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This paper aims to analyze the potential variables explaining the compliance value added tax (VAT) gap, which basically represents an estimate of the unpaid VAT in the economy. A major component of compliance VAT Gap is represented by tax fraud; there exist other causes too, like insolvencies, bankruptcies, optimizations practices and maladministration. The objective of our paper is to revisit the main determinants of the VAT compliance gap for the European Union (EU)-27 member states. Using econometric modeling, our study identifies the relationship between the VAT gap and various determinants of it.

Our work focuses on the shadow economy, final consumption, VAT revenues, standard VAT rates, differences between the standard and reduced rates, economic prosperity, press freedom, political stability and others, as determinants of European VAT compliance gaps, for the 2005–2020 time interval. The methods include panel data analysis through simple and multiple regression modeling, the combinatorial approach, fixed and random effects.

Our study validates the direct impact of shadow economy and the indirect impact of VAT revenues, economic prosperity and press freedom, upon VAT compliance gaps. Upon subsampling of EU member states within old and new ones, our results estimate a larger positive impact of shadow economy upon old member states, compared to new ones.

The policy implications include leverage effects of governments acting upon a reduction in shadow economy phenomena and boosts of economic development, political stability and press freedom, in order to attain the contraction of compliance VAT gaps.

Our paper sheds light in a poorly explored scientific area, that of the determinants of VAT gap, especially in relationship with financial and economic crime phenomena.

The purpose of this paper is to present an up-to-date estimation of the tax gaps (TGs) of 35 countries (28 EU member states and 7 additional countries – Australia, Canada, Japan, New Zealand, Turkey, Switzerland and the USA, both as a percentage of the gross domestic product (GDP) and a nominal value (in US$).

The authors’ empirical study was carried out on 35 selected countries. To estimate the TG, indirect methodology has been applied, where the basic components used in the estimation procedure are the level of the shadow economy estimated with the multiple indicators multiple causes method, the GDP at current prices (in US$), the total tax rate (TTR) of a given country and the indirect method of follow-up and estimation of lacking data.

The basic finding of the research is that the level of the TG is determined individually for a given country and is strongly correlated with the GDP, i.e. if the GDP is high, the TG as the percentage of the GDP is lower in the majority of countries. It is particularly easily noticeable in countries such as the USA (TG – 3.8 per cent of the GDP), the Great Britain (TG – 3.2 per cent of the GDP) or Japan (TG – 4.3 per cent of the GDP).

A limitation of the adopted research method is the lack of application of direct (supplementary) methods which would include potentially lost contributions from foreign sources and not registered taxpayers. Another research constraint is that the authors’ estimations do not take into account the so-called direct top-down approach based on the VAT Theoretical Total Liability. The weakness of the adopted procedure of estimation is also the use of TTR only instead of comparative approach including tax burdens and average tax rate.

TG has recently become a hotly debated issue and poses a big challenge to the public finance in many countries. The paper provides some recommendations for the policymakers how to reduce the size of the TG.

Tax evasion and tax avoidance leading to the emergence and expansion of the TG erode the business ethics and distort the rules of fair competition, thus undermining the social trust and moral infrastructure of business transactions.

One of the major research findings is that 30 per cent of the TG in a given country is determined by the TTR, which – for the first time – provides empirical proof that tax policy (as part of overall economic policy) plays an important role and that it may determine the fiscal effectiveness of a given country.

The purpose of this study is to analyze the relationship between tax evasion and firm’s value while determining the moderating role of family management and the ownership’s concentration in this relationship.

The empirical study employs a Panel Data set of 34 firms listed on the Tunisian Stock Exchange (TSE) for the period 2007 to 2014. Regression analysis is used to estimate the relationships proposed in the hypotheses.

The results show that tax evasion has no direct effect on a firm’s value. This study highlighted the presence of a moderating effect of family management on the relationship between tax evasion and firm’s value. However, no moderating effect of the concentration of property on the mentioned relationship was detected.

