technological variety and the size of economies

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Technovation 27 (2007) 650–660

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Technological variety and the size of economies

Andrea Mangani�

Department of Economics, Faculty of Political Science, Via Serafini 3, 56126 Pisa, Italy

Abstract

Several empirical studies show that the size of an economy affects the number of fields where it is technologically active (technological

variety). In this paper I ‘‘quantify’’ the relationship between the countries’ economic size and technological variety by using European

patent data. Thus, technological variety can be distinguished from technological intensity. I find that technological variety accounts for

about 40% of the higher number of patent applications made by larger and richer economies. However, the size/variety relationship is

more robust than the wealth/variety relationship. The empirical results regarding technological activity resemble those on international

trade and may be interpreted combining different theories.

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Keywords: Technological variety; Diversification; Patents

1Other studies adopt a more general approach, which takes into account

the relationships between technological size and diversification, economic

1. Introduction

The technological specialization of countries has beenfrequently investigated by economists of distinct fields ofresearch. The availability of data about internationalpatenting and aggregate R&D expenditure means thatthe historical evolution of specialization in technology canbe traced within several countries. Many studies in thisarea regard the relationship between the countries’economic performance (for example in terms of GDP orGDP per capita) and technological diversification. Archi-bugi and Pianta (1992a, b) showed that larger countriestend to spread their technological activities across manysectors, while smaller economies seem to concentrate onnarrow fields. Pianta and Meliciani (1996) found a generalpositive relationship between the degree of specialization intechnology and higher rates of economic growth, thoughspecialization in electronic-related fields is not associated tobetter economic or technological performances. Malerbaet al. (1997) analyzed the persistence and heterogeneityof innovative activities at the level of the firm, and itsinfluence on the technological change in different industriesand countries. Mancusi (2001) showed the existence of

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two country size effects: economically large countries arecharacterized by a wider range of technologies and theyalso display a higher degree of persistence in the patterns ofspecialization, although mobility across technological fieldsis high in all countries. More recently, Cantwell andVertova (2004) found that the positive size/diversificationrelationship exists as much in the past as it does today,although it has changed structurally since 1965.1

A well established result of all these studies is a positiverelationship between the size of economies and the degree oftechnological diversification. This confirms the resultsobtained by international empirical economists: smallercountries are more open to foreign trade, and they areforced to specialize in exports because their nationalproductive capacity does not allow them to cover allindustries uniformly. Thus, an inverse relationship has beenhighlighted between the size of a country and the variety ofits exports. For example, Hummels and Klenow (2005)found that the variety of exports account for about 60% ofthe greater exports of larger economies. These empirical

growth, and employment. See, for example, Laursen (2000), Ruttan

(2001), Meliciani (2001), Best (2001), OECD (2001), Fagerberg (2002) and

all the references therein.

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ARTICLE IN PRESSA. Mangani / Technovation 27 (2007) 650–660 651

findings, deriving from distinct areas of research, areparticularly important given the ‘‘recent’’ developments ofmacroeconomic growth theory, which attempt to integratethe theory of international trade with the theory ofeconomic growth, when the latter focuses on the economicdeterminants of technological progress.2

The term ‘‘size’’ is used differently by various authors,either the economic size of a country, in terms of GDP,population, etc. (as, for example, in Mancusi, 2001), or itstechnological size, measured through the R&D aggregateexpenditure or the number of patents granted (Cantwelland Vertova, 2004). However, most studies analyzed theeffects of technological size on technological diversificationbecause, as highlighted by Cantwell and Vertova (2004),the economic and technological sizes are positivelycorrelated for the majority of countries.3 These authorselaborated some data drawn from Maddison (1995), andfound that various measures of size, such as populationand GDP, are positively correlated with technological size,measured through the patents filed at the US Patent andTrademark Office (hereafter, USPTO). Therefore, giventhat large countries patent more, a part of additionalpatent applications seems to be explained by a greatertechnological diversification; but, how much?

In order to answer this question, in this paper I use thekey concept of technological variety instead of techno-logical diversification. The difference will be clarified in thenext sections. Then I try to break down the effect ofeconomic size into two areas: the intensity of technologicalactivities (intensive margin), and their variety (extensive

margin). Both effects of country size are expected to bepositive: larger countries present patent applications in awider spectrum of technological fields, and they also patentmore in each technological field. Previous studies did takeinto account the influence of total patent applications ofeach country to determine the degree of technologicalvariety, but they did not decompose and quantify the twoeffects.

Another motivation of the present study is to extend thesize/variety analysis to a higher number of countries. Allprevious studies considered sub-samples of countries.4 Inthis paper I have considered all those countries thatpresented patent applications to the European PatentOffice (EPO) in 2002. Thus, I can verify whether thepositive size—variety relationship holds for many countriesin the world and how sensitive it is to macroeconomiccharacteristics. This analysis is static in nature, so it differsfrom many other studies regarding the ‘‘evolution’’ of

2See Grossman and Helpman (1991). In relation to the links between

specialization in trade and technology, see Laursen (2000) and Meliciani

(2001).3In particular, the GDP shows a stronger correlation with patenting

than does population.4For example, Cantwell and Vertova (2004) analyzed the size/

diversification relationship for eight rich countries; Mancusi (2001)

considered 10 advanced economies; Archibugi and Pianta (1992a) studied

the specialization in technology in OECD countries.

