Structural shift and increasing variety of Korea, 1960-2010
: Empirical verification of the economic development model by the creation of new sectors
Jung-In Yeon1, Andreas Pyka2, and Tai-Yoo Kim1
1Technology Management, Economics and Policy Program (TEMEP), Seoul National University, Seoul 151-742, South Korea
2Economic Institute, University of Hohenheim, Wollgrasweg 23, D-70599 Stuttgart, Germany
Abstract
In this paper, we examine the experiences of Korean economy to verify the theoretical knowledge of economic development and structural change. To demonstrate the generalized hypotheses in structural changes, input-output tables of Korea, from 1960 to 2010, are analyzed. Our interest in taking a time series form of Input-output tables originates from the following two questions. Firstly, we inquire whether the change of Korean industrial structure has been followed a certain pattern of structural shift as well as increasing variety. Secondly, if so, it is questioned how the meso-level conditions for the economic development could be explained out of such a pattern. To complete the set of answers, we start from adopting a model of the economic development by the creation of new sectors, TEVECON model, as our theoretical framework. Using this growth model, it is preliminarily experimented how the structural change could impact on the economic development, and then, we figured out how the empirical analysis of Korean economy verifies and more deepens our understandings of the structural change and development. Therefore, this paper contributes to empirically identify the theoretical knowledge of economic development by the emerging of key sectors as well as the creation of new sectors.
Keywords Structural change, Increasing variety, Unrelated variety, Input-output table, Korean economy, TEVECON model, Economic development, Economic growth
1. Introduction
Invariantly, the utmost importance of economics is to elucidate the natures and causes of economic growth and development. The theory associated with such issues, thereby, has been constantly modified and evolved into more explanatory forms, following the critical moments in economic history. For instance, the moment when the existing production structure was dramatically switched due to the industrialization or when the world-wide economy was in deep recession due to Great Depression should be clarified by theoretical frameworks. And, now we are in a new era of so-called knowledge- based society, meaning the emergence of new products and new industries becomes natural and ordinary as a result of innovation. Therefore, this moment plays a role of the momentum again to make an advancement in the field of growth theories. In this paper, accordingly, we interpret such an emergence phenomenon of new industries as the compositional change of economic systems, and then revisit the studies on structural changes and economic development. In order to verify and complement the theoretical discussion so far, this study more focuses on the relationship between 'increasing variety' at the industrial-level and economic development on the empirical analysis.
In fact, since the Classical economics is the beginning to discuss the wealth of nations together with structural changes, the long history of this study is nothing compared to any other research topics. However, in the wake of the marginal revolution, the focus of the economic theory changed from the national level of production and distribution to the micro level of market balance and pricing mechanism, thereby some tricky factors related to the structural issue tended to be assumed away(Harris 1982). As the world economy experienced various events into the twentieth century, scholars deliberated again on economic growth and structural development in the theoretical perspective. Meanwhile, in this line of modern economics, three different perspectives on economic growth have been developed into three branches of the growth and development theory: the first branch is the new growth theory(Lucas 1988; Romer 1990; Grossman and Helpman 1991; Aghion and Howitt 1992), and the second branch is the innovation-driven growth theory on the evolutionary perspective(Dosi and Nelson 1994; Saviotti and Pyka 2004; Metcalfe, Foster, and Ramlogan 2006), and the third branch is the field of development economics and others(Lewis 1954; Rostow 1959; Chenery 1960).
In this study, we cover the first and second strands of growth theories in accordance with how they incorporate structural changes into their frameworks. Among other theories, a model of economic development by the creation of new sectors, TEVECON model(Saviotti and Pyka 2004, 2008), is specified in details as the theoretical background of this study. From the literature review, three hypotheses on structural changes and economic growth are formulated, and we test the hypotheses by empirical analysis on the Korean economy, 1960-2010. We use input-output tables of Korea for the analysis, published from the Bank of Korea on the quinquennial-base. As pointed out by (S. Kuznets 1973) and Chenery (1960), Gross-Output(GO), extracted from input-output tables, is the more suitable data for observing overall structural changes because it captures intermediates as well as final goods transactions. Thus, this study shows a distinct merit of the comprehensive analysis on structural changes, in comparison to a myriad of previous literatures using GDP data only. So as to systematically analyze structural changes on the view of economic development, this study starts from redefining that the structural change is the combination of structural shift phenomena and increasing variety phenomena, and we decompose the overall structural change into the three component structural changes. By doing this, we can probe into the relationship between changes in the total industrial structure and economic growth.
This paper is organized as follows. In section 2, we review previous literatures on two aspects respectively, structural shift and the increasing variety as following the definition of the structural change here. In addition to this, we narratively describe the key mechanism of TEVECON model in order to specify the theoretical background of this research design. In section 3, details of the research design including the subject of analysis, the data treatment, and the method are presented, and we discuss the result in section 4. Finally, in section 5, we conclude with the contribution of this study and implication.
2. Literature Review
The interest of economists in structural change and economic progress of nations has a long tradition, from the beginning of classical economic growth theory(Harris 1982). Meantime, the scope of ‘structure’ and definition of 'structural change’ has been treated a bit differently depending on the historical and academic background. Before going into any further, in this study, we redefine that the structural change is the phenomenon combining structural shift between sectors and increasing variety of the economic structure, and confine the scope of ‘structure’ to the industrial structure constituting total economic production of the country. By comparison with the general definition of the structural change, e.g. ‘the long-term persistent changes in the composition of an aggregate (Syrquin 2010)’, the new definition in this study is suggested with intent to emphasize the two different aspects out of vagueness in the term ‘changes in the composition’.
In details, although the two aspects, structural shift and increasing variety, reveals their features both through the process of compositional changes, the messages from the two aspects are significantly different. For the first aspect, the structural change in the terms of structural shift, we focus on the average impact on the aggregate productivity of nations. Therefore, the discussion of the structural shift tends to be which sector or cluster holds the largest majority in the ‘constant set’ of the industrial structure. In this context, so-called ‘structural bonus hypothesis’, meaning the average productivity increase via structural changes leads to the economic growth, has been verified empirically(Fagerberg 2000; Timmer and Szirmai 2000; Peneder 2003). They mostly apply the shift-share analysis using value-added data and labor productivities for each sector. On the second aspect, the structural change in the terms of increasing variety, we concentrate on the emergence of a new sector and thereby the increase of the number of total industries. In this regard, the creation of new products, new demands, and new industries has been incorporated as a determinant role for the economic growth into the analytic framework(Kim and Heshmati 2014) and into the explicit growth models(Saviotti and Pyka 2004; Montobbio 2002). In particular, Saviotti and Pyka (2004) and Montobbio (2002) tried to capture the importance of the economic variety at the industrial-level as a formal theory of economic growth. In other words, this is to highlight the procedural aspect of the structural change by filling a gap by the consideration of ‘meso-level’1 stages into the mico-macro model of economic growth.
In short, the two aspects reflect two different points: One is on the specific role of certain industries for economic growth, and the other is on the overall picture composed by emerging and declining industries. Therefore, we firstly review on literatures more related to the structural shift phenomenon in section 2.1, and then review on studies about the increasing phenomenon in section 2.2. After that, in section 2.3, TEVECON model is reviewed more in depth as the theoretical framework for the structural change and economic development.
