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In this paper, we estimated the standard (macro-economic) import equation over the period 1995-2021Q2, using an import intensity-adjusted measure of aggregate demand (IAD) calculated from input-output tables at country level, and compared the results with regressions using GDP. Initially introduced by Bussière (2013), this "synthetic" concept of IAD was perfected, inter alia, by the IMF (2016) and by us (2017), with a view to explaining the "missing" trade flows unpredicted by GDP-based import models during the trade collapse of 2009 and subsequent recovery from it. At the time, it appeared that the integration of IAD helped predict over three-quarters of the changes in global imports, a better performance than if using GDP (two-thirds) or any other measure of aggregate demand. We had found much value to this method, as a complement to existing analytical tools, enabling to measure the relative importance of each component of demand in the variations of country/global imports, over entire economy cycles (a phase of trade expansion, a sudden collapse and a recovery). Moreover, by weighting each aggregate demand component by its direct and indirect traded inputs, import-adjusted integrated a supply-side dimension to such macro-economic modelling. By extending our estimates to cover global trade during the (on-going) Covid-19 pandemic (1995-2021 Q2), we found the IAD-based model to continue performing well, predicting 79% of changes in global imports during the period 1995-2021Q2 (10 percentage points more than when using GDP). We also found that, on average, 97% of the difference in global import growth between the pre-pandemic (2012-2019) and the pandemic period (2020), was attributable to IAD. Most of the variations in imports can be explained by changes in the growth of investment and exports, the two-most trade-intensive elements of demand, by 29% and 45%. The variations of consumption also accounted for a significant share of global import variations during this period (25%).

This paper looks at the extent to which the shift in the lower value added production to countries in the following development "tier" is actually becoming a reality. Several countries in East Asia have been upgrading production patterns and moving up the value chain, this paper looks at how this helps and offers new opportunities to less advanced countries to integrate in world trade. The paper uses a combination of techniques, from an analysis of disaggregated trade flows by country and sectors, to the calculation of trade intensity indices by country and sector, and value-added trade by sector. It finds combined evidence of forward and backward trade increasing between several neighbouring Asian economies and China, in the most labour-intensive industries in particular. Econometric analysis shows that relative unit labour costs are an explanatory factor of increased trade links. In cases, the intensification of trade links on the export side can relate to a strongly expanding local market (for example India for electronic products such as smartphones), but mostly the intensification of trade links takes place both on the import and export sides with markets which are much smaller than China (Vietnam, Bangladesh, etc.), and which experienced increased outward-processing activities as a result of China's production upgrade.

Since the recovery from the great financial crisis in 2010, global real trade flows grew much slower than pre-crisis, in both absolute terms (growth rates) and relative terms (relative to GDP, from 2:1 in the great 1990’s to 1:1 since 2012) A debate has arisen as to whether this global trade slowdown, and related falling trade-to-income elasticity, was structural or cyclical. Some papers emphasized the slowing pace of international vertical specialization. Other works emphasized the prominent role of aggregate demand, notably when weighted by its trade component. Our paper goes in this latter direction. We estimated the standard import equation for 38 advanced and developing countries over the period 1995-2015, using an import intensity-adjusted measure of aggregate demand (IAD), calculated from input-output tables at country level, and compared results with regressions using GDP. The integration of IAD allows us to predict 76% to 86% of the changes in global imports, a better performance than if using GDP. The use of IAD also enabled us to measure the relative importance of each component of demand, according to their trade intensity. The model is able to account for over 90% of the recent trade slowdown (2012-2015), with IAD alone explaining 80% of it. The slowdown in global value chains explains more than half of the remaining share of the global trade slowdown, not explained by demand factors. Protectionism does not come up as statistically significant.