Mongolia vs Philippines: Balanced international merchandise trade statistics (BIMTS)

Mongolia
0.1731 US dollars, exchange rate converted
in 2016
Philippines
0.2526 US dollars, exchange rate converted
in 2024
Mongolia rank
54th
Philippines rank
51st

Balanced international merchandise trade statistics (BIMTS) over time

  • Mongolia
  • Philippines
0123199520092024

How they compare

Philippines currently reports 0.2526 US dollars, exchange rate converted against 0.1731 US dollars, exchange rate converted in Mongolia, a difference of 0.0795 US dollars, exchange rate converted.

That makes Philippines's figure about 1.5 times Mongolia's.

Across all 8 years both countries report, Philippines has been ahead every year.

Mongolia ranks 54th and Philippines ranks 51st of 96 countries.

Philippines has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Mongolia Philippines Difference Ahead
1990s 0.0171 US dollars, exchange rate converted 1.56 US dollars, exchange rate converted 1.54 US dollars, exchange rate converted Philippines
2000s 0.0033 US dollars, exchange rate converted 0.6805 US dollars, exchange rate converted 0.6772 US dollars, exchange rate converted Philippines
2010s 0.0599 US dollars, exchange rate converted 0.202 US dollars, exchange rate converted 0.142 US dollars, exchange rate converted Philippines

Averages of every year both report within each decade.

Frequently asked questions

Which has higher balanced international merchandise trade statistics (bimts), Mongolia or Philippines?
Philippines, at 0.2526 US dollars, exchange rate converted against 0.1731 US dollars, exchange rate converted in Mongolia as of 2024.
What is the difference in balanced international merchandise trade statistics (bimts) between Mongolia and Philippines?
0.0795 US dollars, exchange rate converted, with Philippines ahead.
How many years of comparable data are there for Mongolia and Philippines?
8 years are reported by both, from 1997 to 2016.
How do Mongolia and Philippines rank globally for balanced international merchandise trade statistics (bimts)?
Mongolia ranks 54th and Philippines ranks 51st of 96 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Balanced international merchandise trade statistics (BIMTS) - HS2017-2D. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Mongolia vs Philippines: Balanced international merchandise trade statistics (BIMTS). Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 23 August 2026, from https://economy.statizoid.com/compare/balanced-international-merchandise-trade-statistics-bimts-hs2017-2d/mongolia/philippines/

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About this data

Indicator
Balanced international merchandise trade statistics (BIMTS) - HS2017-2D
Unit
US dollars, exchange rate converted
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
112 places, 2,446 data points, 1995–2024
Last refreshed

The OECD Balanced International Merchandise Trade Statistics (BIMTS) dataset provides a complete, consistent, and balanced matrix of international merchandise trade statistics. It includes annual bilateral data for approximately 200 reporters and partners, covering around 98 products in HS2017 at the 2-digit level from 1995 to 2024. BIMTS is also available in the HS 2017 classification at 4-digit and 6-digit levels of aggregation currently available via the Related Files (bottom of the page) and also in the Statistical Classification of Products by Activity (CPA 2.1) at the 2-digit level of aggregation. BIMTS is complete and consistent. The OECD methodology leverages all available official statistics and combines them with estimations and adjustments to provide users with a complete matrix covering virtually all economies in the world. To provide users with consistent and long time series, the data is presented according to either HS2017 or CPA 2.1. BIMTS is balanced. The OECD has developed a transparent approach to reconcile asymmetries in international merchandise trade statistics. A sequence of adjustments, documented in the BIMTS technical paper, significantly reduces asymmetries in the dataset before the final balancing procedure is performed. An important feature of BIMTS is a novel algorithm which identifies re-export flows and reallocates them to the producer countries before the balancing. To avoid double counting of flows between producers and trade hubs (already accounted for in the trade between producers and final users), BIMTS breaks down the final balanced values into a domestic component and a re-exports component. Users will therefore find two different measures of balanced trade flows (under the ‘Adjustment’ dimension): Total balanced value: Represents the total reconciled bilateral trade flow, including re-exports. Balanced value adjusted for re-exports: Represents the reconciled bilateral trade flow, adjusted for re-exports. This adjusted value is deemed to more accurately reflect economic reality and is therefore the preferred measure. In this database, the Reference area denotes the exporter, while the Counterpart area denotes the importer. Because the data are balanced, exports from the exporter to the importer equal imports by the importer from the exporter, and the flow is therefore recorded only once. Note that zero trade flows are represented in BIMTS as missing records (marked as “..”). This approach reduces the dataset size and improves processing times in the OECD Data Explorer. For convenience, users can also retrieve data for total merchandise (“_T”, denoting all products) and partner world (“W”). BIMTS will be regularly updated and continually improved as new data becomes available. For more information on: The methodology: The OECD Balanced International Merchandise Trade Dataset (BIMTS). Balanced trade statistics related pages: Balanced trade statistics, or The statistics compiled by the OECD Statistics and Data Directorate Users are encouraged to send their questions, or to signal any apparent errors, regarding this database to STAT.Contact@oecd.org