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Tamás Gáspár Department of International Economics, Budapest Business University, Budapest, Hungary

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Magdolna Sass Department of International Economics, Budapest Business University, Budapest, Hungary
Institute of World Economics, Centre for Economic and Regional Studies, Budapest, Hungary

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Krisztián Koppány Department of International and Applied Economics, Economic Modelling Research Group, Széchenyi István University, Győr, Hungary

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Shulei Bi Doctoral School of Entrepreneurship and Business, Budapest Business University, Budapest, Hungary

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Abstract

Trade analysis for open economies is strategically important. Even though Hungarian trade relations are oriented towards the EU, the direct and indirect influence of Asia, mainly China, needs special attention. The paper focuses on direct bilateral relations between Hungary and China. The global value chain perspective enables the research to detect inter- and intra-industry dependencies and unfold and compare the industry focuses and dynamics of backward and forward linkages between 2000 and 2018. We used a mixed methodology, combining input-output analysis with company case studies based on a wide range of literature both from Chinese and East-Central European researchers. The findings support the significance of global value chain relations, highlight the restructuring of Hungarian trade relations with China over the past twenty years, and indicate the strong concentration of relations in terms of the number of companies.

Abstract

Trade analysis for open economies is strategically important. Even though Hungarian trade relations are oriented towards the EU, the direct and indirect influence of Asia, mainly China, needs special attention. The paper focuses on direct bilateral relations between Hungary and China. The global value chain perspective enables the research to detect inter- and intra-industry dependencies and unfold and compare the industry focuses and dynamics of backward and forward linkages between 2000 and 2018. We used a mixed methodology, combining input-output analysis with company case studies based on a wide range of literature both from Chinese and East-Central European researchers. The findings support the significance of global value chain relations, highlight the restructuring of Hungarian trade relations with China over the past twenty years, and indicate the strong concentration of relations in terms of the number of companies.

1 Introduction

Many countries, including Hungary, are far more open to the world economy than the average. Foreign trade performance strongly determines the production process, while, besides the big companies, it offers a new stage for the development of small and medium sized firms as well (Vakhal 2020). However, traditional trade analysis and measurement do not give an accurate picture since a wide range of industries are embedded in the international flows of intermediaries. Viewing foreign relations in terms of the global value chains (GVC) confers a different perspective (Gáspár 2020).

It is well known that Hungary's foreign trade links are highly concentrated in the EU, mainly with Germany. About one-fourth of the exports and imports and over 10% of the total global value chain linkages are related to Germany (KSH 2022; OECD 2021). In addition, the Central-European regional links are traditionally strong, and recently they have become tighter, mostly with the other Visegrad countries (Czechia, Poland and Slovakia), with a share of 4–4.5% of both imports and exports in each case (KSH 2022).

In the last decade, the dependence of the EU on Asian trade flows has strengthened, and the increasing role of China is visible. In 2022, China was the third largest partner for EU exports (9% of the total) and the most important country to import from (20.8%) (Eurostat 2023). In addition, even if their trade has shrunk, China has been flexible enough to change its export structure to target high-demand markets such as healthcare and medical equipment (Jindřichovská – Uğurlu 2021).

The role of China in Hungarian foreign trade has also strengthened. Like other emerging economies, China benefited from the extension of global value chains (Timmer et al. 2014). In the last twenty years, China has become one of the most global suppliers of manufacturing goods (Gereffi 2016). Koppány (2020) points out that the trade-influencing power of China on the Hungarian economy is outstanding, even if Hungary is a small country and its absolute share of Chinese exports is negligible. However, its direct shares, mainly in the electronic industry, and the indirect effects via the Germain supplies highlight that the dependence of Hungary on China is much higher than expected.

Despite the facts presented above, the literature still needs more studies on Hungarian-Asian global value chain relations. The motivation of this paper is twofold: first, even if there is extensive literature on Hungary's external links, the non-EU relations are less researched than the EU-relations; second, it is strategically important to detect how the Chinese relations influence or determine the Hungarian industrial network and performance. Additionally, the data we used allowed us to differentiate between GVCs led by foreign-owned multinational corporations operating in China and GVCs led by Chinese companies. Therefore, we can show how the Hungarian economy slowly changes its dependence from the first to the second one.

The main contribution of the paper is a detailed examination of the structure of the flows of semi-final and final goods between China and Hungary as well as how these structures changed over almost twenty years. The analysis is based on OECD input-output tables for several years. In terms of methodology, the analysis is restricted to tracing the direct global value chain flows, which far underutilizes the input-output analysis potential. However, we wish to highlight that the direct linkage analyses are regularly neglected, yet the low value added total flows might be considered in absolute terms and can have a greater influence on a country than expected. In addition, the research contextualises the ‘pure figures’ by discussing, through case studies, the different companies, ownership structures, and production processes that exist behind the macroeconomic data.

The main research questions are as follows: To what extent did direct Sino-Hungarian intermediate trade rise between 2000 and 2018, relative to ‘traditional’ foreign trade? What industry focuses and dynamics can be detected in both backward and forward directions, and to what extent do they overlap? How can company level data supplement the results of the macro or sector level analyses?

The paper first gives an overview of the literature, focusing on the significance of GVC analysis, how Chinese publications discuss Central-European relations, and what aspects and results Hungarian and East-Central European research provide. The methodological framework is followed by complementary approaches such as input-output data analysis and company case studies. Finally, we discuss the results and draw conclusions.

2 Literature review

Participation in GVCs can, on the one hand, increase trade between countries if there is intensive trading in parts, components, and final goods, and even related services; and, on the other hand, can have a substantial impact on the composition of trade in terms of goods categories (see e.g. Van Assche – Gangnes 2019, or Zhang et al. 2021). It can also result in differences between gross and value added exports at the level of individual countries (ECB 2013). The impact of GVCs on trade between China and the Central and Eastern European (CEE) countries, including Hungary, has been studied in the literature at both ends, i.e., in China and the CEE countries.

Like other CEE countries, Hungary is highly integrated into GVCs (Sass – Szalavetz 2014; Cieślik et al. 2021). Cieślik et al. (2016) showed that CEE economies differ in their level of participation in GVCs, but Germany's role is uniformly decisive. The CEE countries are integrated into GVCs via Western European countries and have mainly backward participation. Braun (2020) documented that the Hungarian automotive, electronics, and machinery industries have significant cross-border exposure through their high integration in GVCs. Most of these strong interdependencies are linked to the German economy, but for some sectors, there is a strong dependence on China on the one hand and other European countries, such as Italy, Austria, and Denmark, on the other hand. Vakhal (2021) showed the leading role of Germany, the USA, and China in terms of direct and indirect value added flows to Hungary.