2.1. Structural change and economic growth and development
Up to recently, the economic system of nations, as the industrial structure, has been steadily received attention from policy makers because of the high correlation with the aggregate productivity growth. Here, the aggregate productivity means the average value of all industrial productivities when each industry (or sector) has a different productivity. As such, the argument that changes toward a certain combination of the industrial structure can guarantee the long-term economic growth via the higher aggregate productivity is easily derived. In fact, such an obvious argument became plausible since we actually witnessed that there existed a specific sector with a commanding lead on productivities. In the light of the revolutionary change by industrialization, therefore, the early studies(Fisher 1939; Fabricant 1940; Clark 1960) noted that the transformation toward the manufacturing economy enables to accelerate the economic growth. That is to say, researches on structural changes mainly focused on the structural shift phenomenon at the moment.
In details, Fisher (1939), which can be called the most classic of them, stressed that it is necessary to classify the economic production as primary, secondary, and tertiary sector. According to him, the classification would ‘give a lead in answering about what direction is desirable at this stage of our history to accelerate the rate of economic development(Fisher 1939, p.30)’. Afterwards, scholars have studied on the process how the majority of the economic production is succeeded along the sectoral development path(Baumol 1967; S. Kuznets 1973) 2 and researched on the importance of
1 According to Dopfer, Foster, and Potts (2004) and Dopfer (2011), he insists the importance of the meso-level consideration on the economic process, so he developed the analytic framework of micro- meso-macro architecture. In addition to this, according to the interpretation of Hanusch and Pyka (2007), the meso-level appreciation, between the micro and the macro levels of economic analysis, is necessary to understand the decisive structural and qualitative changes.
2 In particular, Kuznets (1973) pointed out the third characteristic of modern economic growth is related to the structural change, shifting away from agriculture to non-agricultural pursuits, and then manufacturing sectors as an engine of growth(Cornwall 1977; Szirmai 2012). Furthermore, recent studies on structural changes and economic growth(Fagerberg 2000; Peneder 2003; Timmer and Vries 2008) have extended the focus to the correlation between aggregate productivities and technological advancement rates of industries. Thus, based on the subdivided classification of industries in accordance with different innovation rates3, the comparative studies at the country-level have been conducted to comprehend the divergent pattern of economic growth.
In summary, many of researches on structural changes have tried to elucidate the high relevance of economic growth and structural shift by means of an average productivity, and the studies have mainly been carried out as a form of appreciative theorizing (the terminology of Nelson and Winter 1985, p.46) based on empirical inferences and intuitive understandings. Ironically, however, scholars in the field of formal theories on economic growth have given slight consideration in the structural change so far. Although several endogenous growth models (Romer 1990; Grossman and Helpman 1991; Aghion and Howitt 1992; Ngai and Pissarides 2007) have made an attempt to integrate the structural features of multi-sectoral economies, they mostly failed to capture the key aspects of structural changes due to the following limitations.
First of all, Romer(1990) presented the product-variety model, taking a multu-sectoral production of intermediates into account. From the point of view on structural changes, the model has a contribution to extend the growth theory with the one-sector economy to the structured economy, but it has a logical distance from structural changes in the real industrial-level that the diversified sectors of intermediate goods sector end up producing only one kind of final goods. Meanwhile, the quality-ladder model of Grossman and Helpman (1991) complements the variety and quality problem by incorporating the obsolescence relation across sectors of intermediate production, In other words, they addressed the model explains ‘quality-upgrading’ economic growth by introducing vertical differentiated products. However, this type of quality-upgrading growth confines the qualitative change to the ‘intra’-sectoral differentiation, so the model describes nothing but a proportional growth of the single industrial economy. In conclusion, so far, the serious consideration of the meso-level changes does not exist in their growth models.
Aghion and Howitt (1992) also presented an advanced endogenous growth model by adopting the concept of creative destruction, and thereby called the Schumpeterian model. In their model, despite modeling the creation of new sectors, the symmetric assumption among sectors results in a constant composition of each sector, so it precludes further discussion on the structural shift of majority shares. In addition, since the creation number of new sector is set identical to the extinction number of old sectors, the model has no correlation with the increasing variety at the meso-level either. On the other
from industry to services. His perspective explicitly shows the structural shift aspect.
3 Generally, this approach is originated from Salter (1966), and he stated that ‘the interindustry patterns of growth’, which could be interpreted to the structural change, was explained by ‘uneven rates of productivity growth’ across industries with the empirical proof. hand, multi-sectoral growth models at the level of final consumption goods have been introduced(Ngai and Pissarides 2007; Foellmi and Zweimüller 2008), and they directly pursue the analysis of structural changes by their models. For the model of Ngai and Pissarides (2007), as an example, the multi- sectoral structure is suggested to deepen the hypothetical knowledge of Baumol(1967), which is related to the employment share growth in the stagnant sector as a consequence of further economic growth. In this case, the main contribution of the multi-sectoral growth models is to replicate the appreciative theories about structural shift into the formalized framework, so the models hardly convey the new insight on structural change issues.
To sum up, the traditional studies on structure changes and economic growth reported the phenomena on the structural shift aspect, and the endogenous growth models of multi-sectoral system provided the theoretical basis of economic growth and such phenomena by means of technology and innovation. That is to say, we cast a question about the productivity-enhancing effect by the structural shift and the correlation of sectoral feature (e.g. high-technology base) and economic growth. Hence, based on the previous discoveries, the first hypothesis of this study can be synthesized as below.
Hypothesis 1. Structural shift, leading to the growth of emerging industries, contributes to the long- term economic growth when emerging industries show higher productivities.
2.2. Increasing variety and economic development and development
It is too obvious that ‘a very large number of new sectors have been created since the industrial revolution, and examples of these sectors are those producing cars, aircraft, computers, radios, television, refrigerators, plastics, etc.’ (Saviotti and Pyka 2013). In other words, we have observed the structural change by changing the constitution of the structures with manifold sectors, as well as shifting away from sector to sector. Therefore, we discuss the variety issue of the industrial constitution in this section, which has not been highlighted in the traditional studies of structure changes despite such an obvious observation. To search for the theoretical approach in the increasing variety, we need to start from the evolutionary growth theories. This is because the evolutionary perspective appreciates the different rate of innovation in each technological regime so that the sector, relevant to each technological regime, definitely shows a different rate of growth along the life cycle(Dosi and Nelson 2010). Accordingly, the economic development of the industrial structure, composed of such sectors, could be analyzed compatible with the structural change on the increasing variety aspect. Thus, we review several growth models especially focusing on the variety issue for the economic development(Montobbio 2002; Saviotti and Pyka 2004; Kim and Heshmati 2014). In addition to this, we briefly review the studies on ‘related and unrelated varieties’ as another strand of the variety studies(Frenken, Oort, and Verburg 2007; Castaldi, Frenken, and Los 2015), and discuss how we make use of their methodology to this study.
