International production, trade and investments are increasingly organised within global value chains (GVC); GVCs where different stages of the production process are located across firms of other countries. Despite the
rapid evolution of the literature, a lot remains to be done in order to fully understand the complexity of the phenomenon.
One of the main challenges concerns the measurement of GVCs. This deliverable tackles such a “measurement issue” presenting new empirical evidence on:
i) the consistency of micro and macro level data on GVCs;
ii) the micro-foundation of the global Inter-Country Input-Output (ICIO, henceforth) accounting framework.
The first contribution “Consistency of Micro- and Macro-level Data on Global Value Chains: Evidence from Selected European Countries” is authored by A. Giunta; P. Montalbano; S. Nenci and published in International Economics (171, 2022, 130 – 142). The contribution investigates the degree of consistency and fungibility of micro and macro sources of GVC data.
The study combines two datasets for selected European countries (France, Germany, Italy, and Spain) over the period 2001–2014: the European Union-European Firms in a Global Economy (EU-EFIGE) firm-level dataset (integrated with panel balance sheet data from Amadeus) and the World Input–Output Database (WIOD) at the country and sectoral level. Although the two datasets come from different sources and are based on different
assumptions, it is found full consistency in the two datasets. In particular, it is found that:
(i) the WIOD-based country and sectoral GVC indicators are positively correlated with firm-level proxies based on EFIGE data;
(ii) the GVC indicators from both sources are positively correlated with firm-level labor productivity.
(iii) these outcomes are robust to various empirical tests and specifications, as well as to controlling for the firm, sector, and country heterogeneity.
The results hold relevance for scholars by demonstrating that the available ICIO data can be used to compensate for the (well-known) scarcity of firmlevel data for evidence-based GVC analyses.
The second contribution “Micro-based indicators of GVC participation and positioning” is authored by I. Fusacchia, A. Giunta, M. Mantuano, E. Marvasi, S. Nenci, L. Salvatici, D. Vurchio.
It goes beyond the consistency’s evaluation of GVC micro and macro data, using microdata in the construction of a global ICIO accounting framework. The contribution improves input-output data based on the GTAP Data Base by disaggregating IO tables for Italy, thus tracking GVC linkages at higher resolution.
To this aim, export, import as well as production firm-level data are used to improve estimates of the sourcing and allocation of imported inputs across sectors, thus enhancing the quality of data used for the computation of trade in Value Added indicators.
The databases used are drawn from several sources and cover the 2013-18 period:
firm-level data from Frame SBS (Structural Business Statistics), which is the Italian National Institute of Statistics (ISTAT) statistical register on economic accounts of Italian enterprises in the Industry and Services
sectors. We gathered data, for around 4,3 million firms on selected variables;
ISTAT statistics from the survey on foreign trade (COE) in goods of both intra- and extra-EU trade flow for about 215,000 Italian firms and foreign trade operators The outcome of a three steps procedure (detailed in section 3.2.2) is an integrated database used to compute improved GVC-related indicators.
Specifically, the participation and positioning of Italian firms in GVC. Particular attention to the agrifood sectors is devoted throughout this section.
The GVC participation index is given by the sum of a ‘backward’ component (the value of imported intermediate inputs in exports) and a ‘forward’ component (the value of intermediate exports sent indirectly through third
countries to final destinations). Combining the two components, one can have a comprehensive assessment of a country’s participation in GVCs, both as a user of foreign inputs and supplier of intermediates used in other
7 countries’ exports. The larger the indicator, the higher the intensity of involvement of a particular country (or sector) in GVCs.
It is worth underlining that, thanks to the inclusion of micro-data into the GTAP database, the contribution provides a significant improvement in the measurement of imports and in the division between intermediate and final and their sources. This, in turn, refines the calculation of GVC participation indicators, especially the backward component. Focussing on the agrifood sectors and concerning GVC participation indexes, three are the main findings:
Paddy rice is the agrifood sector showing the highest forward GVC participation for Italy;
The geographical composition of Italian forward participation highlights that Germany is the main destination and exporter of Italian value-added (the second one being France). In other words, Germany acts as an implicit export platform for Italian value-added. In fact, 57% of Italian agrifood value-added exported by Germany ends up within the EU
Sugar, Vegetables oils and fats, are the agrifood sectors with the highest backward participation, all above 30%. Thus, Italian exports of these sectors strongly depend on foreign value-added.
The GVC positioning index: a focus on the upstreamness index. The upstreamness index measures the distance to the final demand of a sector along the production chains. In other words, a relatively upstream sector is
one that sells a small share of its output to final consumers (Antràs and Chor, 2019).
The upstreamness indicator can assume values equal to or greater than 1: larger values are associated with relatively higher levels of upstreamness of the output originating from one sector.
Focussing on the agrifood sectors and concerning GVC upstreamness index, two are the main findings:
Agricultural products – such as cereal grains, rice, oil seed, and sugar cane/beet- are collocated upstream in the GVC, showing more than 2.5 steps from the final market;
Conversely, food products, especially bovine meat and meat products, are less upstream, with less than 2 steps from the final consumption.
Finally, Section 3.2.4 of this deliverable is devoted to the comparison between the standard GTAP-MRIO and the new GTAP-Micro; in other words, it is highlighted to what extent the finer measurement of intermediate imports by sourcing country does change the sector share reallocation.
Focusing on the agrifood sectors, we find that:
In the case of Beverages and tobacco products, the share reallocation seems to be large. In fact, in the GTAP-Micro data, other EU27 countries are a less relevant source (from 48.1% to 29.8%), while Germany (from 28.7% to 38.6%), France (from 10.8% to 13.1%) and the UK (from 1.8% to 3.8%) gain importance as sources of intermediates.