higher aggregate

incomes (figure 16) for the low quality scenario are to be observed only in the first periods.

The trend of higher growth rates in income changes around period 1000 and the income

differential becomes smaller. In period 1800 finally aggregate incomes in the high quality

scenario overtake despite the lower employment levels.

The picture that emerges from these experiments is that in the early stages of economic

development our artificial economic system would have had a higher rate of growth of

aggregate income and of aggregate employment if it had been developing by creating new

sectors based on new products and services, but if it had not improved the quality of these

new products and services after they had been created. However, this higher rate of

aggregate growth would have occurred with lower wages, lower sectoral demand and a

lower quality of human capital. Thus, a larger employment pool would have been created

but with a lower quality of human capital of the workforce and, consequently, with lower

wages and with a lower sectoral demand. In summary, the low quality scenario would have

entailed more jobs with lower competencies and lower wages than the high quality scenario.

The previous results are not independent of the time horizon chosen. Thus, the tradeoff

between the faster rate of aggregate growth and the lower level of individual welfare of the

low quality scenario and the lower rate of aggregate growth and the higher level of

individual welfare of the high quality scenario which exists for income in a relatively short

time horizon disappears in a relatively longer time horizon in which the high quality scenario

dominates both aggregate income growth and individual welfare. On the other hand

employment keeps growing faster in the low quality case whatever time horizon we take

into account.

To interpret correctly these results we have to bear in mind that in our TEVECON model a

new sector is created when the pre-existing ones are saturated. The distinction between the

23

low and the high quality scenarios implies that saturation can occur both in volume and in

value (Saviotti, Pyka, and Krafft 2007). In the low quality scenario only volume saturation can

occur. In the high quality scenario volume saturation need not occur and the market can

keep expanding beyond that if higher quality products can fetch higher prices. Thus, value

saturation can be expected to occur later and give rise to longer industry life cycles. As a

consequence, in TEVECON with a high quality scenario the inducement to create new sectors

would be delayed, thus leading to a lower rate of emergence of new sectors. Finally, we

have to bear in mind that the comparison we explored here is rather extreme. In any real

economic system the choice would never be between zero and a very high degree of quality

change within a sector but rather between the resources allocated to intra-sectoral quality

improvements and the creation of new sectors. Presumably, then the differences between

the rates of growth and the levels of individual welfare of the two cases would be less

pronounced and the dominance of the high quality scenario could begin for shorter times.

Furthermore, we have to bear in mind that the actual development of any real economic

system could have started in the low quality case and switched gradually to the high quality

case as society became more affluent.

4.2) PREFERENCES, DEMAND AND INNOVATION

In the previous part of the paper we studied the formation of disposable income and the

influence that efficiency and product quality can have on it. The existence of an adequate

disposable income is a necessary condition for consumers to be able to purchase the new

goods and services which are created by innovation. However, consumers will do that only if

they have an adequate set of preferences. In this section we study how different preference

systems can affect the time path of demand and of economic development. To do this we

represent two very simplified preference systems which we call progressive and

conservative. We realize that in a real economic system preferences of these different types

would be distributed within a consumer population and that they would not be immutable.

Consumers can learn and change their preferences in the course of time. Our main objective

here is simply to show that consumer preferences can affect directly demand and indirectly

the macroeconomic growth performance of the economic system.

24

Consumers with a progressive preference system value more highly new goods and services

than older ones. Consumers with a conservative preference system value more highly old

goods and services than newer ones. These two preference systems are represented with a

new parameter kpref,i in the modified demand equation (7).

i

ii

iDispiipref

t

ip

YYDDkD

,

0

, (7)

Where kpref,i is a parameter which is constant for each sector in the course of time but can

vary between different sectors. The two preference systems are then represented as

follows:

Progressive preference system: kpref, i+1 > kpref,i

Conservative preference system: kpref, i+1 < kpref,i

In different experiments we varied the degree of progressiveness or conservativeness of our

consumers by changing the Δkpref between sectors i and i+1. Thus, a large and positive Δkpref

between sectors i and i+1 indicated strongly progressive consumers while a smaller but still

positive Δkpref indicated mildly progressive consumers. Likewise, a large and negative Δkpref

between sectors i and i+1 indicated strongly conservative consumers while a smaller

negative Δkpref indicated mildly conservative consumers. In the experiments which we

carried out we calculated the number of firms in each sector Nit, sectoral demand, sectoral

disposable income, the rate of growth of employment and the rate of growth of income. The

typical results of these experiments are shown in figures 17 a, b, c, d and e for mildly

progressive preferences.