To begin with, Pasinetti (1983) is one of the classical work that is often referred in the Schumpeterian economic development studies. According to Syrquin (2010), Pasinetti has been arguing that economic progress should be understood as ‘a view of growth as a process of continuous change, not steady balanced growth, and not a traverse between such states, but a never ceasing transformational process(p.252)’. His structural dynamic analysis was systematically designed into the supply-side role and the demand-side role for the economic development. Firstly, the process innovation of industries results in increasing incomes of consumers via rising up labor productivities, and then this income effect influences on the structure of demand. As borrowing the expression of Krüger (2008), this process shapes the ‘direction‘ of structural change. More importantly, when technical progress in the supply-side takes another form as the product innovation, the final consequence of introducing new goods is modeling into the introduction of new ‘sectors’(Pasinetti 1983, p.89). From this point of view, his theory provide the ample grounds for the studies of increasing variety and economic growth, in terms of the emergence of new industries. Therefore, although there are methodological limitations and difficulties in the application to empirical studies (Krüger 2008), the structural dynamic analysis of Pasinetti has a profound effect on Schumpeterian economic studies. And, this is because his theory was taken the key-functions of innovation into account, efficiency-growth via process innovation and sector-creation via product innovation.
In the meantime, the mechanism of creating new sectors, which was pointed out by Pasinetti as above, took a concrete form as a growth model by Saviotti and Pyka (2004), known as TEVECON model. Consequently, the structural change caused by the emergence of new industries has attracted academic interests again, and the overall phenomena of such qualitative changes have been discussed on the view of the increasing variety. Saviotti and Pyka (2004) presented that TEVECON model embodied the causal loop from the innovation activity of firms to the creation of new sectors, and thereby economic development could be modeled in the form of cumulative result of the causal loop. In this process, it is assumed that old sectors remain in the economic system instead of extinction or substitution4. Therefore, while the number of total industries increases, the relative weight of old sectors decreases. This exactly shows the increasing variety phenomena of structural changes, and TEVECON model captures the concept of variety as a necessary requirement for the long-term growth.
On top of that, Montobbio(2002) presented a theoretical model applying the relationship between the structural change and aggregate productivity growth on the evolutionary perspective. He suggested the standard replicator model for multi-sectoral economy, and the model is the extended version of (Metcalfe 1994) for the single industrial dynamics into the macro-level. The standard replicator model is characterized by understanding the diversity of the multi-sectoral economy on the view of the industrial dynamics. Accordingly, he also indicated that the emergence of ‘sectoral variety’(Montobbio 2002, p.407) plays an important role in structural change and economic growth, In the model, sectoral variety is related to several variables, which are the degree of substitutability across sectors, the sector-
4 According to Saviotti and Frenken (2008), the Schumpeterian concept of creative destruction can be reconsidered in that there is more creation than destruction at the industrial-level under historical observations, and the assumption here is in the same line of this perspective. specific unit cost average, and the income elasticity of demand. Unfortunately, the model did not cover actual simulation results to show the impact of sectoral variety on aggregate growth5, but his study is of great theoretical significance to consider the emergence of sectoral variety in the inter-sectoral context.
Besides the formal theorizing as above, the increasing variety aspect of structural change has been mentioned in the verbal appreciative theorizing for the economic growth(Kim and Heshmati 2014). Kim and Heshmati (2014) suggested an analytic framework to distinguish the difference of structural features in agricultural, commercial, and industrial economy and to elucidate the source of accelerating economic growth, especially in industrial societies. According to their framework, the Expansive Reproduction Structure of industrial society, the economic growth is described by the increase in existing demand and the creation of new demand, and ‘the new demand created by new products’ is the engine of accelerating growth in industrial economy. In particular, they pointed out the advancement of industrial structure by continuously creating new demand so as to sustain the accelerating growth(Kim and Heshmati 2014, p.78). In this context, the qualitative advancement of industrial structure embraced the increase in inter-sectoral variety as well as intra-sectoral variety even though the concept of variety has not been specified. Therefore, the essence of Kim and Heshmati (2014) is also summarized in terms of increasing variety through the structural change.
In conclusion, many studies show the significance of increasing variety issues in terms of long- term economic development, so the structural change on the increasing variety aspect should be equivalently treated with the structural shift aspect. In respect of empirical verification, then, we should think about how to measure the increasing variety aspect, in comparison to aggregate productivity measuring, the well-known empirical approach to the structural shift. Of course, counting the number of total industries in the entire system could be a prime candidate. However, when the overall phenomena of increasing variety appear in the form of compositional change as well, it is reasonable to quantify the degree of increasing variety as an aggregated index of sectoral relative weights. In this way, Pyka and Saviotti (2011) once presented the variety level by taking an informational entropy function in TEVECON model, Frenken et al.(2007) empirically applied the entropy index to measure varieties in the economic system. Hence, empirical studies of the entropy index should be shortly discussed as supplementary knowledge.
From the point of contents, Frenken et al.(2007) is one of recent studies discussing whether the industrial structure should be diversified or specialized in order to promote the regional economic growth(Imbs and Wacziarg 2003; Klinger and Lederman 2004; Rodrik 2007). The main concern of the studies is the inter-industrial spillover effect to promote further innovation, so-called Jacobs externalities stemming from technological proximity across sectors. In order to clarify the growth-promotion effect of increasing variety, Frenken et al.(2007) suggested two different level of variety index, unrelated and
5 In fact, the model rather showed that the variety is ‘eroded’ due to the initial number of firms and sectors is given (Montobbio 2002, p. 405), and it seems more apt to describe the transitional properties of structural changes. related variety, in accordance with the sectoral proximity. Accordingly, the entropy of unrelated variety (UV) and related variety (RV) was measured by using industrial-level data with different aggregation level of classification, and he concluded that related variety of industrial structure effectively leads to Jacobs externality. For sure, this is an extension of the studies on how the differences in variety and economic growth are correlated, but rather it seems beyond the scope of what we verify in this study6. Therefore, instead of going deep into the topic of variety and externalities, we take advantage of the empirical methodology to measure the economic variety in their works. The entropy of industrial structure, in this study, will be a useful index to represent the degree of variety.
2.3. A model of economic development by the creation of new sectors, TEVECON model
By reviewing previous literatures, we confirm that structural changes can be described by structural shift between sectors and increasing variety of the economic structure in terms of long-term economic growth. Also, we figure out that each theory (or model) has its strengths and limitations at the same time. Back to the main point, the aim of this study is to verify and complement our knowledge of structural changes and economic development. It means, therefore, it is important to adopt and focus on which theoretical approach to the empirical analysis, and to understand attentively the main features of the theory. In this study, we base the setup of two more hypotheses upon TEVECON model7, and also we apply the perspective of ‘economic development by the creation of new sectors’ to designing empirical validation on the hypotheses. As Malerba addressed, TEVECON model as a formal theory will be a helpful tool ‘for leading to the insight about the key variables(Malerba et al. 1999, p.5)’, and this study also has a contribution to empirically confirm the formal theory. Hence, in this section, we elaborate the theoretical approach of TEVECON model8.