Numerous studies analyse the group of CEE countries, including Hungary, from the point of view of their GVC relations with China. Ye (2016) developed an export value added model to analyse China's exports to CEE countries at the national and industry levels, showing the significant impact of participation in GVCs on bilateral trade. Wang and Ji (2018) found that China's goods imported and exported from and to CEE countries contain mainly capital-intensive products, and Chinese goods have stronger competitive advantages in these goods compared to the CEE countries. Xiao (2020) showed a higher concentration of import and export in the CEE countries compared to China, with exports mainly dominated by vehicles and electronics, and imports of mineral products, with a mismatch between the leading export products and competitive advantage products for each country. Wei and Zhang (2020) analysed the bilateral import potential based on import data and found that although the distribution of trade potential between China and CEE countries is uneven, China's market size, bilateral cooperation mechanisms, and the supply capacity of CEE countries are the reasons why there is still great room for tapping the bilateral trade import potential. Bai et al. (2020) examined bilateral trade relations in terms of goods exports and imports between China and CEE countries. The results showed that the bilateral goods trade grew rapidly, though its volume is still small and structural imbalances exist. Furthermore, China's role is determining, as it is at the core of the import-export network relationships and determines an industrial division of labour between itself and the CEE countries (Cui-Li 2018). As for the Visegrad countries' trade with China, Cieślík (2019) indicated that they have particularly strong GVC linkages, especially in the automotive, electronics, and metalworking industries. In these industries, the Visegrad countries are in a worse position than China in terms of value added, and there is an increase in the reliance of the Visegrad countries on Chinese inputs.

Particularly for Hungary, Éltető and Völgyi (2013) indicated quite early that the role of GVCs may be of determining importance in the bilateral trade between the country and China. Other authors called attention to dynamic changes in bilateral trade after the 2008–2009 crisis due to the reorganisation of GVCs (Szalavetz 2016) and links between Chinese equity investment in Hungary and GVC participation (Gerőcs 2022). Czakó and Vakhal (2020) and Koppány (2020) disclosed a significant share of value added originating from China in Hungarian electronics exports. These results were reinforced by Braun (2020).

It is important to note that we cannot ignore changes in GVCs and the participation of the studied countries in them. These changes characterise China, especially after the 2008–2009 crisis. According to Garcia and Nguyen (2019), based on the analysis of data up until 2018, China has become more vertically integrated, and thus its dependence on Asian and global chains has gradually decreased. At the same time, Europe's value chains increasingly depend on China at the expense of their own regional integration. This means that China imports increasingly fewer intermediate goods from the EU, but it exports increasingly more intermediates to EU member states for their re-export. Thus, the EU depends more on Chinese inputs for exports, while China relies less on EU goods for its exports. Consequently, the EU's integration with China's value chain is becoming more asymmetric in China's favour.

3 Methodology

The research uses a mixed methodology for data collection and analysis. The documentary analysis collects and compares the main experiences of the literature. The quantitative input-output analysis follows the Miller and Blair (2009) foundations and reveals the main characteristics of Hungarian-Chinese direct global value chain relations. To include indirect relations in total (direct plus indirect) linkages, we exploited the decomposition scheme of Wang et al. (2017). It highlights that important direct linkages that deliver significant gross output with lower value added contributions can remain hidden in a more complex, trade in value added oriented GVC analysis. These linkages, however, can play a key role for both partners. This suggests that it is important to analyse direct relationships, which are the focus of this study.

The third pillar is a series of case studies that test and complement the figures we received in the input-output analysis and unfold the background of the data. The chosen studies represent several layers of foreign relations, namely the experiences of Chinese multinational corporations in Hungary, big Hungarian companies in China, and foreign multinational corporations in both countries.

The figures and tables in the paper are based on the 2021 edition of the OECD Inter-Country Input-Output (ICIO) Tables. This database contains a world input-output table for each of the years between 1995 and 2018. These tables distinguish 69 countries and country groups and 45 industries. The total time series offers 300 billion cells that reflect the value of the intermediate and final transactions among each country and industry in current million USD and the value added they produce. Our research uses the tables from 2000, 2007, and 2018 as a comparison. The raw ICIO and result tables of the Wang et al. (2017) model were processed by a self-developed Excel programme and pivot tables.1

Table 1 presents a schematic ICIO table where rest of the world (ROW) now means all countries other than Hungary and China (not the original ROW category in ICIO). As our analysis focuses on the direct backward and forward relations between Hungary and China, we have highlighted related blocks within matrices Z (containing interindustry transactions) and F (final use). The first subscripts indicate the sources, and the second ones denote the destinations of product flows. Dots mean all countries/industries. Vector f contains the total final product, x is the vector of output, and v’ is the vector of value added by producer country-industries.

Table 1.

The blocks of the ICIO tables related to the China-Hungary trade analysis

Source: authors.

It is important to note that the ICIO tables distinguish CN1 and CN2 in terms of China (similar to Mexico). CN2 covers the input, performance, and output of the companies that belong to the so-called export processing zones (EPZs2), which represent a significant role in the Chinese economy. The CN2 industries sell only to countries outside of China; however, they can purchase inputs from the non-EP sectors (CN1) of China. CN1 contains the economic performance of those companies that sell both to local and export industries in terms of semi-final and final products. The input and output indicators of CN1 and CN2 considerably vary, which results in different value chain mechanisms. This is why the OECD database distinguishes CN1 and CN2, which we follow in the research to preserve information.

For the total linkage analysis, Wang et al. (2017) suggest a V=cLf decompositions of the world's value added or final product (at a global level, they are the same), where c is the diagonal matrix of value added rates (chevrons denote diagonalization), L is the global Leontief-inverse, and V is the matrix of value added contents, which one can organise into a table presented in Table 2.

Table 2.

The blocks of Wang's decomposition scheme related to the China-Hungary trade analysis

Source: authors.

In Table 2, the rows show value added flows in a forward direction, and the columns express the backward flows. Block matrix VHUN,CN1, for example, represents the value added of Hungarian industries embodied in CN1 final products, while in the opposite direction, VCN1,HUN contains the Chinese (CN1) value added components of Hungarian final products.

4 Data analysis

Based on the components shown in Table 2, we start our analysis by investigating Hungary's total backward and forward value added linkages to China.3 Indicators of other important GVC trading partners have also been added to Fig. 1 to show China's changing relative position in Hungary's value added trade. In terms of partner countries, Hungarian global value chain links are dominated by Germany to an increasing extent, and the rest are mostly networked in Europe. The figure reflect the asymmetric role of Russia: the second most important value chain partner, but only in the backward links (primary goods). This reflects the relatively high reliance of Hungary on imported energy and raw materials from Russia. In addition, regional and Central European relations have been increasing and taking up a larger share of backward relations, mainly with Poland and the Czech Republic.

Fig. 1.
Fig. 1.

The position of China in the total GVC linkages of Hungary (%)

Source: compilation of the authors using OECD (2021).

