Why You Should Know About Global Value Chains

Abstract

Over the terminal ii decades, world trade and product have go increasingly organized effectually global value chains (GVC). Contempo theoretical work has shown that countries can benefit from participation in GVCs through multiple channels. Nevertheless, piddling is known empirically about the economic importance of supply chains. Nosotros use the Eora MRIO database to compute different measures of GVC participation for 189 countries and illustrate global patterns of supply bondage as well every bit their evolution over time in order to contribute to this topic. Nosotros find that GVC-related merchandise, rather than conventional trade, has a positive impact on income per capita and productivity, however in that location is large heterogeneity and the gains appear more signifcant for upper-heart and high-income countries. We document that "moving up" to more high-tech sectors while participating in major supply chains does accept place just is not universal, suggesting other factors matter. We confirm the findings of the standard gravity literature for GVC trade; highlighting the key part of institutional features such as contract enforcement and the quality of infrastructure as determinants of GVC participation.

I. Introduction¹

Over the last two decades, trade and production accept become increasingly organized around what is commonly referred to as global value chains (GVC) or global supply chains. The advances in information and transportation technologies as well as falling trade barriers accept allowed firms to unbundle product into tasks performed at different locations to take reward of unlike factor costs (Feenstra and Hanson 1997; Grossman and Rossi-Hansberg 2008). Such production fragmentation means that intermediate goods and services cross borders several times along the concatenation, often passing through many countries more than once. These complex global product arrangements have changed the nature of trade (Figure 1).

Effigy i.

Traditional and GVC Merchandise

(Percentage of nominal world Gdp)

Citation: Imf Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations based on Eora database. Traditional trade comprises exports of goods and services that are produced in ane country and absorbed in the destination.

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Figure 1.

Traditional and GVC Trade

(Percent of nominal world GDP)

Citation: International monetary fund Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations based on Eora database. Traditional trade comprises exports of appurtenances and services that are produced in one country and absorbed in the destination.

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Although the welfare consequences of international merchandise accept been largely studied in both the theoretical and empirical literature, effects of participation in GVCs remain less-explored.

In adult economies, GVCs provide access to more competitively priced inputs, higher diversity, and the economies of calibration (Baldwin and Lopez‐Gonzalez, 2013). Meanwhile, for emerging economies GVCs are viewed as a fast track to industrialization. Baldwin (2011) argues that internationally fragmented production allows emerging economies to join existing supply chains instead of building them. With increased composure of appurtenances, joining a supply chain removes the need to gain comparative advantage in a broad range of production stages domestically.

Theoretical literature offers support for these views. Studies have shown that productivity gains associated with offshoring and GVCs tin arise through multiple channels: finer division of labor across countries (Grossman and Rossi-Hansberg 2008), availability of greater input varieties (Halpern, Koren, and Szeidl 2015), increased competition, learning externalities, and technology spillovers (Li and Liu (2014), Kee (2015)). While some of these gains are associated with conventional trade too, welfare gains tin can theoretically be larger if i uses a multiple-sector framework and considers the input-output linkages (eastward.1000., Caliendo and Parro 2015, Ossa 2015).

Empirical investigations of the aforementioned effects of GVC participation have been express, but this area of research is expanding with increasing availability of data. Earlier empirical work on GVCs documented the considerable rise in fragmentation of production. Seminal works by Hummels, Ishii, and Yi (2001) and Hummels, Rapoport and Yi (1998) show that GVCs are responsible for a large share of trade growth in world trade from 1970–1990s. Works by Johnson and Noguera (2012) and Baldwin and Lopez-Gonzales (2013) prove that this growth accelerated further in 2000–09. The pace of expansion of supply chains slowed in the backwash of global financial crunch, contributing to an important part of the trade slowdown in this menstruation (IMF, 2016a). A key step in the analysis of GVCs was put forward by seminal works of Koopman and others (2014) and Wang and others (2013) who proposed methodologies to break-down gross merchandise flows to origins of value-added. Since then such data and methodology have become available to researchers through several initiatives. These include the Merchandise in Value-Added Statistics (covering 63 countries), the World Input Output Database (43 countries), and near recently the Eora Multi-Region Input-Output (MRIO) database (henceforth referred to equally Eora (Lenzen and others, 2013) for 189 countries. With availability of these data, the focus is shifting to analyzing the impacts of GVCs on economical outcomes (Constantinescu and others, 2017; World Bank 2016, and 2017).

Covering countries across different income levels, the EORA database provides an opportunity for a more comprehensive study of the impact of GVCs on income growth and convergence. Although the narrative of convergence and growth through supply chains has been around for a while, especially for China and some Asian countries (Figure 2), a systematic study of such links has been incomplete due to data limitations. As will be discussed in section IV, then far uncovering a causal relation has been challenging given the smaller number of countries in other databases.

This newspaper contributes to the growing literature on the economic consequences of countries' participation in GVCs, by constructing indicators of GVC participation and position for 180 economies at the state, sectoral, and bilateral levels.

Our main findings are:

• Participation in GVCs has a positive touch on income per capita, likewise equally its components, investment and productivity.

• Chiefly, nosotros observe that these gains are related to GVC trade and non to conventional trade. The results appear robust to endogeneity and reverse causality.

• The gains from GVC participation, however, are non automatic. There is large caste of heterogeneity. The upper-middle and high-income countries appear to exist benefiting from such participation, while we find less robust effects for depression and lower-middle income countries.

• The relationship between upstreamness in GVCs and economic development is not straightforward. While financial and business services tend to be upstream and loftier in value-added, the link is less clear in manufacturing.

• We document that "moving upwards" to more loftier-tech sectors as a result of participation in major supply chains does take place merely is not universal, suggesting that gains are probable conditional on other factors.

• Nosotros also confirm the findings of the standard gravity literature for GVC trade; highlighting the key role of institutional features such every bit contract enforcement and the quality of infrastructure every bit determinants of GVC participation.

To our knowledge, this newspaper is one of few papers focusing on this angle. Several studies provide evidence that GVC participation such as the use of higher foreign value-added in exports is associated with the growth of domestic value-added in the participating sectors (Rahman and Zhao, 2013; Kummritz, 2016; World Bank, 2016). Nonetheless, information technology remains a moot question what the broader macroeconomic impacts are on income and whether they are economically meaning. Our results are in line with previous findings and farther shed light on the macroeconomic angles.