As mentioned earlier, TEVECON model, a model of economic development by the creation of new sectors was introduced by Saviotti and Pyka (2004). The model, by the name suggests, presents why new sectors emerge, how such an emergence generates structural change, and if so, how structural
6 The relation between economic variety and spillover effect has been still actively discussed and debated, so the consensus on the effect has not been reached(Boschma and Iammarino 2007; Castaldi, Frenken, and Los 2015; Aarstad, Kvitastein, and Jakobsen 2016). According to Pyka et al.(2009), furthermore, since the variety of industrial structure is a kind of involuntary environment to interact, the spillover effect could be less significant to promote further innovation rather than the voluntary interaction.
7 Kim and Heshmati (2014) also shows a great compatibility to the increasing variety issue, but the framework, the Expansive Reproduction Structure, is not specific enough to apply to the empirical work.
8 In this study, TEVECON model is narratively described without equations so that we focus on the theoretical meaning out of the mechanism of TEVECON model. The detailed model description is referred in Saviotti and Pyka (2004) and Pyka and Saviotti (2011). change contributes to economic development. First of all, ‘search activity’ of firms could be the basis to understand TEVECON model. Search activity, which is generally called R&D activity as innovation efforts, is endogenized as a part of driving forces for economic growth, and the economy is set to grow by local equilibrium without considering the optimization process. In this process, local equilibrium means the market adjustment between actualized demand and production capacity, and here actualized demand and production capacity are affected by search activity of firms. From this point of view, the model is called ‘Innovation-driven’ economic growth model, embodying the Schumpeterian perspective on qualitative changes and economic development.
In details, on the mechanism of creating new sectors9, we can begin with the situation after a certain radical innovation (or pervasive innovation) occurs. Owing to the generation of radical innovation, the new potential market is created, and firms start to actualize the demand in the market by producing new products as establishing a sector. In this process, ‘adjustment gap’, the difference between the maximum potential demand and the actual demand in the market, is established. As firms eager to take advantage of this new market by search activity to internally differentiate products, the actual demand becomes saturating along a logistic curve. This means that adjustment gap is getting toward zero, and it is transported to firms as the decreasing signal on the rate of profit. Consequently, firms try to open up new opportunities by setting up a niche. In the meantime, as innovation efforts of firms meet together with the increasing effect of the fundamental research activity of the economic system, a new radical innovation is about to be appeared in the system. Subsequently, it drives the economic system repeating the process of creating new market and then new sector again. During the process, existing sectors remain in the economic system, and all new and old sectoral demand curves are cumulated so that the economy at the aggregate-level grows quantitatively and qualitatively.
In summary, TEVECON model elaborately demonstrates economic development by the structural change in terms of the creation of new sectors and the accumulation of innovation activities. Figure 1 shows the representative results of TEVECON model (Pyka and Saviotti 2011). In fig. 1(a), each S- curve shows a dynamic of the sectoral output, and fig. 1(b) shows the growth of aggregated income. Fig.1(c) relevantly shows an increasing trend of economic variety at the inter-sectoral level.
9 TEVECON model, a ‘sector’ is defined as the collection of firms that produce differentiated products. Here, the differentiation of products means intra-sectoral differentiation in terms of quality improvement and internal modification, so differentiated products should not be confused with new distinguishable outputs which lead to increasing inter-sectoral variety. Figure. 1 Simulated results* of TEVECON model: (a) Dynamics of sectoral product services, (b) Dynamics of aggregated income, and (c) Dynamics of inter-sectoral variety
As figure 1 shows, the simulation result graphically shows reasonable trends of economic growth and structural changes, and, especially, it enables to discuss substantive issues in relation to increasing variety and economic development. However, although the approach of TEVECON model shows such a great compatibility to the real world, the theoretical understanding of the model has not been empirically tested or calibrated so far. In this study, hence, we formulate two hypotheses based on the perspective of TEVECON model as below10, and verify the hypotheses empirically.
Hypothesis 2. The structural change by the creation of new sectors, called increasing variety, is a necessary requirement for the long-term economic development.
Hypothesis 3. The long-term economic development is a combinational process of structural shift and increasing variety as a complementary relation.
3. Research design
3.1. Case of Korean economy, 1960 to 2010
The Korean economy has long been known for the exemplary case, in terms of rapid economic growth with successful structural changes(Kuznets 1988; D.-S. Cho 1994; Lee 1999; Fagerberg 2000; Singh 2004; Timmer and Vries 2008; MaO and Yao 2012). To rephrase it, the case of Korea must be the suitable candidate for the empirical verification in this study. Not only the history itself, but also the statistical data of the Korean economy, the time-series set of input-output tables from 1960 to 2010, is eligible to analyze the long-term economic growth and development in accordance with the changes in industrial structures. Input-output tables of Korea, moreover, have been released every 5 years on
10 Based on two hypotheses in Saviotti and Pyka (2008), hypothesis 2 and 3 are re-stated in this paper, in accordance with main focus and context of this study.
average since 1960, and the Bank of Korea has tried to capture internal changes of the economic structure as far as possible into statistics through several modifications on the industrial classification(The Bank of Korea 2014). Therefore, we choose the case of the Korean Economy for the empirical verification, and utilize the time-series set of input-output tables in this study. For the time- period of the verification, we analyze from 1960, as the initial point of the fully fledged economic development in Korea(Cho 1997; Lee 1999), to 2010, due to the limitation of data. In this section, we shortly describe the economic development history of Korea as preliminary knowledge, focusing on the perspective of industrial policies and industrial structures.
To begin with, we divide fifty years of the analysis period into three phases as shown in Figure 2, on the basis of the moment when regimes of political and economic policies underwent the breakpoint in Korea. As briefly saying, Phase 1(1960-1981) is the first period of the government-led development plan, and the strong government pushed ahead so-called ‘growth-first’ policies. Phase 2(1982-1997) is the second period of the government-led development plan, but rather the government became aware of needs to balance between government and private sectors. In this period, therefore, the government laid the cornerstone of ‘modern industrial policies’ and tried to simulate the adjustment of the market distortion caused by the previous industrial policies(Shin 2012). In Phase 3(1998-present), the first few years of this phase was the period of full-scale transformation finally into the market-driven economy in the wake of the IMF crisis of Korea. The detailed descriptions of each the Five-year Economic Development Plan and other industrial policies are as follows.
Figure 2. The 3-Phase classification of Korean economic development history
Data; GDP per capita (constant 2005 US$), from World Development Indicators
Until the IMF crisis of Korea, the Korean economy was strongly controlled by the government leadership. Since the Five-year Economic Development Plan, firstly beginning in 1962 and carried out by seven times, primarily targeted at industrialization and modernization of the economy, the ‘industrial’ structure of Korea took shape due to the implementation of industrial policies in the development plan. First of all, the first and second plan (Phase 1-1, 1962-1971) aimed at the independence in terms of economy. The government, at the moment, tried to foster the growth of light industries, under the title of ‘export-drive’ to secure investment resources for the further advanced industrial structure. Also, in order to deploy such resources, the government established policies for social framework conditions, for example, financial system and training system for engineers(Shin 2012). Through the third and fourth plan (Phase 1-2, 1972-1981), the increase in export as well as the quality of economic growth became the main topic for framing industrial policies. In order to sustain a growing trend in export, the government selected the six strategic industries for highly contributing to economic growth, and executed policies to promote so-called ‘infant industries’ by tax incentives and financial subsidies. In this respect, the six strategic industries were mostly categorized in heavy industries so that the 1970s were known for the period of heavy and chemical industrialization(Heo 2012).
