This is consistent with the fact that, after the global financial crisis, there has been a slowdown in the rate of growth of trade in goods and services, relative to global GDP. This is a sign that global integration stalled after the financial crisis. The integration of global value chains is a common source of measurement error in trade data, because it makes it hard to correctly attribute the origin and destination of goods and services.
We discuss this in more detail below. You can visit the AEC website to see this composition country by country. The settings tab allows you to choose alternative product classes, trade flows choices, and the level of product aggregation. If you move the time slider below the tree map, you can also change the year for which the data is plotted. If we consider all pairs of countries that engage in trade around the world, we find that in the majority of cases, there is a bilateral relationship today: Most countries that export goods to a country, also import goods from the same country.
The interactive visualization shows this. In this chart, all possible country pairs are partitioned into three categories: the top portion represents the fraction of country pairs that do not trade with one-another; the middle portion represents those that trade in both directions they export to one-another ; and the bottom portion represents those that trade in one direction only one country imports from, but does not export to, the other country. As we can see, bilateral trade is becoming increasingly common the middle portion has grown substantially.
As we can see, up until the Second World War the majority of trade transactions involved exchanges between this small group of rich countries. But this has been changing quickly over the last couple of decades, and today trade between non-rich countries is just as important as trade between rich countries. Here is a stacked area chart showing the total composition of exports by partnership.
The last few decades have not only seen an increase in the volume of international trade, but also an increase in the number of preferential trade agreements through which exchanges take place. A preferential trade agreement is a trade pact that reduces tariffs between the participating countries for certain products. The visualization here shows the evolution of the cumulative number of preferential trade agreements that are in force across the world, according to the World Trade Organization WTO.
These numbers include notified and non-notified preferential agreements the source reports that only about two-thirds of the agreements currently in force have been notified to the WTO , and are disaggregated by country groups. This figure shows the increasingly important role of trade between developing countries South-South trade , vis-a-vis trade between developed and developing countries North-South trade.
In the late s, North-South agreements accounted for more than half of all agreements — in , they accounted for about one quarter. Today, the majority of preferential trade agreements are between developing economies. The increase in trade among emerging economies over the last half century has been accompanied by an important change in the composition of exported goods in these countries.
Two points stand out. First, there has been a substantial decrease in the relative importance of food exports since s in most countries although globally in the last decade it has gone up slightly. And second, this decrease has been largest in middle income countries, particularly in Latin America. Regarding levels, as one would expect, in high income countries food still accounts for a much smaller share of merchandise exports than in most low- and middle-income-countries.
Economic costs include physical inputs the value of the stuff you use to produce the good , plus forgone opportunities when you allocate scarce resources to a task, you give up alternative uses of those resources. The forgone opportunities of production are key to understand this concept. It is precisely this that distinguishes absolute advantage from comparative advantage. To see the difference between comparative and absolute advantage, consider a commercial aviation pilot and a baker.
Suppose the pilot is an excellent chef, and she can bake just as well, or even better than the baker. In this case, the pilot has an absolute advantage in both tasks. Yet the baker probably has a comparative advantage in baking, because the opportunity cost of baking is much higher for the pilot.
At the individual level, comparative advantage explains why you might want to delegate tasks to someone else, even if you can do those tasks better and faster than them. This may sound counterintuitive, but it is not: If you are good at many things, it means that investing time in one task has a high opportunity cost, because you are not doing the other amazing things you could be doing with your time and resources. So, at least from an efficiency point of view, you should specialize on what you are best at, and delegate the rest.
The same logic applies to countries. In countries with relative abundance of certain factors of production, the theory of comparative advantage predicts that they will export goods that rely heavily in those factors: a country typically has a comparative advantage in those goods that use more intensively its abundant resources.
Colombia exports bananas to Europe because it has comparatively abundant tropical weather. Under autarky, Colombia would find it cheap to produce bananas relative to e. The empirical evidence suggests that the principle of comparative advantage does help explain trade patterns. Bernhofen and Brown 25 , for instance, provide evidence using the experience of Japan.
The graph here shows the price changes of the key tradable goods after the opening up to trade. It presents a scatter diagram of the net exports in graphed in relation to the change in prices from —53 to As we can see, this is consistent with the theory: after opening to trade, the relative prices of major exports such as silk increased Japan exported what was cheap for them to produce and which was valuable abroad , while the relative price of imports such as sugar declined they imported what was relatively more difficult for them to produce, but was cheap abroad.
