THE DEFINITION OF DIGITAL SHADOW ECONOMY REMEIKIENE, Rita; GASPARENIENE, Ligita; SCHNEIDER, Friedrich Georg
Technological and economic development of economy,
03/2018, Volume:
24, Issue:
2
Journal Article
Peer reviewed
Open access
Considering the lack of the scientific studies on the selected topic, the authors of this article raise the aim to set up the definition of digital shadow economy and identify its distinctive ...features and channels. Thus far, the studies on illegal digital activities have covered ambiguous interpretations of digital shadow economy that incorporated both criminal and economic aspects of the activities performed. The results of the empirical research have enabled to formulate the definition of digital shadow economy that refers to illegal activities, such as digital service provision and sales of goods/services online, when operating exceptionally in digital space, the entities violate the existent legal norms and regulations with a pursuit of illegal mutual interest and material benefits. The newly formulated definition of digital shadow economy has served as a corner-stone for identification of the distinctive features and channels of this phenomenon. Hence, the results of the research may make a significant and weighty contribution to the development of the theory of economics and may raise the awareness of what the phenomenon of digital shadow economy implies.
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CEKLJ, IZUM, KILJ, NUK, PILJ, SAZU, UL, UM, UPUK
This paper uses a multivariate analysis to examine how countries’ tax morale and institutional quality affect the shadow economy. The literature strongly emphasizes the quantitative importance of ...these factors in understanding the level of and changes in the shadow economy. Newly available data sources offer the unique opportunity to further illuminate a topic that has received increased attention. After controlling for a variety of potential factors, we find strong support that a higher tax morale and a higher institutional quality lead to a smaller shadow economy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
This paper presents estimations of the shadow economies for 162 countries, including developing, Eastern European, Central Asian, and high income OECD countries over 1999 to 2006/2007. According to ...our estimations, the weighted average size of the shadow economy (as a percentage of 'official' GDP) in Sub-Saharan Africa is 37.6%, in Europe and Central Asia (mostly transition countries) 36.4% and in high income OECD countries 13.4%. We find that an increased burden of taxation (direct and indirect ones), combined with (labour market) regulations and the quality of public goods and services as well as the state of the 'official' economy are the driving forces of the shadow economy.
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BFBNIB, NUK, PILJ, SAZU, UL, UM, UPUK
This study examines the influence of financial development (FD), along three dimensions (financial depth, financial access and financial efficiency) in two main sub-sectors (financial institutions ...and financial markets), on the shadow economy’s (SE) size. Several econometric techniques and estimation strategies were applied to a balanced panel data set of a global sample of 114 economies and three sub-samples (low and lower-middle-income economies (LMEs), upper-middle-income economies (UMEs) and high-income economies (HIEs)) for the period 2002–2015. First, nine financial indicators were found to minimise the SE. Interestingly, financial institutions, especially financial institutions’ efficiency, had a more significant effect on the SE than financial markets. Second, there was evidence that the non-linear nexuses between FD and SE were U-shaped for eight of the nine financial indicators, the exception being financial institutions’ efficiency. Third, financial depth and financial access had a positive impact on the SE in the short run, while financial institutions appeared to reduce the SE in the long run. Fourth, the negative effects of FD on the SE were noticeable in LMEs and UMEs and dominant in HIEs in the long run. The non-linear relationships were consistent in UMEs, despite some variations in LMEs and HIEs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
5.
METHOD OF ESTIMATING THE VOLUME OF THE SHADOW ECONOMY V. Yu. Ilin; T. P. Nazarenko; I. V. Suprunova ...
Fìnansovo-kreditna dìâlʹnìstʹ: problemi teorìì̈ ta praktiki (Online),
01/2021, Volume:
1, Issue:
32
Journal Article
Peer reviewed
Open access
The shadow economy at the transitional stage of development of Ukraine became an integral part of the economy, began to solve a number of macro and microeconomic problems of the state. Today, the ...shadow economy has a significant impact on all socio-economic processes occurring in the country. But the shadow economy’s share of gross domestic product today is so large that it poses a threat to national security. A significant level of the shadow economy leads to the criminalization of society, the growth of corruption, the formation of an atmosphere of legal nihilism in the state. Tendency to evade taxes causes significant damage to Ukraine’s budget. This, in turn, narrows the transition to a welfare state model, as it reduces resources for infrastructural upgrades, social payments, medical and other social services for the population.
Official estimates of the size of the shadow economy by various government agencies have considerable differences. Inaccurate assessment of the impact of the shadow economy on all spheres of the country’s activity leads to irrelevant assessments of socio-economic processes and their tendencies, miscalculations in the formation of domestic and foreign policy of Ukraine. The shadow economy has been researched by many scholars, but in the considerable number of works on this topic there are no even well-grounded data on the shadow economy. Therefore, the urgent task is to develop an algorithm for estimating the shadow economy. To do this, the article analyzes various terminological approaches to defining the shadow economy and its components. The classification of existing methodological approaches to the identification and assessment of the extent of shadow economic activity is carried out. A mathematically correct method of estimating the size of the shadow economy which is suitable for practical use has been proposed and substantiated. The analysis of the obtained mathematical equation showed that it is possible to formulate mathematically precisely the conditions for a stable level of the shadow economy and the growth of the shadow economy. The estimation of the correlation functional of the shadow economy size became mathematically accurate.