Citation: Society and Economy 45, 3; 10.1556/204.2023.00018

Outside of the European continent, the USA, Japan, and China are Hungary's primary partners. China (CN1) is an increasingly important partner for Hungary. In the past two decades, it has experienced the most dynamic increase. The strengthening of the links partly substituted for the share of Japan, which was among the most decisive partners in 2000; its share is partly due to the shift in strategy of Japanese companies in Hungary, towards establishing affiliates in the country rather than supplying from Japan.

As a comparison, we learned from the OECD database that the Chinese value chains are mostly linked to the USA and Japan, while CN2 is the major forward market for CN1. At the same time, there are reshoring tendencies in CN2 from overseas to the Asian region (CN1, Japan, Korea, Australia). The role of Hungary in the Chinese value chains is marginal, though measurable, and shows an increasing share over time.

As Fig. 1 reveals, the CN2 total linkages of Hungary in value added terms are minor compared to those of the CN1 total linkages. However, their value in gross output terms in the backward relation is quite close. This is due to the lower value-added contributions in China-Hungary trade relations. As a supplier, however, CN2 represents almost the same magnitude for Hungary as CN1. When considering the importance of a given direct supplier or buyer of a given country-industry or thinking about the risks and the consequences of losing them (i.e., a possible and very close disruption of the value chain), however, using gross value based direct linkages is more appropriate than value added content based total linkages.4

Figure 2 compares Hungary's total direct forward and backward relations with China in terms of intermediate and final goods. The first investigation reveals an overall pattern: the flows of intermediate goods dominate the relations, mainly in the forward links. In addition, the backward linkages to China have a higher share than the forward ones, but mainly in final goods. Over the past two decades, Hungarian-Chinese relations experienced a dynamic accretion: first, the backward — mainly intermediate — links before the 2008 crisis, while second, the post-crisis period boosted the forward directions. In terms of partners, the Hungarian suppliers meet mostly CN1 companies, while the backward relations are dominated by CN2 firms. Before the crisis, their role grew substantially; however, CN1 relations have become more dynamic since then and have taken the lead.

Fig. 2.
Fig. 2.

Intermediate and final goods flow of Hungary in relation to China (as a % of the Hungarian total output/total use)5

Source: compilation of the authors using OECD (2021).

Citation: Society and Economy 45, 3; 10.1556/204.2023.00018

5In terms of industries (Table 3), the backward linkages of Hungary are highly concentrated in CN2, mostly linked to computer, electronic, and optical supplies (26). However, in CN1 relations, 2–3 industries represent one third, and 5 provide half of the total value. These are computer-electronic-optical products (26), electrical equipment (27), machinery (28), and textiles (13T15).

Table 3.

Direct backward linkages of Hungary by Chinese industries in terms of intermediate, final, and total use of Hungary from China (%)7

Source: compilation of the authors using OECD (2021).

Notes: Dark blue = one third of total value; light blue = half of total value; light and dark green = increase over time; light and dark brown = decrease over time

While in relation to CN2, the intermediate and final product supplies overlap by industries, the CN1 relations sharply vary: fabricated metal products (25),67 electrical equipment (27), electronic (26), and chemical (20T21) products characterise the semi-final linkages, while textiles and wearing apparel (13T15) dominate the final product imports, as well as machinery (28), trade, and repair services (45T47).

There has been a sharp shift in the industry structure over time, both between CN1 and CN2, as well as within each region, and the two are almost complementary in terms of total use. CN1, while enjoying the most dynamic rise in fabricated metallurgy (25), is replacing CN2 in machinery and electric equipment (28, 27). Conversely, CN1 lost a great share of the computer, electronic, and optical products (26), whereas CN2 increased its participation. In terms of the textile industry (13T15), the semi-final background links have been shifted to final products, mainly in CN1. Even if CN1 takes most of the textile supplies, CN2's participation growth was dynamic between 2000 and 2018. It seems that Chinese-owned companies are gradually overtaking the participation of foreign-owned ones in GVCs in certain industries.

Table 4 reveals an even deeper relationship between the two countries by showing the inter-industry relations: the branches of production in Hungary that are supplied by Chinese linkages.8

Table 4.

Inter-industry relations of the direct backward linkages from China to Hungary (2018, million USD)8

Source: compilation of the authors using OECD (2021).

In the CN1 backward relation, the most outstanding values are the textile imports for Hungarian household final consumption, the computer, electronic, and optical Chinese contributions to the same industry in Hungary, and the machinery input to the motor vehicle industry. The most concentrated is the machinery supply, where most semi-final products are used by only a few Hungarian industries, primarily those that produce the same machinery and the motor vehicle products. Most Hungarian industries are supported by electronic equipment and semi-final products from China. In Hungary, the motor vehicle industry uses the highest amount of semi-final products from different Chinese industries.

The CN2 value links show a slightly different pattern. Here the highest value flows between the machinery and product processes between the two countries. Most Hungarian industries are supplied by the computer, electronic, and optical industries and electrical equipment production. The industry that uses most CN2 supplies is motor vehicle production, as well as many other Chinese industries that provide a great value of final products for gross fixed capital formation.

The maps in Fig. 3 trace the weight of the main Chinese supplying industries in 2018 and their dynamics since 2000. Among industries, three specific groups can be identified. In CN1, fabricated metal products (25) and non-metallic minerals (23) have the most outstanding dynamics over time, and fabricated metal has a high share, too. Machinery and electronic equipment also had a significant increase, higher than average, while they also played a determining role. The motor vehicle industry (29) indicates higher dynamics than the average but has a relatively smaller role in value, together with transportation and storage, which makes it less agile than most of the industries as backward links to Hungary.

Fig. 3.
Fig. 3.

Value and dynamics of Hungary's backward linkages to Chinese industries

Source: compilation of the authors using OECD (2021).

Citation: Society and Economy 45, 3; 10.1556/204.2023.00018

CN2 also shows considerable differences in terms of its industry links to Hungary. One extreme is the computer, electronic, and optical industries, which have had an average amount of change over time but whose importance in value is outstanding. Machinery (28) and electronic equipment (27) are other extremities with relatively high significance in the CN2 production structure towards Hungary and very high dynamics. The textile industry is the third extremity, with a smaller contribution and a relatively low increase in the CN2-Hungary relationship.

If we consider the industry structure of the forward linkages of the Hungarian economy to China (Table 5), both for CN1 and CN2 as well as in intermediate and final use, the motor vehicle industry (29) and the computer, electronic, and optical industry (26) have been dominating. However, while motor vehicle components dominate the supplies to CN1, almost 44% of the CN2 linkages come from the computer, electronic, and optical industries.9

Table 5.

Direct forward linkages to China by Hungarian industries in terms of total Chinese intermediate and final use from Hungary (%)9

Source: compilation of the authors using OECD (2021).

