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Technological shifts and convergence in a Europeanperspective since 1950.

Lennart SchönDepartment of Economic History

Lund UniversityLennart.Schon@ekh.lu.se

Paper for THE VICE-PRESIDENTIAL SESSIONConvergence and Non-convergence since the Second World War, at the XIV

International Economic History Congress, Helsinki 21-25 August 2006.

Introduction

This is a discussion paper on some aspects of OECD and European growth andconvergence from 1950 to the early 2000, with some perspectives also on the pre-First World War globalization era. The discussion will address the role oftechnological shifts (industrial revolutions) and the perspectives of traditional andnew growth theory on convergence/divergence and in particular it will try to developa measure of these forces as a continuous process. The analysis draws mainly upondata that have been available internationally (Maddison 1995, Williamson 1995,Groningen Growth and Development Centre 2006). It should be emphasised from thebeginning, though, that “theory has run ahead of measurement, especially withregard to examining differences within the advanced countries”. (Crafts/Toniolo,1996 p. 16)

Three perspectives on growth

Since the early 1990s, perspectives on growth from two different branches ofeconomic theory have had a decisive impact upon economic history – oneperspective is focussed on the mechanisms of convergence and the other on growthas an endogenous process. These two strands of thought give largely very differentperspectives on growth and a different understanding of the process. They will becompared and discussed in relation to a structural analysis of growth that has beenfollowed in research at Economic History in Lund.

Convergence in history

Convergence of income levels and relative prices is a main characteristic in analysesof market integration or globalisation in history - notably by Williamson/O’Rourke(1994) and Williamson (1995,1996). Their analysis is based upon standard neo-classical Economics with a Solow-model with diminishing returns to theaccumulation of factors of production. Growth is not the direct object of study, butconvergence and growth run largely parallel. There are mainly two sources of

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growth. One is technical change that is exogenous to the model. The other is thereallocation of resources to more productive ends. That is the central mechanism inthis analysis. According to Jeffrey Williamson the interaction between labour, capitaland commodity markets should be in focus of studies in economic growth. Economichistorians “should attack these issues first before elevating internationaltechnological transfer to the status of prime mover, a thesis so ably argued byGerschenkron that it has dominated the convergence debate ever since.” (1995, p162)

When markets widen through integration of different national economies (in theprocess of globalisation), relative prices will change in a systematic way. In a giveneconomy, prices of factors that prior to integration were relatively abundant will riseand consequently prices of scarce factors will fall. Thus, globalisation will increasethe returns to labour in labour-abundant economies and to capital in capital-abundanteconomies. Through the flow of goods, labour and capital, prices and relative incomelevels will converge within a globalised economy. This is of course the mechanismof factor price equalisation put forward by Eli Heckscher and Bertil Ohlin, basedupon experiences in the late 19th century and early 20th century. The First World Warand the breakdown of international institutions put very effectively an end to thatprocess of globalisation and convergence that was to recur after the Second WorldWar. Thus, modern history has witnessed two periods of globalisation andconvergence according to Williamson et.al. – from 1870 up to the First World Warand the period after the Second World War.

Endogenous growth

The new growth theory that was launched within Economics in the 1980s (notablyRomer 1986, 1990; Lucas 1988) gives a very different perspective on the growthprocess and its outcome. Through the accumulation of “broad capital” that includesknowledge, human capital and innovations, growth was made endogenous to theprocess. Thus, knowledge was produced as any other investment good by thecalculated use of labour and capital. The inclusion of knowledge as a key factor andasset had further consequences. While other factors had diminishing returns and wereconsumed in the production process, knowledge grew when it was used.Furthermore, through externalities including spillovers and complementarities theaccumulation of knowledge was endowed with increasing returns. Newcomplementarities arose through the advance of knowledge in different areas andnew complementarities were created between human capital and technology.

Convergence between economies at different income levels is not the logicaloutcome of a model with increasing returns, externalities and complementarities.Rather it will predict divergence since initial differences are enlarged in anendogenously determined growth process with such characteristics. Divergence isbrought even further due to agglomeration forces (new economic geography) andthese forces are rather strengthened through market integration.

There are of course modifications and qualifications of the basic models thatdiminish the gulf between them. The concept of social capability (Abramovitz 1986)emphasises that there are decisive socially determined differences in the ability tointegrate productivity-increasing methods and to transform structures and thus

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differences in the ability to join convergence clubs at certain historical points of time.Furthermore, in the augmented Solow-model the concept of capital is broadened toinclude knowledge. (Mankiw et.al. 1992) Basically, however, there are two verydifferent propositions of the “normal” outcome of the growth process – one ofconvergence and one of divergence.

Analysis of structural change

Analysis of historical growth performance may give ground for another positionConvergence and divergence are components in that process in a quite logicalmanner; i.e. different periods are characterised by convergence and divergencerespectively not because of shortcomings in the external conditions but because ofqualities inherent in growth. Furthermore, this variation between convergence anddivergence in growth rates and income levels may have followed a certain regularitythat can be expressed in a model of the historical process that combines aspects fromboth bodies of standard economic theory. (Cf. a structural model presented in e.g.Krantz/Schön 1983, Schön 1994, 1998 and 2000).