During the first stage of Phase2 (1982-1991), the fifth and sixth plan conducted to enhance the export competitiveness, and the Korean economy started to leap in gross production owing to the favorable condition of internal and international economy11. With this as a momentum, the government began to realize that the export competitiveness could be accelerated by a close cooperation with private sectors. Especially, the government reflected opinions of private sectors in carrying out the plans for electronics industry and automotive industry, which were the strategic industries for the moment(Shin 2012). Afterwards, the seventh plan (1992-1997) was specifically enforced to embrace the economic system of private sector-led innovation and demand-oriented technology development. Meanwhile, the effects of the Uruguay Round negotiation in 1993 was diffused also in the industrial policy regime, and Korea confronted a wide range of trade liberalization. Therefore, the government had to switch the basis of industrial policies from directly promoting strategic industries as ‘export-drive’ toward securing core technologies of promising industries.
In 1997, the Korean economy severely experienced financial crisis, so finally the government asked the support from the IMF. Then, the IMF approved to give loans under the requirement of deregulated market including financial market and privatized industries, so the government was forced to revise the explicit government-led development plan. In this way, the Korean economy entered Phase 3 (1998- present) as facing the inevitable flow of liberalization and globalization, hence the government set up the new slogan of economic development as ‘innovation policy’ based on science and technology. One of notable details for this period is that the government under President Kim Dae-jung(1998-2002) pursued the promotion of technology-based SMEs and the aggressive investment for the high-speed Internet infrastructure and market. Because of the effort, the growth of information and communication industries in Korea was facilitated. Recently, government policies related to industries have become broadened and transformed in an indirect-manner, as promoting the promising technologies for future, or the convergence of inter-industries for new market creations. The description of Phase1, 2, and 3
can be summarized as shown in Table 1.
11 Internally, the government sought for the price stability, and externally the Korean economy was benefited from low interests, low oil prices, and the depreciation of the dollar(Shin 2012). Table. 1 Description of the 3-Phase classification of Korean economy
PHASE 1 PHASE 2 PHASE 3 1-0 1-1 1-2
Data 1960 1966, 1970 1975, 1980 1985, 1990, 1995 2000, 2005, 2010
Increase in Export Science and Keyword Initial state Export-drive export competitiveness technology base
Mainly Promoting light Promoting Technologically Promoting agricultural industries1 6 strategic advancing in industries related to industries industries2 competitive 6 promising industries3 technologies4 Features Developing the Supporting industry competitiveness in convergences the automotive industry
1 Simple assembly industries of imported intermediates and simple processing industries; 2 Iron and Steel, Chemical, Non-Ferrous Metals, Machinery, Shipbuilding, and Electronics; 3 e.g. Electronics, Machinery industries; 4 IT(Information Technology), BT(Bio Technology), NT(Nano Technology), ET(Environmental Technology), ST(Space Technology), CT(Cultural Technology)
3.2. Data
As noted above, we use Input-output tables released by the Bank of Kores in this paper. Input- output table of Korea started to be officially published in 1960 on a regular basis, and the primary purpose of the statistical data has been the baseline information for economic policy-making since then. In this respect, through several modifications on the industrial classification the Bank of Korea has tried to ensure that the significant changes of the industrial structure could be reflected on Input-output tables (The Bank of Korea 2014). Therefore, we can access the time-series set of input-output tables from 1960 to 2010, based on actual survey results by every five years. Besides of every benchmark year12, the Bank of Korea often releases the extended tables by applying RAS method to the data of benchmark years. However, since the extended tables maintain the same structure of the industrial classification for the benchmark year, we only consider Input-output tables for benchmark year with actually surveyed statistics in this study of structural changes. We collect 11 sets of Input-output tables for the analysis period, and figure out that every year took the modified standard on the industrial classification except
12 Here, the benchmark years are 1960, 1966, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, and 2010. 2000. Therefore, the time-series set of input-output tables is reconstructed with consistency for the quantitative analysis as follows.
To start with, all 11 sets of Input-output tables are total transaction tables based on producer’s price. In a transaction table as a matrix, each row of transaction matrixes represents the value of each sector's production, and each column represents the value of each sector’s intermediate demands and each institution’s final demands. Also, each set of Input-output tables is composed three types of tables in accordance with three-different aggregation level of industries, which are a transaction table of top- class, a transaction table of mid-class, and a transaction table of sub-class. The top-class level of aggregation is compared to the high-level classification of ISIC Rev.4, which is known with the label A to U in total 21 sectors. However, the manufacturing group of ISIC Rev.4 is subdivided into more detailed sectors in the top-class level of this study. As an example, a transaction table of top-class in 2010 represents 30 sectors of industrial production as a whole. The mid-class level of aggregation is compared to the 2-digit level classification of ISIC Rev.4, and as an example a transaction table of mid- class in 2010 represents 82 sectors of industrial production as a whole. The sub-class level of aggregation is compared to the 3-digit level classification of ISIC Rev.4, and as an example a transaction table of sub-class in 2010 represents 161 sectors of industrial production as a whole. As shown in table 2, we summarize detailed information of the industrial classification for all benchmark years.
Table. 2 The number of industries, according to the level of aggregation
Year 1960 1966 1970 1975 1980 1985 1990 1995 2000 2005 2010
Top-class - - - - 19 20 26 28 28 28 30
Class Mid-class 43 43 56 60 64 65 75 77 77 78 82
Sub-class 109 117 153 164 162 161 163 168 168 168 161
In this study, the hypotheses of structural shift and increasing variety are the discussion on inter- sectoral level(Saviotti and Pyka 2013) or unrelated variety level(Frenken, Oort, and Verburg 2007), so the hypotheses are tested by using transaction tables of top-class. In order to reconstruct the data set with consistency, therefore, we re-aggregate all mid-class tables into the top-class tables with respect to the same standard, the 2010 version of the industrial classification as shown in Table A1. The reason why we choose the 2010 version of the industrial classification as the new standard is as follows. The 2010 version of the industrial classification definitely captures the newest industrial structure of Korea so that it covers a wide variety of industries as well as most specific industrial productions. By properly treating merged industries or non-existent industries at the year, in this respect, we can reconstitute Input-output tables under all different bases as the time-series data set with consistency. Thus, we also use the transaction tables of sub-class for the separation of merged industries. In addition, if there exist non-existent or unspecified industries at the former classification, we set the value of relevant production by zero13.
3.3. Method
As for how Input-output matrix meets the balance, the sum of each column or row represents the sectoral gross output, and the sum of each sectoral gross output together with deducted total import value14 is distributes to intermediate demands across industries and final demands for each institution. In other words, we can analyze the changes not only in the overall industrial composition by gross output values but also in the segmented industrial composition by each institution of demands. Therefore, we firstly verify the hypotheses by the overall structural change in terms of gross output. Secondly, we supplement the result by the decomposed structural changes in terms of intermediates (INTM), private consumption expenditures (PCE) and export (EXP), as shown in Figure 3. As a matter of fact, the decomposition analysis on structural changes is the distinctive part of this study from other empirical studies using GDP data in general. With regards to the importance of embracing the factor of intermediates, we can easily present the grounds by the case of Korea, as shown in Fig. 4(a). Along with the history of the Korean economy, the share of intermediate demand has gradually become converging to 50%. It means that the analysis on total industrial structures is not sufficient to consider the final demand only, meaning just another half share of gross output. In addition, Fig. 4(b) shows the grounds for selecting private consumption expenditures and export among other institutions15 of final demand as most of final demand is explained by them. In the case of private fixed capital formation, we exclude this factor out of the decomposition analysis because the composition of majority tends to be invariant16. In other words, this factor is not significant in either structural shift or increasing variety.