(a) (b)

25

(c) (d)

(e)

fig. 18 a, b, c, d, e: Number of firms (a), sectoral demand (b), sectoral disposable income (c),

sectoral employment and rate of employment growth (d), rate of income growth (e)

The comparison of the different preference systems is shown in figures 19 and 20, where the

slopes of the rates of growth of income and of employment are plotted for each case.

Fig. 19: Influence of the different preference systems on the rate of growth of income

26

fig. 20: Influence of the different preference systems on the rate of growth of employment

Figures 19 and 20 show that the rates of growth of income and of employment are affected

by the different preference systems. In particular, progressive preference systems tend to

give higher rates of growth of income or employment than conservative preference systems.

However, there clearly are some non-linearities, since strongly progressive preference

systems give lower rates of growth of income or employment than mildly progressive

preference systems. This occurs because as consumers allocate more and more of their

demand to emerging sectors they 'starve' mature sectors to the point where the whole

process of economic development suffers. The purpose of our paper is to show the potential

impact of the consumers’ preferences on economic development. A deeper analysis to

disentangle the complex interactions of preferences and economic development is beyond

the scope for the present paper, but on our agenda for future research.

5) SUMMARY AND CONCLUSIONS

In this paper we study the interaction between innovation and demand in the process of

economic development. Co-evolution involves the mutual feedback between innovation and

demand, which occurs by means of search activities, of investment, of the creation of

employment and income, which in the end generate demand. Amongst all the factors

involved in the above co-evolution we focus on the creation of the disposable income

required to purchase the goods and services of emerging sectors. We found that the

creation of disposable income occurs and that it is favoured, for example, by the use of

physical capital, by the growing quality of human capital and by growing product quality. In

this paper we carry out a limited number of experiments on the parameters which could be

expected to affect the interaction between innovation and demand. However, given its

highly interactive nature, our TEVECON model contains a large number of interactions which

27

could in principle affect this co-evolutionary process. For example, search activities are a

necessary requirement for the creation of innovations. Yet in TEVECON search activities rise

with accumulated demand. In turn, demand is itself affected by search activities which

contribute to raise product quality and product differentiation. Thus, the complete analysis

of all the interactions between innovation and demand goes far beyond the experiments in

this paper.

The basic dynamics of our artificial economic system is rooted in the interaction between

innovation and demand. In our previous work, following Pasinetti (1981) we had studied the

potential bottleneck in economic development induced by the imbalance between

saturating demand and continuously rising process efficiency, which we call the Pasinetti

trap. In the present paper we show that the emergence of new sectors can still make a

contribution to economic development even if complete demand saturation does not occur.

Furthermore, in addition to the emergence of new sectors we study the impact of the

growing product quality and internal differentiation sectors during their life cycle. We show

that these two processes contribute to economic development by raising disposable income,

wages and human capital with respect to a scenario in which output remains constant during

the life cycle of a sector.

In this paper we investigate the mechanisms whereby the disposable income required to buy

the new products and services of emerging sectors is created. The creation of such

disposable income is mainly due to the combination of growing efficiency of incumbent

processes and of the income effect from the investment to create the production capacity of

new sectors.

Also, we explore the impact of different preference systems on economic development. We

found that a change in the preference system has an impact on the rates of growth of

income and of employment. For example, we found that a progressive preference system, in

which consumers value the products of new sectors more than those of older ones, tends to

give higher rates of growth of income and of employment than conservative preference

systems, in which consumers value the products of older sectors more than those of new

ones.

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The processes which we studied are part of a more general co-evolutionary pattern in which

innovation, education levels, labour force competencies, product quality and differentiation,

wages, disposable income and product prices co-evolve.