Inventions may appear and knowledge may accumulate at a rather constant pace, butthe impacts upon the economy vary very much over time due to properties within theeconomic system such as complementarity and externality. Radical innovations thatcreate important and far-reaching new complementarities as the steam-engine, therailway, the electrical motor and the combustion engine, the motor-car, the micro-processor, the Internet are rare and their diffusion spread over long periods. In the1990s the ICT-revolution attracted increasing attention and such radical innovationswere named General Purpose Technologies by some economists.(Bresnahan&Trajtenberg 1995) and applied also by some economic historians thathad been sceptical to the concept of industrial revolutions (e.g. Crafts 2002). Theimportance of the phenomenon of new complementarities created around innovationswas of course recognized much earlier by many economic historians. With a SwedishSchumpeterian concept the complementarities around innovations form developmentblocks that are at the centre of the growth process. (Dahmén 1950, 1988)

The creation of new complementarities within a development block changes therelative price structure – as does market integration but with another logic. In centralareas of innovation relative output prices will generally fall that intensifiescompetition against old combinations of production factors. The expansion ofactivities in the innovating areas will, however, increase demand for inputs of goodsand services and for complementary production that are supplied less elastically andfor these, prices will rise. Within the development block remuneration to the factorsof production will increase either as a consequence of increased productivity (supplypush) or as a consequence of increased prices (demand push). Within old blocksremuneration will decrease.

Furthermore, complementarities around radical innovations appear suddenly andunexpectedly, despite the fact that the breakthrough has been preceded by a longperiod of innovative activity. The wider repercussions of the innovation that formsthe development block make a new turn of events. Such was the case with theelectronic revolution (the third industrial revolution) following the advent of themicroprocessor or with the second industrial revolution following upon the

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accumulation of engineering and scientific knowledge at the end of the 19th century.In such periods of more rapid transformation, regions and nations react differently.Evidently, there are leading regions and nations, since innovations appear in specificcircumstances and from the existence of geographically confined complementaritiesand externalities. Diffusion is more rapid to regions and nations that are favoured bynew demands – due to their resource endowments, their institutional characteristicsand their social capability. For the same reasons, the new turn of growth direction isunfavourable to other regions and nations. They may be firmly attached to oldcombinations and/or have endowments that are less advantageous under newcircumstances. Under those conditions growth rates will diverge. Furthermore, it isreasonable that rich economies well endowed with knowledge and acting at theproduction/consumption frontier will be better situated to take the lead – thusdivergence will follow.

Over time however (due to investments) competencies, infrastructures andinstitutions will be more generally adapted to the new complementarities. Hence thedevelopment blocks will be more widely diffused. Since further innovate activity(i.e. economic use of potentially available new combinations from the accumulationof knowledge) is restricted by the structure of complementarities and interestscreated (i.e. by path-dependency), the accumulation of broad capital will be capturedwithin the confinements of diminishing returns. Further growth will be moredetermined by diffusion of the new technology and by the working of the marketmechanism. In that diffusion process, the favourable position of the leaders isundermined while laggards will improve their position. Thus, divergence in growthrates and income levels will turn into convergence (among countries involved in thisprocess). Diminishing returns will however shift relative profitability betweenestablished and emerging complementarities that pave the way for crisis and newstructural transformation.

Thus, from this perspective the growth process may be periodised in two parts. Thefirst period is characterised by radical transformation of structures whendevelopment in a geographical context is uneven with growth accelerating in smallnuclei. The second period is characterised by rationalisation when gaps are beinglevelled and the economy is made more homogenous with growth accelerating (to acertain point) in a wider context. Hence, convergence and divergence put theirimprint on different phases and the traditional and the new growth theory evolvearound properties that have characterised growth alternately.

Two major discontinuities or technological shifts are indicated by the concepts of theSecond and Third Industrial Revolutions – both witnessing the early breakthroughsof innovations prone to become General Purpose Technologies. Thus, one may seethe 1890s as a decisive period of the Second Industrial Revolution and thebreakthrough of the modern industrial society. In the centre of development, therewas a diffusion of new motors, electrical or combustion engines, with a wideningscope for mechanisation within industry. In the interwar period, and still moremarked after the Second World War, new development blocks were created around awidening of electrification and the diffusion of automobiles. In both cases, therewere waves of investments around the development of an infrastructure from thebasic innovations of the preceding cycle. In case of electricity, a much broader

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spectrum of applications was created ranging from the processing of electro steel tosmall motors in handicraft and household.

From the mid-1970s the appearance of the microprocessor gave the spark to thetechnological shift of the Third Industrial Revolution and electronics became thecentre in new development blocks. The use of knowledge and information inproduction of goods and services advanced with leaps, marking new directions ofgrowth.