The rest of the paper is organized as follows: section Ii briefly describes the data and the methodology employed in computing GVC participation measures. Section III nowadays stylized facts. Department IV explores the empirical relationship between GVC participation and income, equally well as its components. Department Five explores the determinants of bilateral GVC participation and Department 6 concludes.

Two. Data

The cadre dataset used for this report is the Eora Multi-Regional Input-Output (MRIO) database, which provides information on input-output linkages between 189 countries and 26 sectors (including services) over the menstruation 1990–2013 (see Annex Tabular array one for listing of sectors). The input-output linkages information is used to compute several measures of GVC participation.

We adopt a methodology developed by Koopman and others (2011) and described in Aslam and others (2017) to decompose gross exports to value-added components based on the location of value-added creation and its purpose. As illustrated in Figure 3, gross exports are decomposed into ii broad components: the strange value-added (FVA) embedded in gross exports of a land (astern linkages) and the domestic value-added in exports (DVA). The latter part is farther decomposed into exports that are absorbed in the destination country and those that are further used equally intermediate inputs for exports to third countries (forrad linkages) or returned home.

Based on this decomposition, the two measures of GVC participation (vertical specialization) are defined every bit: Backward linkages – the share of foreign value-added in total exports of a state; Forward linkages -s the domestic value-added embodied in intermediate exports that are further re-exported to tertiary countries, expressed as a ratio of gross exports.

While astern linkages, also known every bit foreign value-added exports is a common measure of GVC integration, the forward linkages measure out is less widely used and known. Equally we will discuss in department III, information technology is important to utilise both measures to understand the nature of vertical specialization. For example, as volition be seen in Secttion III, frontwards linkages are more than useful in understanding GVC participation of the service sector. Throughout the paper, GVC participation is defined every bit the sum of frontward and backward linkages, unless otherwise stated.

In add-on to GVC participation measures, we also calculate indices that measure countries' and sectors' positions in the value chains (Koopman and others, 2014; Antras and others, 2012). At the industry level, the Upstreamness alphabetize reflects the number of production stages, that the output of that industry has to go through before it reaches the final consumers. Intuitively, upstream industries contribute more value-added to other countries/sectors than others contribute to them, or in other words, their value-added trickles down and travels down to other sectors earlier reaching the final consumers. On the other mitt, the Downsteamness index reflects the number of product stages embodied in a good produced within a sector. Every bit a result, the larger this indicator is, the more complex the production process of the terminal product is. Consequently, Downstreamness tin can be considered a proxy for the complication of the production engineering for a specific final product. Of course, ii countries can take identical values of the GVC position index in a sector while having very different degrees of participation in GVCs. Therefore, the position alphabetize should exist used in conjunction with participation indices, which summarize the importance of GVCs in the economy.

In the next section, we provide some stylized facts regarding the participation and position of countries and sectors in GVCs.

Iii. Stylized Facts

Figure iv illustrates the ascent trend in GVC participation— measured as the sum of the then-called forrad and backward linkages in vertical specialization. Betwixt 2000 and 2013, the share of exports that were involved in GVC trade increased from about threescore to seventy percent in Europe. Over the same period, this ratio increased on average by five percentage points in Asian and Western Hemisphere countries. Even though, at that place is pregnant heterogeneity beyond and inside regions, Europe is highly integrated through GVCs, reflecting the European Union'southward (EU) status as a single market and gratis trade zone. In add-on, the foreign product linkages of the Euro Area are comparable in magnitude with those of other important trade blocks, including Communist china, with an increasing participation of services in the value chains (Amador et al., 2015).

Figure four.

GVC Participation Index

(Percent of exports, sum of forwrd and astern linkages)

Citation: Imf Working Papers 2019, 018; x.5089/9781484392928.001.A001

Sources: EORA Database; and IMF staff calculations. Note: GVC = global value chain; WH = western hemisphere, comprising the Usa, Canada, Mexico, Argentina, Brazil, Republic of chile, Colombia, Peru, Venezuela. Dots represent countries, and the box reflects the 25–75^th percentiles.

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Figure 4.

GVC Participation Alphabetize

(Percentage of exports, sum of forwrd and backward linkages)

Citation: International monetary fund Working Papers 2019, 018; x.5089/9781484392928.001.A001

Sources: EORA Database; and Imf staff calculations. Notation: GVC = global value chain; WH = western hemisphere, comprising the US, Canada, Mexico, Argentine republic, Brazil, Chile, Colombia, Peru, Venezuela. Dots stand for countries, and the box reflects the 25–75^th percentiles.

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Figures 5 and six map the astern and forward linkages measures in 2013. Darker greens reverberate higher values of GVC measures. A couple of points are worth noting. In Figure 5, Europe equally a region stands out equally highly integrated and so does southeast Asia. Small open countries tend to have more backward linkages. In Effigy 6, the forward linkages paint a somewhat different picture. Commodity exporters such as Russia and countries in the Middle East and Africa exhibit high values of forward linkages measures, reflecting the fact that exports of commodities from these countries are inputs in other countries' production and travel along GVCs. Countries with high forrad linkages tend to be upstream in GVCs. However, countries with high forward linkages are not limited to article exporters. The United states exhibits high values in Effigy half-dozen due to large exports of business and financial services that tend to be used as intermediate inputs in GVCs.

From the perspective of economical sectors, the rise of GVC merchandise in services and the then-called servicification of manufacturing exports has been an important tendency. The share of services exports in full globe exports increased by 5 percentage points over 2000–13 (Figure 7). More than chiefly, when measured in value-added terms, the share of services exports in earth exports is well-nigh twice as large every bit what official statistics on gross exports show (Effigy 7). The deviation between the two concepts reflects the fact that a part of manufacturing exports is value-added by the services sector. This is in line with the findings of IMF (2018) on the rise of servicification of manufacturing.

The nature of GVC participation by services and manufacturing sectors is markedly unlike, with services exhibiting more forwards linkages. Table 1 provides a breakup of world exports to major manufacturing and services sectors, by gross and value-added terms. Services, including business and financial services and wholesale trade, accept very high forrard linkages reflecting that they are intermediate inputs in their export destinations, and have limited backward linkages reflecting that the product of business organization and financial services uses limited foreign inputs. Similarly, they tend to have higher values in the upstream index (altitude to final consumer) than the downstream alphabetize (steps embodied in production). On the other hand, the largest manufacturing sectors tend to have sizable strange inputs (backward linkages). They tend to take a higher downstream alphabetize than upstream alphabetize (Tabular array one). It'southward worth noting that the level of upstream index is not significantly different between manufacturing and services.

