#tradeXpresso Lungo: Who took the Gini out of the trade bottle?
Lucian Cernat
Head of Global Regulatory Cooperation and International Procurement Negotiations at European Commission
Lucian Cernat*
Head of Global Regulatory Cooperation and International Procurement Negotiations, DG Trade.
*Disclaimer: the views expressed herein are those of the author and do not necessarily reflect an official position by the European Commission. The author would like to thank CARMEN DIAZ MORA , Oscar Guinea and Hein Roelfsema for their useful suggestions and valuable feedback.
A few days ago, the IMF released its latest World Economic Outlook. The IMF expected world trade growth to decline from 5.1 % in 2022 to 0.9 % in 2023. Many reasons were behind this sudden drop in global trade. Growing geopolitical tensions, global fragmentation, wars and national disasters were all to blame. Trade policy too. According to the IMF report, in 2022 alone, countries around the world imposed almost 3’000 new restrictions on trade, up from fewer than 1’000 in 2019.
?“Why should we care about trade when the world has far bigger problems?”, one could legitimately ask. Well, trade still matters for millions of people worldwide, whose livelihoods and jobs depend on trade. Exporting firms are more productive , more innovative and pay higher wages. French exporters are 20% more productive than non-exporters, whereas Italian exporting firms are 40% more productive than non-exporting firms. The same is true for exporting firms in developing countries .
?Trade policy is therefore key for macroeconomic stability and prosperity, and hence it is usually monitored at macro-level using more or less sophisticated indicators (e.g. total trade values, growth rates, market shares or trade balances). However, one needs to realise that countries do not trade, firms do. When going beyond macro to firm-level trade realities, policy makers need different “Trade Policy 2.0 ” key performance indicators (KPIs). These indicators are well-grounded in economic analysis . Hence, in order to understand national comparative advantage and measure the impact of trade policy on competitiveness, we need new KPIs that put the firm at the centre of trade policy analysis.
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Figure 1. The number of EU exporters has more than doubled since 2012
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The simplest “Trade Policy 2.0” indicator would be the number of exporting firms (Figure 1). Simple indicators are powerful: the number of EU exporters more than doubled since 2012, reaching 717’000 exporting firms in 2020, the vast majority of which are small and medium enterprises (SMEs). Among these new KPIs, a set of new indicators could also measure the ability of SMEs to participate in global trade. Why focus on SMEs? The answer is simple: SMEs are not always the most productive firms in an economy but exposure to foreign markets has positive effects on firm productivity, an effect known as learning-by-exporting .
?While larger numbers of SMEs engaged in global trade are good news, there is also strong evidence that export performance is an activity dominated by “super-exporters ”. The top 1% of exporters account for almost 90% of total exports in Botswana, almost 70% of total value of German or Spanish exports and more than 50% of Portuguese exports. This high concentration of export value generated by a small number of firms renders countries vulnerable to external shocks. If a handful of exporters generate a disproportionate share of total exports concentrated in a few products, then export performance may be vulnerable to “black swan” events. More detailed supply chain indicators are also needed for macroeconomic stability. Recent IMF work has shown that central banks can stabilize inflation and output more efficiently by monitoring global supply chains and adjusting the monetary policy stance accordingly. The gains from monitoring supply chain disruptions are particularly large for open economies.
?We therefore need a more elaborate indicator that could measure the skewness of trade, just as we measure the skewness of various economic indicators (e.g. wealth and income distribution, access to land or education, consumption inequality, etc.). The best-known indicator is the Gini index . Invented by Italian statistician Corrado Gini, and named after him, the Gini index ranges from 0 (which represents a perfect equality) to 1 (indicating perfect inequality). ??Applying the Gini index to measure a country’s trade structure leads us to a new, more elaborate indicator of trade structures – the Gini Trade Index (GTI). A country where all exporters would export perfectly equal values would have a GTI equal to 0. In contrast, a country where all exports would be generated by a single exporter would have a GTI value of 1.
?Just like the traditional Gini inequality index, the Gini Trade Index measures the skewness in trade based on the numbers of exporters and their share in export values. Ideally, the GTI would be measured on firm-level trade statistics. Unfortunately, that that kind of data is not readily available across all EU countries. A second-best proxy for the data needed to measure the GTI is the Eurostat Trade by Enterprise Characteristics (TEC) database that indicate the number of micro (less than 10 employees), small (less than 50 employees), medium (less than 250 employees) and large firms (more than 250 employees) engaged in trade and the trade values exported by each category. So the Gini Trade Index can be calculated across these four size classes of exporters from micro firms with less than 10 employees, all the way to “super-exporters” (large firms).
Figure 2. The Gini Trade Index (GTI), selected countries
?Figure 2 illustrates the Gini Trade Index for several EU countries in 2021 and compares it with 2010 values. Countries with higher GTI are shown in red, those that have a decline in GTI are in blue. The relatively high GTI values (over 0.7 for most countries) confirm that trade performance is very skewed towards larger firms. The second interesting finding is that the GTI has been growing for all the EU countries depicted in Figure 2 since 2010, except Finland, Luxembourg, Bulgaria and Cyprus. This indicates that the participation of micro and small EU exporters in global trade remains uneven, in terms of trade values. However, the demographics are encouraging: as shown in Figure 1, the overall increase in exporting firms (which are mostly SMEs) indicate that small firms remain competitive. At the same time, the Gini Trade Index indicates that there has not been a similar increase in their export values.
?The increase in export concentration is not an isolated phenomenon. It mirrors a trend of growing industry concentration across countries , more generally. While this can be problematic for trade competition and economic dynamism, this is not true across the board. Some countries see a growing participation of SMEs, both in terms of numbers and in terms of their importance in total trade values. Some SMEs of today may become the unicorns of tomorrow. This is important for EU competitiveness and productivity. Trade participation goes hand in hand with productivity. And since some argue that Europe has a growth and productivity gap , a robust trade participation by a growing number of small firms might help both in terms of competition and productivity.
?Beyond Europe, the Gini Trade Index may offer valuable indicators to policymakers. In the developing world, the participation of small firms in global supply chains is one of the surest ways to increase firm productivity, wages, and overall welfare. A “Trade Policy 2.0” approach focussed on such firm-level KPIs can help, including for export sectors subject to specific standards and certification requirements . New trade metrics might also be needed to unleash the full potential of e-commerce .
?The world is changing, and new trade realities require new trade indicators. Let’s take the Gini out of the trade bottle and ensure that small firms can continue to benefit from global trade.
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Ministry of Commerce & Industry| International Trade & Investment Policy Advisor Economist| Trade & Investment Law & Policy| FTA| Digital Transformation| Digital Economy| Capacity Building| MSME| eLearning| Entrepreneur
1 年Putting the Gini back in the bottle? Interesting idea Lucian Cernat
Research Associate @ The University of Waikato | Economics | ARTNeT
1 年BTW, I guess there is no data for Croatia for 2010?
Research Associate @ The University of Waikato | Economics | ARTNeT
1 年If only we would have some way to add sex-differentiated data into those KPIs so we find more about how trade (expansion or contraction) impacts women viz men!