The forward global chains experienced considerable changes between 2000 and 2018. First and foremost, the supply of motor vehicles and motor vehicle components has significantly increased for both CN1 and CN2 intermediates and CHN as final products, partly at the expense of computer and electronic products. Machinery has also gained shares as a semi-final or final product. Among the supplies for final use, fabricated metal and pharmaceutical products show a dynamic increase. As for intermediate products, it was mainly basic metals which lost their share — and leading role in CN1 — with the shift in the industrial structure. In terms of the final product, accommodation and food services as well as food products, beverages, and tobacco shrank over time.

The deeper analysis of the inter-industry relations (Tables 6 and 7) reflects that the intra-industry flows between the Hungarian and Chinese (CN1) motor vehicle and computer, electronic, and optical industries are the most significant. However, the performance of these industries is not limited to the inter-industry linkages; they — as well as electrical equipment and various services — also provide the widest range of Chinese industries. In addition, most Hungarian producers are also linked directly to the motor vehicle, computer, and electronic industries in China, while construction is a significant destination industry. It is also worth mentioning that even if the links are considerably concentrated, there are notable intra-industry flows in a wide spectrum of industries. In the CN2 relation, the computer and electronic intra-industry link dominates the forward participation. In addition, while the motor vehicle industry supplies are the most differentiated among the CN2 buyers, the computer and electronic industry collects the most Hungarian industry outputs in value.

Table 6.

Inter-industry relations with direct forward linkages from Hungary to CN1 (2018, million USD)10

Source: compilation of the authors using OECD (2021).

Table 7.

Inter-industry relations with direct forward linkages from Hungary to CN2 (2018, million USD)11

Source: compilation of the authors using OECD (2021).

When comparing the total weights and the dynamics of the industries (Fig. 4), we can identify different patterns in terms of the two China destinations. Towards CN1, the motor vehicle industry (29) is most significant, though its dynamic is relatively low among the most extreme industries. Paper and printing (17, 18), pharmaceutical products (21) and non-metallic minerals (23) do not perform well, but their growth is the most outstanding — in this case, mainly due to the low base figures in 2000. The computer, electronic, and optical products (26) are distinguished by their higher significance than average in value with a lower-than-average increase over time, while machinery (28), rubber, and plastic products (22) were more dynamic, though with a not outstanding share in value. In contrast, machinery and motor vehicle intermediates were the most dynamic in the CN2 direction, while the computer and electronic industries had the highest share. The non-metallic minerals, like in the case of CN1, have also experienced a phenomenal increase.

Fig. 4.
Fig. 4.

Value and dynamics of Hungarian industries' direct forward linkages to China

Source: compilation of the authors using OECD (2021).

Citation: Society and Economy 45, 3; 10.1556/204.2023.00018

5 Company case studies

The statistical analysis showed considerable shifts in Sino-Hungarian foreign trade, and the impact of the participation of the two countries in GVCs is obvious from this point of view. In order to show that all three types of companies — Chinese-owned, Hungarian-owned, and third-country-owned — have an important impact on the changes in bilateral trade, we have selected a few companies to show their cases in detail. The company selection was limited by the availability of data. The balance sheets and supplementary material, all publicly available for certain firms, present data on the main country sources of inputs and country destinations of output. In certain cases, detailed data are published on trade with affiliated companies. We selected four such companies for whom information was available.

10

5.1 A Chinese multinational corporation: Huawei

11Huawei Technologies Limited is the flagship ICT company in China, with substantial investments in Hungary. As we saw, the computer, electronic, and optical industries excel in Hungary-China GVC relations. Huawei may be one of the key players in that respect.

Huawei was founded in 1987 and is headquartered in Shenzhen, China. It provides various goods but also solutions (services) for its partners. As of December 2021, Huawei had over 195,000 employees and subsidiaries around the world, with operations in more than 170 countries and regions, serving more than 3 billion people worldwide (Huawei 2021), and it can be considered a global company. Its internationalisation is not confined to production or services: it has 21 R&D institutes, 36 joint innovation centres, and 14 research institutes around the world, all of which are part of Huawei's synchronised global R&D system. In 2021, Huawei's business benefited from 5G network construction and the digital, intelligent transformation of the enterprise. Among its markets, the largest revenue came from Europe and Middle East Africa, surpassing substantially Asia Pacific and the Americas (Huawei 2021).

In the global network of Huawei, there are executive centres (in the US; France, UK, and Germany in Europe; Germany hosts the European headquarters); finance centres (Romania and UK in Europe); R&D centres (Belgium, Finland, France, Germany, Ireland, Italy, Sweden, and the UK in Europe); network operation centres (Italy, Netherlands, Romania, Spain, and the UK); and supply chain centres (Hungary and Poland in Europe). It has announced plans to open its first outside-China manufacturing plant in France in 2020 (Albert 2020).

Huawei has been present in Hungary since 2005; thus, it could influence changes in bilateral trade between 2000 and 2018, as analysed in the previous section (ACEH 2022). The Hungarian government considers Huawei a strategic partner, as evidenced by the agreement signed in 2013 (AP 2019). Huawei has two factories and a logistics centre in Hungary, with a total warehousing area of 62,000 square metres. Huawei has built the largest overseas production and supply centre in Hungary, the Huawei Europe Production and Supply Centre, which provides product supply and logistics services to more than 50 countries. The principal activity of the company is the wholesale trade of electronic and communication equipment and parts. Up to now, Huawei has invested over US$1.2 billion in Hungary, directly or indirectly creating more than 2,000 jobs. Local purchases exceeded USD 246 million and contributed USD 277 million to local taxes. Huawei's local partners include all the leading local telecommunications firms in Hungary. Huawei obtained a leading market position in mobile networks, next-generation fixed access networks, core networks, optical networks, mobile broadband terminals, and mobile phones (Cooperation Between China and the Central and Eastern European Countries 2020). It has a considerable impact on the Hungarian economy (Oxford Economics 2020).

As far as flows within the company network are concerned, an estimation based on the information contained in the supplement to the balance sheet of Huawei Technologies Hungary Ltd. revealed that the most significant revenue was generated by Huawei International Co. Limited for the provision of headquarters services to the European Supply Chain, the Regional Centre, the European Supply Centre, and the European Returns Centre. Furthermore, on the revenue side of the Hungarian subsidiary, Huawei Device (Hong Kong) Co. Limited paid a substantial amount for the sale of spare parts for consumer equipment to support repair services. Altogether, revenues from linked (by ownership) companies amounted to around one third of the total. On the other hand, the Hungarian subsidiary is more closely linked to fellow companies in terms of the goods and services it offers, as these represent more than three-fourths of total costs. The most significant parts are represented by Huawei Device Co. Limited (a production company located in China and Vietnam) (D&B n.d.), which supplies all consumer devices sold in Hungary, and by Huawei International Co. Limited (registered in Hong Kong). As the company is the only skilled distributor of Huawei products in Hungary, significant purchases of equipment and services related to the network and enterprise and government business groups are realised from the latter company. Of course, these only cover the partially realised trade flows in GVCs led and managed by Huawei. Also, these flows represent a minor part of bilateral trade (2% of Hungarian exports to China and 1% of Hungarian imports from China in 2021, based on the foreign trade data of the Hungarian Central Statistical Office). However, this short case study illustrates how GVCs affect China-Hungary trade, even in the case of Chinese multinational corporations.