technological specialization. However, previous workshowed that the patterns of technological specializationare rather stable (Mancusi, 2001; Cantwell and Vertova,2004). In addition, the countries considered in the presentpaper differ considerably in their degree of economicdevelopment, thus the results may be coupled andcompared with those deriving from the analyses whichuse a dynamic approach.Finally, the paper compares the results in terms of

technological variety to the empirical findings regardingvariety in production and international trade. Recentempirical studies quantified the role of product variety inexplaining the greater exports of larger and richercountries. Since this branch of literature inspired thedetermination of technological variety in the present paper,I can interpret the empirical results taking into account thetheories that link the structure of technological activity tothe patterns of foreign trade flows.The rest of the paper is organized as follows. In the next

section I present the possible theoretical predictions aboutthe relationship between the size of economies and theintensity/variety of technological activity. Section 3describes the data, introduces the methodology of empiri-cal analysis and presents the results. Section 4 describes thetheoretical relationships between variety in technology andin trade, and discusses the results along with the empiricalstudies about product variety in international trade. Thelast section provides some final comments along with thepossible directions for future work.

2. Empirical hypotheses

In this section I briefly describe the possible theoreticalpredictions about the relationship between technologicalvariety and the size of economies. These hypotheses consistof simple general correlations between macroeconomiccharacteristics of countries and the structure of innovativeactivity, but they may be incorporated in the broaderliterature that explores the linkages between technology,structure of internal production and international tradethat are discussed in the fourth section. In the course of theanalysis, countries will be the unit of analysis. Thus, forexample, the degree of technological variety is related toactivities performed by firms which locate within nationalborders (while the expression ‘‘technological diversifica-tion’’ is usually adopted by the firm level). Although thisapproach presents some problems (caused, for example, bythe innovative activity performed by multinational firms),it is frequently adopted by researchers and experts oftechnological specialization. In addition, investigating thepatterns of innovation at the country level is justified by theemergence of the ‘‘national systems of innovation’’, aphenomenon described, among others, by Lundvall (1992).On the one hand, investments in R&D are risky.

Therefore, options theory suggests that a country (and itsfirms) should diversify its investments in order to mitigatethe risk. On the other hand, economies of scale may induce

ARTICLE IN PRESSA. Mangani / Technovation 27 (2007) 650–660652

a country to concentrate its resources in a limited numberof technological areas, to exploit such economies. Inaddition, the theory of comparative advantages suggeststhat countries have different initial resource endowmentswhich are necessary to undertake R&D investments, thusthey may prefer to focus their innovative efforts wherethose endowments are higher.

These qualitative considerations imply that large econo-mies (in terms of GDP and population), endowed withhigher resources, may spread and diversify their invest-ments across many technological fields, and still be able tomeet the minimum efficient scale for obtaining excellence inall these fields. In contrast, small countries face moreconstraints and thus they need to use their resources in fewtechnological areas. Of course, this does not mean thatsmall countries will concentrate the innovative efforts inthe same areas. In particular, Walsh (1987) argues thatsmall advanced economies tend to develop their compe-tencies in niche markets, as this may give them some degreeof product differentiation in international markets. Thisprediction seems to be confirmed by empirical observations(see, for example, Soete, 1988; Archibugi and Pianta,1992a,1994; Laursen, 2000).

In addition, large countries have a greater domesticmarket and a demand effect may induce large economies tospread their innovations in many sectors. In fact, a largedomestic market means more consumers with highlyheterogeneous preferences, in relation to both final andintermediate goods. This may create an incentive fornational firms to invest more in innovation, in order tocreate higher product differentiation when the innovationsare introduced in the markets. Therefore, larger countriesshould be characterized by greater innovative efforts bothwithin each field (the ‘‘intensity’’ of technological activity)and across different fields (the ‘‘variety’’ of technologicalactivity). Moreover, large countries have a higher numberof large companies that are technologically active and thatdiversify their investments in R&D, and this should bereflected in a higher degree of technological variety at thecountry level. The empirical analysis may show whichfactors are more important in explaining the greaterpatenting activity of large economies.

Another possible hypothesis is that the effect of theincreasing availability of resources on technological varietyis higher in less advanced economies. This is because poorcountries need to ‘‘look into’’ many technological fields tofind where it is possible to compete at an internationallevel, by exploiting economies of scale through thespecialization in some technological areas. This ‘‘static’’hypothesis is consistent with the ‘‘evolution’’ of techno-logical specialization described, for example, by Cantwelland Vertova (2004) and Pianta and Meliciani (1996),although they focus their analysis on advanced economies.These authors show, respectively, that large countries havebecome less diversified in their technological specializationin the last 40 years, and that there exists a positive linkbetween the degree of sectoral specialization and the

countries’ economic growth. Hence, it seems that poorestcountries need to ‘‘explore’’ the whole spectrum oftechnological fields in order to find the patterns ofspecialization which allow them to improve their economicperformance. Once the size and income of economies ishigher, size and income still affect positively the variety ofinnovative efforts (for the reasons described at thebeginning of this section), but the link is probably lessstrong in large countries. In reality, some studies (see, forexample, Acemoglu and Zilibotti, 1997) show that aggre-gate volatility tends to fall with income per capita. Thismeans that small and poor countries are forced, on the onehand, to explore the technological opportunities to becomeinternationally competitive, and, on the other, to facegreater risks in R&D investments. Again, empiricalobservations may be useful to find the predominant factorsin the determination of countries’ technological variety.

