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ISSN 2067-3310, E-ISSN 2067-7669 

Vol. 17, No. 2 (2023), pp. 99-104 

 

99 
 

INTERNATIONAL EXPERIENCE IN MEASURING THE DIGITAL 

ECONOMY 

 

S. KHALIL, A. IBRAHIMOV 

 

Saida Khalil 1, Aykhan Ibrahimov2 

Dokuz Eylul University, Turkey 
1 ORCID No. 0000-0003-3695-7755, E-mail: saida_khalil@unec.edu.az 
2 ORCID No. 0000-0003-4679-1576 

 

Abstract: The article discusses the importance and challenges of measuring the 

digital economy. It evaluates the overall benefits of the GDP framework and introduces 

new concepts to define the digital economy as an object of measurement. The concepts 

used to define the digital economy as an object of measurement are the following. In 

order to quantify the benefits associated with the digital economy, a new metric is 

introduced to formally link it to traditional GDP and the concept of gross income is 

used as the main indicator to assess its economic impact on the regional economy. The 

main methodological approaches for constructing relevant indicators are described. 

The methodology for measuring the digital economy and the prospects for improving 

the knowledge base are identified.  

Keywords: Digital economy, measurement of economy, GDP, total incomes. 

 

INTRODUCTION 

Digitalisation is "a general process beyond the industrial revolution that refers to 

the replacement of machines that depend upon humans and machines that do not depend 

upon humans by machines that can think for themselves, are intelligent and capable of 

working independently, participating in the production of sectors and causing 

fundamental changes in business life" (Yilmaz, 2020).  The digital economy, 

meanwhile, is defined as "an economy that is extensively based on digital computer 

technologies" (Kalkınma Bakanlığı, 2018). 

By renewing business processes in production, digitalisation supports the 

symbiosis of man and machine in working life in order to increase productivity and 

reduce production costs. However, the expected productivity gains are not keeping pace 

with the speed of the digitalisation process, despite the rapid pace of technological 

innovation and transformation. As any change in its own reality takes time to manifest 

its economic or social effects, these effects of digital transformation are expected to 

become more apparent over time. In particular, the adoption of digital by the public 

sector, the increase in the share of high-tech digital firms and the adaptation of business 

models to digital technologies should facilitate the adjustment of the productivity rate to 

the pace of digital transformation (OECD, 2021). 

 

Measuring the Digital Economy 

New Perspectives maps existing indicators across a range of domains, including 

education, innovation, entrepreneurship, and economic performance, against the current 

mailto:saida_khalil@unec.edu.az


INTERNATIONAL EXPERIENCE IN MEASURING THE DIGITAL ECONOMY 

 

100 
 

policy challenges of the digital economy, as reflected in the OECD's Internet Policy 

Guidelines (2011). 

The essence of the definitions is also influenced by the specifics of a particular 

historical period. The first definitions were based on contrasting earlier concepts such as 

the "information economy" and the related broader concept of the "information society". 

Don Tapscott (1996), for example, stated that the digital economy encompasses two 

types of economic activity. The first type, informational, involves basic tasks such as 

uploading static information to online resources; the second type, communication, 

includes activities made available by the Internet. 

The definition of a concept reflects the times and current trends, especially in the field 

of technology. Early interpretations (Mesenbourg, 2001, Tapscott, 1996) focused on 

Internet technologies, which became a kind of technological mainstream of the 1990s, at 

least in the global North. 

A number of works provide specific interpretations, but current approaches are 

generally simplified versions of the definition of the digital economy as a "digitally 

based economy" (EC, 2013). 

The measurement of the digital economy is a priority, given the increase in the 

number of economic activities that are made possible by digital technologies and the 

consequent growth in their economic importance. But there are many challenges: High 

quality data is needed for good policy making, fiscal policy and resource allocation. At 

the moment, this component is lacking in the digital economy and, as a result, it is 

unlikely that public policies will be fully supportive of the development of the digital 

economy (House of Commons, 2016). 

