Why Doesn’t International Trade Data Add Up?

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November 18th, 2021

Trade statistics may be accurate. But if you don’t know which trade statistics are the most accurate, then this article is for you. We will discuss the reasons why there is so much discrepancy between different sources and what you can do about it.


By Arpit Saxena


If you walk into a supermarket and find Italian pizza, Mexican honey, and a bottle of South African wine, then you just experience some impacts of international trade. I have always been intrigued by international trade and how it allows countries to expand their markets and access goods and services that otherwise would not have been available domestically.


During one of my early escapades involving international trade research, I surveyed over a dozen “official sources” which provided international trade data. To my consternation, none of them agreed with each other. It was mind-boggling as I did not have any idea which one to believe! If you also had a similar experience, please spend a few minutes with me exploring why there are such large discrepancies between different sources of international trade data.


If you compare the data from these different sources, you will find that they are not in agreement with each other.


In 2010, China’s total estimated value of exports was $1.58 trillion as per the data provided by the WTO, whereas, it was $1.48 trillion according to World Bank Open Data. That’s a difference of $100 billion.


As per IMF data, the value of goods that Canada exported to the US was almost $20 billion more than the value of goods that the US reported importing from Canada.


Global Trends of International Trade from 1950 to 2020

The total international trade in 2019 stood at 19.014 trillion US dollars. This number had fallen to 17.582 trillion in 2020 as travel, and distribution services had decreased (due to the mobility restrictions and social distancing measures imposed for public health reasons), unavailability of labor to unload the ships at ports, and also limiting the mobility of workers affects a variety of trade processes, from physical inspection of goods for SPS(Sanitary and Phytosanitary) to testing, and certification for TBT(Technical Barriers to Trade). These services are not expected to recover until the pandemic weakens.


During the global recession of 2008 to 2009, international trade collapsed. The real-world trade fell by about 15%, exceeding the fall in world GDP by roughly a factor of 4.


Figure- 1

Source: Statista


More than 12 major international organizations report on the international trade data

Carrying out the trade at an international level is way more complex when compared to a domestic one because it involves numerous factors such as government policies, economy, judicial laws, and currency.


To make the process of international trade more comfortable, various trade organizations were formed. These organizations work towards the growth of international trade as they ensure trade flows smoothly and as freely as possible (this is done by administering trade agreements, cooperating with international organizations, resolving trade disputes, etc.). It also helps in reducing trade barriers. (For example Tariffs, and Non-tariffs barriers, shifting rates, etc.)


Figure- 2

Source: Our World in Data


Reasons for Disparity in measuring international trade statistics


All of the various data sources(refer to figure-2) measure the same thing (the value of goods data from one country to the rest of the world) and also the value of exported goods, expressed as the share of national GDP. Still, different data sources tell different stories.


Many countries still stick to FOB (free on the board) for export values and CIF (Cost, Insurance, and Freight) for importing the goods. Generally speaking, the export of goods from country A to country B  should be the same as the imports of country B from A but in reality, that is not the case.


Figure- 3

Source: Our World in Data


The difference between the value of goods imported by the US from other countries to the value of goods exported from other countries to the US.


If all the asymmetries were coming from CIF-FOB differences, then all the values that we see in the chart would be positive (Note: Unlike FOB values, CIF includes all the cost of transportation, so that’s why CIF values are larger than FOB). But as we can see in the chart, there are both positive and negative values.


So, what’s going on? 


Some issues come up when comparing trade data from various sources:

  1. The difference in export and import valuation: Are the transactions valued in FOB or CIF prices? 

  2. Inconsistent attribution of trade partner: How are the origin and final destination of merchandise established?

  3. The difference in underlying records: Is trade measured from National Accounts data rather than directly from custom or tax records? 

  4. Differences occur in exchange rates: How are values converted from local currency units to the currency that allows international comparisons (commonly used US-$)?

  5. Other Issues: Time of recording, product classification, and manipulating the prices.


Organizations that came up with the approach to prevent asymmetries in Trade data


The factors that are mentioned above are the reasons for having asymmetries in international trade statistics. Indeed, international organizations have often incorporated corrections, in an attempt to improve the trade data.


For example, OECD uses its own approach to correct and adjust the international merchandise trade statistics. The corrections applied in OECD’s balanced series make it the best source for cross-country comparisons.


The countries across the world have chosen to rely on CEPII(Centre d’Etudes Prospectives Et d’Information Internationales) as the main source for exploring long-run changes in international trade but also rely on World Bank and OECD data for up-to-date cross-country comparisons.


There is no obvious way of choosing between sources. This interpretation of data is not appropriate, since the mismatches in the data can, and often do arise from the inconsistencies in measurement rather than malfeasance.


The views expressed in this article are those of the author alone and not the WorldRef.


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