High income: nonOECD vs Peru: Goods, Credit/Revenue (Share of Goods Exports in Total Exports)
Goods, Credit/Revenue (Share of Goods Exports in Total Exports) over time
- High income: nonOECD
- Peru
How they compare
Peru currently reports 90.45 against 60.67 in High income: nonOECD, a difference of 29.78.
That makes Peru's figure about 1.5 times High income: nonOECD's.
Across all 5 years both countries report, Peru has been ahead every year.
High income: nonOECD ranks 11th and Peru ranks 10th of 12 groups.
Peru has averaged higher in every one of the 5 decades both report.
Head to head by decade
| Decade | High income: nonOECD | Peru | Difference | Ahead |
|---|---|---|---|---|
| 1970s | 66.94 | 82.94 | 16 | Peru |
| 1980s | 64.99 | 80.56 | 15.57 | Peru |
| 1990s | 64.63 | 82.75 | 18.12 | Peru |
| 2000s | 63.61 | 88.96 | 25.35 | Peru |
| 2010s | 60.67 | 90.45 | 29.79 | Peru |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher goods, credit/revenue (share of goods exports in total exports), High income: nonOECD or Peru?
- Peru, at 90.45 against 60.67 in High income: nonOECD as of 2014.
- What is the difference in goods, credit/revenue (share of goods exports in total exports) between High income: nonOECD and Peru?
- 29.78, with Peru ahead.
- How many years of comparable data are there for High income: nonOECD and Peru?
- 5 years are reported by both, from 1979 to 2014.
- How do High income: nonOECD and Peru rank globally for goods, credit/revenue (share of goods exports in total exports)?
- High income: nonOECD ranks 11th and Peru ranks 10th of 12 groups.
- Where does this data come from?
- International Monetary Fund, published as Goods, Credit/Revenue (Share of Goods Exports in Total Exports, Period Average (end-of-period)). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
Using the IMF’s Balance of Payments Statistics database as a source, the statistics provided here are the first of its kind providing a compilation of detailed historic and new data on world trade in services. This can be a useful resource for researchers, policymakers and businesses for decisions in macroeconomic competitiveness and understanding how technological forces are affecting rapid resource reallocation in specific sectors. The dataset covers exports of services from 1970 to 2014. See reference Loungani, Mishra, Papageorgiou, Wang (2017). There is ongoing work to extend the dataset, which will be made available in the future.