3. Data, methods and results

The empirical analysis of this paper is based on the useof patent statistics as a proxy for profiles of countries interms of technological size and variety. Patent statisticsmay not be totally reliable as indicators of technologicalactivity. In fact, some patents are important and revolu-tionary for technological progress, while others are notindicative at all: the quality of patents is difficult toascertain, unless one conducts specific analyses on patentcitations and renewals. Important inventions are notnecessarily always patented, but some of them neverthelessbecome innovations. Finally, the propensity to patentvaries across firms, industries and countries. In spite of allthese drawbacks, patent statistics provide a very detailedindicator for studying the patterns of technological variety.Thus, they are a unique data source on innovation activity(for a review about these themes see Pavitt, 1982; Basberg,1987; Griliches, 1990).I use patent data drawn from the EPO official statistics

and thus I consider international patenting in a thirdgeographic area: the European Union. Previous empiricalstudies have generally used USPTO data, regarding thepatents in force within US. Effectively, given the size ofthe market and the technological development of the US,the invention patented in the US are expected to have aprominent influence on the economic and technologicalactivity of the rest of the world. However, the Europeanmarket has now a considerable size and can represent agood reference point. In addition, using European statisticsmeans that foreign patenting for all countries can be takeninto account. In fact, with the USPTO statistics, the USdomestic patents are used instead of foreign patents. Ofcourse, the analysis may be replicated by consideringpatenting activity in other areas.I chose a single year both for the sake of methodological

simplicity, and because it is reasonable to assume that thepositive relationship between economic size and techno-logical variety holds in a single year, since it has been


proved to be historically stable (Mancusi, 2001; Cantwelland Vertova, 2004).

The main cross-section analysis regards patent applica-tions made in 2002, sorted by country and technologicalfield (technical units according to the terminology of theEPO, that currently uses 32 technical units in its officialstatistics, shown in the Appendix, Table A1).5 I havecollected applications instead of registrations becauseregistrations made in one year may regard applicationsdeposited in different years, thus forming a non-homo-geneous set. This may lead to some methodologicalproblems when patents are related to macroeconomicvariables such as GDP, GDP per head, and population.6

Since I am interested in a quantitative and non-qualitativeanalysis of the size—variety relationship I have notdetermined the sectors where countries exhibit a techno-logical specialization. For advanced economies, such ananalysis can be found, for example, in Archibugi andPianta (1992a) and Eaton et al. (1999).

The analysis of patent data is slightly different withrespect to previous work on technological specialization.Previous studies employed various indexes to characterizethe extent of specialization of a country in a technologicalfield. For example, Mancusi (2001) defined and discussedthe Technological Revealed Comparative Advantage(TRCA) index and the Revealed Technological Advantage(RTA) index, both based on patent data. For the latter, thespecialization of country i in the technological sector j isgiven by

RTAij ¼Pij=

PjPij

ð1=NÞP

j Pij=P

jPij

� � , (1)

where Pij denotes the number of patents of country i in thesector j, and N is the total number of technological fields.7

At the aggregate level, the degree of specialization intechnology shown by countries was measured by observingthe distribution of these indexes across sectors. A commonfeature of previous studies was that they did take intoaccount the technological size (i.e., the total number ofpatents granted or deposited) of each country in determin-ing its degree of technological variety/specialization,but they did not clearly distinguish and quantify thetwo phenomena of intensity and variety in technology.

5Using a single method of patent classification may create some

problems for economic and technological analysis. For example, the poor

concordance between economic sectors and technical fields makes it

difficult to interpret the ‘‘direction’’ of innovative efforts. In addition, the

probability to be active in a technological field depends on the relative size

of the field.6Some previous studies consider patent applications. See Archibugi and

Pianta (1992a) and Mancusi (2001). I have replicated the empirical

analysis using patent registrations (that is, patents granted) in 2002 and

2003, in order to check the robustness of results. Results were similar using

this different data set.7Thus, this index compares an economy’s share of patenting in a given

technological field to its average patenting share in all fields. A value of

RTAij above unity indicates that country i specializes in field j.

The ‘‘analytical’’ explanation is that the various indexes ofvariety/specialization incorporate the number of totalpatents (in other words, the technological size and thetechnological variety are inseparably linked). In this paperthe variety and intensity of technological activity will beseparately quantified.Moreover, while previous work defined technological

diversification as the opposite phenomenon of technologi-cal specialization (or concentration), I use a differentapproach. The number of technological fields where acountry is active reveals its technological variety: the higherthe fields, the greater the variety. When a country presentspatent applications in few technological fields, this does notmean that its ‘‘specialization’’ is higher, but only that itstechnological variety is low.8 This is done in order toquantify, separately, the effects that economic size produceson the ‘‘technological variety’’ and on the ‘‘technologicalintensity’’, which will be shortly defined. This approachmay cause some problems of interpretation, as I discusslater on.To sum up, I assume that economic size is positively

associated with technological size. Most importantly, Isuppose that this association is due to both variety andintensity: economically larger countries are technologicallyactive in a wider range of fields, and they also exhibit agreater technological activity in each field.In order to quantify these effects, I use the following

methodology, which is inspired by the studies of interna-tional economics about export variety (see Hummels andKlenow, 2005, and references therein). I define theextensive margin (EMj) of country j simply as nj, thenumber of technical units where country j deposited at leastone patent in 2002. In addition, I define the intensive

margin of country j with

IMj ¼

Pnj

i¼1X ji

nj

, (2)

where Xji is the number of patents filed by country j in classi. In other words, IMj is the average number of patents ofcountry j per technical unit. I clearly have that

X j ¼ EMj � IMj, (3)

where Xj is the total number of patent applications ofcountry j. Compare, for example, the Spanish andPortuguese patent applications in 2002. Given each size,it is not surprising that Spain’s applications (603) wereabout 21 times larger than Portugal’s (23). This can bepartially explained by the greater number of technical unitscovered—Spanish patents were spread over 29 technicalunits, while Portugal covered 15 classes. Another partderives from a greater average number of patents: onaverage, 20.79 Spanish patents per technical unit, against1.53 Portuguese patents. Here the different number ofpatent applications is due both to intensive and extensive

8In other words, in this paper the term ‘‘variety’’ is not the synonym of

diversification, nor the antonym of specialization.