Table 1.

GVC Participation and Position by Sector, 2013

Sources: Authors' calculations.

^1/ Backward linkages refer to FVA in gross exports. Forward linkages refer to parts of DVA exports that are further re-exported. Both as share of gross exports.

^2/ Downstream alphabetize refers to number of previous stages embodied in the exports of detail land or sector. Upstream index refers to number of additional steps to last consumer.

Table one.

GVC Participation and Position by Sector, 2013

	Share in World Exports		GVC Participation Index ane/		Position Index ii/
	Value added concept	Gross concept	Backward linkage	Forwards linkage	Downstream Alphabetize	Upstream Index
Manufacturing
Electrical and Machinery	37.seven	46.vii	32	15	2.8	2.four
Petroleum and Chemical Products	15.0	fifteen.three	33	25	2.six	3.1
Ship Equipment	5.2	8.i	37	10	3.0	2.0
Metallic products	v.ane	4.three	29	35	2.9	3.6
Textiles and Wearing Apparel	three.eight	4.5	27	11	2.8	ii.ane
Food and Beverages	1.1	ane.4	23	ix	two.6	one.8
Forest and Paper	0.nine	0.vii	26	30	two.5	3.0
Other Manufacturing	0.4	0.half dozen	28	7	ii.8	i.8
Services
Financial and Business organization Services	20.7	five.7	8	91	1.7	2.four
Transport	iii.0	one.vi	nineteen	38	2.2	two.six
Wholesale Trade	1.7	0.6	10	88	one.eight	2.3
Retail Trade	0.6	0.2	12	76	one.9	two.2
Post and Telecommunications	0.three	0.1	14	63	1.9	2.4
Hotels and Restraurants	0.2	0.1	13	23	2.i	1.vi

Sources: Authors' calculations.

^i/ Backward linkages refer to FVA in gross exports. Forrad linkages refer to parts of DVA exports that are further re-exported. Both as share of gross exports.

^two/ Downstream index refers to number of previous stages embodied in the exports of particular country or sector. Upstream index refers to number of additional steps to final consumer.

Global supply chains are organized differently across countries and sectors. Breaking down total world exports to value-added created by country-sector pairs, Table two illustrates the top land-sector supply bondage. Several interesting observations emerge. While the largest supply chains, from the perspective of gross exports, are China's and Frg's Electrical and Machinery sectors, the fiscal and business organization services of the Usa and Germany are the top value creating sectors. This conforms with studies at the production level that, for example, provide a breakdown of exports of iPhones by China to value-added created in Red china vs that attributed to design, inquiry, and marketing in the United states of america. Information technology is also worth noting that GVCs of the same sector seem to exist organized differently across countries. For example, the Electric and Machinery sectors in China and Germany seem to have like GVC participation indices. However, the position of the indices for Communist china's Electric and Machinery sector are larger, suggesting longer supply chains as evidenced in longer distance to the consumer (upstream index) and more steps embodied (downstream index). The auto supply chains (transport equipment) of Federal republic of germany and the US also take unlike characteristics, with Germany's showing higher GVC content and more steps involved.

Table 2.

Largest Global Supply Chains, 2013

Sources: Authors' calculations.

^ane/ Astern linkages refer to FVA in gross exports. Forward linkages refer to parts of DVA exports that are further re-exported. Both every bit share of gross exports.

^2/ Downstream index refers to number of previous stages embodied in the exports of item country or sector. Upstream alphabetize refers to number of additional steps to concluding consumer.

Table two.

Largest Global Supply Chains, 2013

		Share in World Exports		GVC Participation Index 1/		Position Index ii/
		Value added concept	Gross concept	Backward linkage	Forward linkage	Downstream Alphabetize	Upstream Index
State	Sector
CHN	Electrical and Machinery	1.4	3.1	24	12	3.viii	two.9
DEU	Electrical and Machinery	1.ix	2.nine	26	xvi	two.5	2.iv
JPN	Electrical and Machinery	ane.4	1.9	17	19	ii.6	2.4
USA	Electric and Machinery	1.2	1.9	eighteen	nineteen	2.5	2.2
DEU	Petroleum and Chemical Products	i.2	1.viii	33	26	2.7	3.iv
DEU	Send Equipment	0.eight	i.7	34	x	3.2	ii.2
USA	Financial and Business Activities	three.nine	ane.7	three	66	i.half-dozen	2.2
CHN	Textiles and Wearing Clothes	ane.0	1.six	14	8	three.4	2.7
United states of america	Petroleum and Chemic Products	0.9	1.4	24	25	two.5	2.seven
ITA	Electrical and Machinery	0.8	1.3	28	13	2.4	2.0
FRA	Electrical and Machinery	0.7	1.i	27	17	2.iv	2.3
CHN	Petroleum and Chemical Products	one.2	1.ane	16	32	three.3	3.eight
GBR	Electrical and Machinery	0.half-dozen	i.0	33	16	ii.5	two.2
FRA	Petroleum and Chemic Products	0.vi	i.0	36	24	2.5	2.nine
DEU	Metal Products	0.9	0.ix	28	42	ii.8	3.viii
KOR	Electric and Machinery	0.5	0.nine	45	thirteen	3.7	3.2
JPN	Transport Equipment	0.4	0.eight	sixteen	5	3.1	2.ane
DEU	Fiscal and Concern Activities	two.half-dozen	0.viii	7	98	1.7	2.vi
CHE	Electrical and Machinery	0.6	0.eight	25	xix	2.ii	2.ii
USA	Transport Equipment	0.three	0.8	22	eleven	2.8	1.4

Sources: Authors' calculations.

^1/ Backward linkages refer to FVA in gross exports. Forward linkages refer to parts of DVA exports that are farther re-exported. Both equally share of gross exports.

^2/ Downstream index refers to number of previous stages embodied in the exports of particular state or sector. Upstream alphabetize refers to number of boosted steps to final consumer.

Given the large heterogeneity across countries and sectors in GVC participation and position, the next section formally explores the role of GVCs in raising income and productivity.

