When people use statistics to investigate a problem or support a hypothesis, they often want to make comparisons. They may examine changes over time, look at different parts of a country, or compare figures from different countries. To be sure that they are not comparing apples with oranges, they need to be confident that the different figures they compare are measuring the same thing in the same way.

For example, if we want to know which part of the country has the highest level of youth unemployment, we need to be sure that the statistics for each different area count people in the same condition as being employed or unemployed. And we can’t compare a figure for 15-18 year-olds in one region with a figure for 16-25 year-olds in another.

The most efficient way to ensure fair comparisons is to establish standards, so that users don’t have to look up the precise details every time they use statistics. There are standards for concepts (what does ‘poverty’ mean?); for definitions (which people do we count as ‘living in a country’?); and for methods (how do we derive a final GDP figure from raw data?).

While any country could develop its own standards, it’s much more useful for end users – and efficient for those who produce them—if those standards can be made and shared across all countries. When we hear reports in the news about inflation and economic growth in different countries, for instance, we can safely assume that all of the figures use the same standards which have long been established internationally. And countries don’t have to spend lots of time and money figuring out how to define and calculate things for which standards already exist.

When producers of statistics use international standards, the task of ensuring transparency (principle 3) is made much easier, as they can point users to the standards, mitigating any risk of doubts about their approach. Without published international standards, statistical producers could be accused—rightly or wrongly—of manipulating their methods to produce favourable statistics, or simply of making accidental errors by not carefully developing concepts, definitions and methods. In the same vein, a commitment to international standards protects official statistics producers from deliberate or inadvertent outside influence. It might ‘look better’ if an indicator were calculated in a certain way, but a policy of strict adherence to internationally-agreed standards means that official statisticians can hold steadfastly to their principles and steer clear of such influence.

National Bureau of Statistics of the Republic of Moldova

Video produced by the National Bureau of Statistics of the Republic of Moldova, posted on Youtube at this link Article prepared by National Bureau of Statistics of the Republic of Moldova as part of the anniversary campaign published on this link