ARTICLE IN PRESSA. Mangani / Technovation 27 (2007) 650–660654

margins. There are other cases where only one margin isresponsible for the difference in technological size. Forinstance, UK firms deposited 4709 patents in 2002,amounting to 1.8 times more than Sweden (2565). Sinceboth countries’ patents were spread over 31 technical units,here the intensive margin plays the prominent role.

One could object that this method of decompositionleads to overstate the technological variety. For example, ifcountry A has only one patent in each of 31 technical unitsand 1000 patents in the last 32nd technical unit, it wouldhave the highest extensive margin (32), while its technologyis effectively highly concentrated in the last technical unit.However, though country A does specialize in the lasttechnological field, it also has the ability to spread itstechnological activity in all fields. In other words, thetechnological activity of country A is characterized by highspecialization, and also by great variety. However, theinfluence of extensive margin would be overstated, ‘‘inaggregate’’, if there were several countries with a greattechnological variety and also with a highly skeweddistribution of patents across classes (that is, if there weremany countries similar to country A). Is this a character-istic of the sample? The following graph reports, for eachpatenting country in 2002, the number of technical unitswith at least one patent application (extensive margin), andthe coefficient of variation (CV) of patent applicationsacross technical units.

Fig. 1 shows that there is an inverse relationship betweentechnological variety and the variability of patent applica-tions across technological fields. This means that somecountries may be highly specialized in a technological field,but they do not spread their technological activity in manysectors. The only cases that are worth to mention are theBarbados, India and Finland. The Barbados presentedmany patent applications in class 4 (chemical processes),

0

1

2

3

4

5

6

0 10 20 30

Extensive margin

Coeffic

ient of variation

Barbados

FinlandIndia

Fig. 1. Extensive margin and variability of patent applications across

sectors. Notes: The figure reports a cross-section of patenting countries in

2002. Extensive margin: number of technical fields with at least one patent

application. The Y-axis measures the variability of patent applications

across technical fields.

while India presented many patent applications in class 5(hydrocarbons, mineral oils, fuel, igniting devices) andclass 13 (general industrial equipment). However, these twocountries do not exhibit a great technological variety. Onthe other hand, Finland shows a great technological variety(EM ¼ 30) while it presented most patent applications inclass 31 (miscellaneous metal product). All in all, it seemsthat only Finland cannot influence the general result toomuch. Hence, the extensive margin does not risk to beoverstated, at least when it is used to compare thetechnological variety of different countries.9 Of course,the probability that a country presents a patent applicationin a technical field, thus increasing its extensive margin,depends on the size of the field. This bias might be limitedwith an ex post analysis of countries’ patenting activity; buta general solution is much more problematic, because ofthe particular nature of any classification of patents. Thesein fact are requested to work for classifying newlypublished documents disclosing inventions that are ‘‘bynature’’ novel, although they may have been formedorganizing and re-elaborating existent documents disclos-ing existent inventions. Therefore, whatever assumptionabout the extent of technological fields (which could drivethe determination of technological variety) would bearbitrary.I have considered all countries that presented at least one

patent application to the EPO in 2002.10 These are in theAppendix (Table A2). For each country, I constructed theextensive margin and the intensive margin. I then regressedthe natural log of total patent applications and of eachmargin on the country’s log GDP, at current exchangerates (YA). Separately, I regressed each value on thecountry’s log population (N) and on log GDP PPP percapita (YB/N). Data on GDP, population and GDP percapita were collected from the World Bank officialstatistics. The regression samples are cross-sections ofpatenting countries in 2002. Since I regressed the extensiveand intensive margin on each country’s macroeconomicvariable, this approach produces simple correlations, but ithas an interesting advantage: because OLS is a linearoperator, the regressions additively decompose the marginsalong which larger, more populated, or richer economiespatent more.Table 1 presents the results of the regressions for all

countries. The number of observations may vary becausethe macroeconomic variables are not available for alleconomies.

9A similar question regards those countries which deposit few patents.

Should a country with only one patent application be considered as a

country with total concentration of innovative activities? The answer is no.

The only thing that can be said about this country is that both intensive

and extensive margin are very low.10Therefore, I include in the sample countries that present very few

patent applications. Although this permits to consider a sample larger

than in other studies, it is more likely that the results are random. This

problem may be controlled replicating the empirical analysis with patent

registrations (see footnote 6).