IV. GVC Participation and Economical Outcomes

GVC participation matters for economic development. Specifically, the ability of countries to prosper depends on their participation in the global economic system, i.e. their role in GVCs (Gereffi and Lee, 2012). Furthermore, the merchandise, investment, and knowledge flows that underpin GVCs, provide mechanisms for rapid learning, innovation, and industrial upgrading (Cattaneo, Gereffi, Staritz 2010). In addition, GVC participation tin provide local firms with better access to data, open new markets, and create opportunities for fast technological learning and skill acquisition. Montalbano and others (2018) confirm the positive relationship between participation in international activities and firm functioning, where both the participation and position inside GVCs matter. Similarly, a World Banking concern (2017) study shows that complex GVC-related cross-border production-sharing activities were the virtually of import forcefulness driving globalization and the growth of global Gdp during 1995–2008. A written report by Kummritz (2016) illustrates that an increase in GVC participation leads to higher domestic value added simply the effect is only significant for middle- and loftier-income countries. The results also highlight that both upstream suppliers of intermediates and downstream users of foreign inputs do good from product networks equally. At the aforementioned time, results regarding the human relationship between GVC participation and investment accept been mixed. Liu (2015) finds that for many emerging economies, GVC participation attracts more investment. However, while involvement in GVCs may contribute to alluring investment, the relationship is not clear cut as investment crucially depends on broader policy and institutional framework (OECD, WTO, UNCTAD, 2013).

GVC participation has also been shown in the literature to have a positive effect on productivity. Specifically, productivity tin can be enhanced by the relocation of some of the parts of production within a GVC through various channels (Amiti and Wei, 2009; Schwörer, 2013). The basic argument is related to a house's relocation of the least efficient product stages to concentrate on more productive cadre activities. Furthermore, firms take advantage of cheaper, better quality inputs through offshoring; it may too provoke efficiency upgrading through the reorganization of a firm's action or induce applied science transfer from strange suppliers. Finally, every bit a toll saving phenomenon, offshoring should increase profits which in turn can be transferred into innovation activities. Criscuolo and Timmis (2017) point that participating in GVCs can stimulate productivity growth through the potential for house specialization in core tasks, access to imported inputs, cognition spillovers from foreign firms, and pro-competitive effects of foreign competition. By specializing in those cadre tasks, firms can reap productivity gains (Grossman and Rossi-Hansberg, 2008). Emerging evidence is too revealing how the liberalization of service markets, particularly the entry of new foreign service providers, tin lead to substantial productivity gains in downstream manufacturing firms (Arnold and others, 2011 and 2016).

Our empirical report of the outcome of GVC participation on countries' economic performance is motivated by facts illustrated earlier in Figure 2. Specifically, measures of GVC participation are positively correlated with income per capita. Moreover, changes in GVC participation are associated with income convergence (Figure 2, panel ii). Although instructive, these are unproblematic correlations that exercise not detect the channels through which participation in global value chains tin can impact countries' income per capita.

In fact, the theoretical literature suggests that these positive correlations could arise for several reasons, including productivity effects of GVC and investment boosting. Figure 8 is suggestive of this last machinery – it shows that bilateral GVC participation measures and bilateral FDI volumes are positively related. However, since GVC participation could as well encourage domestic investment, we volition farther study its effect on total investment.

Figure 8.

GVC and Foreign Directly Investment

Citation: IMF Working Papers 2019, 018; x.5089/9781484392928.001.A001

Source: Imf Balance of Payment Statistics and Authors' calculations. Red dots stand for European countries. FVA and FDI represent foreign value-added in exports and Foreign direct investment. Information refers to year 2013 and is in 1000s of electric current USD.

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Figure 8.

GVC and Foreign Directly Investment

Commendation: International monetary fund Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Source: IMF Balance of Payment Statistics and Authors' calculations. Carmine dots represent European countries. FVA and FDI represent strange value-added in exports and Foreign direct investment. Data refers to year 2013 and is in 1000s of current USD.

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In this department we provide a more formal econometric analysis of the relationship between GVC participation and income per capita, likewise every bit the main factors that contribute to the formation of Gross domestic product per capita – productivity, investment, and human capital.

A. Theoretical Framework

The regression framework is motivated in a simple theoretical setting. Following Frankel and Romer (1999), the methodology relies on a product function and its decomposition. For a country i, gross output Y_i can exist expressed in a Cobb-Douglas production function with equation (1), where V_i is domestic value-added and X_i is foreign value-added:

$\begin{array}{cc}{Y}_i=V_i^{1-\alpha }{X}_i^{\alpha }& \left(1\right)\end{array}$

At the aforementioned time, country i'south domestic value-added (Gross domestic product) is produced using majuscule, labor, and human capital. This can be expressed with equation (two) where Thou_i and Northward_i denote a land's endowment in capital and labor, A_i is labor augmenting productivity, S_i represents the workers' average years of schooling and ΦP(S_i) is a piecewise linear function that transforms years of schooling into human upper-case letter.

$\begin{array}{cc}{V}_i=K_i^{\beta }{\left(e^{\mathrm{\Phi }\left(S_i\right)}{A}_i{\mathrm{Northward}}_i\right)}^{\mathrm{one}-\beta }& \left(\mathrm{two}\right)\end{array}$

Following Frankel and Romer (1999), equation (2) can be rewritten equally:

$\begin{array}{cc}{V}_i={\left(\frac{K_i}{{\mathrm{Five}}_i}\right)}^{\frac{{\alpha }_i}{1-{\alpha }_i}}{e}^{\mathrm{\Phi }\left({\mathrm{Southward}}_i\right)}{A}_i{N}_i& \left(3\right)\end{array}$

Dividing both sides past N_i and taking logs, presents the following decomposition of country i'southward GDP per capita:

$\begin{array}{cc}\log \frac{{\mathrm{Five}}_i}{{\mathrm{Northward}}_i}=\frac{{\alpha }_i}{\mathrm{i}-{\alpha }_i}\log \frac{{\mathrm{One\; thousand}}_i}{V_i}\mathrm{\Phi }\left(S_i\right)+\log A_i& \left(4\right)\end{array}$

To gauge empirically the effect of GVC participation on income per capita, the reduced class equation (5) is used, where share_i(t-1) represents the range of lagged merchandise and GVC participation related variables:

$\begin{array}{cc}\log {\left(\frac{V}{N}\right)}_{it}=\alpha +{\mathrm{\Sigma }}_{i=1}^{\mathrm{due\; north}}{\beta }_i{share}_{i(t-1)}+\gamma X_{it}+{\eta }_t+{\eta }_{it}& \left(\mathrm{five}\right)\end{array}$

We written report separately the effect of final goods merchandise and intermediate goods trade too as GVC-related intermediate appurtenances trade and trade in intermediate goods that are absorbed in the land and are therefore non related to GVC. We utilise lagged trade variables to address endogeneity associated with reverse causality. In addition, we command for country characteristics such as population and expanse, per Frankel and Romer (1999), to reflect the outcome of internal trade (as opposed to international trade) on a country'due south income per capita.

