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Census results of great significance: numbers of inhabitants - Part 6: Statistics

We statisticians are also waiting for the results of the 2011 Census. After all, many sets of statistics are based on official numbers of inhabitants. In the last part of our series we will therefore give you two examples illustrating the role which official numbers of inhabitants play in statistics and why current data are needed on the German population.

Example 1: Microcensus

The microcensus is the official representative statistics of the population and the labour market in Germany. By surveying about 1% of the population each year, the microcensus continuously provides information on a wide range of topics – for instance on household and family structures, the labour market situation and employment, education and (further) training, migration background and income situation.

To make sure that the results of the microcensus really are representative, respondents are selected at random by a sampling procedure which ensures that all households have the same inclusion probability. Sample areas are chosen from the entire federal territory based on the numbers of inhabitants, and all households and persons living there are surveyed.

The results of these interviews are extrapolated to all inhabitants using numbers of inhabitants. This means that the microcensus draws upon the official number of inhabitants both at the beginning and the end of the survey. In other words: without numbers of inhabitants as a basis for sampling and subsequent extrapolation, there would be no such sample-based statistics as the microcensus.

The sample areas used for the microcensus are still defined on the basis of data material from the 1987 Population Census; a comparable sampling frame for the new Länder has been compiled by means of a specific “statistics” population register. The sample is updated using the statistics of building activity. This makes it quite clear that the bodies of official statistics urgently need current numbers of inhabitants to produce data of a permanent high quality.

Example 2: Gross domestic product (GDP)

Some sets of statistics can be compiled without there being any relationship to the number of inhabitants. The gross domestic product (GDP), the central indicator of growth and economic activity, is among the most popular ones. It measures the value of all goods and services produced in the domestic territory, provided they are not used as intermediate goods in the production of other goods and services.

The gross domestic product does not only serve as a basis of central political decisions and stocktaking but is explicitly referred to in the Maastricht Treaties pursuant to which the government deficit in the member states must not exceed 3% of gross domestic product. Government debt must not exceed 60% of gross domestic product.

And what relevance does the number of inhabitants have for that economic indicator?

It is quite simple: to make the level of well-being comparable at all in relation to the gross domestic products of different sized economies, the gross domestic product per inhabitant is calculated. This is common practice in European and international comparison so as to determine the overall economic activity and thus the stage of economic development. Funding granted from EU structural funds, for instance, also depends on the respective gross domestic product per inhabitant.


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