5.2 A non-Chinese multinational corporation present both in China and Hungary

Though the importance of these firms is still dominant, it is declining gradually at the expense of Chinese-owned firms. Third-country-owned multinational corporations are the ones that determine bilateral trade flows between the two countries. From these, we have found relatively detailed data for a US subsidiary in Hungary, which owns subsidiaries in China as well. National Instruments produces computer hardware and software; thus, it is active in the computer, electronic, and optical industries highlighted in the statistical analysis. It has been present in Hungary since 2002. The Hungarian subsidiary executed transactions with numerous affiliated companies (74 affiliated firms), including one China-based (Shanghai) and one Hong Kong-based subsidiary. For the Hungarian company, these two subsidiaries represented very low shares in foreign supplies coming from affiliated companies (0.001% and 0.003%, respectively); however, they accounted for a relatively large portion of foreign sales realised towards affiliated companies (10% and 1.3%, respectively). This latter is true for the overall sales of the Hungarian subsidiary as well because the overwhelming majority of transactions were realised between the parents and subsidiaries, i.e., within the company network (National Instruments 2021). In terms of total Hungarian exports to China, the Hungarian subsidiary represented 3.4% in 2021.

5.3 A Hungarian multinational company

The pharmaceutical industry (21) figures among the top industries in Chinese intermediate and final use from Hungary (Table 3). One key company player here is Richter Gedeon, a well-known Hungarian pharmaceutical multinational company with a long tradition. Its predecessor was established in 1901. Richter Gedeon is a highly innovative company responsible for the highest share of Hungarian R&D (as a company), and it has registered a large number of patents. Its main activities are research, development, manufacturing, and marketing of pharmaceutical products. It is a highly internationalised company with a TNI12 above 50% (Antalóczy – Sass 2018). The company is present in 50 countries and has eight manufacturing sites. In terms of foreign affiliates and subsidiaries, it is present mainly with representative offices and three production units in former CMEA countries (Poland, Romania, and Russia). In Western Europe, it is present in almost all EU member states, with trading affiliates and two production units in Germany and Switzerland. From the point of view of our analysis, it is especially important that a key focus of its foreign expansion is in Asia, where there is a production unit in India and numerous trade representative offices. In China, Richter Gedeon formed a joint venture, Rxmidas Joint Venture Co. Ltd. In 2013, it acquired GRMed Company Ltd, and by 2017, the joint venture and the acquired company were merged (Richter Gedeon 2021: 169). The fully owned Chinese (and Hong Kong-based) subsidiaries carry out distribution and marketing activities. (The fourth main locus of foreign expansion is the Americas, where the firm is present mainly through trading affiliates and trading joint ventures.)

Detailed data are available about the share of various markets in Richter Gedeon's sales. However, data are not available about where the locally sold pharmaceutical products are produced. In 2021, China accounted for 3.4% of total sales and was ranked 7th among the countries in terms of sales (behind the US, Russia, Hungary, Germany, Poland, and Spain). The majority of the sales are concentrated on women's healthcare pharmaceutical products (Richter Gedeon 2021). Assuming all Chinese sales originated from Hungary, this would represent 2% of Hungarian exports to China.

6 Discussion and conclusion

In terms of the research questions, the analysis revealed some novel information about the Sino-Hungarian direct trade relations and contributed to the literature: Participation in global value chains involving China is increasingly significant in the Hungarian foreign economic network. While the backward links to China have a higher share of the production than the forward sales in the expenditure, the forward linkages have been more dynamic in the past ten years. The analysis has revealed that mainly the flow of semi-final products has increased over time, both in terms of backward and forward participation, which supports the increasing importance of global value chains in the bilateral relations of the two countries.

The industry content is quite concentrated. The CN1 (mainly Chinese multinational corporations) and CN2 (foreign multinational corporations operating in China) relations are not similar, though they overlap, and a significant shift can be seen between 2000 and 2018. In terms of CN1, we found that backward relations are dominated by the (final product) textile industry, while motor vehicle components and final products characterise mostly the forward links. The computer and electronics industries have a relatively high weight but lower dynamics than the average. The non-metal minerals have an increasing role, and the fabricated metal products have a determining influence on backward relations.

In the CN2 relation, the computer and electronic industry has the most significant relevance both in backward and forward terms, while machinery products provide a higher-than-average rise over time. Motor vehicle industry relations are unbalanced: in backward chains, they have a relatively small weight in value but high dynamics, while in forward links, the importance is outstanding with a smaller-than-average increase. Electronic equipment is also inconsistent: their supply has a considerable weight and low dynamics backward, and while their importance remains high, their future growth is relatively low.

Fabricated metal products receive special attention, not only because the industry has become significant in Hungarian-Chinese relations, but also because the value chain flow of fabricated metal products has shifted around: while in 2000, Hungary supplied mainly to China, in 2018, Chinese production and export have taken over this relationship.

As for the case studies, the activities of multinational companies have a significant impact on bilateral trade. High shares of individual intra-company trade flows in total Sino-Hungarian bilateral trade lend credence to the idea that transactions within the network of multinational companies have a determining impact on foreign trade between the two analysed countries. While foreign (third country) multinational corporations can be of determining importance from the point of view of bilateral foreign trade developments, ‘own’ multinational corporations increasingly influence trade flows, as was indicated in the statistical analysis on the part of China and, to some extent, Hungary.

Acknowledgement

This research was conducted in the Centre of Excellence for Future Value Chains, Budapest Business University. The research of Magdolna Sass for this paper was supported by the Hungarian Research Fund NKFIH (project no. 132442).

References

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    • Search Google Scholar
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    • Search Google Scholar
    • Export Citation
  • Cieślik, E.Bieganska, J.Środa-Murawska, S. (2016): The Intensification of Foreign Trade in Post–socialist Countries and Their Role in Global Value Chains. Acta Oeconomica 66(3): 465487.

    • Search Google Scholar
    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
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    • Export Citation
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    • Search Google Scholar
    • Export Citation
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  • Szalavetz, A. (2016): Post‐crisis Developments in Global Value Chains – Example of Foreign Investors' Hungarian Subsidiaries. IWE Working Papers 219.

    • Search Google Scholar
    • Export Citation
  • Timmer, M.Erumban, A.Los, B.Stehrer, R.de Vries, G. (2014): Slicing up Global Value Chains. Journal of Economic Perspectives 28(2): 99118.