Furthermore, we report the channels through which GVC participation impacts welfare. In social club to exercise so, we backslide each of the contributing components of economic growth on the same range of lagged merchandise and GVC participation measures. For those specifications, nosotros use the human majuscule index developed by Barro and Lee (2010) and we calculate productivity as a remainder.

B. Empirical Evidence

Our results ostend that GVC participation is related positively to income per capita. Specifically, we notice that it is mostly merchandise in intermediate goods as well as the share of GVC related merchandise flows, rather than conventional trade, that contribute to a country's income per capita (see columns 1 and 2 respectively in Table ii). Investment is likewise affected positively by GVC-related trade flows. Human capital and productivity mirror this relationship.

Table iii below summarizes our principal findings. Column (1) reports the results from a regression exploring the relationship between (lagged) shares of final and intermediate goods merchandise in a country's Gdp and income per capita. It suggests that it is generally trade in intermediate goods that contributes to a land's income per capita. In column (two) we distinguish between GVC-related and non-GVC-related merchandise. GVC-related merchandise is divers as imports and exports that either embed foreign value-added or are exports of domestic value-added that are re-exported in other countries' exports. GVC-non-related trade is, in plough, defined as imports and exports that get directly absorbed in other countries. The OLS results suggest that it is mostly the share of GVC-related trade flows in a state's GDP that is positively related to income per capita.

In columns (3) – (5), we written report the channels through which GVC participation and merchandise could touch on income per capita. Interestingly, our results suggest that although the GVC-related trade share positively affects investment, the non-GVC-related trade share has a negative impact on information technology. This result could exist explained by the competition effect of international merchandise: once a country opens upwards to trade, it faces tougher competition from abroad, which makes some (less productive) firms leave the market place, which might cause investment to go downwardly.

Nevertheless, further exploration of this result is needed. Columns (4) and (v) show that the GVC-related trade share also positively affects human capital and productivity, measured as a residual in the income decomposition equation. In column (half-dozen), we find that the results of column (one) can't be replicated if we restrict the sample to fifty countries typically available in other databases of value-added, highlighting the importance of the larger Eora database for studying GVCs.

In columns (vii) and (8) we explore if income gains from GVC trade depend on a country's income level or its position in GVCs. Column (seven) replicates the regression in column (1) but instead we interact the variable GVC-trade with dummy variables for iv categories of income level:depression, low-middle, high-middle, and loftier income as defined by the World Bank. GVC-trade appears to positively impact income in high-middle and high-income countries, but the impact for low income and low-middle income countries is either insignificant or significant but not robust to changes in the specification. This finding is consequent with the thinking in Rodrik (2018) that GVCs and new technologies showroom features (such as being biased towards skills and other capabilities) that limit the upside and may even undermine developing countries' economic performance. It is also consistent with the policy literature that cautions that gains from GVCs are not automatic and depend on other supporting factors (OECD, WTO, UNCTAD, 2013).

In column (8), we include measures of the position in GVCs, only practise not discover whatever significant effects for either downstream or upstream indices either individually or combined. For the regression in cavalcade (8) we exclude commodity exporter countries which tend to have higher upstream position to ameliorate capture the idea of upstreamness related to services (design, R&D, marketing) rather than commodities (including those countries leads to coefficient of upstream index being negative and pregnant).

In terms of economic significance of the findings, an increase in the share of GVC merchandise in Gdp by 10 percentage points (from median country in distribution to 75 percentile) would represent an increment in income levels by 15 to 30 percent (based on coefficients in columns 2 and 7 of Table three), representing an economic meaningful impact.

Table 3.

GVC Participation and Income per Capita

Amassed robust standard errors in parentheses; Country and year fixed effects are included. *** , ** , and * denotes significance at 1, 5, and 10 pct. In column (ix), the instrument for share of GVC-trade in Gdp is the average of the value-added originating from Frg, Japan, and the United States that is embodies in the exports of three countries of most similar income level to the country in question. F-statistics for the weakness of the instrument exceed the Stock-Yogo (2002) disquisitional values. A similar exercise when IV is based on 3 neighboring countries to the state in question is also conducted. Results are like to column (9).

Table iii.

GVC Participation and Income per Capita

	(ane) $Log\left(\frac{Y}{\mathrm{Due\; north}}\right)$	(2) $Lom\left(\frac{Y}{\mathrm{Due\; north}}\right)$	(3) $Log\left(\frac{I}{\mathrm{Northward}}\right)$	(4) Human capital	(five) Productivity	(6) Small Sample $Lo\mathrm{chiliad}\left(\frac{Y}{N}\right)$	(7) Income class $Log\left(\frac{Y}{\mathrm{North}}\right)$	(8) Upstream $Lo\mathrm{grand}\left(\frac{Y}{\mathrm{Northward}}\right)$	(nine) IV $Log\left(\frac{Y}{N}\right)$
Share of final trade in GDP	0.143 (0.728)
Share of Intermed. trade in Gross domestic product	1.610*** (0.339)
log(population)	-0.041 (0.068)	-0.060 (0.069)	-0.007 (0.020)	-0.024 (0.043)	-0.059 (0.051)	0.019 (0.052)	-108 (0.58)	-0.069 (0.697)	-0.055 (0.074)
log(area)	-0.012 (0.061)	-0.013 (0.060)	0.007 (0.013)	0.028 (0.036)	-0.030 (0.047)	0.043 (0.l)	0.0145 (0.064)	-0.0130 (0.065)	-0.016 (0.077)
Share of regular trade in Gdp		0.227 (0.458)	-0.07*** (0.002)	0.402 (0.302)	-0.351 (0.489)	.617 (.531)	-0.0383 (0.387)	0.301 (0.549)	0.520 (0.738)
Share of GVC-trade in Gross domestic product		two.738** (1.148)	0.367*** (0.103)	1.366* (0.750)	1.869* (1.107)	-.409 (0.990)		2.080** (one.030)	2.011** (1.011)
GVC-trade*(Low Income)							-0.947 (0.3875)
GVC-trade*(Low Eye Income)							1.413* (0.915)
GVC-merchandise*(High Center Income)							ii.143** (0.855)
GVC-merchandise*(High Income)							2.848*** (0.948)
Upstream Index								-0.370 (0.2561)
Downstream Alphabetize								0.102 (0.229)
Constant	9.459*	9.674***	two.943***	1.562***	half dozen.573***	9.939***	10.160***	9.758***	9.674***
Observations	3,049	3,049	3,045	2,777	ii,625	970	2,770	1,165	2,320
R-squared	0.172	0.183	0.042	0.261	0.072	0.170	0.160	0.275	0.132