There is still another long term pattern – the First and Second Industrial Revolutionswere followed by a wider diffusion of blocks around infrastructural development andinstitutional adaptation in the mid-19th and mid-20th centuries. One may hypothesisethat forces of divergence are relatively strong in periods denounced as industrialrevolutions while convergence would be more emphasised not only in the diffusionprocess of the technology in production but particularly in the ensuing period ofinfrastructural development.

Phases of growth

In a survey of post-war European growth Nicholas Crafts and Gianni Toniolo stated:“It is useful to think in terms of epochs of growth”. (1996, p. 32) There is a well-established periodisation of European economic development since 1870 that is asfollows:

1870-1914 – the era of the classical Gold Standard1914-1950 – the period of wars and reconstruction1950-1973 – the post-war Golden Age of high growth rates1973- – deceleration and restructuring into “a new economy”

This periodisation appears clearly in figure 1 and table 1 that depicts a measure of anaggregated European GDP per capita calculated from 14 countries and with a singlePPP-benchmark in 1990. Although the construction of GDP series in individualEuropean countries have progressed immensely in the last decades, there are still anumber of problems and difficulties in these long-term cross country constructionsthat are far from solved and are being addressed by a number of European economichistorians. (See for instance Prados 2000) In the present context, however, focus willbe on some rather well established trends.

Even if this broad periodisation fits rather well to overall trends in growth, it mayobscure trend breaks that are vital for a discussion of the dynamics of growth.

Graph 1 about here

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Table 1. Growth rates in GDP per capita in Europe. Average of 14 countries.

Period Annual growth rate of GDP per capita1870-1914 1,21914-1950 0,91950-1973 3,81973-2004 1,91870-1994 1,8

Note: The countries are Austria, Belgium, Denmark, Finland, France, Germany, Italy, the Netherlands,Norway, Portugal, Spain, Sweden, Switzerland and the UK.Sources: Maddison (1995), www.ggdc.net (2006).

Two periods of growth in the era of the classical Gold Standard.

In their work on globalisation, Williamson et.al. treat the decades of the GoldStandard from 1870 to the First World War as a homogenous period of convergence.The flows of capital and labour were particularly important in the process of globalfactor price equalisation. That equalisation occurred both within Europe and in theAtlantic Economy.

Overall convergence was, however, very much a result of growth and factor pricedevelopment in the Scandinavian countries and the United States, which is apparentfrom Williamson’s data and that is clearly shown in table 2. According to figuresfrom Williamson and Maddison, the relative change of factor prices in Sweden wasextraordinary but the change was almost as strong in Denmark and Norway. (On theimportance of capital imports in Sweden, see Schön 1989, 1997) Increases in realwages clearly outstripped a fairly rapid growth in GDP per capita. In the highwageeconomy of the United States development was the opposite. Growth of wages wassluggish while GDP grew quite rapidly. In low-wage Latin Europe (the Iberian andApennine peninsulas) GDP growth was weak but wage growth was even weaker.Thus, the Scandinavian countries clearly formed a convergence club at the end of the19th century that joined in modern economic growth, while Latin Europe generallydid not.

Table 2. Annual growth in indexes of real wages and in GDP per capita in Europeancountries and the United States 1870-1910.

Country Annual growth of realwages 1870-1910

Annual growth of GDPper capita 1870-1910

Sweden 2,8 1,7Denmark and Norway 2,6 1,3France, Germany and UK 1,1 1,2USA 1,1 1,6Italy, Portugal and Spain 0,6 1,0

Sources: Wages from Williamson (1995); GDP, see table 1.

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However, the classical Gold Standard era was not a very homogenous period. Therewas a decisive turning point around 1890. In the period 1870-1890 growth rates weremuch more even among countries – also in a Scandinavian/Latin Europeancomparison. That was a period characterised by the market integration that tookplace after the introduction of new institutions at mid-19th century as well as thecreation of a new infrastructure of railways, steam-ships and telegraph cables. It wasan expansion built upon innovations of the first industrial revolution and the ensuinginfrastructure development and upon the complementarity between an industrialcentre and a largely raw-material producing periphery. From 1890 developmentchanged character, however. While growth of GDP and wages accelerated inScandinavia (as in the United States), it decelerated in Latin Europe (and stagnated inthe United Kingdom). Development diverged both in the European periphery and inthe Atlantic core countries. There was divergence also within Latin Europe. Theeconomies of Spain and Portugal stagnated almost completely, while there was astrong industrial spurt in Italy from around the turn of the century that served toincrease the diversity between northern and southern Italy even more.

The diverging growth rates from 1890 reflect different reactions to the new basis thatwas created for growth with the so-called second industrial revolution.Manufacturing industry became more sophisticated. Electricity and the combustionengine transformed the energy system, machinery became more complex, a newchemical industry arose – all this gave a more central role to engineering, toeducation, to research and science. Abramovitz and David (1973) stated that thisdecade meant a new basis for growth in the United States. In the 19 th century, andparticularly 1850-1890, American growth could by and large be explained by theaccumulation of the traditional factors of production – of land, labour and capital.Capital accumulation was of particular importance in enabling a growing labourforce to take into use the abundant resources of land. But from 1890 the importanceof that accumulation diminished. From this point of time human capital became allthe more important to the increase in growth rates and to a sustained increase in theproductivity of the traditional factors (i.e. in total factor productivity). Thus, thecentre of industrialisation shifted from the building of railways, factories, andresidential constructions to the development of competent labour and management.The returns from investments in knowledge and education increased. A similar newturn was recently pointed out by Goldin and Katz (1996) that found a newcomplementarity between capital and skills arising in the US in combination with thefirst wave of electrification.