 

Challenges of the digital economy 

There are several obstacles to measuring the digital economy: 

 Definitions/frameworks: As the discussion above shows, definitions of the 

digital economy are very diverse and sometimes inconsistent. This does not in 

itself make it difficult to measure the digital economy, but it does make 

comparative analysis difficult. The same definitions that cannot draw a clear line 

between the traditional and the digital economy also make the initial 

measurement difficult (OECD, 2014).  

 Data quality problem: Currently, especially in developing countries, there is a 

fundamental problem with the data being collected - it is either missing or 

unreliable. This is exacerbated by further innovation - data collection always 

lags behind technological progress. 

 The cost problem: Moore's Law and similar phenomena - "my watch has more 

computing power than the computer that launched Apollo" - mean that the cost 

of the same amount of ICT power, storage capacity, etc. is constantly falling. 

Something similar can happen with types of ICT-related services, which also 

undergo qualitative changes that do not always affect their value; the emergence 

of free products (such as Wikipedia) that still add value is relevant (House of 

Commons, 2016, OECD 2016).  



Saida KHALIL, Aykhan IBRAHIMOV 
                                     

101 
 

 Adjustments are needed to take this into account, but this is no longer relevant to 

science (OECD 2014, 2016). The virtuality of the digital economy: Many types 

of digital economic activity do not immediately produce a finished product. 

Some of these types of services may be intermediate at the business-to-business 

or consumer level; there may be difficulties in calculating value added; and 

digital services are delivered in virtual space and therefore may not be easily 

traceable, especially when there is cross-border e-commerce6 or the digital 

consumer-as-producer phenomenon (House of Commons, 2016, OECD, 2016, 

WEF, 2015).   

 Some researchers argue that these obstacles make measuring the digital 

economy using traditional methods of economic analysis "not only 

incomprehensible, but unrecognisable" (Sheehy, 2016). At present, unresolved 

difficulties mean that the size of the digital economy is "substantially 

underestimated". 

 

RESEARCH METHODOLOGY 
Policymakers use GDP data to make decisions about everything from 

infrastructure to R&D, from education to cybersecurity. Regulators use this data to 

make policy decisions that affect technology companies and others. Because the 

benefits of digitalisation are dramatically overlooked, most of these policies remain 

divorced from reality. For example, a study by Felix Eggers of the University of 

Groningen found that Facebook has created $225 billion in unrecognised value for 

consumers since 2004. If we start from the fact that digital products and services are 

growing at an incredible rate in our economy, we better understand the need to solve 

this problem as soon as possible. 

The main reason why the digital economy is under-represented in GDP is that 

GDP is defined in terms of the price people pay for a product or service. Therefore, with 

few exceptions, if the price of a product or service is zero, its contribution to GDP is 

also zero. However, many of us use free digital applications such as search engines and 

online maps much more than we use their paper versions. 

In order to measure these benefits related to the digital economy, a new measure 

was developed to map them onto traditional GDP in a formal way. This new measure is 

called GDP-B, due to its reliance on GDP to consider the advantages (instead of the 

cost) of new and free goods (Brynjolfsson, et al., 2019).  GDP-B was developed by 

Erwin Diewert as a way to complement GDP in order to capture the welfare gains of 

new and free goods, together with Felix Eggers and Kevin Fox. It is recommended that 

policy makers and managers use this measure of GDP-B when focusing on the welfare 

of the consumption side of the economy, instead of the production side. They found that 

the average annual GDP-B growth in the US since Facebook's inception in 2004 would 

increase by between 0.05 and 0.11 per cent if Facebook's benefits were included. While 

our GDP-B estimates are not as precise as GDP measurements, they at least attempt to 

directly measure economic well-being, which in the digital age is not adequately 

captured by GDP. Our measure of GDP-B remains within the neoclassic framework, 

reflecting only the private economic benefits related to the digital revolution (Collis and 

Brynjolfsson, 2020, Brynjolfsson, et al., 2019). 



INTERNATIONAL EXPERIENCE IN MEASURING THE DIGITAL ECONOMY 

 

102 
 

Figure 1.  Spectrum of well-being measures 

 

 
 

Source: https://www.brookings.edu/wp-content/uploads/2020/01/WP57-Collis_Brynjolfsson_updated.pdf  

 

Macroeconomic indicators are easy to measure, but they only tell part of the 

story, and well-being measures provide a more realistic picture of how consumers are 

faring, but they too may be subjective. By considering a combination of measures, 

including our proposed GDP-B, policymakers, regulators and managers would be better 

placed to make decisions (Figure 1). 