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Table 1

All countries: economic size and technological variety (2002)

Independent variable- YA Adj. R2 N Adj. R2 YB/N Adj. R2

Dependent variablek

Overall patents 1.13*** 0.59 0.35*** 0.08 2.69*** 0.53

(0.11) (0.12) (0.28)

Intensive margin 0.68*** 0.53 0.23*** 0.09 1.55*** 0.44

(0.07) (0.07) (0.19)

60% 65% 58%

Extensive margin 0.45*** 0.49 0.12** 0.05 1.13*** 0.49

(0.06) (0.05) (0.13)

40% 35% 42%

Countries 80 92 79

Notes: All variables are in natural logs. The table reports univariate OLS regressions. YA ¼ 2002 total GDP (market exchange rates). N ¼ 2002

population. YB ¼ 2002 GDP PPP. *Statistically significant at the 10% level. **Statistically significant at the 5% level. ***Statistically significant at the 1%

level. Standard errors in parenthesis.

Data Sources: World Bank for GDP and Population. European Patent Office for patent applications.

Table 2

Richest countries: economic size and technological variety (2002)


Dependent variablek

Overall patents 1.12*** 0.71 1.07*** 0.51 4.98*** 0.38

(0.12) (0.17) (1.01)

Intensive margin 0.84*** 0.70 0.81*** 0.52 3.54*** 0.34

(0.09) (0.12) (0.78)

75% 76% 71%

Extensive margin 0.28*** 0.49 0.26*** 0.38 1.44*** 0.34

(0.05) (0.06) (0.31)

25% 24% 29%

Countries 39 39 39

Notes: All variables are in natural logs. The table reports univariate OLS regressions. YA ¼ 2002 total GDP (market exchange rates). N ¼ 2002

population. YB ¼ 2002 GDP PPP. *Statistically significant at the 10% level. **Statistically significant at the 5% level. ***Statistically significant at the 1%

level. Standard errors in parenthesis.


A. Mangani / Technovation 27 (2007) 650–660 655

The first row shows that larger economies in terms ofGDP and population patent more. For example, countrieswith twice the population deposit 35% higher patents. Inaddition, the elasticity of patents with respect to the GDPper capita is very high. The second and third rows showhow these effects may be attributed to intensive andextensive margins. The extensive margin accounts foraround 40% of higher patent applications of larger andricher countries. Therefore, larger and richer economiespatent more, and this occurs, for about 40%, because ofhigher technological variety (the indication of eachmargin’s percentage contribution to overall patent applica-tions may not be particularly meaningful when thecoefficients are not significantly different from zero). Thepositive relationship between population and patents,already considered ‘‘weak’’ by Cantwell and Vertova(2004), is effectively not strong. Broadly speaking, thegeneral results of previous studies are confirmed: largeeconomies spread their technological activity across many

sectors, as observed by Archibugi and Pianta (1992a) andCantwell and Vertova (2004) among others. Moreover,Table 2 confirms the results of Pianta and Meliciani (1996),consisting of a strong negative relationship betweentechnological specialization and GDP per capita.However, previous works focused on advanced coun-

tries, so it is important to investigate how the findingsreported in Table 1 are affected by the macroeconomiccharacteristics of nations. To do this, I splitted the countrysample and performed the regressions separately for therichest and poorest economies, in terms of GDP per capita.The results are reported in Tables 2 and 3.Table 2 shows that all coefficients are positive and

significant, as it was expected given the results of previousinvestigations reported in Section 1. The coefficients incolumn five are very high: countries with twice the GDPper capita present a number of patent applications fivetimes larger. Finally, the contribution of the extensivemargin is lower than that reported in Table 1, for each

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Table 3

Poorest countries: economic size and technological variety (2002)


Dependent variablek

Overall patents 0.71*** 0.56 0.62*** 0.46 0.83 0.03

(0.10) (0.10) (0.55)

Intensive margin 0.23*** 0.47 0.22*** 0.45 0.12 �0.02

(0.04) (0.04) (0.20)

32% 35% 14%

Extensive margin 0.48*** 0.51 0.40*** 0.40 0.71* 0.06

(0.07) (0.08) (0.38)

68% 65% 86%

Countries 40 40 40

Notes: All variables are in natural logs. The table reports univariate OLS regressions. YA ¼ 2002 total GDP (market exchange rates). N ¼ 2002 population.

YB ¼ 2002 GDP PPP. *Statistically significant at the 10% level. **Statistically significant at the 5% level. ***Statistically significant at the 1% level.

Standard errors in parenthesis.


A. Mangani / Technovation 27 (2007) 650–660656

column: in richest countries, the extensive margin accountsfor 24–29% of additional patent applications by larger,more populated, and richer economies. A partiallysymmetrical situation is shown in Table 3, which reportsthe results of the cross-sections for poorest countries. Thecoefficients of GDP and population are positive andsignificant, although they are lower than in Table 2. Therole played by the extensive margin is prominent: inpoorest countries, the extensive margin is responsible for65–68% of additional patent applications by larger andmore populated economies. On the other hand, thepatents/GDP per capita relationship is not significant.

These results may be affected by the patenting activity ofEuropean countries. European firms may have a higherincentive to obtain a patent that is in force within theEuropean Union. Since many European countries presenta high income per capita, the effect of macroeconomicvariables on the margins under review may be over-estimated. However, the set of rich European countries isnot much representative today: the European Unioncomprises 25 countries, some of which are economicallysmall or have a rather low income per capita.

Finally, it is important to note that the method ofclassification may affect the results in terms of thepercentage contribution of the extensive (intensive) margin.In fact, if it were possible to have more disaggregatedtechnical units, the extensive margin would probably play amore important role in the pooled sample. Although I haveused a high level of aggregation, the extensive margin doesplay a prominent role, because it explains almost the half ofadditional patent applications of larger countries. Thisconsideration is important when one compares the resultsof distinct empirical studies (see next section).