This study represents a first empirical essay focusing on the relationship between tax evasion and firm’s value. Furthermore, it analyzes the moderating effect of some aspects of governance, such as family management and ownership’s structure, on this relationship in a Tunisian context.

The main purpose of this paper is to explore size of the shadow economy of 31 European Countries in 2014 and size of the shadow economy of 28 European Union countries over 2003-2014 (in per cent of official GDP). An additional objective is to identify tax evasion, as the problem of all the EU countries, answering the questions how better combat the tax fraud.

Estimates of the shadow economy for all 28 European Union countries and other three countries from Europe, i.e. Norway, Switzerland and Turkey – MIMIC method was applied.

The average size of the shadow economy in 28 EU countries was 22.6 per cent in 2003 and decreased to 18.6 per cent (of official GDP) in 2014. We also consider the most important driving forces of the shadow economy. The biggest ones are with 14.6 per cent unemployment and self-employment, followed by tax morale with 14.5 per cent and GDP growth with 14.3 per cent. The proportion of tax evasion (accounting for indirect taxation and self-employment activities) was on average 4.2 per cent (of official GDP) in Poland, 1.9 per cent in Germany and 2.9 per cent in the Czech Republic.

The MIMIC statistics do not address a large part of the wholly illegal economy (of typically criminal nature) and, accordingly, it is not an absolute magnitude of the whole unofficial economy. However, it does not seem that other, alternative, methods of measuring the unofficial economy are better in individual terms.

Current statistical research should lead to practical acceptance in the framework of need for developing better organizational & legal ways for multi-level governance within the European Union, leading to effective methods of counteracting – in particular intra-Union fraud. In addition, the presentation of a review of typology of the main theories and studies regarding the unofficial economy aspects relating to tax evasion constitutes a practical review of the pursued research areas.

Safeguarding the national economy as a whole, by seeking ways of reducing the scope of shadow economy.

Both regarding presentation of the latest shadow economy estimates and typology of its main studies and theories.

The main aim of this chapter is to systematize observations regarding changes in entrepreneurship in Serbia during the previous decade, having in mind some key factors such as high-impact low-probability (HILP) events, dynamic development in the sphere of information technologies (IT), and foreign direct investments (FDI). The choice of these factors was made in accordance with the fact that there were no significant changes in other external factors in the sphere of entrepreneurship (regulatory framework, financial conditions, and socio-political instability). This chapter discusses the assumptions that HILP events and FDI can have both positive and negative impacts on individual sectors or agglomerations of entrepreneurship, while only positive impacts are attributed to IT development. Using official databases and annual financial and business reports given by entrepreneurial agencies and micro and small enterprises we created a set of reports that indicate the strength and direction of the influence of the mentioned factors and their consequences in the sphere of entrepreneurship at the level of Serbia and selected cities, based on the fact that the entrepreneurial ecosystem in those cities faced greater than average challenges. The selected ratios indicate changes in the growth rate of the entrepreneurship sector (number of entrepreneurs and employees) as well as in the improvement of its competitiveness (productivity, assets, and profit per employee).

The purpose of the research is to study the consequences of total (comprehensive) automatization of entrepreneurship for interested parties through the prism of competition human and artificial intellectual capital in production and distribution in Industry 4.0.

The research is conducted with application of scenario analysis, regression analysis, imitation modeling, forecasting and non-linear multi-parametric optimization with the simplex method.

The authors perform scenario modeling of competition between human and artificial intellectual capital in production and distribution in Industry 4.0 and offer recommendations for pro-active management of competition between human and artificial intellectual capital in production and distribution in Industry 4.0.

Contrary to the existing approach to studying competition between human and artificial intellectual capital in Industry 4.0, automatization of distribution, not production, is most preferable. This shows increase of the value of human intellectual capital in distribution during its automatization based on AI. This is an unprecedented and breakthrough conclusion for the modern economic science. It allows creating a completely new direction of research of competition between human and artificial intellectual capital in production and distribution in Industry 4.0, in which optimization of social consequences is achieved not by means of restraint of automatization but by means of its stimulation. The key condition is stimulation of automatization of distribution with limited automatization of production. Based on this conclusion, it is recommended to continue research in continuation of the presented work.