At the other extreme, United Kingdom failed to accelerate in the second industrialrevolution. On the other side of the Channel there was a group consisting of France,Belgium and the Netherlands with “close-to-UK” growth rates and only weakacceleration from the 1890s. Thus, we find a sphere of western Europe from UKdown to Spain and Portugal with weak performance in the second industrialrevolution 1890-1910. On the other hand, there was a Continental group of Germany,Austria and Switzerland with “close-to- Scandinavian” growth from 1890. Thus wealso find a strong central axis from Scandinavia (particularly Sweden with the newengineering industries) down to northern Italy – with Sweden and Italy matching USgrowth rates. This paper will not go further into the background of the differingEuropean reactions to this industrial revolution. It will only emphasise that theclassical Gold Standard era holds two distinct periods that may not show up in

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aggregate growth rates. It also emphasises that the reactions to the second industrialrevolution were strongly diverging among European countries, creating scope for anew convergence at a higher level than that of 1870-1890 – a convergence that wasto be delayed due to war and disintegration from the 1910s to the 1950s.

The two post-war periods

It is widely recognised that the 1970s saw a structural break in the post-war period.In the mid-1970s there was not only a shift from high to low growth rates. There wasalso a shift from strong convergence to weak convergence or even divergence, atleast within the industrial world. This was clearly so in the relation between theUnited States and Europe but there was also diverging trends at a regional basis.(Crafts/Toniolo, p 4 ff) Divergence was of course particularly strong in a widerEuropean setting with the catastrophic development in Eastern Europe. While growthrates were quite acceptable in communist Europe in the post-war era of industrialgrowth up to the 1970s, the new conditions of the information revolution meant acatastrophe in terms of growth.

Table 4. Growth rates in Western and Eastern Europe and in the USA 1950-2003.

Western Europe Eastern Europe USA1950-1975 3.6 3.3 2.11975-2004 1.9 -0.1 2.1

Source: Groningen Growth and Development Centre, www.ggdc.net (2006).

Lower growth rates and weaker convergence are problematic to theories ofendogenous growth and of convergence respectively. The shift to weakerconvergence or divergence is problematic to a theory on globalisation andconvergence since there was no breakdown of international integration comparableto that of the interwar period. On the contrary, globalisation rather gained strength.The shift is not emphasised by Williamson who treats the period from 1950 to thelate 1980s as a homogenous one from the perspective of convergence andglobalisation. (1996) It ought to be a problem to the new growth theory that growthdecelerated at a time when knowledge became more intensively used in mostproduction processes. (Cf. “Jones’ critique”, Jones 1995, Josephson 2005) There is ofcourse a reply to the latter objection by referring to the extraordinary character of the1950s and 1960s in Europe. When compared with long run growth 1870-1950, thepost-1973 record in Western Europe is not very disappointing.

Eichengreen (1996) formulated an explanation to the trend-breaks in growth ratesand convergence in Western Europe in the 1970s. The high European growth rates aswell the strong convergence were driven by a double catch-up process that formedpost-war European institutions but eventually, in the 1970s, the process eroded itsown basis. The double catch-up was a result of “the gaps that had opened up vis-à-visboth the United States and Europe’s own pre-war trend” in the two decades ofdepression and war since 1930. (p. 38) With such possibilities to catch-up,institutions and social arrangements were constructed conducive to rapid andforeseeable growth; i.e. wage moderation enabled high levels of investment that were

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directed into clearly defined areas. When catch-up possibilities dwindled, theinstitutional framework of wage moderation broke down.

These conclusions on the European post-war development can be put in a moregeneral framework of the dynamics of uneven development. When newcomplementarities and development blocks have arisen in regions that have forgedahead, the divergence gives rise to differences in productivity and profitability thatbecome the driving force both in market integration and in a catch-up process thatproduces convergence but eventually erodes its basis. The long-run dynamicsdisappear either if new complementarities or development blocks fail to arise in theensuing crisis (no imbalances created) or if market integration fails (no catch-upfollows). In the history of European growth the first failure has not occurred as yetwhile the second failure marred the 1910s and the interwar period.