4. Discussion: variety in technology and trade

The concept of product variety has been the focus ofrecent empirical studies in the fields of both technological

innovation and international trade. It may therefore behelpful to link the principal results together. Broadlyspeaking, most economics scholars recognize the existenceof a strong relationship between technological innovationand the export specialization patterns of different coun-tries. Empirical research found an indirect confirmation ofthe relationship between technological intensity andcomparative advantage, and in other cases, that theoutcomes of R&D activity may drive foreign trade flows.These studies focused mainly on the US economy (Keesing,1967; Gruber et al., 1967). Similar results were alsoobtained by Hirsch (1975), Wells (1969) and Baldwin(1971). Using a different approach, Dosi et al. (1990)showed that countries tend to be strong exporters in thoseindustries that invest a lot in R&D and/or register a highnumber of patents; while the direction of causality isdebatable, these examples confirm the idea that innovationis one of the most important determiners of performance ininternational trade. In addition, Dosi et al. (1990) noted thepersistence of rather different technological competenciesamong advanced countries, both in terms of innovativeactivity and export models. Therefore, the evolutionaryview and the ‘‘new’’ theory of international trade, based oneconomies of scale and product differentiation, claim thattechnology plays a fundamental role in explaining foreigntrade flows, in contrast to the ‘‘orthodox’’ theory ofinternational trade (Ohlin, 1933; Heckscher, 1949; Jones,1965). In fact, the new trade theory indicates economies ofscale both at the company (Krugman, 1980) and industry(Krugman, 1987) level as the decisive factor in describingthe characteristics of international trade.These theories highlight the possibility of national

knowledge spillovers and the importance of a country’ssize in terms of favoring and increasing such effects.Knowledge spillovers may also emerge at an internationallevel. When this happens, the larger the economicintegration of countries, the greater the knowledge spil-lovers will be (Laursen and Meliciani, 2002, analyze the


relative importance of international and national technolo-gical linkages for international competitiveness, whileLaursen and Meliciani, 2000, study the upstream anddownstream intersectoral linkages at a national level).

The relationship between foreign trade and technologicalinnovation was explored in detail by Grossman andHelpman (1991), who used an original approach withinthe neoclassical literature on economic growth. Theseauthors show that a greater integration of markets mayhave ambiguous effects on the incentive to innovate and onthe welfare of the countries involved. In fact, integrationenlarges the size of the market available for each producer,in each country. Thus, the effect of trade increases, per se,the profit opportunities of each innovator. On the otherhand, commercial integration increases the degree ofinternational competition. In a world of free trade, eachproducer must compete with higher varieties of productsderiving from R&D. This greater competition maydecrease the profit opportunities for each firm and thusreduce the incentive to innovate. In particular, when bothlarge and small countries compete internationally, marketintegration may increase the innovation in large countriesand decrease it in smaller ones. In fact, the relatively largeramount of capital stock in large countries means that newproducts can be introduced more quickly, so largecountries may capture a rising share of internationalproduct varieties and global demand. In small countriesthe process is the opposite. If the share of global demandfalls, firms expect capital losses and this leads to lowerinvestments in R&D. Hence, international trade reducesthe profitability of R&D because local producers face anexpanding set of differentiated and imported products.

The negative effects of international trade on techno-logical innovation are higher when the technological gapbetween large and small countries is large. Finally, thiseffect is greater when the nature of knowledge spillovers is,for the most part, national. These results were obtained, asis usual in the theory of international trade, by consideringthe two poles of total isolation and total integrationof a country in relation to trade and/or technology.Nevertheless, they confirm that history and initial condi-tions may significantly affect the relationship betweeninnovation and trade. For instance, when knowledgespillovers emerge at a national level, initial conditions willplay a fundamental role in explaining the patterns of tradeand the rate of growth of innovation. On the other hand, ifinternational knowledge spillovers dominate, factor en-dowments and the initial structure of exports will have lessimportance.11

The combination of these theories provides a morecomplete interpretation of the observations reported in this

11In relation to national knowledge spillovers, some authors (for

example, Lundvall, 1992) stress the importance of national interactions

between users and producers in the diffusion of new technologies. If the

linkages between these agents are frequent and sophisticated, there will be

advantages for both categories.

paper. Large (and rich) countries present more patentsbecause a greater capital stock enables them to engage inR&D in more fields, but also because their firms investmore in each technological field, in order to build andmaintain competitive advantages in terms of innovativeproducts. Higher variety and quality of products enablelarge countries to establish and increase the competitiveadvantage at an international level, when we assume thatinternational trade is free, though not completely.From a quantitative point of view, it may be useful to

