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Data Quality Scores

National Footprint Accounts use internationally available data from multiple datasets for all countries for each year going back to 1961. In some cases data may be limited, unavailable, or may contain apparent errors. While the accounts include some data error improvement and estimation of missing data, results for countries and/or years are inevitably of variable reliability. As part of the completion of each edition of the National Footprint Accounts, Global Footprint Network researchers assess a level of confidence in the final results for each country, as follows:

Criteria for qualifying NFA results and the implications of the data quality scores for publication of results:

Each country in the National Footprint Accounts 2018 Edition is given a quality score comprised of two elements, time series score [1-3] and latest year score [A-D].

ScoreCriteria and Implications
3ANo component of BC or EF is unreliable or unlikely for any year.
3BNo component of BC or EF is unreliable or unlikely for the latest data year.

Some individual components of the EF or BC are unlikely in the latest data year.

The total EF and BC time series results are not significantly affected by unlikely data.

3CNo component of BC or EF is unreliable or unlikely for the years prior to the latest data year.

Some individual components of the EF or BC are unlikely in the latest year.

Total EF and BC values are unlikely or unreliable in the most recent data year, but the ability to ascribe creditor/debtor status is unaffected in latest year.

3DNo component of BC or EF is unreliable or unlikely for the years prior to the latest data year.

Some components of the EF or BC are very unlikely in the latest year.

EF and BC results in the latest year are significantly impacted by the unlikely or unreliable values, making them unusable.

2AEF or BC component time series have results that are very unreliable or very unlikely, except in the latest data year.

The total EF and BC time series results are not significantly affected by unlikely data.

No EF and BC results in the latest year are significantly affected by unlikely data.

2BEF or BC component time series have results that are very unreliable or very unlikely, including the latest year.

The total EF and BC time series results are not significantly affected by unlikely data.

2CTotal EF or BC time series and component EF and BC time series results are unreliable or unlikely, especially in the latest year.

The total EF and BC time series results are not significantly affected by unlikely data.

The unlikely or unreliable values have most likely not impacted the creditor/debtor status in the latest year.

2DTotal EF or BC time series and component EF and BC time series results are unreliable or unlikely, especially in the latest year.

The total EF and BC time series results are not significantly affected by unlikely data.

EF and BC results in the latest year are significantly impacted by the unlikely or unreliable values, making them unusable.

1ASeveral components of the EF or BC are very unreliable or unlikely, except the latest year.

The EF and BC time series results are significantly affected by unlikely data, and are unusable.

No EF and BC results in the latest year are significantly affected by unlikely data.

1BSeveral components of the EF or BC are very unreliable or unlikely, except the latest year.

The EF and BC time series results are significantly affected by unlikely data, and are unusable.

The total EF and BC results in the latest year are not significantly affected by unlikely data.

1CSeveral components of the EF or BC are very unreliable or unlikely.

The EF and BC time series results are significantly affected by unlikely data, and are unusable.

The unlikely or unreliable values have not impacted the creditor/debtor status.

1DThere is too much unreliable or unlikely data to make any conclusions about the timeline or latest year of this country.

Note: Through further nation-specific research, preferably in collaborations with researchers from those countries (particularly from government agencies) it is possible that the Data Quality score (i.e., the quality of the results) can be improved. Improved data sets, methodological improvements in the National Footprint Accounts, and better data cleaning processes have also helped to increase the Data Score of some country results in past Editions, as is likely in the future.

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