To estimate the total income of digital economic activity, we use the following 

formula (Glinsky, et al., 2011): 

𝑀 =  𝑀𝑇 + 𝑀1 ×
1

1−𝑅
 (Formula 1) 

where M - total income (direct and indirect, taking into account the multiplier effect) 

from digital activities in the region; 

𝑀𝑇 - direct economic effect from digital activity (the amount of funds generated by the 

digital economy in the first round of circulation of funds, included in the GRP of the 

region) ; 

𝑀1 - the part of the proceeds (income) of the digital economy that has an impact on 

GRP (the volume of GRP caused by orders of digital activities) ; 

𝑀1 =
𝑌×𝑄𝑇×(𝑉𝑇−𝑍𝑇İ)

𝑋
 (Formula 2) 

𝑉𝑇 - volume of produced products and services of the digital economy in value terms 

(the value of goods and services of the digital economy);  

𝑍𝑇İ - volume of expenditures for the purchase of goods and services for digital 

production from other enterprises (cost of goods and services of the digital economy);  

𝑌 - gross regional product;  

X - gross domestic product;  

𝑅 - coefficient reflecting the degree of closedness of the regional economy and 

reflecting the relationship between two consecutive circles of circulation of digital 

economy funds in the region;  

𝑄𝑇 - the share of digital economy costs remaining in the national (regional) economy 

(Lovelock, 2018, Katz,2017).  

 

RESULTS 

GDP-B- (Measures consumer rent generated 

by free digital goods, services and other non-

marketable products) 

Measures of well-being (e.g. 

happiness, life satisfaction) 

 

Macroeconomic indicators 

(e.g. GDP, productivity) 

 

High 

Low 

Relevance to prosperity 

Subjective Objective Certainty 

https://www.brookings.edu/wp-content/uploads/2020/01/WP57-Collis_Brynjolfsson_updated.pdf


Saida KHALIL, Aykhan IBRAHIMOV 
                                     

103 
 

The basis for the calculations is the estimation of MT - the amount of funds 

generated by digitalisation in the first round of circulation, included in the GRP of the 

region (direct economic effect from digital activity).  As the main indicator for assessing 

the economic impact of digitalisation on the region's economy, this methodology is 

based on the concept of total income from the digital economy. The total income is 

understood as a set of annual benefits, both direct and indirect, received by the region as 

a result of digital activities and is expressed in value terms (Glinsky and Serga, 2021, 

Glinsky et al. 2011). This is a measure of how much money is spent by digital 

businesses, digital infrastructure businesses, information and communication 

businesses, and non-digital businesses on production, consumer goods, and services. 

Moreover, the indirect income for the region from digital activities is only the part of 

the expenditure (direct and overall cost) which stays within the region. 

The following points should be taken into account when calculating total 

revenues from the digital economy (Glinsky and Serga, 2021):  

1. The gross value added by the type of economic activity 'information and 

communication activities' (annual calculation of GRP) is the volume of funds generated 

by digitalisation in the first cycle of funds circulation.  

2. Expenditure on the services of third parties used in the production of information and 

communication services is assumed to be equal to the volume of expenditure on the 

purchase of goods and services for digital activities from other enterprises (costs 

constituting the cost of the digital product).  

Multiplier effects in monetary terms can be estimated using multipliers, 

especially on gross domestic product. 

 

CONCLUSIONS 

The study focuses on the methodological issues involved in assessing the 

contribution of digital economy activities to national and regional revenues, discusses 

possible methods for assessing the digital economy, and specifies the points to be taken 

into account when calculating total revenues.  

In conclusion, the digital economy is a transforming power for the global 

economy and has considerable potential for revenue generation. However, there are a 

number of barriers to its development, the overcoming of which is essential for the full 

realisation of its benefits. Accurate definition and measuring their effects on GDP are 

essential for informed policy and economic analysis. Policy makers, regulators and 

managers can make better decision-making by evaluating a range of measures together, 

including the proposed GDP-B. Focus not only on price but also on the value created. 

 

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