In summary, our results prove that the time path of economic development which we

observed could not have been generated by taking into account innovations alone without

making reference to the formation of an adequate demand for them. Three innovation

based processes contribute to economic development, growing productive efficiency, the

emergence of new sectors and the increasing quality and differentiation of existing products.

They need to be combined because each one individually would not suffice. However, even

the combination of these three processes needs the formation of an adequate demand to

sustain long run economic development.

REFERENCES: Aghion, P., and Howitt, P. 1992. “A model of growth through creative destruction.”

Econometrica 60: 323-351.

Aoki, M., and Yoshikawa, H. 2002. “Demand saturation-creation and growth.” Journal of Economic Behavior and Organization 48: 127-154.

Andersen, E.S. 2001. “Satiation in an evolutionary model of structural economic dynamics.” In Escaping Satiation, the Demand Side of Economic Growth, edited by Witt, U., 165-186. Berlin: Springer.

Andersen, E.S. (2007), ‘Innovation and Demand’, in Hanusch, H. and Pyka, A. (eds), The Elgar Companion to Neo-Schumpeterian Economics, Elgar, Cheltenham, 754-765.

Aversi, R., Dosi, G., Fagiolo, G., Meacci, M., Olivetti, C. 1999. “Demand dynamics with socially evolving preferences.” Industrial and Corporate Change 8: 353-399.

Bianchi, M., ed. 1998. “The Active Consumer.” London: Routledge.

Chai, A., and Moneta, Retrospectives Engel Curves, A. Journal of Economic Perspectives—Volume

24, Number 1—Winter 2010—Pages 225–240 This feature addresses the history of economic terms and

Ciarli, T., Lorentz, A., Savona, M., and Valente, M. (2010), The effect of consumption and production structure on growth and distribution. A micro to macro model, Metroeconomica, 61(1):180-218

Foellmi, R., Zweimuller, J., (2006), Income distribution and demand induced innovations, Review of Economic Studies 82, 95‐112

Freeman, C., and Soete, L. 1997. The Economics of Industrial Innovation. 3rd ed. London: Pinter.

29

Georgescu-Roegen, N. 1954. “Choice, expectations and measurability.” Quarterly Journal of Economics 68: 503–534.

Georgescu-Roegen, N. 1965. “The institutional aspects of peasant communities.” In Georgescu-Roegen, N. ed. Energy and economic myths, Pergamon Press, New York (originally published 1965).

Georgescu-Roegen, N. 1966. “La science Economique, ses Problemes et ses Difficultes” Paris: Dunod.

Granovetter, M., and Soong, R. 1986. “Threshold models of interpersonal effects in consumer demand.” Journal of Economic Behavior and Organization 7: 83–99.

Grossman, G. M., and Helpman, E. 1991. “Innovation and Growth in the Global Economy.” Cambridge Mass: MIT Press.

Hirsch, F. 1976. “Social limits to growth.” New York: Harvard University Press.

Hobsbawm, E. 1968. “Industry and empire.” Harmondsworth: Penguin Books.

Ironmonger, D. S. 1972. “New Commodities and Consumer Behavior.” Harvard University Press: Cambridge Mass.

Jovanovic, B., and MacDonald, G. M. 1994. “The life cycle of a competitive industry.” Journal of Political Economy. 102: 322-347.

Kaldor, N. 1957. “A model of economic growth.” Economic Journal 67: 591-624.

Klepper, S. 1996. “Entry, exit growth and innovation over the product life cycle.” American Economic Review 86: 562-583.

Klepper, S., and Simons, K. L. 2005. “Industry Shakeouts and Technological Change.” International Journal of Industrial Organization 23(1-2): 23-43.

Lancaster. K. J. 1966. “A new approach to consumer theory.” Journal of Political Economy 14: 133-156.

Lancaster, K. J. 1971. “Consumer Demand: a New Approach.” New York: Columbia University Press.

Malerba, F., Nelson, R., Orsenigo, L., Winter, S. 2007. “Demand, innovation, and the dynamics of market structure: The role of experimental users and diverse preferences.” Journal of Evolutionary Economics 17: 371-399.

March, J. G., and Simon, H. A. 1958. “Organizations.” Blackwell: Oxford.