Clustered robust standard errors in parentheses; Land and yr stock-still effects are included. *** , ** , and * denotes significance at 1, 5, and 10 percent. In column (nine), the instrument for share of GVC-merchandise in GDP is the average of the value-added originating from Germany, Nippon, and the United States that is embodies in the exports of iii countries of most similar income level to the land in question. F-statistics for the weakness of the instrument exceed the Stock-Yogo (2002) critical values. A similar practice when IV is based on three neighboring countries to the country in question is likewise conducted. Results are like to column (9).

To ensure that the results are not due to endogeneity or reverse causality, we likewise use an Instrumental Variable arroyo (IV). The concerns for endogeneity ascend as GVC participation itself can exist driven by income levels or its correlates such as meliorate institutions and quality of infrastructure, for example. We adopt an IV arroyo in the spirit of Baldwin and Lopez-Gonzalez (2013), Autor, Dorn and Hanson (2013) and used in Constantinescu and others (2017). We construct an instrument to strip out parts of GVC participation that are driven past the overall income level and its correlates such as infrastructure quality and business environment. In particular, for each country c and year t, the instrument is computed as the average strange value added from the United States, Japan and Frg embodied in exports of industry s of iii countries in the sample that are closest in income level or geography to country c. This identification strategy is like to the approach used in the seminal work of Autor, Dorn and Hanson. (2013) who instrument the growth of Us imports of Chinese goods with the penetration of Chinese goods in other high-income markets. The results of the IV approach, reported in Cavalcade (ix) are broadly like in terms of significance and magnitude.

Does GVC Participation Atomic number 82 to Moving up Value Chains?

Given that GVC trade is shown to lead to higher income and productivity gains, a natural question is whether this proceeds takes identify through higher productivity gains within sectors of a country or through a change in the sectoral composition of the economy? While both could exist at play, due to the lack of employment information at the sectoral level, we are unable to test whether productivity at the sector level increases with GVC participation. The 2nd channel, i.due east. a shift in the sectoral composition, is particularly interesting, as frequently in the policy arena at that place is a business that GVC participation for low and eye-income countries may remain limited to "low wage" sectors which are oft referred to as downstream sectors (Kummritz (2016) and Helpman et al. (2012)).

Here, we briefly explore how GVC participation relates to the loosely defined concept of "moving upwardly value chains."

First, it is useful to note that "moving up", if understood as moving to upstream sectors, is not necessarily a characteristic of higher income countries. As shown in Table ii, and illustrated in Figure 8 below, there is no potent link between countries' income levels and their position in GVCs. Loftier income countries can participate in diverse stages of product, especially in manufacturing (Figure 8, console 2). As such, the position index doesn't appear to be a relevant indicator to gauge the "moving up" question.

Figure 9.

Position in GVCs and Income Level

Citation: International monetary fund Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Source: Authors' calculations of GVC position alphabetize at country-sector level; and Globe Economic Outlook.

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Effigy 9.

Position in GVCs and Income Level

Citation: Imf Working Papers 2019, 018; ten.5089/9781484392928.001.A001

Source: Authors' calculations of GVC position alphabetize at country-sector level; and Earth Economic Outlook.

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A more than useful indicator to explore the "moving upwardly" concern, is to examine how the share of loftier-tech sectors in value-added exports of a state has inverse over time. Figure 10, panel ane shows that the share of labor-intensive manufacturing in value-added exports has decreased over time for many countries in Asia and Latin America. This conforms with the narrative of many Asian counties starting off with GVC trade in labor intensive sectors initially and and then expanding to other sectors. For European countries, the labor-intensive share in full manufacturing of GVC exports has been relatively stable over time, closer to the 45-degree line in Effigy 10, panel 1. For many countries, there has been a rise in the share of services exports in total value-added exports (Figure x, console ii), well-nigh drastically evidenced in the U.s.a., Japan, Germany, and China, while the change in the rest of the countries has been more than modest.

Using bilateral value-added export data, we likewise examine how the participation in any of the major global supply chains (listed in Table 3) has affected the sectoral composition of a participant country. For example, consider Federal republic of germany's auto supply chain. We breakdown the FVA in Germany's automobile exports to value-added by participant country and sectors. Figure 11, panel one shows the contribution of dissimilar low and high-tech manufacturing and services to Germany's auto supply concatenation in 2013. For each state contributing to this supply chain, we calculate the ratio of hi(depression) tech services (manufacturing) in its contribution and normalize information technology by the value of that ratio in yr 2000. The results for all participant countries are illustrated in Figure 11, panel 2. On average, the ratios are amassed around ane, reflecting that the relative importance of each sector has on average remained the same over time. Nonetheless, there is big heterogeneity in each category. For instance, China'due south and Denmark'south contribution to the German motorcar supply concatenation bear witness a shift towards more than loftier-tech services. Regarding the manufacturing sector, Russia'south contribution to the German auto supply chain became more intensive in depression-tech manufacturing (due to mining and quarrying sector). For the Czech republic, Hungary, Poland, and Slovak Republic the ratios have remained shut to 1, reflecting broadly similar sectoral composition over time. For Romania, there has been a shift away from low-tech to more high-tech manufacturing.

Figure ten.

Does Sectoral Pattern of Value-Added Exports Change Over Time?

Citation: IMF Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations. Labor intensive manufacturing comprise Textile and Wearing Apparel, Wood and Paper, Mining and Quarrying, and Food and Beverages.

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Effigy 10.

Does Sectoral Pattern of Value-Added Exports Change Over Time?

Citation: IMF Working Papers 2019, 018; x.5089/9781484392928.001.A001

Sources: Authors' calculations. Labor intensive manufacturing comprise Textile and Wearing Apparel, Wood and Paper, Mining and Quarrying, and Food and Beverages.

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Figure 11.

Does Exposure to Major Supply Bondage Atomic number 82 to College-Tech Exports?