The double catch up may be phrased in another way, in the framework of structuralanalysis. It was not only a catch-up in relation to USA and to some “mystical growthtrend” but a catch-up in relation to two sets of complementarities that had arisen inearlier decades and that Europe to a large extent had been unable to implement anddiffuse. One set was the new technologies that arose in the second industrialrevolution from the 1890s including sophisticate engineering and chemistry andabove all tayloristic methods of mass-production including the use of new motivepower. These had developed up to 1910 primarily in the US and Germany and tosome extent in Sweden, and could have been diffused more widely in Europe in the1910s and 1920s but for the First World War and the following institutionalshortcomings. The second set of complementarities involved a proper infrastructurebuilt upon electrical motors and combustion engines as well as social arrangementsfor the industrial society widening participation in both economic and political terms.In this transformation, Sweden was a progressive country with new trends from the1930s, whereas most of Europe was drawn into another long and violent conflict.

From the early 1950s institutions were created both internationally and withinEurope that facilitated the double catch-up process – a diffusion that created stronggrowth and convergence within Europe as well as globally but with diminishingreturns and profit squeezes that eventually ended in crisis in the 1970s. From thattime the electronic revolution and the IT-revolution grew in momentum with an endto the strong convergence and with new elements of divergence infused.

Rates of convergence in OECD and in Europe 1950-2004

In this section a more systematic analysis of the convergence process within OECDand within Europe will be performed following the Barro and Sala-i-Martin (1992)formulation of the estimation of beta convergence as expressed in equation 1.

1/T * ln(Yfinal/Yinitial) = alfa -((1-e^beta*T)/T) * ln(Yinitial) + E (1)

where Y is GDP per capita in the respective sample countries and T is the number ofyears.

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Furthermore, convergence in Europe is estimated in two groups, one for WesternEurope and one for all Europe. Of OECD countries Turkey is excluded as an outlier,while all Europe includes the former communist economies and Turkey. In table 5the rates of convergence are estimated both for the whole period 1950-2004 and forthe two sub-periods 1950-1975 and 1975-2004. Thus, for the two periods 1950-1975and 1950-2004 the convergence rates are regressed upon the initial year 1950, whilethe estimate of convergence between 1975 and 2004 is regressed upon the initial year1975 as base year.

Table 5. Annual convergence rates in OECD and in Europe 1950-2004, fixed baseyears.

1950-2004 1950-1975 1975-2004 b P-value b P-value b P-alue

OECD (pre 1994) 1,37 0,000 2,42 0,000 1,61 0,004Western Europe 1,30 0,000 1,96 0,000 2,02 0,001All Europe 0,15 0,512 0,90 0,001 -0,70 0,082

N: OECD 23; Western Europe 17; All Europe 26.

The result in table 5 is in one sense very clear. From the first two columns one canconclude that convergence within OECD and Western Europe was strong until 1975with beta-coefficients above or around 2 percent but that convergence wasconsiderably weaker when 2004 is regressed upon 1950. In both cases, though,convergence is highly significant statistically. For All Europe there is a rather weakconvergence (slightly below 1 percent) until 1975 that almost disappears with thelonger time period. These results all indicate that convergence, when estimated fromthe 1950 basis, came to a halt or was considerably weakened in the period after 1975.

This conclusion is further strengthened by the measure of sigma convergence (thevariance of income per capita within the group of countries, measured annually).That is demonstrated in figure 2 by the sigma convergence of the OECD countries1950-2004. This measure indicates a strong convergence from 1950 up to the early1970s when income variance was roughly halved and then there were fluctuations ofabout 7-8 years (Juglars) on a stable level all through the 1980s, 1990s and early2000s.

Graph 2 about here

When the estimation of beta convergence is made separately for the period 1975-2004, and consequently with 1975 as basis, the result is rather different, though, as isshown in the third column of table 5. In the OECD group of countries there is stillconvergence and it is only slightly weaker than prior to 1975, while convergencewithin Western Europe becomes even stronger than in the post-war decades. Theseseemingly ambiguous results, for Western Europe in particular, is a version of thetraditional index problem with the shifting of base years in the estimation of betaconvergence. It can easily be demonstrated by the relation between income levelsand growth rates in Germany and Great Britain respectively. Germany was on a verylow level and Britain on a high European level in 1950 but to be surpassed byGermany until 1975. In the following decades however Britain once again overtook

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Germany and was on a substantially higher level in 2004. Thus, in both sub periodsthere was convergence in relation to the base years 1950 and 1975, while the lastperiod meant a reversal of trends in relation to the basis of 1950 and thus weakenedconvergence in the 1950-2004 perspective.

Furthermore, the conflicting results also demonstrate the differences and limitationsof the concepts of beta and sigma convergence. While sigma only measures thevariance each year irrespective of the position of the particular countries any otheryear, the beta just measures the latter, namely the change of the position of eachcountry in relation to its prior base year position. (Cf. Quah’s critique of theseconcepts, 1993). Thus, if there is beta convergence, there may or may not be sigmaconvergence, while if there is sigma convergence there must also be betaconvergence of some magnitude.

