Measuring the internet economy in The Netherlands a big data analysis 2016 | 14

To show, by proof of concept, the possibilities of new measurement methods for producing
statistics.
The internet is one of the most promising avenues for big data collection and thus for
increasing the availability of timely and relevant data. This study has made an important step
in demonstrating how big data from the internet can be combined with existing standard data
sources in order to further capitalise on the valuable insights provided by big data from the
internet. We have developed a complex linking methodology (based on different linking key
combinations) which facilitates an optimised link between big data from the internet and the
other standard sources. While there are many challenges to overcome in combining big and
standard data sources (which will be discussed later), this study has shown that meaningful
and novel insights can indeed be generated in this way. The fourth research aim is:
To explain differences from standard statistical concepts/classifications and existing statistics.
As has already been mentioned, the standard method for studying particular sectors of the
economy is to rely on the SIC codes. The methodology in this study begins not by classifying
businesses, but by classifying websites. The classification of businesses is made on the
basis of the classification of the websites which link to the business. This is a fundamentally
different statistical approach to classifying businesses.
In section 3, we have discussed definitions which are related to the concept of the internet
economy. In some cases, the definition used in this study (henceforth ‘our definition’) defines
an internet economy which can be loosely thought of as ‘subset’ of the internet economy
conforming to other definitions. In other cases, there is overlap between our definition and
other definitions, but neither can be considered a subset of the other. Our definition defines
an internet economy which is a subset of the internet economies derived by NIESR and
Growth Intelligence (2013) and the OECD (2013). In the case of NIESR and Growth Intelligence
(2013), our definition results in a subset because it exclude digital activities not related to the
internet. In the case of OECD (2013), our definition results in a subset because it excludes the
social and cultural values of the internet. The definitions employed by CBS (2016) of the ICT
economy and of the Boston Consulting Group (2011), define economies which overlap with
the economy resulting from our definition. In the cases of the CBS ICT economy definition,
this is because only the internet related elements of the ICT economy are included in our
definition. In the case of the Boston Consulting Group, it is more challenging to identify the
source of the overlap because their definition is a macro-data approach instead of the microdata
approach adopted in this study. In any case, the definitions share some conceptual
similarities. On this basis, we can expect overlap. Finally, the central research question is:
To explore the possibilities to deepen our understanding of the importance of the internet
economy.
In this study, we have employed a method which demonstrates how it is possible to gain
insights into the internet economy by combining existing CBS micro-data with big data
available from the internet. To properly explore the possibilities, we need to analyse the
strengths and weaknesses of this method.
CBS | Discussion Paper, 2016 | 14 42