This paper investigates whether board composition, a family chief executive officer (CEO) and the firm's managerial capabilities affect proactive tax management in family small and medium-sized enterprises (SMEs). The main statement is that the professionalisation of corporate government and management practices explains the difference in tax avoidance behaviour in closely held family SMEs.

Using the 2012 Spanish thin-capitalisation rule as a quasi-experiment, the authors estimate panel regressions with firm fixed effects and robust standard errors. This model represents a triple difference-in-differences combined with propensity score matching (PSM-DID).

Analysis shows that having a high proportion of non-family board members and a high endowment of managerial capabilities lead to tax liability optimisation in family SMEs. Conversely, familial boards and family SMEs with low managerial capabilities lack enough expertise to weigh the costs of tax avoidance over the benefits, resulting in a reluctance to engage in tax optimisation behaviours. Alike, results show no significant relation between CEO's family affiliation and tax management behaviour.

When implementing fiscal policies, the specific needs of family SMEs should be considered, and how these needs interact with corporate governance and managerial mechanisms. Moreover, policymakers need a deeper understanding of family SMEs in order to develop policies appropriate to their characteristics. A more comprehensive knowledge of how family firm heterogeneity affects corporate decisions, such as indebtedness and fiscal decisions, may improve public policies.

This study addresses the issue of tax behaviour in family SMEs in a particular event that implies a specific logic to weigh the pros and cons of each alternative: reducing debt or paying more taxes. This study’s conclusions are based on a model that deals with potential endogeneity problems, which avoids bias in the findings.

The purpose of this paper is to provide a new modelling framework for distribution network strategy and to study how various transfer-pricing schemes cope with stochastic demand under different countries tax policies.

Use is made of real options to quantify the available options for supply chain network design. The application of real options approach relies on three main conditions, such as the existence of uncertainty (market), flexibility (different network design) and irreversibility (investments) in the decision process.

Evaluation of the potential impact of changes in local tax policies on long-run plant and distribution centers location decisions. A more intensive tax regime tends to promote changes in the distribution network that support multinational companies. In high uncertain markets, the options to change the network are more attractive – uncertainty is linked with an increase in flexibility.

The present study provides decision makers with a useful tool for supporting the design of global logistics networks, considering different scenarios and therefore determines a more after-taxes profitable logistics network configuration.

Integrate financial issues while studying different scenarios for supply chain network designs. It presents a model that focus on distribution network design considering transfer-pricing methods as decision variables and aiming after-taxes bottom-line results maximization. There are relatively few “reported” implementations of global profit maximization models for large-scale networks. Thus, we believe that the implementation of global profit maximization models represents a potentially significant unrealized opportunity worthy of serious consideration by many firms.

Modelling of the multiproject cash flow decisions in a contracting firm facilitates optimal resource utilization, financial planning, profit forecasting and enables the inclusion of cash‐flow liquidity in forecasting. However, a great challenge for contracting firm to manage his multiproject cash flow when large and multiple construction projects are involved (manipulate large amount of resources, e.g. labour, plant, material, cost, etc.). In such cases, the complexity of the problem, hence the constraints involved, renders most existing regular optimization techniques computationally intractable within reasonable time frames. This limit inhibits the ability of contracting firms to complete construction projects at maximum efficiency through efficient utilization of resources among projects. Recently, artificial neural networks have demonstrated its strength in solving many optimization problems efficiently. In this regard a novel recurrent‐neural‐network model that integrates multi‐objective linear programming and neural network (MOLPNN) techniques has been developed. The model was applied to a relatively large contracting company running 10 projects concurrently in Hong Kong. The case study verified the feasibility and applicability of the MOLPNN to the defined problem. A comparison undertaken of two optimal schedules (i.e. risk‐avoiding scheme A and risk‐seeking scheme B) of cash flow based on the decision maker's preference is described in this paper.