Measuring the Value of Data and Their Treatment in Macroeconomic Statistics

The paper studies the role of data as an economic asset in the digital economy. The research is focused on the development of an approach to comprehensive data valuation and their adequate treatment in macroeconomic statistics.
The first part of the paper reviews the major publications on the so-called Solow productivity paradox: the impact of digital technologies on the productivity growth slowdown. Considering points of view of various researchers, the author takes an opinion that the existing statistical methodology does not permit comprehensive measuring of the digital economy contribution to the productivity dynamics. At the same time, the author does not support the proposal to include the value of data generated by unpaid household activities in macroeconomic accounting and expand the scope of key macroeconomic indicators such as GDP.
In the second and the third parts the methods of data valuation used by companies as assets in production, as well as major discussed proposals on methods for measuring the value of data in macroeconomic statistics, are considered. These two aspects of data valuation are closely related, both informationally and methodologically. The author concludes that an increase in the need for the valuation of data at the micro level will inevitably lead to corresponding changes in the methodology of macroeconomic statistics.
The last part of the paper explores more elaborately the issues of data valuation as a non-produced asset. The need for such an approach is caused by the existing gap between the marketed assessment of the contribution of data to production and the existing possibilities for accounting for them at the costs of their production. In the author’s opinion, this is a promising direction, allowing to overcome the indicated gap. In support of this, the article provides examples of experimental calculations based on IFRS reports of four Russian companies involved in the production of digital services.
Experimental valuation of non-produced assets using the net present value method shows that the value of the non-produced assets involved in the production of data-driven companies differs from the values recorded in their financial statements. This, in particular, occurs due to the underestimation or overestimation of the value of the data used in production, which, according to the author, constitutes the bulk of the unidentified unproduced assets of digital companies.
The author concludes that the development of methods for accounting for the value of data as a non-produced asset used in the production of digital products is one of the priority tasks of developing the methodology of the system of national accounts.

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