Matsuyama, K., (2002), The Rise of Mass Consumption Societies, Journal of Political Economy 110, 1035‐70.

Metcalfe, J. S. 2001. “Consumption, preferences and the evolutionary agenda.” Journal of Evolutionary Economics 11: 37-58.

Murphy, K, Schleifer, A., Vishny, R., (1989) Industrialization and the Big Push, Journal of Political Economy 97,1003-26

Nelson, R. R. 1994. “The Co-evolution of Technology, Industrial Structure, and Supporting Institutions.” Industrial and Corporate Change 3(1): 47-63.

30

Nelson, R. R., and Consoli, D. 2010. “An evolutionary theory of household consumption behaviour.” Journal of Evolutionary Economics 20 (2010): 665-687.

Pasinetti, L. L. 1981. “Structural Change and Economic Growth.” Cambridge: Cambridge University Press.

Perez, C. 1983. “Structural change and the assimilation of new technologies in the economic system.” Futures 15: 357-375.

Perez, C. 2007. “Finance and Technical Change: A long-term View.” in: Hanusch, H., and Pyka, A. (eds.), The Elgar Companion to Neo-Schumpeterian Economics, Edward Elgar, Cheltenham, 775-779.

Pyka, A. and Saviotti, P.P. (2009), The Co-Evolution of Technologies and Financial Institutions, in: Pyka, A., Cantner, U., Greiner, A. und Kuhn T. (eds.), Recent Advances in Neo-Schumpeterian Economics - Essays in Honour of Horst Hanusch, Edward Elgar Cheltenham, 81-100.

Pyka, A. and Saviotti, P.P. (2010), Economic Growth through the Emergence of New Sectors, in: Mann, S. (ed.), Sectors Matter - Exploring Mesoeconomics, Springer, Heidelberg, Dordrecht, London, New York, 55-102.

Romer, P. 1990. “Endogenous technical progress.” Journal of Political Economy 98: 71-102.

Rosenberg, N. and Mowery, D. (1978), The influence of market demand upon innovation: A critical Review of some recent empirical Studies, Research Policy, Vol. 8, 103-153.

Saviotti, P. P., and Metcalfe, J. S. 1984. “A Theoretical Approach to the Construction of Technological Output Indicators.” Research Policy 13: 141-151.

Saviotti, P. P. 2001. “Variety, growth and demand.” Journal of Evolutionary economics 11: 119-142.

Saviotti, P. P., and Pyka, A. 2004a. “Economic development by the creation of new sectors.” Journal of Evolutionary Economics 14 (1): 1-35.

Saviotti, P. P., and Pyka, A. 2004b. “Economic development, qualitative change and employment creation.” Structural Change and Economic Dynamics 15: 265-287.

Saviotti, P. P., and Pyka, A. 2004c. “Economic development, variety and employment. “ Revue Economique 55 (6). Special issue on Structural change and Growth, (J.L Gaffard, P.P. Saviotti eds.).

Saviotti, P.P., Pyka A., and Krafft, J. 2007. “On the determinants and dynamics of the industry life cycle.” Paper presented at the EAEPE conference 'Economic growth, development, and institutions - lessons for policy and the need for an evolutionary framework of analysis', Porto, November 1-3.

Saviotti, P.P., and Pyka, A. 2008. “Micro and macro dynamics: Industry life cycles, inter-sector coordination and aggregate growth.” Journal of Evolutionary Economics 18: 167-182.

Saviotti, P.P., and Pyka, A. 2009. “Innovation, demand and growth.” Paper presented at the 'AFSE Conference ' in GREDEG, Sophia Antipolis, June 25-26.

31

Simon, H. A. 1954. “Theories of decision making in economics.” American Economic Review 49: 223-283.

Simon, H. A. 1955. “A behavioral model of rational choice.” Quarterly Journal of Economics 69: 99-118.

Utterback, J. M., and Suarez, F. F. 1993. “Innovation, competition and industry structure.” Research Policy 22: 1-21.

Wadman, W. M. 2000. “Variable Quality in Consumer Theory.” New York: M.E. Sharp.

Witt, U., 2001. “Learning to consume: a theory of wants and the growth of demand.” Journal of Evolutionary Economics 11.