13 For example, there was not the industry of precision machineries and instruments until 1996 and emerged such industry in 1970 on the classification. Therefore, the production for this industry in 1960 and 1966 are treated by zero. For the case of the industry of research and development, it did not be specified until 1975 in the mid-class tables, and it started to be measured as the industry of education and R&D from 1980 to 2000. Therefore, based on the detailed value in the sub-class tables, we divide the merged value into the industry of R&D and the industry of educational services. In Table A2, we summarize which industries are merged or unspecified in each benchmark year by the number of industries.
14 At present, the total production of Korean economy is composed roughly 15% of import and 85% of domestic production. Traditionally, the contents of import used to be raw materials, mineral resources, and other high-tech production equipment, but recently the dependency on high-tech machineries has become steadily decreasing. See Figure A1 in appendix.
15 Generally, the final demand is structured by private consumption expenditures(PCE), government consumption expenditures(GCE), gross private fixed capital formation(PFC), gross government fixed capital formation(GFC), and export(EXP).
16 As not shown in this paper, we figured out that 90% of private fixed capital formation has been invariantly assigned in the industry 17, 10, 13, and 11 since 1970. Figure. 3 The Scheme of the empirical verification on structural changes
Figure. 4 (a) Relative ratio of intermediate and final demands, and (b) Relative ratio of private consumption expenditures (PCE), gross private fixed capital formation (PFC), and exports (EXP) in the total final demand
Coming to the main point, we design the method to test three hypotheses in accordance with the definition of the structural change in this study, structural shift and increasing variety. Firstly, in order to discuss the structural shift issue, we analyze how the industrial configuration for top 70% of total value for each year evolves. Then, we measure the entropy index for top 70% of total value, and thereby investigate the phenomena of increasing variety. In this point, the reason why we take the criterion as not the entire value but top 70% is to clearly monitor emerging and declining industries along the structural shift process, and then to relate to the role in the production majority for the growing economy. Moreover, we can confine the changes of increasing variety to the configuration of production majority by the criterion, so in this case the creation of new sectors plays a complementary role to the structural shift process. As for the cut-off line of 70%, we base on the perspective of Saviotti and Pyka (2013), which is ‘economic development process from necessities to imaginary worlds’. By the meaning of ‘necessities’, we take the Engel’s coefficient in the 1960s of Korea, which was just below 70% (Heo 2012), as a reference. This coefficient is also coherent to the level of final demand in 1960, as shown in Fig. 3(a). Along with economic growth of Korea, hence, we can trace how the composition of the production majority has been evolved since 1960 when the production majority was almost for necessities.
As for the measure of economic variety, the entropy index(H) is employed in this study. From the origin of the information entropy function, many scholars has modified and revise the way of entropy calculation according to own purposes (Theil 1972; Grupp 1990; Boschma and Iammarino 2007; Castaldi, Frenken, and Los 2015). In this study, we adopt the method of Frenken et al.(2007) for the entropy at the aggregation level of top-class, or unrelated variety as below.
퐺 1 H = ∑푔=1 푃푔 log2 ( ) eqn. (1) 푃푔
In eqn. (1), let g = 1,2, ⋯ , 퐺 stand for the total number of industries on top 70%, and 푃푔 represents the 퐺 normalized share of industry g where ∑푔=1 푃푔 = 1 . By adopting the index in this way, we can reasonably quantify increasing variety including the difference in the total number of industries and relative weight of each industry. The value of H is bounded from zero to the theoretical maximum which is 4.39, attained if all 푃푔 are identical where 퐺 = 21 on top 70%.
4. Results
4.1. Preliminary test: The case of Korea, through the lens of TEVECON model
In this section, we preliminarily evaluate whether the perspective of TEVECON model is reasonably applied to the Korean economy as an empirical verification subject, by comparing the simulated results of TEVECON model and the equivalent data of the Korea economy. In the pursuit of this purpose, we cite the previous research using TEVECON model (Saviotti and Pyka 2013) as a control experiment. According to their study, the TEVECON model reproduced two featured paths of economic development by controlling the rate-determining parameters of the core mechanism as described in section 2.3. Thus, we discuss how much the experimented paths from theory match up with conditions and consequences of economic development of Korea. By doing this, we confirm the way of understanding the case of Korea at the macroeconomic-level through the lens of a model of economic development by the creation of new sectors at the meso-level.
Saviotti and Pyka (2013) states that the process of economic development has been followed by the emergence of new industries since the Industrial Revolution, from the economy of necessities to the economy of various products beyond basic needs. In this respect, they pointed out the evolutionary process of economies could be bifurcated due to differences in generating output variety and improving product quality. Accordingly, the experiment of TEVECON model was designed to give different values to the parameters in relation to search activity and product differentiation process. As a result of this experiment, two types of economic development were reproduced in accordance with the level of innovation opportunity and quality, as shown in Fig. 5(a). One is called the ‘LQ-type’ which is short for ‘the low-quality type of economic development’, and the other is calls the ‘HQ-type’ which is short for ‘the high-quality type of economic development’. The LQ-type economy shows the diminishing rate of income growth because of the lower chance for innovation activities while the HQ-type economy shows the self-accelerating shape of income growth owing to the higher chance for innovation activities. In that case, although two types of economy present the sustained aggregate growth, the HQ-type economy is finally overtaking the LQ-type economy, shown in Fig. 5(a). In other words, we infer that the two economies appear to diverge unless the qualitative change through the structural shift is undergone.
When taking these two theoretical economies as a control experiment, we firstly need to devise the comparison process to the case of Korea as a real economy with different groups of industries. Accordingly, we suggest to classify the data of sectoral gross outputs into the group of LQ-type and HQ- type with respect to the technology intensity of industries17, and we add the group of necessity-type by matching with the industry of agricultural, forest, and fishery goods. In Fig. 5(b), we present the growth paths of three different groups. By comparison with Fig. 5(a), the growth path of HQ-type industries almost corresponds with the self-accelerating shape, and the growth of necessity and LQ-type industries are much slower and smaller than the growth of the HQ-type group.