consider the results of Hummels and Klenow (2005), whoanalyzed exports carried out in 1995 from 126 exportingcountries to 59 importers, and broke down the largeramount of trade of larger economies in terms of intensiveand extensive margins. In addition, they compared theprices and quantities of exports of different countries togiven market categories, and estimated quality differencesacross exporters. One of the main findings was that the‘‘extensive margin’’, which measures export variety, ac-counts for 60% of the biggest exports of larger economies,which trade in several categories, and with severalpartners.12 Therefore, variety is important when weconsider patents, but it seems to play a more prominentrole when considering exports. Unfortunately, we can onlyconsider a few patent classes (32) compared to the multiplecategories of exports (for example, Hummels and Klenow,2005, considered about 5000 six-digit product categories).Therefore, firms from larger countries tend to file theirpatents in many fields, and the same would occur withexports if these were aggregated into broader categories.For example, the USA, Belgium, Japan, Netherlands,France, Germany, Italy and Switzerland, presented patentapplications in all 32 technical fields. Most large countries,in terms of GDP, also belong to the group of richcountries, so a similar argument may apply to this subsetof nations. The result is that the intensive margin is moreimportant in explaining the differences in overall patentapplications. On the other hand, poorer countries exhibitan extensive margin which is similar to that reported byHummels and Klenow (2005). If it were possible to havemore disaggregated technical fields, the extensive marginwould probably also play a more important role in thepooled sample. Hummels and Klenow (2005) admit thatthe level of aggregation at which the extensive margin ismeasured clearly affects how it varies according to countrysize. For example, if the extensive margin is measured atthree-digit level, it accounts for 39% of higher exports bylarger countries.In conclusion, current research cannot establish whether

carrying out R&D in given sectors produces systematicallycomparative advantages that in turn lead to certainpatterns of export specialization. Neither can it ascertainwhether export specialization (caused by particular re-source endowments or by historical and cultural factors)

12Similar findings can be found in Feenstra (1994), Funke and

Ruhwedel (2001) and Schott (2004).

ARTICLE IN PRESS

13Actually, almost all studies described in Section 1 considered indexes

of correlation between economic size and technological variety. Notwith-

standing, the general interpretation of the observed phenomena was

substantially based on an order of causality which goes from economic

size to technological variety. See Cantwell and Vertova (2004).


determines the structure of a country’s innovative efforts.As to the order of causality, theoretical and empiricalstudies do not provide conclusive results. However, itseems quite clear that technological variety and tradevariety increase, in a similar way, with the size andwealth of nations. Both in technology and trade, the sizeof economies affects the mechanisms that shape the degreeof variety, i.e., the capacity to be active in severaland distinct economic fields. Since economics scholarsrelaxed the assumption of perfectly competitive marketsand homogeneous products, economies of scale andproduct differentiation drastically change our way ofthinking about the relationship between macroeconomicvariables, foreign trade flows, and innovation. Of course,the economic dimension of a country is not the onlyelement to consider when explaining the differences intechnological and trade variety, as claimed by scholarsbelonging to the evolutionary area. Cultural features arealso important, as well as the adoption of specifictechnological policies. Despite this, although industrialand technological policy may induce firms to devote theirtechnological efforts to a particular sector and createcompetitive advantages at a global level, the influenceof economic size on technological variety remains signi-ficant and capable of overwhelming other importantfactors.

5. Conclusions

This paper has quantified the role of technologicalvariety in the higher patenting activity of larger economies.The methodology adopted to obtain this result differs fromthat used in other studies that analyze the degree oftechnological diversification in countries and/or firms.Broadly speaking, the positive relationship between eco-nomic size and technological variety is confirmed for morecountries than those considered in previous analyses. If weconsider the pooled sample, the cross-section analysisshows that technological variety accounts for about 40%of additional patent applications of larger and richereconomies. Therefore, technological variety has a crucialrole in explaining the different overall technologicaldimensions. In the subset of poorest countries, technolo-gical variety is important in explaining the additionalpatent applications of larger economies. On the otherhand, the GDP per capita has not much explanatory powerin poorest countries.

These findings regarding technological variety reassertthose of Hummels and Klenow (2005) about foreign trade.Although it is demonstrated that opening the internationaltrade strengthens the patterns of export specialization,larger economies spread their economic activities in a widerrange of fields. This also occurs in the internationaltechnological activity measured via international patenting.In addition, the magnitude of technological variety issimilar to the degree of product variety observed in foreigntrade flows. These empirical results present several limitations,

some of which have been illustrated throughout the paper.Two other points merit to be mentioned.First, the analysis is static in nature, because it consists

of simple cross-sections regarding the patent activity of thecountries in the sample. From the point of view of the‘‘quantitative’’ stability of the results, multiple observa-tions in different years (and regarding both patentapplications and registrations) confirm that the techno-logical variety does not vary too much across the sample.However, a more important objection is that the techno-logical variety of a country may (qualitatively) vary if oneanalyses, each year, ‘‘which’’ technological fields areconcerned by patenting activity. In other words, myanalysis does not consider the possibility that a country’sinnovative efforts might radically change their destinationin the very short run. This aspect is particularly importantespecially in small and less advanced countries, which areforced to explore the spectrum of technological opportu-nities to emerge in the global market.Another reason for being careful about the main find-

ings is that it is tacitly assumed that the intensity andvariety of technological activity are dependent variables.This approach has been used in previous works on thistheme, although there is no established model whichdescribes the cause-effect mechanism between economicvariables and the degree of variety of technologicalactivity.13 To avoid this problem, also this paper uses theconcept of the size/variety correlation. Broadly speaking, itwould be useful to elaborate a formal model that drives theempirical analysis. So far, the empirical studies (includingthis one) regarding the relationship between economicsize and technological variety have been conducted withoutany rigorous theoretical framework. The qualitativeapproach described in the second section, though sup-ported by some theoretical and empirical findings, providesgeneral and useful insights to understand the phenomenaobserved, but a formal model could probably betterexplain the non-linearity of some relationships, and mightconstitute a solid theoretical background for futureempirical works.

Acknowledgements

I wish to thank two anonymous referees for their helpfulcomments.