Citation: International monetary fund Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations. Depression, medium and high-tech sectors are divers based on OCED (2011) past matching Eora sectors to similar SITC sectors. See Annex Table one for listing of sectors in each category. "Other" in pie chart represent sectors for which a clear technology intensity was non defined. On the right nautical chart, dots represent countries and the box the 25–75th percentile range of distribution.

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Effigy 11.

Does Exposure to Major Supply Bondage Lead to College-Tech Exports?

Citation: Imf Working Papers 2019, 018; x.5089/9781484392928.001.A001

Sources: Authors' calculations. Low, medium and high-tech sectors are divers based on OCED (2011) past matching Eora sectors to similar SITC sectors. Come across Addendum Tabular array ane for list of sectors in each category. "Other" in pie chart represent sectors for which a clear technology intensity was not divers. On the right nautical chart, dots stand for countries and the box the 25–75th percentile range of distribution.

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A similar assay for other major supply chains is summarized in Annex Effigy 1.

Overall, information technology appears that "moving up" the value-chain in the form of a sectoral shift to services or more high-tech manufacturing has taken place, however in that location is big heterogeneity beyond countries. This shift is more modest in European countries and is starker in some Asian countries. This finding, nonetheless, should exist treated with some caution as shifts to high tech sectors could have also taken place within much narrower sub-sectors that are not visible through the lens of 26 sectoral limerick in this study. Farther research using more than granular data could provide more than insights.

With this, we shift our focus to the final assay of the newspaper, on determinants of GVC participation.

V. Determinants of Bilateral GVC Participation

The factors determining a country'southward participation in a global supply concatenation are of import from a policy making perspective. The assay from the previous section suggests that countries with higher GVC participation have higher income per capita besides equally investment, human being capital, and productivity. However, information technology is also important to understand how countries can increase their participation in global value chains. For example, Kowalski and others (2015) place geography, size of the market, and level of development equally the fundamental determinants of GVC participation. Trade and investment policy reforms as well as improvements of logistics and customs, intellectual property protection, infrastructure and institutions tin also play an active function in determining GVC participation^two. This section investigates what determines a country'southward participation in a global supply chain.

A. Empirical Strategy

Nosotros rely on the structural gravity equation which can exist written as follows:

$\begin{array}{cc}\log \left({F\mathrm{Five}A}_{ijt}\right)={\beta \mathrm{Ten}}_{ijt}+{\eta }_{it}+{\eta }_{jt}+{ϵ}_{ijt}& \left(\mathrm{vi}\right)\end{array}$

In equation (half dozen), X_ij represents the country-pair characteristics such as distance, mutual linguistic communication, mutual currency, and colonial ties, η_it is time varying source-land fixed furnishings and η_jt is time varying destination-country fixed effects. We as well include ii policy variables. 1 is an indicator of a preferential merchandise agreement between two countries and the other ane captures commutation rate volatility.

In addition, we investigate the time-invariant characteristics that contribute to a state's participation in GVCs. In gild to do and then we apply time-varying source and destination fixed effects and estimate equation (7) where η_it is either source or destination stock-still effects estimated in equation (vi).

$\begin{array}{cc}{\eta }_{it}=\log \left({GDP}_{it}\right)+{\alpha X}_i+{\eta }_t+{ϵ}_{it}& \left(7\right)\end{array}$

B. Results

Table 3 shows the results of an OLS estimation of equation (half-dozen). Columns (1) and (2) suggest that concrete proximity likewise equally standard country-pair characteristics such every bit common border, common language, and colonial linkages are important determinants of GVC participation measured with foreign value-added. Columns (3) and (4) include additional policy-related variables in the gravity equation specification, i.due east. preferential trade understanding indicator, exchange rate volatility, and common currency indicator. The results suggest that having the aforementioned currency or at least lower exchange rate volatility increases countries' bilateral value concatenation participation.

Taking advantage of the Eora dataset, which allows u.s.a. to calculate bilateral GVC participation at the industry level likewise, we estimate equation (6) at the industry level for the twelvemonth 2013. Instead of time-fixed effects we include source state-sector and destination country-sector fixed effects, which helps control for country-sector heterogeneity. We find that at the industry level, geographical proximity is more than important for the manufacturing manufacture. International trade of goods and services from upstream industries is more sensitive to distance compared to goods closer to final demand.

The land fixed effects obtained from regression (half dozen) help united states of america to gauge which countries participate in GVCs above or beneath average. For example, Figures 12 and 13 prove that amidst European countries, Turkey, Albania, and Bosnia and herzegovina tend to have lower GVC participation than implied by fundamentals. We as well explore which institutional and country characteristics help explain the country fixed effects. We examine specification (7), using the source-country fixed effects on the left side and a large set of structural and institutional variables on the right side. Results for the most significant variables are reported in Tabular array 5.

Table iv.

Determinants of Bilateral GVC Participation

Table iv.

Determinants of Bilateral GVC Participation

Log (distance)	-1.010*** (0.019)	-0.752*** (0.013)	-0.579*** (0.013)	-0.574*** (0.013)
Mutual border	1.823*** (0.071)	1.390*** (0.096)	1.386*** (0.078)	(0.078)
Mutual language		0.349*** (0.025)	0.266*** (0.022)	0.261*** (0.022)
Common colonial history		0.402*** (0.097)	0.494*** (0.096)	0.513*** (0.095)
Common currency			1.513*** (0.107)	1.416*** (0.106)
Preferential Trade Agreement			0.648*** (0.024)	0.627*** (0.024)
Exchange charge per unit volatility				-1.183*** (0.207)
State-Year Fixed Effects	Yes	Yes	Yes	Aye
Observations	544,170	544,170	544,170	537,775
R-squared	0.899	0.907	0.913	0.913

Table 5.

Time Invariant Exporting State Characteristics and GVC Participation

Source: Authors' calculations.

Table 5.

Fourth dimension Invariant Exporting Land Characteristics and GVC Participation

	(1)	(two)	(3)	(4)	(five)	(6)	(7)
Log(Gdp)	0.740*** (0.024)	0.753*** (0.022)	0.705*** (0.028)	0.742*** (0.025)	0.742*** (0.025)	0.841*** (0.037)	0.826*** (0.042)
Contract enforcement		0.085*** (0.027)
Rule of police force			0.167*** (0.062)
Concern entry procedures				-0.024* (0.014)
Unit labor costs (lag)					-0.411** (0.169)
Man capital (lag)						0.564** (0.243)
Infrastructure quality							0.075 (0.085)
Constant	-2.74***	-three.16***	-ii.65***	-2.24***	-2.24***	-two.80***	-3.35**
Observations	531,527	482,021	528,316	288,499	288,499	114,067	98,350
R-squared	0.854	0.905	0.860	0.843	0.843	0.924	0.934

Source: Authors' calculations.