Figure. 5 Economic development paths: (a) theoretical results from TEVECON model*, and (b) observed results from the empirical data of Korea
However, the groups of necessity and LQ-type industries turned out not to follow the self-limiting shape of growth in the actual data. In this way, it is noted that the theoretical model is assumed respectively as a pure constitution of low-quality sectors or high-quality sectors, unlike three groups of necessity, LQ, and HQ-type industries are interdependence in the real economy. Therefore, we can
17 According to annex 1 of ISIC Rev. 3 (OECD), the definition of technology intensity is presented in term of low, medium-low, medium-high, and high technology. In regard to the sectoral output data at the aggregation level of top-class, we match the industry 3, 4, 5, and 14 with the group of LQ-type, and match the industry 10, 11, 12, and 13 with the group of HQ-type. argue that the self-accelerating growth of HQ-type industries exerts the production inducement effect on the group of LQ-type industries in the real economy. In addition, in the real economy with a combination of LQ and HQ-type industries, the generation of GPT(General Purpose Technology) simultaneously influences upon total industrial performances. For this reason, the group of LQ-type industries can be offset the self-limitation effect in the Korean economy. Moreover, as pointed out also in Saviotti and Pyka (2013), since the real economic system has gone through the structural shift from the LQ-type to the HQ-type economy, the empirical evidence is likely interpreted to take the combination of two development paths of the theory.
For the theoretical feature of overtaking, we clearly identify the same phenomena in the real economy of Korea. As shown in Figure 6, by passing through each phase of economic development, the relatively ‘lower’-quality group tends to be overtaken by the ‘higher’-quality group. During Phase 1, the group of necessity-type industries caught up with the group of LQ-type industries first, so after 1970 the LQ-type industries presented a significant growth. In Phase 2, the HQ-type industries started to overtake the performance of necessity-type in 1985, and thereafter surpassed the growth of LQ-type industries in 1995. Finally, the HQ-type industries have sustained the accelerating growth in Phase 3. This result also corresponds with the history of the Korean government actions as already mentioned in Table 1.
Figure 6. The observed overtaking phenomena, along with (a) Phase 1, (b) Phase 2, (c) Phase 3 of Korean economy
In conclusion, we confirmed that the empirical evidence of economic growth of Korea is well described by the theoretical appreciation of TEVECON model. Therefore, we have the ground to test hypotheses on structural changes by using the case of Korea through the perspective of the economic development by the creation of new sectors.
4.2. Structural change: The dynamics of gross output(GO)
Gross output(GO) of Korean, in total transaction tables, has been exponentially growing in the same trend with GDP growth, as shown in Figure A2, but the gap between GO and GDP began to increase and then became double in 2000. In this progress of quantitative growth in GO, the compositional change of GO, including not only final demand but also intermediate demand, has been performed as well. Therefore, in this section, we analyze the overall structural change of the Korean economy by using the time-series set of sectoral gross output data, and thereby verify the hypotheses. In order to analyze the overall structural change, we prepared the configuration of top 70% for each benchmark year as shown in Table A3, and the average cut-off percentage was 71.5 ± 1.1 %.
Firstly, Figure 7 presents the result of the overall structural change in terms of the structural shift, and Fig. 7(a) directly shows how the industrial configuration of top 70% has been evolved. In details, before the launch of the government-led development plan in 1962, the Korean economy used to be specialized in the low value-added sectors. As shown in Fig 7(a), the first column of 1960 is mostly composes by primary industries and simple manufacturing industries18 in the production majority. Then, the characteristic transition of the production majority was caused by the emergence of petroleum and chemical industries in 1970, so the middle part of Fig 7(a) presents the structural shift toward the heavy industrial economy. In 1985, emerging the industry of electronic and electrical equipment made a change of the industrial configuration again. Thus, the structural shift to the high-tech industrial economy took shape, followed by the emergence of automotive and transportation equipment industry. The emergence of key industries into the production majority is represented as shown in Fig. 7(b), and it definitely confirms Hypothesis 1. In the meantime, we also observed the emergence of finance and insurance service industry in 1990, and it will be discussed in the next section.
Figure 7. Structural shift phenomenon: (a) The compositional change of top-70% of gross output(GO) and, (b) The emergence of new industries into top-70% of GO
Meanwhile, we found out that the substitution relation between creation and destruction of
18 In this point, the simple manufacturing industries means mostly domestic manual industries of textile and leather products. industries rarely appeared in the empirical evidence of the top-class level data. Although the industry of agricultural, forest, and fishery industry became left behind and finally excluded in 1995, such change does not accompany with any equivalent emergence of industries. Besides the agricultural industry, most of industries which has once included in the production majority tend to remain in the economic system and adjust contribution shares in the majority. At this point, we need to better grasp of this situation together with the increasing variety and the entropy index. Fig. 8(a) directly shows the increasing trend of the total number of industries on top 70%, and Fig. 8(b) presents the entropy index accordingly. For the first 25 year, the entropy index seems drastically influenced by the increasing total number of industries, and then for the other 25 years the index varies within the small range of fluctuation due to the changes in shares of industries. In other words, the increasing trend of the entropy index confirmed Hypothesis 2. Moreover, in consideration of the configurational change by the emergence of key industries in Fig. 7(b), the increasing variety of the production majority is also involved with the structural shift. Hence, Hypothesis 3 is confirmed as well.
Figure. 8 Increasing variety phenomenon: (a) The number of industries in top-70% of gross output and, (b) The entropy change of top-70% of gross output
4.3. Decomposition of structural change: Intermediates, Private consumption expenditures, and Export
So far, we tested three hypotheses and verified the theoretical knowledge by analyzing the overall structural change. However, the analysis of the overall structural change has the aspect of phenomenological approach in part, so we still have unresolved issues in structural changes. For example, in Fig. 7(b) we do not come up with the right explanation about the emergence of finance and insurance service industry, or the difference between the emergence of this kind of service industries and key industries for the structural shift. Therefore, in this section, we discuss more on the functional role of the structural change, and deepen our understanding with regard to the long-term economic development path. As shown in Figure 4, we follow the decomposition procedure on the overall structural change, by taking the sub-data set of intermediates, private consumption expenditures, and exports. Firstly, the structural change of intermediates are more advantageous to certify key industries of the sectoral constitution because it reflects the domestic transactions across industries. The same method and criterion are applied to the sub-data set of intermediate demand, and the average cut-off percentage was 72.1 ± 1.3 %. In Fig. 9(a), the emergence of petroleum and chemical industries occurred one period ahead in comparison to the overall structure. As joining the industry of basic metal products into the majority in 1975, the domestic industrial transaction became dominated by the heavy industries in fact. Accordingly, the demand of so-called light industries were diminished and finally left out of the industrial transaction majority in 1995. In addition, since relative weight of electronic, machinery, and automotive industries appeared to grow after 1995, the industrial structure of the Korean economy began to be further modernized. By the decomposition analysis for intermediate demand, therefore, we can support the verification of Hypothesis 1 and complement the explanation about the structural shift. In the point of the entropy index, we also found out the aspect of increasing variety along with the decomposed structural change, and the degree of increase was moderate in comparison to the overall structural change. When we interpret this as the increasing complexity and modernization of domestic production, Hypothesis 3 can be supported again.
