1. Introduction

2. Global problems of shadow economy estimation methodologies: theoretical background

3. The statistics of shadow economy scope in Lithuania by different methodologies

4. The features of digital shadow economy

5. Conclusions

Funding

Reference

The article covers an extremely topical but hardly researched problem of digital shadow economy estimation. Thus far, the phenomenon of digital shadow economy has not been universally defined either by scientists or by institutions responsible for the combat with shadow economy. Traditional shadow economy is commonly estimated applying direct and indirect methods possessing their strengths and weaknesses. As a result, final estimations of shadow economies are rather variant. For instance, with reference to Schneider (2014), the scope of shadow economy in Lithuania achieved 27 per cent rate in 2014 whereas the figure estimated by Lithuanian Department of Statistics composed 15 per cent rate. It can be presumed that the divergence of the results has been determined by application of different shadow economy estimation methods. The interviews with the experts of shadow economy have revealed that although the volumes of e-trade and e-transactions are increasing, indicators of digital shadow are not still included in the estimations of shadow economy.

Introduction

Topicality of the problem. The phenomenon of digital shadow economy has been analysed in numerous scientific and information sources due to its specificity and depth of the problem. Thus far, the concept of shadow economy has not been precisely defined either in national or in international levels, which serves as the key reason for rather different scopes of shadow economy calculation and estimation. According to Zukauskas (2013), estimation of the real scopes of labour market shadow, as well as estimation of the other shadow economy activities, is complicated since shadow market operators are inclined to hide their activities. For the purpose to describe shadow economy and estimate its scopes, at least roughly, the variety of methods is engaged. Following the statistics, the figures of shadow economy in European countries are significantly different. The scopes of shadow economies in the countries of Central, Eastern and Southern Europe are considered to be the highest. Transfer of business activities to electronic space alongside with increasing volumes of e-trade determine the need to establish which share of shadow economy has been transferred to remote (electronic) platforms. The fact that the concept of shadow economy has not been universally defined in any official documents, proposes that this sphere has been insufficiently researched.

1. Introduction

2. Economic, ego and demographic determinants of subjects’ participation in digital shadow economy: theoretical background

3. The methodology of the empirical research

4. The results of the empirical research

5. Conclusions

Funding

References

This article is aimed at theoretical and empirical identification of economic and demographic characteristics of the subjects, operating in digital shadow economy. Although, in general sense, the characteristics of the subjects, operating in digital shadow economy, are not extremely different from the ones of the subjects, operating in traditional shadow economy, the expert evaluation has enabled to identify the distinctive features of an illegal digital market seller, who can be represented as a young or middle-aged male with higher education, a professional in his operational field. With reference to the research results, sellers in digital shadow economy include the entities with officially registered activities, who are trying to evade taxation of the revenues earned from the operations in e-space. On the other hand, according to the experts, the amount of the officially accounted revenue earned by these entities may reach up to 300 EUR. Hence, the defined profile of an illegal seller, as of a subject, operating in digital shadow economy, proposes that a seller in digital shadow economy is an intellectually developed person with advanced professional skills, but insufficient financial earnings.

Introduction

As argued by Wall (2005), the empowering of an individual to exploit networked technology to carry out incredibly complex and far-reaching tasks countless times globally is one of the most profound transformations of trade. With an attraction of opportunities, including easy availability, use and control of technologies (Ingram & Hinduja, 2008; Amasiatu & Shah, 2014; Camarero et al., 2014), variety of products and services on sale economy (Mikalajunas & Pabedinskaite, 2010; Sirkeci & Magnusdottir, 2011) low price (Mikalajunas & Pabedinskaite, 2010; Ho & Weinberg, 2011; Vida et al., 2012; Yu et al., 2015), time saving (Ho & Weinberg, 2011; Williams et al., 2010; Yu et al., 2015; Amasiatu & Shah, 2014 and others), convenient delivery terms (Vida et al., 2012; Sirkeci & Magnusdottir, 2011) and e-communication with a consumer (Mikalajunas & Pabedinskaite, 2010), more and more product buyers and service providers are entering the e-trade. Nevertheless, difference between corporate and personal, typical of e-environment (Calluzzo & Cante, 2004; Shang et al., 2008; Williams et al., 2010), in combination with the lack of public self-consciousness (Taylor, 2012; Arli et al., 2015; Amasiatu & Shah, 2014) determine subjects’ participation not only in formal, but also in digital shadow economy. Although the precise scopes of digital shadow economy have not still been estimated due to the lack of universally acceptable methodologies and difficulties to track all kinds of activities, one recent estimate of global corporate losses stands at around €750 billion per year (Europol, 2011).