Using stock returns from a sample of 94 countries over the period from 22 January to 24 March 2022, we document a negative relationship between the Ukraine–Russia war and world stock market returns. ...We thus provide the first empirical evidence.
•We provide the first empirical evidence of the effect of the Ukraine–Russia war on world stock market returns.•The war has negatively impacted the world’s stock indices and this effect was more significant after the invasion of Ukraine.•The countries bordering Ukraine and Russia were the most affected, as were the UN countries that condemned the war.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
7.
Informational Autocrats Guriev, Sergei; Treisman, Daniel
The Journal of economic perspectives,
11/2019, Volume:
33, Issue:
4
Journal Article
Peer reviewed
Open access
In recent decades, dictatorships based on mass repression have largely given way to a new model based on the manipulation of information. Instead of terrorizing citizens into submission, ..."informational autocrats" artificially boost their popularity by convincing the public they are competent. To do so, they use propaganda and silence informed members of the elite by co-optation or censorship. Using several sources, including a newly created dataset on authoritarian control techniques, we document a range of trends in recent autocracies consistent with this new model: a decline in violence, efforts to conceal state repression, rejection of official ideologies, imitation of democracy, a perceptions gap between the masses and the elite, and the adoption by leaders of a rhetoric of performance rather than one aimed at inspiring fear.
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CEKLJ, IZUM, KILJ, NUK, PILJ, SAZU, UL, UM, UPUK
This paper develops and estimates an equilibrium model where heterogeneous firms can exploit two margins of informality: (i) not register their business, the extensive margin; and (ii) hire workers ...“off the books,” the intensive margin. The model encompasses the main competing frameworks for understanding informality and provides a natural setting to infer their empirical relevance. The counterfactual analysis shows that once the intensive margin is accounted for, firm and labor informality need not move in the same direction as a result of policy changes. Lower informality can be, but is not necessarily associated with higher output, TFP, or welfare.
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BFBNIB, CEKLJ, INZLJ, IZUM, KILJ, NMLJ, NUK, ODKLJ, PILJ, PNG, SAZU, UL, UM, UPUK, ZRSKP
This study deviates from extant studies by examining the effect of shadow economy (SE) on environmental pollution, and the role institutional indicators play in moderating the effect in West Africa ...between 1992 and 2015. Specifically, the study employed three institutional indicators (corruption control COR, law and order LAW, and bureaucratic quality BUQ) to mediate the effect and also determine its threshold values. SE is measured using Multiple Indicators Multiple Causes (MIMIC) while environmental pollution is proxy by carbon dioxide (CO2) per capita. Two step system Generalized Method of Moments (GMM) is used to drive out the conclusions of the study. The findings reveal that SE, COR and LAW contribute significantly to environmental pollution, while BUQ though not significant, reduces environmental pollution in the region. Further, the interactive effect of SE with all the institutional indicators shows that strong institutional indicators abate environmental pollution through reduction in the presence of SE. The threshold value of institutional indicators, which reduces SE and abates environmental pollution, are 3.8 and 3.7 for COR, and LAW, respectively, on an ordinary scale of 0–6, while 2.8 for BUQ on an ordinary scale of 0–4. Nevertheless, most of the countries in the region operate below the threshold level of institutional indicators in the region. The results are robust to different proxies of environmental pollution. The implications of the study are discussed.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Mounting environmental pressures led China to focus on the effectiveness of the environmental regulation to control pollution. Since the shadow economy, or underground economic activities that are ...not included in official statistics, accounts for an increasing fraction of China's economy, its impacts on environmental quality should be carefully evaluated. In this study, the main research questions are as follows: 1) What is the extent of the effect of environmental regulation on environmental quality? and 2) What are the factors that influence the impact of environmental regulation on environmental pollution? A theoretical model is developed to explain the relationship among the environmental regulation, shadow economy, and environmental quality in China. An empirical analysis is conducted to test the three propositions of the model, thereby examining the explanatory power of the theoretical model. Concretely, using panel data from 30 provinces for the period of 1998–2012, the generalized method of moments (GMM) method is employed to control for potential endogeneity and introduce dynamic effects. The estimation results indicate that stringent environmental regulation and the level of the shadow economy are both positively related to China's environmental pollution; however, the results also indicate that tighter environmental control would help reduce pollution at a given level of the shadow economy. Moreover, an increase in the proportion of corrupt officials may weaken the environmental regulation, which would consequently lead to the increase in illegal production and total pollutant emissions. Besides, many economic and social factors may also affect the environmental quality. For instance, the development of secondary industry contributes toward an increase in pollutant emissions; however, increased research and development (R&D) spending on eco-friendly industrial operations can help to reduce pollution.
•Impact of environmental regulation, shadow economy and corruption on the environment is examined.•A theoretical model is built to explain the relationship.•Three propositions of the theoretical model are empirically tested.•Levels of environmental regulation and shadow economy are positively related with pollution.•Environmental regulation is effective only when shadow economy and corruption are controlled.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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