    • Search Google Scholar
    • Export Citation
  • Vakhal, P. (2020): Magyar kis– és középvállalkozások a globális értékláncokban. [Hungarian SMEs in the Global Value Chains]. Külgazdaság 64(5–6): 3059.

    • Search Google Scholar
    • Export Citation
  • Vakhal, P. (2021): Possible Alteration of Global Value Chains in the CEE Region. In: Xin, C. (ed.) The Restart of European Economy and Its Impact on Central and Eastern Europe Budapest. China-CEE Institute, pp. 4861.

    • Search Google Scholar
    • Export Citation
  • Van Assche, A.Gangnes, B. (2019): Global Value Chains and the Fragmentation of Trade Policy CoalitionsTransnational Corporations 26(1): 3160.

    • Search Google Scholar
    • Export Citation
  • Wang, L.Ji, Q. (2018): Research on the Commodity Structure of China's Exports to Central and Eastern Europe – Data Based on China Business Database Analysis. Journal of Beijing Vocational College of Labor Security 2: 3540 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Wei, J.Zhang, H. (2020): Analysis of China's Import Trade Potential with Central and Eastern European Countries – An Empirical Study Based on Time–Varying Follower Foreword Gravity Model. Regional Economic Review 1: 116124 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Xiao, L.Li, J. (2020): Analysis of the Characteristics of Goods Trade and Comparative Advantages of Exports of Central and Eastern European Countries. Journal of Chongqing University of Commerce and Industry 5: 111 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Ye, Z. (2016): Analysis of the Value Added of China's Trade with Central and Eastern Europe Based on the Perspective of Global Value Chains. World Economic Research 7: 3648 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Wang, Z.Wei, S.Yu, X.Zhu, K. (2017): Characterizing Global Value Chains: Production Length and Upstreamness. NBER Working Paper No. 23261.

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    • Search Google Scholar
    • Export Citation
1

We must express our gratitude to Pál Pusztai, who helped in programming the conversion VBA package.

2

These zones have been defined by the ILO (2022) as ‘industrial zones with special incentives set up to attract foreign investors, in which imported materials undergo some degree of processing before being exported again’.

3

Total backward linkages measure the ratio of all foreign supplies from any industries that contributed to the final products of Hungary. In the case of China, it can be calculated by taking the total of VCN1,HUN and the total of VCN2,HUN relative to the sum of all v•,HUN elements. Total forward linkages express how much of the value added of any Hungarian industry appears as a final product in another country. For the Chinese forward relations, they are a total of VHUN,CN1, and a total of VHUN,CN2 per sum of vHUN,•.

4

Koppány (2020) applies Leontief and Ghosh's inverse-based output-to-output elasticities to analyse China-Hungary total linkages. The most important components of the gross output-based total linkages are always the direct ones. Thus, the results of a total linkage analysis can be well approximated by a simpler direct linkage investigation. In our further research, however, we will extend our investigations to indirect relationships as well.

5

The formulas behind the charts are (i’ ZHUN,CN1 i) / (i’ xHUN) and (i’ ZHUN,CN2 i) / (i’ xHUN) for upper-left, (i’ FHUN,CHN i) / (i’ xHUN) for upper-right, (i’ ZCN1,HUN i) / (x’HUN i) and (i’ ZCN2,HUN i) / (x’HUN i) for lower-left, and (i’ FCN1,HUN i) / (f’,HUN i) and (i’ FCN2,HUN i) / (f’,HUN i) for lower-right. Vector i is the identity or summation vector.

6

Though it demands further investigation, this figure most likely covers light metallurgy, especially aluminium products. Aluminium is an essential product for modern motor vehicles and electronic production. China provides 60% of the global aluminium supply.

7

The table contains the breakdown of vectors ZCN1,HUN i, FCN1,HUN i, ZCN1,HUN i + FCN1,HUN i, ZCN2,HUN i, FCN2,HUN i, and ZCN2,HUN i + FCN2,HUN i by Chinese supplying industries, respectively.

8

Tables show selected rows and columns of matrices ZCN1,HUN II FCN1,HUN and ZCN2,HUN II FCN2,HUN. II denotes the concatenation of the matrices.

9

The table contains the breakdown of vectors ZHUN,CN1 i, FHUN,CHN i, and ZHUN,CN2 i by Hungarian supplying industries, respectively.

10

The table shows selected rows and columns of matrices ZHUN,CN1 II FHUN,CHN and ZHUN,CN2.

11

The table shows selected rows and columns of matrices ZHUN,CN1 II FHUN,CHN and ZHUN,CN2.

12

TNI or the Transnationality Index is a composite index measuring the level of internationalisation of a multinational firm. It is the arithmetic mean of the ratios of foreign assets to total assets, foreign sales to total sales, and foreign employment to total employment.

  • ACEH (2022): Huawei Technologies Hungary Kft. Chamber of Commerce for Chinese Enterprises in Hungary. https://aceh.hu/members/, accessed 20/07/2023.

    • Search Google Scholar
    • Export Citation
  • Albert, E. (2020): Huawei Doubles Down on Europe with New Factory. The Diplomat. https://thediplomat.com/2020/03/huawei-doubles-down-on-europe-with-new-factory/, accessed 20/07/2023.

    • Search Google Scholar
    • Export Citation
  • Antalóczy, K.Sass, M. (2018): The Internationalisation of Richter Gedeon, the Hungarian Pharmaceutical Company, and Entrepreneurship in Hungary. In: Tõnis, M.Arnis, S.Danica, P. (eds.): Entrepreneurship in Central and Eastern Europe: Development through Internationalization. London: Routledge, pp. 159176.

    • Search Google Scholar
    • Export Citation
  • AP (2019): Hungary Says Huawei to Help Build its 5G Wireless Network. https://apnews.com/article/688e48fac84a4eeca73fdb5e17732c5f, accessed 20/07/2023.

  • Bai, J.Wang, Y.Liang D. (2020): Competitive Complementarities and Dynamic Changes of Trade between China and Central and Eastern European Countries. Finance and Economics Science 7: 92105 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Braun, E. (2020): Kockázatok a magyar gazdaság szerkezetében [Risks in the Hungarian Economic Structure]. Külgazdaság 64(9–10): 6289.

    • Search Google Scholar
    • Export Citation
  • Cieślik, E. (2019): Looking for the Sectoral Interdependence: Evidence from the Visegrad Countries and China. Quality & Quantity 53: 20412062.

    • Search Google Scholar
    • Export Citation
  • Cieślik, E.Bieganska, J.Środa-Murawska, S. (2016): The Intensification of Foreign Trade in Post–socialist Countries and Their Role in Global Value Chains. Acta Oeconomica 66(3): 465487.