1. Introduction

2. Digital shadow activity related terms and interpretations

3. The methodology of the empirical research

4. The results of the empirical research

5. Conclusions

References

The article covers a new topic in the sphere of digital shadow economy – consumers’ attitudes towards this phenomenon. Increasing transfer of transactions to electronic space determines the growth of the number of illegal digital operators and promotes consumers’ involvement in digital shadow trade. Scientific literature does not contain any universal definition of digital shadow economy. Hence, the variety of terms, interpretations and features relevant to this phenomenon is rather wide, which determines the necessity to define the precise concept of digital shadow economy from the point of view of consumers as active participants in this field. This article is aimed at definition of the concept of digital shadow economy from consumers’ position and identification of the measures would discourage potential consumers from participation in digital shadow economy. To increase the size of the survey sample, the method of “snowball” was engaged. The results of the research have revealed that consumers are inclined to distinguish criminal activities (drugs, prostitution, credential steals, etc.) from illegal economic activities, which also violate established legal norms and regulations. The participants of the survey perceive that the activities of digital shadow economy are performed exceptionally in electronic space without official registration of business and evading tax payment. Participation in digital shadow economy is voluntary and mutually beneficial to both transaction parties (a trader and a consumer). With reference to the results of consumers’ evaluation, definition of digital shadow activities as illegal ones, development of the efficient legal framework, containing clearly established criminal and/or administrative responsibility for a consumer as a party of digital shadow transaction, public announcement and availability of the information on illegal e-traders in e-space, availability of appropriate protection software, more intensive supervision and control, establishment of e-police department and assurance of the sufficient number of supervising officers can be considered the most efficient measures of digital shadow economy prevention.

Introduction

With reference to Petrovic – Lazarevic and Sohal (2004), e-business, which refers to the transactions conducted over computer networks, has been of considerable interest to practitioners and researchers primarily because of its influence on digital market participants. Removing numerous barriers (e.g. geographical, complex transaction, complicated payment, etc.) and ensuring the variety and availability of products and services on offer, an explosive growth of online business has provided a wealth of opportunities for consumers to become participants of digital shadow economy, i.e. obtain items and services from illegally operating online entrepreneurs (Dobson et al. 2015). Numerous social drivers such as the contrast between personal and corporate or low level of public selfconsciousness determine social acceptability of online purchases without making sure whether a supplier operates with complete legality or even realising the offensive nature of the activities. Thus far, the studies on the topic of digital shadow consumption have basically covered the analysis of the particular forms (e-fraud – Gregg, Scott, 2006; Blackledge, Coyle, 2010; Akintoye, Araoye, 2011; Vlachos et. al. 2011; Amasiatu and Shah, 2014 and others; digital piracy – Hill, 2007; Higgins, 2007; Williams et. al., 2010; Belleflamme, Peitz, 2010; Yoon, 2011; Camarero et. al.2014; Vida et. al. 2012; Taylor, 2012; Yu et. al., 2015 and others or social determinants (contrast between personal and corporate – Calluzzo, Cante, 2004; Shang et al., 2008; Williams et al., 2010; low level of public self-consciousness – Amasiatu, Shah, 2014; social bonding – Higgins et al. 2008; Yu et al., 2015; relativism – Arli et al., 2015) of this phenomenon. However, the concept of digital shadow economy from consumers’ point of view has hardly been researched. The research of consumers’ attitudes towards digital shadow economy is scientifically significant due to several reasons.

By their nature, black-market activities are difficult to measure. Nevertheless, there is widespread agreement that black-market activities account for a significant portion of GDP in many countries.1 Less clear, however, are the welfare effects of such activities, particularly those motivated by tax evasion. In his leading undergraduate text on public finance, Rosen (2005, p. 353) states a second best argument for why a black market, or an “underground economy,” might be efficiency-enhancing in some cases: “Then under certain conditions, the existence of an underground economy raises social welfare. For example, if the supply of labor is more elastic to the underground economy than to the regular economy, optimal tax theory suggests that the former be taxed at a relatively low rate.” But Slemrod and Bakija (2004, p. 179) expound an alternative view: “…because tax evasion depends on opportunities that are tied to particular activities, it provides an incentive—which is inefficient from a social point of view—to engage in those activities for which it is relatively easy to evade taxes.” 2 The first view focuses on the potential for the black market to increase incentives to provide resources to taxed activities, whereas the latter view emphasizes the distorting effect of the tax system on the allocation of resources across different taxed activities.

The relative merits of these two views might seem to be purely an empirical matter, but the current paper argues that surprisingly sharp results can be obtained by placing both views within a single model. Following Slemrod and Bakija, we model a set of activities that differ in the expected rewards from operating in the black market. In particular, our activities are distinguished by the levels of assets that the tax authority is able to seize in the event that tax evasion is discovered. Low-asset activities (per unit of output) self-select into the black market because the potential fine from detection is relatively low. For simplicity, the model abstracts from the myriad other considerations behind the decision to enter the black market; in particular, all firms are randomly audited for tax purposes. Following Rosen, we next assume that the tax system distorts the decision of whether to devote resources to any taxed activity. In particular, activities are ranked by a continuous parameter called “quality,” interpreted here as the attribute of a good produced by firms. Each consumer purchases at most a unit of a variable-quality good, with choices based on a heterogeneous “taste” parameter. Recognizing the costs involved in administering a quality-differentiated tax system, we assume that the government’s expenditure needs are met by taxing all variable-quality goods at a uniform statutory rate. Such a tax system causes consumers with low tastes for quality to drop out of the market — that is, they devote no resources to purchasing variable-quality goods, whereas those who remain reduce the qualities of the goods that they purchase.

With such a setup, we provide conditions that determine whether the black market consists of low- or high-quality goods. In the latter case, neither the Slemrod–Bakija nor Rosen arguments are relevant: a small black market (maintained through an appropriately low expected fine) does not distort consumption towards too much quality, because quality choices are already too low under a uniform tax; and it does not bring new consumers into the market for variable-quality goods. This case illustrates how a black market can be desirable, even when audits are costless, because it partially corrects the distorting effect that a uniform tax system has on the allocation of resources across taxed activities.