Does the import diversity of inputs mitigate the negative impact of COVID-19 on global value chains?

Abstract

This study sheds light on the role of the import diversity of inputs and explores the effects of COVID-19 on global value chains (GVCs). Using monthly export data of final machinery products for 35 countries and indicators of diversity with 252 trade partner countries, we investigate the supply-side effects of COVID-19 on GVCs during the period from January to August 2020 and examine how the import diversity of inputs influences such effects. As a result, we find the negative supply-side effects in all three machinery industries, with the greatest ones in the transport equipment industry. In addition, such negative impacts on machinery industries are larger during the trade–fall period from February to May 2020. Furthermore, we demonstrate that the import diversity of inputs had a significant influence in partially mitigating the harmful supply-side effects of COVID-19, particularly during the early period of February–March 2020.

KEYWORDS:

• COVID-19
• Global value chains
• supplier diversification
• gravity

JEL Classifications:

• F15
• F53

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For example, see Tomlin and Wang (2005), Babich, Burnetas, and Ritchken (2007), Wang, Gilland, and Tomlin (2010), Tang and Kouvelis (2011), Mizgier, Wagner, and Jüttner (2015), Ang, Iancu, and Swinney (2017), Chod, Trichakis, and Tsoukalas (2019), and Jain, Girotra, and Netessine (2020).

2 The examples of the recent studies on GVCs include Reddy and Sasidharan (2021) and Thang et al. (2021), which examine the effects of firms’ financial constraints and rules of origin, respectively.

3 Regarding the theoretical analyses, see Acemoglu and Tahbaz-Salehi (2020) and the literature review available in the study.

4 Inoue and Todo (2020), George et al. (2020), and Pichler et al. (2020) provided simulation analyses of the effect of COVID-19 on GVCs. Inoue and Todo (2020) simulated the economic effect of Tokyo’s possible lockdown on production through supply chains in Tokyo as well as other parts of Japan.

5 See https://connect.ihsmarkit.com/gta/home.

6 The reporting countries and their trade partners are listed in Appendix A.

7 See the next section for the definition of final machinery products and parts and components applied in this study.

8 Baldwin and Freeman (2020) summarized the impact of COVID-19 as the following three shocks: “demand disruptions” (due to macroeconomic drops in aggregate demand, wait-and-see purchase delays by consumers, and investment delays by firms), “direct supply disruptions” in the affected countries, and fears of a “supply-chain contagion” in the less affected countries through supply chains. Also see Hayakawa and Mukunoki (2021) for the negative supply chain effects of COVID-19.

9 See Baldwin and Freeman (2020) for value-added shares of direct and indirect inputs from China in each country’s total manufacturing output.

10 For Figure 3, the data on imports from China by 35 reporting countries are used and expressed as an index to January 2019, instead of taking a ratio of the same month of the previous year, considering issues related to the timing of the Chinese New Year holiday. As mentioned above, a possible time lag issue for monthly import data may remain.

11 The largest drop in US imports of machinery parts from China in March 2020 may partially reflect a time lag in import statistics as well as a delay in input imports from China.

12 Ando (2021) presented a detailed investigation of the impact of COVID-19 on Japan’s exports and imports, highlighting the direct and indirect negative supply shocks in February 2020, negative demand shocks, and product-specific positive demand shocks. Positive demand shock products are those related to teleworking, disinfection, and the “stay-at-home” environment due to the nature of COVID-19 restrictions.

13 In this industry, the change for final products has been over one since June, while that for parts and components has not yet reached one. This indicates that positive demand shock products contribute to such an increase in final products, though the negative effects on this industry as a whole still remain.

14 Most of the final products in this industry are “postpone-able” goods. In addition, e-commerce is not very active for such products, unlike some final products in the general and electric machinery industry. The nature of these products may also induce more severe demand shocks in this industry.

15 We thank the reviewer for suggesting these elements.

16 Namely, we examine the composite type of these three elements, rather than each of them separately. We further discuss this issue in Section 4.2.

17 Some specific inputs may be produced by a very limited number of suppliers. Since it is almost impossible to diversify the suppliers of these specific inputs, the disruption of such suppliers causes a global shortage. Obviously, our index based on inputs at the HS six-digit level does not enable us to investigate this specific effect.

18 Input–output (IO) tables are useful for assessing these input values from other chapters. However, industry classifications in the IO table are too rough to examine the input diversity of products. Furthermore, the country coverage in the international IO table tends to be limited and is insufficient for exploring the diversity over countries.

19 Korea and Japan are included in the top 10 export countries (Table 1).

20 Relatively lower diversity does not necessarily indicate fewer trade relationships. For instance, half of the East Asian countries show a larger number of country–product pairs with positive trade than the average. This implies that East Asian countries have production linkages with more countries, although the weight of regional transactions, including domestic procurement, is heavy in this industry. The corresponding figures for the number of trade relationships are available upon request.

21 See Ando and Kimura (2013, 2014) for further insight on the strengthening of production linkages of East Asia as input suppliers with production networks in Europe and North America.

22 See https://data.europa.eu/euodp/en/data/dataset/covid-19-coronavirus-data.

23 As previously described, for China, January and February of both years are omitted due to a lack of data on monthly exports (reported by China) for January and February 2020, separately.

24 Some singleton observations were dropped due to our inclusion of fixed effects.

25 See ACEA (2020).

26 See the Nikkei article: https://www.nikkei.com/article/DGXMZO59273230Z10C20A5000000.

27 See the Daily Automotive News online article: https://www.netdenjd.com/articles/-/234519.

28 The input disturbance was severe for some firms, including unstable imports from affected countries (such as India and the Philippines) due to lockdown policies, delayed imports (from Southeast Asian countries) due to COVID-19, and unstable procurement from domestic suppliers due to workers being infected with COVID-19. See the Nikkei article: https://www.nikkei.com/article/DGXMZO58087210V10C20A4I00000 and the online Daily Automotive News article: https://www.netdenjd.com/articles/-/233746.

29 The results for (II) in Table 3 with the number of COVID-19 deaths for the general and electric machinery industry indicate somewhat different patterns; although the coefficients for two COVID-19 variables have opposite signs with statistical significance in Panel (a), they are insignificant in Panel (b). In addition, the coefficient for the interaction term for (I) in Table 3 is positive but statistically insignificant. More details regarding the implications will be discussed later.

30 Around 60% (over 50%) of the worldwide exports of these parts and components (final products) are from East Asian countries listed in the top 10 in Table 1.

31 As Table 1 shows, half of the worldwide exports are from Germany, Japan, the US, and France.

32 We thank the reviewer for suggesting these assessments.

33 As discussed in Section 3, our measure depends on the three elements (i.e., the numbers of sourcing countries and machinery parts and the distribution of import shares across input parts and sourcing countries). We have investigated the role of the composite type of these elements. Indeed, since these three elements are highly correlated with one another, the estimates suffer from severe multicollinearity if introduced simultaneously, rendering the results unstable in terms of signs. These results are available upon request.

Additional information

Funding

This work was supported by JSPS: [Grant Number 18H03637].