The estimation of beta convergence is usually made over longer periods, regressinglong term growth rates upon the cross section of income levels of a base year. Suchestimates leave, however, the historical process of convergence out of sight. Thesigma measure on the other hand may be made annually but is an incompletemeasure of convergence. It is possible, however, to estimate the rate of betaconvergence within any time period, e.g. from one year to the next and with aconsequent annual shift of the base year. The resulting estimates of consecutive betacoefficients will then form a time series of a convergence process. The merit of sucha series is e.g. that it may be the starting point for further analysis of impacts uponthe process. There are draw backs as well of course. One is that the statisticalsignificance for each estimate will be lower (see the confidence intervals in thegraphs of the time series) since there is more room for influences of a short termcharacter that are unrelated to differences in income levels.

In the present paper three time series of beta convergence with annually shifted baseyears have been estimated – for the OECD countries, for Western Europe and for AllEurope. They are reported in the graphs 3-5 with confidence intervals.

Graphs 3-5 about here

The graphs of the beta convergence time series show considerable annualfluctuations but on a rather high positive level within OECD and Western Europe inthe post-war period but falling to a low positive level from the early 1970s to theearly 1980s. From then onwards there are great fluctuations between recurrentdivergence and convergence. The All European pattern (including Eastern Europeand Turkey) is somewhat similar but on a lower level of convergence up to the mid-1970s and with a shift to consecutive divergence ending in the catastrophicdevelopment of the early 1990s followed by indication of more persistentconvergence at the end of the period.

The confidence intervals show clearly that most estimates of beta convergence at anannual basis are statistically weak. Quite naturally that goes for estimates ofcoefficients close to zero. One way of evaluating the result is however to investigatethe correspondence between the process of convergence/divergence and otherindicators of economic behaviour in the major economies. One such indicator is theinvestment ratio. It is reasonable to assume that convergence has a negative relation

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to investment growth in the rich US economy, while it has a positive relation toinvestment growth in European economies. Thus a model is formulated (equation 2)where the convergence is determined by the investment ratios in the US and WesternEurope respectively.

Convergence = a C + b1 USinvrat + b2 WEinvrat(-1)+AR(1) (2)

Equations and graphs 6-7 of estimates here

The model gives a good fit to the convergence process within the OECD, inparticular, and in Western Europe (only weak significance though for USinvestments in the latter case). The signs are also as expected – investment increasesin the US contributes to divergence and investment increases in Western Europe toconvergence. One can also notice that there is a time lag from investments toconvergence in Europe but an immediate relation between investments in the US anddivergence, maybe indicating that growth was more investment driven in catching upcountries while in the leading country growth stimulated investments.1 The model isfurthermore especially strong in the period 1955-1986 with high significance for allvariables. In the last two decades variations and deviations from the estimates clearlyincrease. Not too surprisingly the model does not give very satisfactory result for theall European process and certainly not for a period encompassing the divergence ofthe early 1990s. As a general remark, however, it is fair to say that the regressionresults support the economic significance of the annual estimates of the betaconvergence process.

The averages of the annual convergence rates with annually shifted base years (table6) give a somewhat different picture than the convergence estimates with fixed baseyears, in table 5. For the OECD countries and Western Europe the long termconvergence rates 1950-2004 become higher. Furthermore, the periodic patternbefore and after 1975 becomes even more distinct for the OECD and Western Europe– increasing the convergence rates before 1975 and decreasing them after 1975,compared to the fixed base year computations in table 5.

Table 6. Annual convergence rates in OECD and in Europe 1950-2004, annuallyshifted base year.

1950-2004 1950-1975 1975-2004OECD (pre 1994) 1,91 3,10 0,88Western Europe 1,97 2,42 1,57All Europe -0,06 0,88 -0,89

Note: Since the periodic rates are means of annually estimated beta coefficients, noP-values are given.

The convergence process is more clearly visualized in graphs with the annualconvergence rates calculated into a time series from an initial index number of 100,according to the formula: Conv (t) = Conv (t-1) * (1-beta(t))

1 The convergence series is stationary, while there is a weak trend in the investment series. Anestimate on differentiated series gives the same result, however, but with a lower statisticalsignificance.

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Graph 8 about here.

The All European pattern is very pregnant – weak convergence up to mid-1970s andthen accelerating divergence until 1992, followed by stagnation and recovery. ForOECD and Western Europe the accumulated rates show the acceleration ofconvergence in the early 1960s and the slow down from 1972 up to the first years ofthe 1980s. Then two divergences followed, in the first half of the 1980s and 1990srespectively, both giving way markedly to convergence. One can notice that theselatter processes fit to the business cycle pattern in relation both to economic activityand to major technological shifts. From low activity in the early 1980s, a businesscycle upswing saw the diffusion of the PC and the mobile phone as components ofnew developments blocks and organisational change, while the upswing from thecrisis in the early 1990s was connected to the diffusion of Internet and a moregeneral use of ICT. One can also notice that the shifts to convergence weredecisively stronger in Western Europe than within the OECD group in these decades.The variation between divergence/convergence over these decades indicates that theearly phase of these upswings had a positive relation between income levels andgrowth rates while the ensuing diffusion processes saw the recurrence ofconvergence.

