Follow the Value Added: Bilateral Gross Export Accounting

Abstract

The diffusion of international production networks has challenged the capability of traditional trade statistics to provide an adequate representation of supply and demand linkages among the economies. To address this issue, new statistical tools (the Inter-Country Input-Output tables) and new analytical frameworks have been developed. Koopman, Wang and Wei propose an accounting methodology to decompose a country's total gross exports by source and final destination of their embedded value added. We develop this approach further by deriving a fully consistent counterpart for bilateral trade flows, refining the original framework. Along with other contributions, our methodology completes the bridge between traditional trade statistics and the systems of national accounts and provides new tools for investigating global value chains. Here we present two empirical applications of two different versions of our decomposition of bilateral trade flows: one explores the forward linkages of Italian exports; the second derives a measure of the share of value-chainrelated trade and assesses how its evolution since the mid-1990s has affected the relationship between world trade and income.

Measuring Trade Integration in Africa

“…Koopman et al (2014) provide the first full decomposition of a country's gross exports into value-added components by source and other double-counted terms. Borin and Mancini (2015) extend this framework to decompose gross trade at the bilateral level. Those terms make it possible to calculate various indicators, including backward integration and forward integration (African Development Bank et al 2014) or vertical specialization indicators inspired from the work of Hummels et al (2001), Daudin et al (2011), andJohnson andNoguera (2012).…”

The Cyclicality of the Income Elasticity of Trade

“…Their empirical analysis documented that the income elasticity of imports was larger than 1 for essentially all the countries included in their sample, although with relevant cross-country di¤erences. 6 Previous studies have also analyzed the behavior of the income elasticity across very long time spans, relating them to the evolution of trade barriers, as re ‡ected in changes either in tari¤ and non-tari¤ policies or in transportation costs. Irwin (2002), in particular, analyzed the income elasticity for the world economy since 1870, distinguishing three main phases: (i) in the pre-World War I era (1870-1913), characterized by very stable tari¤ rates (which were also very low in Western Europe), the elasticity tended to lie around 1; (ii) in the interwar era (1920)(1921)(1922)(1923)(1924)(1925)(1926)(1927)(1928)(1929)(1930)(1931)(1932)(1933)(1934)(1935)(1936)(1937)(1938), the rise of protectionism and the introduction of foreign exchange restrictions brought the elasticity down, to levels close to zero; (iii) in the post-World War II era , when the GATT and the WTO encouraged a sustained reduction in trade barriers, the elasticity rose well above 1.…”

“…4 Most hypotheses about the causes of the Great Trade Collapse have been presented in Baldwin (2009) and Baldwin and Evenett (2009); for other important contributions not included in those books, see also Eaton, Kortum, Neiman and Romalis (2016) and the extensive literature surveyed therein. Hoekman (2016) gathers several explanations for the post-crisis performance of trade; for other views, see also Borin and Mancini (2015) and IMF (2016). (1) (1) Percentage-point di¤erence between the growth rate at year t as measured in the IMF WEO (World Economic Outlook) published in October at year t + 1 (actual data) and the growth rate at year t as predicted in the IMF WEO published in October at year t 1 1 only to the extent that trade volumes grow faster that real GDP, as they do, for example, when trade barriers decline.…”

Back on Track? A Macro–Micro Narrative of Italian Exports

“…The overall diffusion of global value chains in the period under study has reduced the informative content of standard indicators based on gross exports in assessing the contribution of external demand to GDP dynamics. The availability of global input-output tables such as the World Input Output Database (WIOD) and the OECD Trade in Value Added Database (TiVA) has opened up the analysis of trade in value added as an alternative to that in gross terms (see, for instance, Koopman et al, 2014, Johnson and Noguera, 2017, Timmer et al, 2015, Cappariello and Felettigh, 2015, Borin and Mancini, 2015.…”