Chapter 4 Methodological considerations
Experimental data series
Disclaimer is added to all data tables.
This table, derived from various international data sources, reflects values as reported by Member states. Although it is still in experimental phase and requires further refinement, this statistical series developed by UNCTAD offers insights into gender-in-trade patterns. The data set is labeled as experimental; ongoing testing and development may result in some uncertainties. The user’s feedback is crucial for enhancing accuracy and reliability. Additionally, earnings and employment data reports may have discrepancies due to the differences in reporting of national data, requiring careful analysis, especially at the country level.
Breaks in series
Due to the methodology used to classify industries by export intensity or dependence, there may be breaks in the series by country. Since export intensity/dependence is calculated annually for each country, some industries may shift between categories from one year to another if their export share fluctuates around the defined thresholds. This can result in variations in the employment shares and average earnings reported for each export intensity/dependence category over time.
Dependence on data sources
The frequency of data updates depends on the underlying sources. While ILO data is updated as new reported data becomes available, the OECD TiVA database is updated irregularly, typically on a biennial basis, as it serves as an analytical tool. As a result, the regular updates of the data tables may be affected by the availability of new TiVA data, potentially leading to delays in data production.
The country-specific data are official statistics as reported by countries. Earnings and employment statistics present several complications in terms of their international comparability, most of which arise from the variety of possible data sources. The various sources available – establishment surveys, household surveys and administrative records – differ in their methods, objectives and scope, which influences the results obtained. Thus, potential discrepancies can be identified due to a) discrepancies in data sources; b) classification of activities used by a country; c) informal employment; d) coverage of data source (geographical coverage, economic activities covered, types of establishments covered, etc.); e) working-age population definition.