Google is not using those sub-national divisions (region), that the EU or OECD is using for statistical purposes. This means that any comparison of Google’s Mobility Reports with population, transport, public health, or economic variable requires a sub-national division vocabulary for translation, or in the EU parlance a correspondence table.
Google appears to be using, at least in most of the cases, the
ISO-3166-2 sub-national divisions from the ISO 3166 Codes for the representation of names of countries and their subdivisions with non-standard naming (labels). When we want to analyse the Google Mobility Report together with national statistics, this causes several problems:
ISO-3166-2 is not a hierarchical typology, while Europe’s statistical typologies, the
NUTS3 are hierarchical, so we had to create many hundred lines of
R code to create the necessary descriptive metadata for joining the
ISO-like Google and the
NUTS typologies of Europe.
ISO-3166-2 is changing very fast, within Europe there are many changes every year; however, these changes are not so easy to trace as the changes within the European statistical nomenclature (NUTS). We are unsure how Google handles changes in
ISO-3166-2 over the coverage of the Mobility Reports.
Google is not using either the machine-readable, alphanumeric
ISO-3166-2 codes or the official (Latin) labels, instead it uses a quasi-English unofficial labelling, which requires manual identification of Google’s typology items.
A bit exotic example, Réunion, or, as France calls it, La Réunion, shows some of the statistical impracticalities of the non-hierarchical
ISO-3166 codes. Google used the RE
ISO-3166-1 country code and the corresponding label Réunion to identify the small island in the Indian ocean. However, as a part of France (and the European Union), it is also described in France’s
FR-LRE, labelled La Réunion as an overseas region, and as
FR-RE, as an overseas department. The distinction mirrors France’s administrative laws, and matches the rows in Google’s reports with three potential
ISO-3166 codes. If we want to join Google’s data with regional statistical data from French or EU official tables, we have to use code
FRY4 from the Frech
There are some very small sovereign states that do not have any
NUTS divisions. Luxembourg is not divided (
LU000). Our package can project the national data given by Google to any
NUTS level, so that these part of Europe fall into the right place on country,
NUTS3 level data tables, too.
However, in most cases, the
NUTS typology is hierarchical. If we take the example of Malta, which is the smallest member state with the least number of possible divisions (exactly two:
MT001 refers to the main island of Malta and
MT002 refers to the smaller islands of Gozo and Comino.) We know that in the hierarchy
MT002 belongs to
MT00, which belongs to
MT0, which belongs to the country Malta (
MT). Therefore, if we have a bit of ambiguity with a territory, we can still roughly place it, if we at least know at what level would it fit to Europe’s map. In Malta’s case, Google did not divide the country, so we know that Google’s data refers to
MT00, which makes matching with any national (
NUTS2 level data table possible, although we cannot directly match with
NUTS3 tables which separate
MT002. In this case, we have to use
impute_down_nuts() to impute (project) the
MT00 data to
Google provided extremely detailed data for some small countries like Estonia and Latvia, because the
ISO-3166-2 subdivisons of these relatively small countries are very small, i.e. usually smaller than the
NUTS3 statistical regions. These countries, due to their size, are not divided in
NUTS2 levels (
EE00), but they have statistical subdivisions on
NUTS3 level. The
ISO-3166-2 used by Google tend to be on a lower level (
NUTS earlier contained a
NUTS4 typology, but it was very impractical to use, because divisions at this level tend to change very quickly, and the creation of statistical aggregates is not always possible. For example, it would clearly not be possible disaggregating the GDP in a meaningful to such small territorial units.
Because most Eurostat data is available only on
NUTS2 level, we can simply use the
LV data from Google and project it to the technical
LV00 (both identical to the country itself.) If we would want to match Estonia’s and Latvias data with
NUTS3 levels statistical tables, we would have to created weighted averages from Googles sub-NUTS3 regions for these countries.
In the case of small non-EU member states we applied the same logic, although these countries are at the moment not part of the official NUTS nomenclature. For example, we made Andorra
AD00. Eurostat’s regional data products usually do not contain data from Andorra, but the national data tables sometimes do, and this data can be safely projected down to the identical technical
NUTS1 “region” of
AD0 or the technical
NUTS2 region of
Some non-EU member states, such as Liechtenstein, Norway, Iceland (the European Economic Area), or (potential) EU member canidates on the Balkans, i.e. Albania, Montengro, North Macedonia, Serbia are becoming part of the EU
NUTS2021, which is already defined but not yet used, and currently they have
NUTS equivalent codes.
Cyprus is unfortunately not present in the Google Mobility Reports.
In many cases the
ISO-3166-2 subdivisions used by Google correspond to some
NUTS typology elements. After figuring out the correct
NUTS typology for the Google rows, we can aggregate up
NUTS3 level data or project down
NUTS1 data to the
NUTS2 level, which is the most likely level for practical statistical analysis. In some cases, the
ISO-3166-2 correspond to earlier definitions of
NUTS. We could have chosen to try to match currently non-matched
NUTS2003 definitions, and then try to use a time-wise correspondence among
NUTS definitions. If we did not find an equivalence with any elements of the
NUTS2016 definitions, we probably could have found it in the historical
NUTS2010 or other typologies, and could have tried to use our timewise-correspondence to find an equivalent. Even if there is a formula that connectes a
NUTS2016 typological element to various
NUTS2003 elements, and thus via
ISO-3166-2, it would require an almost case-by-case programming to exploit this connection, given that there are many possibilities in time-wise correspondents (see vignette: Working With Regional, Sub-National Statistical Products). Instead we used some simplifications when the
ISO-3166-2 and the currently used
NUTS1016 typology do not match.
In some cases, Google merged certain statistical regions of Europe. For example, following the ISO-3166-2- subdivisions of Italy the culturally autonomous, partly German speaking part of Italy was merged into a single unit (
IT-32, with Italian labelling Trentino-Alto Adige and with German labelling Trentino-Südtirol, but Google used an unofficial English labelling), even though these are two undivided
NUTS2 regions, i.e. Trentino
ITD20 and Alto Adige / Südtirol (South Tyrol for Google)
ITD10. In this case, comparison is possible, but requires addition or weighting between EU statistical units for joining with Google data. We gave the
ITDX to Trentino-South Tyrol, which clearly identifies the region as part of
ITD for Northeastern Italy, and of course as part of
IT or Italy.
For simplicity, we treated some of these historical regions identical to a current one, if the difference was very small. For example, Bragança district in Portugal (in
PT-04) was coded as
PT11E, because it is almost identical to the
NUTS3 region Terras de Trás-os-Montes.
In other cases, when Google’s typology cuts across current European statistical region lines, we again chose the creation of
pseudo-NUTS codes. For example, we created the irregular
PT11X for the Braga district of Portugal (in
PT-03), because it is certainly part of
PT11 Norte, and the technical
PT for Portugal, but it does not correspond to any
NUTS3 units of Portugal in the
NUTS2016 definition. This coding will not pass the
validate_nuts_code() function, but it certainly gives a strong starting point for data imputation.
We faced many such problems with Portugal and Wales within Great Britain in the United Kingdom.