    • Search Google Scholar
    • Export Citation
  • Cieślik, E.Biegańska, J.Środa-Murawska, S. (2021): Central and Eastern European States from an International Perspective: Economic Potential and Paths of Participation in Global Value Chains. Emerging Markets Finance and Trade 57(13): 35873603.

    • Search Google Scholar
    • Export Citation
  • Cooperation Between China and the Central and Eastern European Countries (2020): Huawei Invests US$1.5 Billion in Hungary. http://www.china-ceec.org/chn/jmhz/202112/t20211224_10475420.htm, accessed 20/07/2023.

  • Cui, W.Li, Z. (2018): Trade Cooperation between China and Central and Eastern Europe: Current Situation, Problems and Suggestions. International Economic Cooperation 11: 43-46 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Czakó, E.Vakhal, P. (2020): Hungary in Global Value Chains. In: Chen, X. (ed.) CEE Countries in Europe: Toward Center or Periphery in Global Value Chains. Budapest: China–CEE Institute, pp. 142149.

    • Search Google Scholar
    • Export Citation
  • ECB (2013): How Have Global Value Chains Affected World Trade Patterns? ECB Monthly Bulletin May: 1014.

  • Éltető, A.Völgyi K. (2013): Integrated in the Global Value Chains – Trade Developments between Hungary and Asia. Eastern Journal of European Studies 4(1): 5779.

    • Search Google Scholar
    • Export Citation
  • Garcia, H.Nguyen, T. (2019): Eurasia Supply Chain Transformation. https://research.natixis.com/Site/en/publication/QkIYFbCpyiyXg5zyEb6a0w%3D%3D?from=share, accessed 20/07/2023.

  • Gáspár, T. (2020): Az ágazati kapcsolatok mérlegének új perspektívái a nemzetközi gazdaság kutatói számára [New Perspectives of Input–Output Tables for International Economic Research]. Statisztikai Szemle 98(5): 373399.

    • Search Google Scholar
    • Export Citation
  • Gereffi, G. (2016): Global Value Chains, Development and Emerging Economies. United Nations University Working Paper Series No. 2015–047.

    • Search Google Scholar
    • Export Citation
  • Gerőcs, T. (2022): The Structural Dilemma of Value–Chain Upgrading: Hungarian Suppliers' Integration into the World Economy. Society and Economy 44(1):159181.

    • Search Google Scholar
    • Export Citation
  • Huawei (2021): Huawei Investment Holdings Limited Annual Report 2021. https://www–file.huawei.com/minisite/media/annual_report/annual_report_2021_en.pdf?version=0401, accessed 20/07/2023.

  • ILO (2022): Export Processing Zones (EPZs). https://www.ilo.org/actrav/areas/WCMS_DOC_ATR_ARE_EPZ_EN/lang--en/index.htm, accessed 20/07/2023.

  • Jindřichovská, I.Uğurlu, E. (2021): EU and China Trends in Trade in Challenging Times. Journal of Risk and Financial Management 14(2): 71.

    • Search Google Scholar
    • Export Citation
  • Koppány, K. (2020): A kínai koronavírus és a magyar gazdaság kitettsége. Mit mutatnak a világ input–output táblák? [The Chinese Corona Virus and the Exposure of the Hungarian Economy. What Do the World Input–Output Tables Indicate?] Közgazdasági Szemle 62(5): 433455.

    • Search Google Scholar
    • Export Citation
  • KSH (2022): Külkereskedelem és fizetési mérleg. [Foreign Trade and Balance of Payments]. https://www.ksh.hu/stadat?lang=hu&theme=kkr, accessed 20/07/2023.

  • Miller, R.Blair, P. (2009): Input–Output Analysis. Foundations and Extensions. Second Edition. Cambridge: Cambridge University Press.

    • Search Google Scholar
    • Export Citation
  • National Instruments (2021): NI Hungary Kft. Kiegészítő Melléklet [Supplementary Annex to the Balance Sheet of the Company].

  • OECD (2021): Inter–country Input–Output Tables. https://www.oecd.org/sti/ind/inter–country–input–output–tables.htm, accessed 20/07/2023.

    • Search Google Scholar
    • Export Citation
  • Oxford Economics (2020): The Economic Impact of Huawei in Hungary. https://resources.oxfordeconomics.com/hubfs/Report_Huawei_Hungary.pdf, accessed 20/07/2023.

    • Search Google Scholar
    • Export Citation
  • Richter Gedeon (2021): Annual Report 2021. https://www.gedeonrichter.com/–/media/sites/hq/documents/investors/financial–reports/annual–report/en/2021/2021–annual–report_audited_final.pdf, accessed 20/07/2023.

    • Search Google Scholar
    • Export Citation
  • Sass, M.Szalavetz, A. (2014): R&D–based Integration and Upgrading in Hungary. Acta Oeconomica 64(S1): 153180.

  • Szalavetz, A. (2016): Post‐crisis Developments in Global Value Chains – Example of Foreign Investors' Hungarian Subsidiaries. IWE Working Papers 219.

    • Search Google Scholar
    • Export Citation
  • Timmer, M.Erumban, A.Los, B.Stehrer, R.de Vries, G. (2014): Slicing up Global Value Chains. Journal of Economic Perspectives 28(2): 99118.

    • Search Google Scholar
    • Export Citation
  • Vakhal, P. (2020): Magyar kis– és középvállalkozások a globális értékláncokban. [Hungarian SMEs in the Global Value Chains]. Külgazdaság 64(5–6): 3059.

    • Search Google Scholar
    • Export Citation
  • Vakhal, P. (2021): Possible Alteration of Global Value Chains in the CEE Region. In: Xin, C. (ed.) The Restart of European Economy and Its Impact on Central and Eastern Europe Budapest. China-CEE Institute, pp. 4861.

    • Search Google Scholar
    • Export Citation
  • Van Assche, A.Gangnes, B. (2019): Global Value Chains and the Fragmentation of Trade Policy CoalitionsTransnational Corporations 26(1): 3160.

    • Search Google Scholar
    • Export Citation
  • Wang, L.Ji, Q. (2018): Research on the Commodity Structure of China's Exports to Central and Eastern Europe – Data Based on China Business Database Analysis. Journal of Beijing Vocational College of Labor Security 2: 3540 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Wei, J.Zhang, H. (2020): Analysis of China's Import Trade Potential with Central and Eastern European Countries – An Empirical Study Based on Time–Varying Follower Foreword Gravity Model. Regional Economic Review 1: 116124 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Xiao, L.Li, J. (2020): Analysis of the Characteristics of Goods Trade and Comparative Advantages of Exports of Central and Eastern European Countries. Journal of Chongqing University of Commerce and Industry 5: 111 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Ye, Z. (2016): Analysis of the Value Added of China's Trade with Central and Eastern Europe Based on the Perspective of Global Value Chains. World Economic Research 7: 3648 (in Chinese).

