Montserrat vs Sao Tome and Principe: Balanced trade in services

Montserrat
0.0692 US dollars, exchange rate converted
in 2024
Sao Tome and Principe
0.046 US dollars, exchange rate converted
in 2024
Montserrat rank
170th
Sao Tome and Principe rank
172nd

Balanced trade in services over time

  • Montserrat
  • Sao Tome and Principe
0.020.040.06200520142024

How they compare

Montserrat currently reports 0.0692 US dollars, exchange rate converted against 0.046 US dollars, exchange rate converted in Sao Tome and Principe, a difference of 0.0232 US dollars, exchange rate converted.

That makes Montserrat's figure about 1.5 times Sao Tome and Principe's.

Across all 20 years both countries report, Montserrat has been ahead every year.

Montserrat ranks 170th and Sao Tome and Principe ranks 172nd of 174 countries.

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

Head to head by decade

Decade Montserrat Sao Tome and Principe Difference Ahead
2000s 0.0446 US dollars, exchange rate converted 0.0145 US dollars, exchange rate converted 0.0301 US dollars, exchange rate converted Montserrat
2010s 0.0474 US dollars, exchange rate converted 0.0318 US dollars, exchange rate converted 0.0156 US dollars, exchange rate converted Montserrat
2020s 0.0533 US dollars, exchange rate converted 0.0354 US dollars, exchange rate converted 0.018 US dollars, exchange rate converted Montserrat

Averages of every year both report within each decade.

Frequently asked questions

Which has higher balanced trade in services, Montserrat or Sao Tome and Principe?
Montserrat, at 0.0692 US dollars, exchange rate converted against 0.046 US dollars, exchange rate converted in Sao Tome and Principe as of 2024.
What is the difference in balanced trade in services between Montserrat and Sao Tome and Principe?
0.0232 US dollars, exchange rate converted, with Montserrat ahead.
How many years of comparable data are there for Montserrat and Sao Tome and Principe?
20 years are reported by both, from 2005 to 2024.
How do Montserrat and Sao Tome and Principe rank globally for balanced trade in services?
Montserrat ranks 170th and Sao Tome and Principe ranks 172nd of 174 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Balanced trade in services (BaTIS). Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

Montserrat vs Sao Tome and Principe: Balanced trade in services. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 06 September 2026, from https://economy.statizoid.com/compare/balanced-trade-in-services-batis/montserrat/sao-tome-and-principe/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under OECD Terms and Conditions (attribution required); please keep the attribution.

<a href="https://economy.statizoid.com/compare/balanced-trade-in-services-batis/montserrat/sao-tome-and-principe/">Montserrat vs Sao Tome and Principe: Balanced trade in services</a> — Statizoid

About this data

Indicator
Balanced trade in services (BaTIS)
Unit
US dollars, exchange rate converted
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
200 places, 3,969 data points, 2005–2024
Last refreshed

The OECD-WTO Balanced Trade in Services (BaTIS) dataset is a complete, consistent, and balanced matrix of international trade in services statistics (ITSS). It contains annual bilateral data covering 202 reporters and partners, broken down by total services and 26 EBOPS 2010 (BPM6) categories from 2005 to 2024. BaTIS is the result of joint efforts by the OECD and WTO. Two main features enable BaTIS to stand out as the international benchmark for any analysis on international trade in services: BaTIS is complete and consistent. At present, only around 65% of world trade in services is bilaterally specified, and the percentage is even lower for the individual service categories. The OECD-WTO 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. BaTIS is balanced. To resolve the asymmetries between reported and mirror flows, exports and imports are reconciled by calculating a symmetry-index weighted average between the two, following a similar approach to that developed for international merchandise trade statistics. Batis provides three measures for each trade flow (under the ‘adjustment’ dimension): Reported. Reflects the value officially reported by the country (where available), some values are rescaled to fit world totals. Adjusted and/or imputed. Reflects, in addition to the reported values, any adjustments made to ensure internal consistency as well as the estimations made by the OECD-WTO to fill in the gaps in the reported information. Balanced. Reflects the reconciled bilateral trade flow, where exports equal mirror imports. Official information on bilateral trade flows was collected from OECD, Eurostat, national sources as well as UNSD. The WTO-UNCTAD trade in services dataset, based on a number of primary sources complemented with estimations, was the main source for data with partner world. The BaTIS dataset can be used as a stand-alone input for economic analysis and policy-making. In addition, balanced trade in services data form an essential input to the OECD Trade in Value Added (TiVA) initiative, for which a balanced view of international trade is crucial. BaTIS is intended to be regularly updated and constantly improved as new data become available. For more information on the methodology, please refer to the technical paper accompanying this dataset The OECD-WTO Balanced Trade in Services (BaTIS) For more information on balanced trade statistics, please go to the topic related OECD page Balanced trade statistics Users are encouraged to send their questions, or to signal any apparent errors, regarding this database to STAT.Contact@oecd.org https://www.oecd.org/en/about/directorates/statistics-and-data-directorate.html