Confronting the series based on annual estimates of the beta and sigma coefficientsmay give further insights into the convergence process. In graph 10, a ratio betweenthe two index series of convergence among the OECD countries shows in whatperiod convergence is driven mainly by decreased variance (sigma) and in whatperiod it is mainly driven by growth rates relative to income levels. Clearly in the1960s and in the period 1985-2004 the latter force contributed much to convergence.Furthermore, the stronger convergence in Western Europe compared to OECD sincethe 1980s indicates that this was mainly a force in Europe, within a more invariantOECD distribution.

Graph 9 about here

Thus, both sigma and beta coefficients indicate a slow-down of convergence after1975 as well as cyclical shifts between divergence and convergence - as noted abovethere are indications of divergence in the early phase of upswings in the 1980s and1990s followed by convergence over the later phase of the swings, particularlystrongly in the 1980s. These spurts in convergence were more pronounced withinEurope than within OECD. Furthermore, there are both technological breakthroughs(the PC and the ICT) and institutional changes with a deepened European integrationand single market reforms. One explanation to the pattern could be that rich andknowledge intensive countries were favoured in the early phase of each breakthrough(endogenous growth) but that convergence followed quite rapidly with marketintegration substantially reducing obstacles to diffusion.

Convergence or divergence is basically driven by the ability in different economiesto adapt to new conditions in technology and markets. One may assume that growthmeans a relatively stronger increase in those sectors that are intensive in usingknowledge and new technology and that convergence means that the rate of increaseis negatively related to the relative initial size of that sector. Thus one may measure

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the structural convergence in modern economies from the relative size and growthrates of knowledge intensive industries (including services).

The Barro/Sala-y-Martin equation is accordingly reformulated into

1/T * ln(Sfinal/Sinitial) = alfa -((1-e^beta*T)/T) * ln(Sinitial) + E (3)

where S is the share of knowledge intensive production of goods and services in eacheconomy. The process of structural beta convergence has been estimated from the setof 60 industries table at the Groningen data base, including 21 OECD countries forthe period 1979-2002.

The structural process is depicted in an indexed annual series in graph 10. The resultis quite unambiguous. In the first half of the 1980s the index fluctuated with somedivergence in the trough years of 1981-83 followed by a pronounced and strongstructural convergence during the second half of the 1980s. Around 1990convergence came to a halt and structural divergence followed in the 1990s. Thus,from the 1990s knowledge intensive industries grew in relative size in countries withrelatively large such sectors. This may indicate that the ICT revolution, which reallygained strength in the 1990s, at this stage favoured relatively rich and knowledgeintensive countries.

Graph 10 about here

There are also shifts in the regional patterns of growth within Europe since 1950 thatmay be explained by these recurrent shifts in the basis of growth. Western Europemay be divided into three regions both geographically and, with some modifications,also economically: that is the rich Northwest (including Ireland, UK, Holland and theScandinavian countries), the middle-income Continent (including Germany,Belgium, France, Switzerland, Austria and Italy) and the poor Southwest (Portugaland Spain). The economic categorization is not fully water-proof for the wholeperiod 1950-2004 and for every region but it gives a generalized view. Table 7 givesthe aggregated growth rates for these regions.

Table 7. Annual growth rates in GDP per capita in regions of Western Europe 1950-2004.

Source: See table 4.

The overall convergence within Western Europe was certainly very strong up to1973 and it continued at a slower pace until 1990. From 1990 there is a clear shifthowever. While the relatively rich Northwest accelerated somewhat, the poorsouthwest decelerated further - though still converging. In Continental Europedeceleration was drastic however. It did not only affect Germany but also the rest ofthe Continent with Switzerland at the bottom in terms of growth rates. It is clear that

Northwest Continental Southwest1950-1973 2.7 4.5 5.41973-1990 1.9 2.1 2.61990-2004 2.0 1.2 2.3

15

the growth pattern from 1990 involves elements of both convergence and divergence.But it is also striking that the acceleration in the Northwest, mainly working fordivergence, fits to a broader global pattern - accelerating growth in English-speakingor relatively English-speaking environments coincides with the ICT-revolution fromthe 1990s. This may involve a crucial element in the diffusion and adaptation processto a new communication standard in a globalising knowledge intensive economy. Itis also an indication of rather complex investment patterns for catch-up processes tocome.

Conclusion

The idea of this paper is mainly two-folded. Firstly, processes of convergence anddivergence, that logically follow from neo-classical theory and new-growth theoryrespectively, characterise different phases of the growth process. Their alternationsmay constitute patterns related to structures behind growth. Secondly, thoseprocesses could form a periodisation of growth. While growth rates apparently werevery even 1870-1890 (built upon the new institutions and infrastructures developedin the 1860s and 1870s), the second industrial revolution introduced new forces ofdiverging rates from the 1890s. The outbreak of war in the 1910s and the dismantlingof market integration obstructed a possible convergence with the diffusion of thesenew development blocks in the following decades. In the interwar period a secondset of complementarities evolved very unevenly and were diffused together withtechnologies from the second industrial revolution in the Golden Ages of growth andconvergence 1950-1973. With the third industrial revolution, gaining momentum inthe second half of the 1970s, forces of divergence and transformation of structureswere released once more. In particular, the ICT revolution of the 1990s releasedforces of divergence comparable to the technology of electricity a hundred yearsearlier but in a different regional and cultural setting. If electricity put its imprint onregional growth patterns then, it is rather English today.