    • Search Google Scholar
    • Export Citation
  • Wang, Z.Wei, S.Yu, X.Zhu, K. (2017): Characterizing Global Value Chains: Production Length and Upstreamness. NBER Working Paper No. 23261.

  • Zhang, R.Jinlong, Z.Jingyuan, Z. (2021): Effects of Free Trade Agreements on Global Value Chain Trade – A Research Perspective of GVC Backward Linkage. Applied Economics 53(44): 51225134.

    • Search Google Scholar
    • Export Citation
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Editor-in-chief: Balázs SZENT-IVÁNYI

Co-Editors:

  • Péter MARTON (Corvinus University, Budapest)
  • István KÓNYA (Corvinus University, Budapest)
  • László SAJTOS (The University of Auckland)
  • Gábor VIRÁG (University of Toronto)

Associate Editors:

  • Tamás BOKOR (Corvinus University, Budapest)
  • Sándor BOZÓKI (Corvinus University Budapest)
  • Bronwyn HOWELL (Victoria University of Wellington)
  • Hintea CALIN (Babeş-Bolyai University)
  • Christian EWERHART (University of Zürich)
  • Clemens PUPPE (Karlsruhe Institute of Technology)
  • Zsolt DARVAS (Bruegel)
  • Szabina FODOR (Corvinus University Budapest)
  • Sándor GALLAI (Corvinus University Budapest)
  • László GULÁCSI (Óbuda University)
  • Dóra GYŐRFFY (Corvinus University Budapest)
  • György HAJNAL (Corvinus University Budapest)
  • Krisztina KOLOS (Corvinus University Budapest)
  • Alexandra KÖVES (Corvinus University Budapest)
  • Lacina LUBOR (Mendel University in Brno)
  • Péter MEDVEGYEV (Corvinus University Budapest)
  • Miroslava RAJČÁNIOVÁ (Slovak University of Agriculture)
  • Ariel MITEV (Corvinus University Budapest)
  • Éva PERPÉK (Corvinus University Budapest)
  • Petrus H. POTGIETER (University of South Africa)
  • Sergei IZMALKOV (MIT Economics)
  • Anita SZŰCS (Corvinus University Budapest)
  • László TRAUTMANN (Corvinus University Budapest)
  • Trenton G. SMITH (University of Otago)
  • György WALTER (Corvinus University Budapest)
  • Zoltán CSEDŐ (Corvinus University Budapest)
  • Zoltán LŐRINCZI (Ministry of Human Capacities)

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Phone: (36 1) 482 5406
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  • Referativnyi Zhurnal

 

2022  
Web of Science  
Total Cites
WoS
not indexed
Journal Impact Factor not indexed
Rank by Impact Factor

not indexed
not indexed

Impact Factor
without
Journal Self Cites
not indexed
5 Year
Impact Factor
not indexed
Journal Citation Indicator not indexed
Rank by Journal Citation Indicator

not indexed
not indexed

Scimago  
Scimago
H-index
15
Scimago
Journal Rank
0.217
Scimago Quartile Score

Business and International Management Q3
Economics, Econometrics and Finance (miscellaneous) Q3
Industrial Relations Q3
Public Administration Q3
Sociology and Political Science Q3
Strategy and Management Q4

Scopus  
Scopus
Cite Score
1.5
Scopus
Cite Score Rank
Sociology and Political Science 602/1415 (57th PCTL)
General Economics, Econometrics and Finance 131/279 (53rd PCTL)
Industrial Relations 31/57 (46th PCTL)
Public Administration 3126/213 (41th PCTL)
Business and International Management 302/436 (30th PCTL)
Strategy and Management 343/473 (27th PCTL)
Scopus
SNIP
0.468

 

2021  
Web of Science  
Total Cites
WoS
not indexed
Journal Impact Factor not indexed
Rank by Impact Factor

not indexed

Impact Factor
without
Journal Self Cites
not indexed
5 Year
Impact Factor
not indexed
Journal Citation Indicator not indexed
Rank by Journal Citation Indicator

not indexed

Scimago  
Scimago
H-index
13
Scimago
Journal Rank
0,196
Scimago Quartile Score Economics, Econometrics and Finance (miscellaneous) (Q3)
Industrial Relations (Q3)
Sociology and Political Science (Q3)
Business and International Management (Q4)
Public Administration (Q4)
Strategy and Management (Q4)
Scopus  
Scopus
Cite Score
1,2
Scopus
CIte Score Rank
Sociology and Political Science 626/1345 (Q2)
General Economics, Econometrics and Finance 131/260 (Q3)
Industrial Relations 35/57 (Q3)
Public Administration 120/190 (Q3)
Business and International Management 292/423 (Q3)
Strategy and Management 340/456 (Q3)
Scopus
SNIP
0,270

2020  
Scimago
H-index
11
Scimago
Journal Rank
0,157
Scimago
Quartile Score
Business and International Management Q4
Economics, Econometrics and Finance (miscellaneous) Q4
Industrial Relations Q4
Public Administration Q4
Sociology and Political Science Q3
Strategy and Management Q4
Scopus
Cite Score
103/117=0,9
Scopus
Cite Score Rank
Business and International Management 305/399 (Q4)
General Economics, Econometrics and Finance 137/243 (Q3)
Industrial Relations 40/54 (Q3)
Public Administration 116/165 (Q3)
Sociology and Political Science 665/1269 (Q3)
Strategy and Management 351/440 (Q4)
Scopus
SNIP
0,171
Scopus
Cites
157
Scopus
Documents
24
Days from submission to acceptance 148
Days from acceptance to publication 50

 

2019  
Scimago
H-index
10
Scimago
Journal Rank
0,228
Scimago
Quartile Score
Business and International Management Q3
Economics, Econometrics and Finance (miscellaneous) Q3
Industrial Relations Q3
Public Administration Q3
Sociology and Political Science Q3
Strategy and Management Q3
Scopus
Cite Score
87/110=0,8
Scopus
Cite Score Rank
Business and International Management 286/394 (Q3)
General Economics, Econometrics and Finance 125/228 (Q3)
Industrial Relations 38/58 (Q3)
Public Administration 114/157 (Q3)
Sociology and Political Science 645/1243 (Q3)
Strategy and Management 330/427 (Q4)
Scopus
SNIP
0,308
Scopus
Cites
132
Scopus
Documents
22

 

Society and Economy
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 900 EUR/article with enough waivers
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Sufficient number of full waiver available. Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access

Society and Economy
Language English
Size B5
Year of
Foundation
1972
Volumes
per Year
1
Issues
per Year
4
Founder Budapesti Corvinus Egyetem
Founder's
Address
H-1093 Budapest, Hungary Fővám tér 8.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1588-9726 (Print)
ISSN 1588-970X (Online)