The trade data mismatch of India and China has attracted wide coverage from both electronic and print media. This mismatch is attributed to ‘under-invoicing’ by Indian importers for the imports originating from China.
There is mismatch of $12 billion with China reporting its exports to India over $103 billion. Indian agencies, on the contrary, are reporting their Chinese imports at $92 billion. This reflects significant asymmetries in international trade statistics, and they can occur for a variety of reasons. This needs understanding of not only the conceptual discrepancies across measurement standards but also of established norms of data collection, tabulation, curation and presentation, which may also lead to potential discrepancies in trade data.
Additionally, one needs to understand trading practices, logistics channels and cross-country trading patterns due to financial, operational and logistical ease of a particular country.
These discrepancies in international trade statistics can result in ill-informed policy decisions. Under-invoicing, as reported, can be only one reason among many others for trade data anomalies.
Firstly, a large number of firms based in India have started the ‘Merchanting Trade’ business as allowed by RBI. In Merchanting Trade Transactions (MTTs) shipment of goods takes place from one foreign country to another without touching India’s customs water i.e. DTA area. To reap trading advantages of Chinese low cost goods in international markets, Indian firms buy goods from China and sell them in international markets under ‘bill to-ship to’ model wherein payments are made by Indian firms to a Chinese exporter.
But actually, these goods end up in a third country with a top-up margins for an Indian firm (re-exporter/re-router). This has been the common practice in Fast Moving Consumer Goods trade in India-China trade in recent years. Similar, to MTT, under ‘switch-bill of lading’, Indian firms buy goods from China and re-route them to third country, leading to trade data asymmetries.
Secondly, there can be instances of High Sea Sale (HSS) transactions, especially for standardised, speculative and bulk goods. For instance, an Indian trader buys chemicals and plastics from China and sells them on HSS basis to a third party in a third country, say in Australia.
In Chinese Trade Statistics, these are recorded as exports to India but the goods never enter India’s territorial waters as they are diverted to third countries on High Sea Sales (HSS) basis, thus this is not reported in India’s trade statistics. HSS transactions witnessed a jump due to supply-chain disruptions caused by Russia-Ukraine war and Indian firms are aggressively scouting for such trading opportunities.
Thirdly, Indian trading firms are leveraging Free Trade & Warehousing Zones to engage internationally. These firms buy bulk goods from China and maintain inventory at FTWZ locations and sell them in a piecemeal manner i.e. selling small quantities at higher profit margins.
For example, a unit located at FTWZ in Chennai buys metals from China, anchoring its business model supported by ‘bulk-price & logistical efficiency arbitrage’ model and subsequently re-export these goods in the third countries. Chinese Statistics will record it as exports, but for India it is not imports as the goods are kept at a FTWZ, a foreign territory, as defined under the SEZ Act, 2005.
In the statistical recording terms, it is known as intermediary merchanting transactions i.e. difference between ‘goods’ and ‘merchandise’ vis-a-vis reporting of re-importing, re-exporting, and re-routing.
Fourthly, the mismatch in trade statistics also happens due to maintenance of records of export statistics on ‘Free-on-Board’ (FOB) and that of import statistics records on Cost, Insurance & Freight (CIF) basis. Looking at the India-China trade statistics, this potentially is not the case as CIF values are always more than that of FOB values.
Fifthly, there can be trade data mismatch due to inconsistent attribution of trade partners; that is how the origin and final destination of merchandise established are dealt with in their Customs Administration. For instance, a country may record statistics on goods destined to claimed territories as ‘others’ instead of reporting it as an exports to an actual country.
Need for broad outlook
Additionally, as China has resorted to yuan-invoicing post Russia-Ukraine war fearing potential use of financial instruments as an economic weapon against it in future. But how are values converted from local currency units to the currency that is used to make the international comparisons most often the US dollar?
Moreover, there can be national differences on reporting of underlying records i.e. statistical norms and standards used to compile trade statistics. It is therefore, inappropriate draw the conclusion that there is wide scale under-invoicing of imports in India. Indian Customs have robust systems in place to safeguard the national interests and trade data mismatches are caused by many factors, under-invoicing only being one among them.
But there is always scope to improve and one can refer to guidelines of International Merchandise Trade Statistics Manual (IMTS). Beyond guidelines, it is important to distinguish between ‘traded merchandise’ and ‘traded goods’.
A micro-level but a comprehensive overview at Indian Customs and RBI trade statistics can help us understand the actual reasons for mismatch of trade data.
Ram Singh, Professor & Head, IIFT New Delhi, Surendar Singh, Associate Professor, FORE School of Management, New Delhi. Views expressed are personal