The resistance that geography imposes on trade has long been studied in the empirical economics literature — and the main conclusion is that trade intensity is strongly linked to geographic distance. Each dot represents a country-pair from a set of 19 OECD countries, and both the vertical and horizontal axis are expressed on logarithmic scales. As we can see, there is a strong negative relationship.
Trade diminishes with distance. Through econometric modeling, the paper shows that this relationship is not just a correlation driven by other factors: their findings suggest that distance imposes a significant barrier to trade. The fact that trade diminishes with distance is also corroborated by data of trade intensity within countries. The colors reflect the percentage of firms which export to each specific country.
As we can see, the share of firms exporting to each of the corresponding neighbors is largest close to the border. The authors also show in the paper that this pattern holds for the value of individual-firm exports — trade value decreases with distance to the border. Conducting international trade requires both financial and non-financial institutions to support transactions. Some of these institutions are fairly obvious e.
For example, the evidence shows that producers in exporting countries often need credit in order to engage in trade. As can be seen, financially developed economies — those with more dynamic private credit markets — typically outperform exporters with less evolved financial institutions. Other studies have shown that country-specific institutions, like the knowledge of foreign languages, for instance, are also important to promote foreign relative to domestic trade see Melitz The concept of comparative advantage predicts that if all countries had identical endowments and institutions, then there would be little incentives for specialization, because the opportunity cost of producing any good would be the same in every country.
So you may wonder: why is it then the case that in the last few years we have seen such rapid growth in intra-industry trade between rich countries?
The increase in intra-industry between rich countries seems paradoxical under the light of comparative advantage, because in recent decades we have seen convergence in key factors, such as human capital , across these countries.
The solution to the paradox is actually not very complicated: Comparative advantage is one, but not the only force driving incentives to specialization and trade. The idea is that specialization allows countries to reap greater economies of scale i. In a much cited paper, Evenett and Keller 33 show that both factor endowments and increasing returns help explain production and trade patterns around the world.
There are dozens of official sources of data on international trade, and if you compare these different sources, you will find that they do not agree with one another. Even if you focus on what seems to be the same indicator for the same year in the same country, discrepancies are large.
Such differences between sources can also be found for rich countries where statistical agencies tend to follow international reporting guidelines more closely. And there are also large bilateral discrepancies within sources. Here we explain how international trade data is collected and processed, and why there are such large discrepancies.
The data hubs from several large international organizations publish and maintain extensive cross-country datasets on international trade. In addition to these sources, there are also many other academic projects that publish data on international trade. These projects tend to rely on data from one or more of the sources above; and they typically process and merge series in order to improve coverage and consistency.
Three important sources are:. In the visualization here we provide a comparison of the data published by several of the sources listed above, country by country, since up until today. For each country, we exclude trade in services, and we focus only on estimates of the total value of exported goods, expressed as shares of GDP. As we can clearly see in this chart, different data sources tell often very different stories. And this is true, to varying degrees, across all countries and years.
Constructing this chart was demanding. It required downloading trade data from many different sources, collecting the relevant series, and then standardising them so that the units of measure and the geographical territories were consistent. So, if all series are in the same units share of national GDP , and they all measure the same thing value of goods exported from one country to the rest of the world , what explains the differences?
Broadly speaking, there are two main approaches used to estimate international merchandise trade:. The distinction is often made because goods simply being transported through a country i. Also, adding to the complexity, countries often rely on measurement protocols that are developed alongside these approaches and concepts that are not perfectly compatible to begin with.
Even when two sources rely on the same broad accounting approach, discrepancies arise because countries fail to adhere perfectly to the protocols. In theory, for example, the exports of country A to country B should mirror the imports of country B from country A.
But in practice this is rarely the case because of differences in valuation. The chart here gives you an idea of how large import-export asymmetries are. Shown are the differences between the value of goods that each country reports exporting to the US, and the value of goods that the US reports importing from the same countries.
The differences in the chart here, which are both positive and negative, suggest that there is more going on than differences in FOB vs CIF values. Another common source of measurement error relates to the inconsistent attribution of trade partners.
An example is failure to follow the guidelines on how to treat goods passing through intermediary countries for processing or merchanting purposes. As global production chains become more complex, countries find it increasingly difficult to unambiguously establish the origin and final destination of merchandise, even when rules are established in the manuals.