Appendix

The list of technical units used by the EPO and thecountries that have applied for patents in 2002 are listed inTables A1 and A2, respectively.

ARTICLE IN PRESS

Table A1

Technical units (EPO database)

1 Inorganic chemicals

2 Organic chemicals

3 Agricultural chemicals

4 Chemical processes

5 Hydrocarbons, mineral oils, fuel, igniting devices

6 Bleaching, dyeing and disinfecting

7 Drugs and bio-affecting

8 Plastics and rubber products

9 Non-metallic minerals, glass and other materials

10 Food and tobacco (processes and products)

11 Metallurgical and other mineral processes

12 Apparatus for chemical, food and glass, etc.

13 General industrial equipment

14 General industrial apparatus

15 Non-electrical specialized and misc. industrial equipment

16 Metallurgical and metal working equipment

17 Assembling and material handling apparatus

18 Nuclear reactors and systems

19 Power plants

20 Road vehicles and engines

21 Other transport equipment (excluded aircraft)

22 Aircraft

23 Mining and wells machinery and processes

24 Telecommunications

25 Semiconductors

26 Electrical devices and systems

27 Calculators, computers, other office equipment

28 Image and sound equipment

29 Photography and photocopy

30 Instruments and controls

31 Miscellaneous metal product

32 Textile, clothing, leather, wood products

Table A2

List of patenting countries in 2002

Country Total patent

applications

Technical

units

Mean

United States of America 30118 32 941.2

Germany 21039 32 657.5

Japan 15912 32 497.3

France 6853 32 214.2

Netherlands 5054 32 157.9

United Kingdom 4709 31 151.9

Switzerland 3882 32 121.3

Italy 3336 32 104.3

Sweden 2565 31 82.7

Finland 1608 29 55.4

Canada 1449 31 46.7

Republic of Korea 1408 29 48.6

Belgium 1328 32 41.5

Austria 929 30 31.0

Australia 889 29 30.7

Denmark 778 28 27.8

Israel 665 26 25.6

Spain 603 29 20.8

Taiwan 426 27 15.8

Norway 365 28 13.0

Ireland 238 22 10.8

China 203 25 8.1

Liechtenstein 157 23 6.8

Luxembourg 148 23 6.4

New Zealand 144 23 6.3

Table A2 (continued )


applications

Technical

units

Mean

India 130 22 5.9

Singapore 112 18 6.2

Barbados 101 10 10.1

Netherlands Antilles 101 19 5.3

South Africa 96 24 4.0

Russian Federation 88 24 3.7

Brazil 85 20 4.3

British Virgin Islands 75 21 3.6

Hungary 64 17 3.8

Greece 43 16 2.7

Czech Republic 39 19 2.1

Slovenia 31 16 1.9

Turkey 30 11 2.7

Iceland 27 9 3.0

Poland 27 13 2.1

Hong Kong 25 9 2.8

Portugal 23 15 1.5

Bahamas 20 12 1.7

Argentina 17 9 1.9

Mexico 17 10 1.7

Cyprus 16 8 2.0

Cayman Islands 16 8 2.0

Monaco 15 7 2.1

Malaysia 14 6 2.3

Malta 13 8 1.6

Saudi Arabia 13 5 2.6

Croatia 11 7 1.6

Slovakia 10 8 1.3

Panama 9 6 1.5

Indonesia 9 5 1.8

Ukraine 8 6 1.3

Bermuda 8 4 2.0

Chile 7 5 1.4

Thailand 7 6 1.2

Romania 7 5 1.4

San Marino 7 5 1.4

Bulgaria 6 6 1.0

Venezuela 6 3 2.0

Gibraltar 6 5 1.2

Lebanon 5 4 1.3

Yugoslavia 5 4 1.3

United Arab Emirates 5 5 1.0

Iran 4 4 1.0

Colombia 3 1 3.0

Belize 3 2 1.5

Egypt 3 3 1.0

Cuba 3 2 1.5

Macao 2 2 1.0

Bahrain 2 2 1.0

Uruguay 2 2 1.0

Costa Rica 2 2 1.0

Tunisia 2 2 1.0

Bosnia and Herzegovina 2 2 1.0

Andorra 2 2 1.0

Mauritius 1 1 1.0

Lithuania 1 1 1.0

Latvia 1 1 1.0

Macedonia 1 1 1.0

Belarus 1 1 1.0

Algeria 1 1 1.0

Peru 1 1 1.0

El Salvador 1 1 1.0

Morocco 1 1 1.0

A. Mangani / Technovation 27 (2007) 650–660 659

ARTICLE IN PRESS

Table A2 (continued )


applications

Technical

units

Mean

Syria 1 1 1.0

Azerbaijan 1 1 1.0

Georgia 1 1 1.0

Moldava 1 1 1.0

Seychelles 1 1 1.0

Anguilla 1 1 1.0

Aruba 1 1 1.0

Cook Islands 1 1 1.0

Turks and Caicos Islands 1 1 1.0

Source: EPO official statistics.


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Andrea Mangani is an associate professor of applied economics at

the Department of Economics, University of Pisa. He is a visiting

professor at the University of Siena and the IULM University of

Milan. He has studied in Pisa, Oxford, and Siena, where he

received his Ph.D. in Economics. His research interests are in

industrial organization, brand and pricing management, and

experimental economics. He has acted in a consultative role for

the Italian Antitrust Authority and the Ministry of Industry.

technological variety and the size of economies

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