Stiff institutional characteristics, such as the business environment and adept infrastructure touch on countries' participation in GVCs as well. A high degree of contract enforcement as well every bit the rule of law facilitate a country's participation in a global value concatenation both on the exporting and importing side (Tables 5 and 6). Similarly, the ease of doing business, proxied past the number of procedures needed to ready a concern, as well as the overall quality of infrastructure, play a role as determinants of GVC participation (Figures 12 and thirteen). However, high labor costs in the exporting country decreases its competitiveness and thus participation in GVC, while this is non a factor for countries on the importing side.

Table 6.

Fourth dimension Invariant Import Country Characteristics and GVC Participation

Source: Authors' calculations.

Table 6.

Time Invariant Import Country Characteristics and GVC Participation

	(i)	(2)	(three)	(four)	(5)	(half dozen)	(7)
Log(Gross domestic product)	0.782*** (0.035)	0.770*** (0.031)	0.685*** (0.035)	0.783*** (0.033)	0.721*** (0.032)	0.781*** (0.066)	0.725*** (0.035)
Contract enforcement		0.231*** (0.040)
Rule of police			0.501*** (0.079)
Business concern entry procedures				-0.088* (0.020)
Unit labor costs (lag)					0.016
Human capital (lag)						0.926*** (0.121)
Infrastructure quality							0.412*** (0.064)
Constant	-2.036***	-3.123***	-one.763***	-i.406***	-3.626***	-1.696***	-4.060***
Observations	531,581	481,785	528,390	288,605	462,710	113,306	371,482
R-squared	0.765	0.836	0.815	0.785	0.841	0.821	0.854

Source: Authors' calculations.

Effigy 12.

Country Fixed Effects and Quality of Infrastructure ^1/

Commendation: IMF Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations and Eora database; World Economic Forum Global Competitiveness Index (Quality of Infrastructure); Doing Concern Indicators (Contract enforcement). Data is for 2013. ^1/ Survey-based indicators reflect investors' perceptions on the business organisation surroundings. The contract enforcement score (normalized 0–10=strongest) takes into account the time and cost for resolving a commercial dispute through a local outset-case court, and the quality of judicial processes index, evaluating whether each economic system has adopted a series of good practices that promote quality and efficiency in the court system.

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Effigy 12.

Country Fixed Effects and Quality of Infrastructure ^1/

Citation: International monetary fund Working Papers 2019, 018; x.5089/9781484392928.001.A001

Sources: Authors' calculations and Eora database; Globe Economical Forum Global Competitiveness Index (Quality of Infrastructure); Doing Business Indicators (Contract enforcement). Data is for 2013. ^1/ Survey-based indicators reflect investors' perceptions on the business environs. The contract enforcement score (normalized 0–10=strongest) takes into account the time and cost for resolving a commercial dispute through a local offset-instance court, and the quality of judicial processes index, evaluating whether each economy has adopted a series of good practices that promote quality and efficiency in the court organisation.

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Figure 13.

Destination Fixed Furnishings and Contract Enforcement ^1/

Citation: Imf Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations and Eora database; World Economic Forum Global Competitiveness Index (Quality of Infrastructure); Doing Business Indicators (Contract enforcement). Data is for 2013. ^1/ Survey-based indicators reverberate investors' perceptions on the business surround. The contract enforcement score (normalized 0–10=strongest) takes into business relationship the fourth dimension and cost for resolving a commercial dispute through a local first-instance court, and the quality of judicial processes index, evaluating whether each economy has adopted a series of good practices that promote quality and efficiency in the court system.

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Figure 13.

Destination Stock-still Effects and Contract Enforcement ^one/

Citation: Imf Working Papers 2019, 018; 10.5089/9781484392928.001.A001

Sources: Authors' calculations and Eora database; Globe Economic Forum Global Competitiveness Index (Quality of Infrastructure); Doing Business Indicators (Contract enforcement). Data is for 2013. ^i/ Survey-based indicators reverberate investors' perceptions on the business surroundings. The contract enforcement score (normalized 0–10=strongest) takes into account the time and cost for resolving a commercial dispute through a local start-instance court, and the quality of judicial processes alphabetize, evaluating whether each economy has adopted a serial of expert practices that promote quality and efficiency in the court system.

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Six. Concluding Remarks

This newspaper uses the new comprehensive Eora MRIO Database to uncover the extent to which both adult and emerging economies participate in global value chains and to judge the determinants and consequences of GVC participation. In doing then, we first c onstruct dissimilar measures of GVC participation besides as the industry and country position in the value concatenation, using a recently adult methodology consistent with the theoretical literature.

We document that the manufacturing and services sectors participate differently in GVCs. In addition, both forrard and backward measures of participation need to be considered to obtain a better picture show of a country'southward GVC participation. Nosotros as well document that in that location is a great caste of heterogeneity in GVC participation equally well equally position measures across countries and industries. We exploit this heterogeneity to written report the relationship between GVC participation and income per capita as well equally its determinants (investment rate, man uppercase and productivity).

Our results suggest that participation in global value bondage, rather than conventional trade, can positively consequence countries' economic performance, although the gains can exist heterogenous. The upper middle and high-income countries appear to exist benefiting from such participation, while we don't find robust effects for depression and lower-middle income countries.

While GVC participation raises productivity and income levels, "moving up" to more hi-tech sectors does not announced to be automatic and frequent. We document that for many countries that contribute to major global supply chains, there is little shift in the sectoral limerick of their participation. Here also, there is large heterogeneity. Specifically, there are cases of large transformations in Asia (less and so in Europe) and notably moves to high-tech services by the United states, China, Germany, and Nihon.

We find that standard gravity variables explain a country's participation in GVCs. In improver, the quality of institutions, quality of infrastructure, and unit labor costs are important determinants of GVC participation. We find that upstream sectors and services are more sensitive to trade barriers.

What does this mean for policy? Beyond the usual call for ameliorate infrastructure, connectivity, and improving institutions, given the gradual rise of services in GVC trade, it is also of import to better understand barriers to services trade and the type of reforms and merchandise agreements that could potentially facilitate it.

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