And there are still more potential sources of discrepancies. Even when two sources have identical trade estimates, inconsistencies in published data can arise from differences in exchange rates. If a dataset reports cross-country trade data in US dollars, estimates will vary depending on the exchange rates used. Different exchange rates will lead to conflicting estimates, even if figures in local currency units are consistent. Asymmetries in international trade statistics are large and they arise for a variety of reasons.
These include conceptual inconsistencies across measurement standards, as well as inconsistencies in the way countries apply agreed protocols. These factors have long been recognized by many organizations producing trade data. Indeed, international organizations often incorporate corrections, in an attempt to improve data quality along these lines. However, this dataset has low coverage across countries, and it only goes back to There are two key lessons from all of this.
The first lesson is that, for most users of trade data out there, there is no obvious way of choosing between sources. And the second lesson is that, because of statistical glitches, researchers and policymakers should always take analysis of trade data with a pinch of salt. For example, in a recent high-profile report , researchers attributed mismatches in bilateral trade data to illicit financial flows through trade misinvoicing or trade-based money laundering.
As we show here, this interpretation of the data is not appropriate, since mismatches in the data can, and often do arise from measurement inconsistencies rather than malfeasance. Hopefully the discussion and checklist above can help researchers better interpret and choose between conflicting data sources.
At some universities you can access the online version of the books where data tables can be downloaded as ePDFs and Excel files. The online access is here. Summary In this entry we analyze available data and research on international trade patterns, including the determinants and consequences of globalization over the last couple of decades.
Over the last two centuries trade has grown remarkably, completely transforming the global economy. Today about one fourth of total global production is exported. Understanding this transformative process is important because trade has generated gains, but it has also had important distributional consequences.
From a historical perspective, there have been two waves of globalization. The first wave started in the 19th century, and came to an end with the beginning of the First World War. The second wave started after the Second World War, and is still continuing.
The private sector is increasingly interested in ensuring that free trade is protected and helps support business opportunities including entry and growth for SMEs and MSMEs as well as participation in global value chains.
Donors contribute to WBG trust funds that support trade and investment climate. Countries are increasingly turning to the World Bank Group for advice on trade and, more widely, on investment climate reform to ensure competitiveness.
The WBG has an opportunity to contribute by sharing the technical evidence that helps developing countries make sound policy decisions on trade and investment climate-related issues that will be critical for future growth and poverty reduction. This milestone presents an opportunity for the World Bank Group to further assist countries to design practical reform strategies — and their implementation — to pursue poverty reduction and shared prosperity. This page in: EN dropdown. Results Briefs April 3, Email Print.
Tweet Share Share LinkedIn. Stumble Upon. Trade is central to ending global poverty. Countries that are open to international trade tend to grow faster, innovate, improve productivity and provide higher income and more opportunities to their people.
Open trade also benefits lower-income households by offering consumers more affordable goods and services.
Integrating with the world economy through trade and global value chains helps drive economic growth and reduce poverty—locally and globally. These projects and others help create a global trading system that is more open, reliable and predictable for all. Challenge Although globalization and trade present new opportunities, it is not without challenges. Using TiVA, we can better identify how much value each country and industry adds to a final product along the global supply chain.
This approach provides a much more accurate picture of trade balances between countries and the contribution of trade to income and employment. This new sharing of production across countries has enabled many more countries to participate in global trade, with developing countries increasing their share of global exports and imports. While the new environment for trade creates new opportunities, it also increases the costs of trade barriers.
When goods and components cross borders many times in GVCs, even small tariffs can add up, and the costs of inefficient border procedures are multiplied. Trade facilitation —the transparent, predictable and straightforward procedures that expedite the movement of goods across borders — is becoming ever more important, and is especially critical for trade in perishable agricultural products or high-tech manufacturing components, both of which are highly sensitive to delays.
Trade facilitation is becoming even more important in the digital era. TiVA data also highlight how important services are to global trade. Even though services generate more than two-thirds of global GDP, employ the most workers in major economies, create more new jobs than any other sector, and are critical to competitiveness, obstacles to trade in services remain pervasive.
Regulatory reforms and liberalisation of trade and investment in services are needed to enhance competition and increase the productivity and quality of services.
Indeed, international trade can be strongly impacted by non-tariff barriers that originate from domestic regulations, or from limitations to foreign investment. The challenge is to meet policy objectives in ways that maintain the gains from trade. Digital techonologies and related new business models are also now changing the way we trade.
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