It may also be the case that technological shifts and forces of divergence areparticularly strong in periods of industrial revolutions, while convergence gainsstrength during the subsequent century – culminating with the construction anddiffusion of infrastructural development blocks that serve to diffuse technologicalchange, increase institutional integration and underpin modern economic growthmore efficiently.

16

Figure 1. GDP per capita in 14 European countries 1870-1994. 1990 Gheary-KhamisDollars.

4000

8000

12000

160002000024000

1875 1900 1925 1950 1975 2000

Note and sources: See table 1.

17

Figure 2. Estimate of sigma convergence in the OECD countries 1950-2004.

.20

.25

.30

.35

.40

.45

50 55 60 65 70 75 80 85 90 95 00 05

Fig 3. Annual convergence rates in All Europe 1951-2003. Estimated with movingbase years. Confidence intervals of the estimations.

-.16

-.12

-.08

-.04

.00

.04

.08

50 55 60 65 70 75 80 85 90 95 00 05

18

Fig 4. Annual convergence rates in the OECD countries 1951-2004. Estimated withmoving base years. Confidence intervals of the estimations.

-.08

-.04

.00

.04

.08

.12

50 55 60 65 70 75 80 85 90 95 00 05

Fig 5. Annual convergence rates in Western Europe 1951-2004. Estimated withmoving base years. Confidence intervals of the estimations.

-.08

-.04

.00

.04

.08

.12

50 55 60 65 70 75 80 85 90 95 00 05

19

Equation (2): Convergence OECD

Dependent Variable: CONVERGOECDMethod: Least SquaresDate: 01/16/06 Time: 13:04Sample(adjusted): 1952 2000Included observations: 49 after adjusting endpointsConvergence achieved after 7 iterations

Variable Coefficient Std. Error t-Statistic Prob.C -0.015281 0.034871 -0.438208 0.6633

USINVRAT -0.360723 0.093989 -3.837918 0.0004WEINVRAT(-1) 0.417809 0.123412 3.385479 0.0015

AR(1) 0.165439 0.136631 1.210842 0.2323R-squared 0.445953 Mean dependent var 0.019398Adjusted R-squared 0.409017 S.D. dependent var 0.021912S.E. of regression 0.016845 Akaike info criterion -5.251411Sum squared resid 0.012769 Schwarz criterion -5.096977Log likelihood 132.6596 F-statistic 12.07353Durbin-Watson stat 1.943770 Prob(F-statistic) 0.000006Inverted AR Roots .17

Fig 6. Annual convergence rates in the OECD countries 1951-2004 with movingbase years (full line) and estimated rates by equation 2 (dotted line).

-.06

-.04

-.02

.00

.02

.04

.06

50 55 60 65 70 75 80 85 90 95 00

CONVERGOECD ESTIMATE

20

Equation (2): Convergence Western Europe

Dependent Variable: CONVERGWESTMethod: Least SquaresDate: 01/16/06 Time: 13:06Sample(adjusted): 1952 2000Included observations: 49 after adjusting endpointsConvergence achieved after 8 iterations

Variable Coefficient Std. Error t-Statistic Prob.C -0.076313 0.048913 -1.560156 0.1257

USINVRAT -0.137088 0.129804 -1.056113 0.2966WEINVRAT(-1) 0.508620 0.174515 2.914483 0.0055

AR(1) 0.363402 0.138501 2.623823 0.0118R-squared 0.321636 Mean dependent var 0.020309Adjusted R-squared 0.276411 S.D. dependent var 0.022117S.E. of regression 0.018813 Akaike info criterion -5.030392Sum squared resid 0.015927 Schwarz criterion -4.875958Log likelihood 127.2446 F-statistic 7.112014Durbin-Watson stat 1.946869 Prob(F-statistic) 0.000520Inverted AR Roots .36

Fig 7. Annual convergence rates in Western Europe 1951-2004 with moving baseyears (full line) and estimated rates by equation 2 (dotted line).

-.04

-.02

.00

.02

.04

.06

.08

50 55 60 65 70 75 80 85 90 95 00

CONVERGWEST ESTIMATE

21

Figure 8. Convergence estimated with annually shifted base in OECD, WesternEurope and All Europe 1950-2004. Index 1950=100.

30

40

50

60

70

8090

100110

55 60 65 70 75 80 85 90 95 00

OECD WE

AllE

Figure 9. The ratio between annually estimated beta convergence and sigmaconvergence in the OECD 1950-2004.

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

50 55 60 65 70 75 80 85 90 95 00 05

22

Figure 10. Structural convergence in OECD countries 1979-2002. Index 1950=100.

60

70

80

90

100

1980 1985 1990 1995 2000

23

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