Figure 9. (a) The compositional change of top-70% of intermediates and, (b)The entropy change of top-70% of intermediates
Secondly, the two main institutions of final demand are private consumption expenditures(PCE) and exports(EXP). According to the meaning of PCE, we consider the structural change of PCE with respect to how the needs of consumers in the domestic market have changed over time. However, when it comes to EXP, we need to consider that key industrial policies has been closely related to the ‘export-driven’ growth. Therefore, we expect that the functional roles of the decomposed structural changes in final demand are differently interpreted. In the analysis of EXP and PCE, the same method and criterion are also applied to the sub-data set of exports and private consumption expenditures respectively, and the average cut-off percentage were 71.7 ± 2.3 % for EXP and 72.7 ± 1.2 % for PCE. Figure 10 shows the result of the structural change analysis on the export transaction. On the one hand, Fig. 10(a) presents the structural shift aspect as a result of fostering the 6 strategic industries through the industrial policies, but on the other we cannot identify the increasing variety in the empirical evidence of the top-class level data. In Fig 10(b), the entropy index tends to decrease after the structural shift to the higher value-added industries. In this respect, it is expected that the decreasing variety of our analysis is originated from the aggregation level of the data. As a matter of fact, the export competitiveness strategy was enacted in terms of sub-class product level, for example electric home appliances, cars, and large vessels. Therefore, such varieties cannot be captured in the top-class level data because it is considered as intra-sectoral varieties in this study. This part can be supplemented with further study focusing on export variety(Saviotti and Frenken 2008).
Figure 10. (a) The compositional change of top-70% of exportsand, (b)The entropy change of top- 70% of exports
In Figure 11, the structural change of PCE shows significantly different patterns. First of all, the industrial configurations of top 70% generally match with the hierarchy of needs, so the structural shift in term of the private transaction majority appeared from industries of agricultural, fishery and food to industries of clothing, shelter, and retails. Especially, the industries of educational, healthcare, and finance have emerged into the private transaction majority since 1990, and it exactly shows the income increase effect from the previous economic progress induced to improve the quality of life. Finally, the full-scale expansion into the consumer service industries started to contribute the overall industrial structure as shown in Fig. 7(b). Interestingly, as reflecting the rapid economic growth of Korea, the entropy index of PCE shows the most dramatic increase. In conclusion for the decomposition of final demand, the structural shift of EXP indicates the complementary change of economic growth while the structural change of PCE represents the consequential change in economic growth.
Figure 11. (a) The compositional change of top-70% of private consumption expenditures(PCE) and, (b)The entropy change of private consumption expenditures(PCE)
5. Summary and concluding remarks
In this paper, we attentively reviewed previous literatures of structural changes and economic development, and thereby we formulated three hypotheses as generalized theoretical knowledge. Accordingly, we confirmed the hypotheses by analyzing input-output tables of Korea from 1960 to 2010in terms of the structural shift and increasing variety. In this process, we focused more on the relationship between 'increasing variety' at the industrial-level and economic development on the empirical analysis. Figure 12 shows the summary of this study. Through this figure, we emphasize that the overall structural change contains two different functional changes. One is the structural change as a necessary requirement for the long-term growth featured by intermediate transaction and export, and the other is the structural change as a consequence of the long-term growth featured by private consumption expenditures. Unfortunately, we cannot identify the increasing variety in the structural change of private consumption expenditures due to the aggregation level of the treated data, so it will remain as a further research. In addition, the presented empirical results provide a starting point to expand TEVECON model into a history-friendly model, bridging the gap between the artificial world of the formal theory and the real world of historical experiences. In this regard, this paper contributes to identify and enhance empirically theoretical understandings of economic development by the emergence of new sectors.
Figure 12. Summary of the result on Structural change and economic development
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[ APPENDIX ]
Table A1. Industrial classification at the level of top-class aggregation
No. Abbr. Name No. Abbr. Name
Agricultural, forest, and fishery Water supply, sewage and 1 AGRI 16 WATS goods waste management 2 MING Mined and quarried goods 17 CONST Construction Food, beverages and 3 FOOD 18 WSRT Wholesale and retail trade tobacco products 4 TEXT Textile and leather products 19 TRPS Transportation services Wood and paper products, Food services and 5 PULP 20 RTHT printing accommodation Coal, petroleum and chemical Communications and 619 PTCH 21 ICTB products broadcasting 7 NMET Non-metallic mineral products 22 FINI Finance and insurance Real estate, leasing and 8 PMET Basic metal products 23 REAL rental services 9 FMET Fabricated metal products, 24 RNDS Research and development 10 EQMA Machinery and equipment 25 BUSN Business-supporting services Electronic and electrical Public administration and 11 ELEC 26 PUBS equipment defense Precision machineries and 12 PMCH 27 EDUS Educational services instruments Automotive and transportation Health and social welfare 13 VEHC 28 HCSW equipment services 14 MANF Other manufactured products 29 SERV Cultural and other services Electricity, gas, and steam 15 ENRG supply
19 Here, in contrast with the original classification of 2010 version, we merge the industry of coal and petroleum and the industry of chemicals into a single industry, No. 6. Therefore, the total number of industries is 29 sectors, not 30 sectors. Table A2. Industries which are unspecified or merged in each benchmark year by the number of industries as Table A1
Type 1960 1966 1970 1975 1980 1985 1990 1995 2000 2005 2010
12, 12, 20, 20, 21, Unspecified 24, 20, 24, 24, or 25, 24, 25 ------25, 25 Non-exsistent 26, 25 26, 27, 27, 28 28
merged ( 22 & 23 ) ( 27 & 28 ) ( 24 & 27 ) - -
Table A3. Composition (relative weight) of top-70% of gross output (GO)
No. Abbr. 1960 1966 1970 1975 1980 1985 1990 1995 2000 2005 2010
1 AGRI 26.7 27.9 18.5 14.2 8.3 7.7 5.2 - - - -
29 SERV 14.5 8.9 0.0 4.4 4.4 3.6 3.7 4.2 4.3 4.8 -
3 FOOD 9.9 8.9 9.0 8.7 10.8 9.1 7.0 5.0 4.2 3.5 3.0
18 WSRT 7.5 9.9 9.8 9.0 7.1 6.6 6.6 5.9 5.0 5.1 6.2
4 TEXT 7.5 8.3 7.8 11.1 8.4 7.3 6.8 4.1 3.4 0.0 0.0
17 CONST 5.7 7.5 9.5 6.7 8.0 8.1 10.5 9.8 7.1 7.3 6.0
6 PTCH - - 6.5 11.7 12.7 11.4 8.4 8.6 10.2 10.4 11.0
19 TRPS - - 5.4 5.0 5.2 4.8 3.8 4.0 3.7 3.8 3.9
5 PULP - - 3.1 ------
8 PMET - - - - 5.1 4.9 5.1 5.0 4.1 5.7 6.3
11 ELEC - - - - - 4.4 6.4 7.9 10.2 9.2 10.6
26 PUBS - - - - - 3.3 - - - - -
13 VEHC ------5.1 5.8 5.4 6.4 6.7
23 REAL ------4.0 4.6 5.9 5.0 4.5
25 BUSN ------4.0 4.0 3.9 2.9
22 FINI ------3.8 4.6 4.3 4.1
10 EQMA ------3.4 3.4
21 ICTB ------3.2
Total (%) 71.9 71.4 69.6 70.7 70.0 71.2 72.7 72.7 72.1 72.7 71.8
Average 71.5 ± 1.1 % Figure A1. (a) Relative ratio of gross output and total imports, and (b) Compositional change of total imports
Figure A2. GDP and GO growth of Korea from 1960