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The study's objective is to examine the relevance of globalization in affecting the size of the shadow economy in selected African nations.

To do this, the authors employ the KOF globalization index and implement both static and dynamic common correlated mean group estimators on a panel of 24 African nations from 1995–2017. This technique accommodates the issue of cross-sectional dependence, sample bias and endogenous regressors. Panel threshold analysis is also conducted to establish the nonlinearity between globalization and the shadow economy. To examine the causality between the variables, the study employs Dumitrescu and Hurlin's panel causality test.

The results show that globalization reduces the size of the shadow economy. The results of the nonlinear analysis suggest a U-shaped relationship. Overall globalization has a threshold impact of 48.837%, economic globalization has 45.615% and political globalization has 66.661% while social globalization has a threshold value of 35.744%. The results of the panel causality show that there is a bidirectional causality between the two variables.

The results suggest that the government and other relevant authorities need to introduce capital controls and other policy measures to moderate the degree of social, political and cultural diffusion. Appropriate policies should be formulated to monitor the extent of African economic openness to other continents to maximize the gains from globalization.

Apart from being the first study in the African region that evaluates the relevance of globalization in controlling the shadow economy, it also analyzes the dynamics and threshold analysis between the two variables using advanced panel econometrics which makes the study unique. The study suggests that globalization tools are useful for affecting the size of the shadow economy in Africa. This study provides fresh empirical evidence on the impact of globalization on the shadow economy in the case of Africa.

The present research aims at identifying the latent factors that are driving the rise of the shadow economy in Palestine, assesses its magnitude from 1998 to 2021 and investigates the influence that its size has on the financial sustainability of Palestine's public budget.

The researchers employed the multi-indicator multi-causes (MIMIC) model to estimate the size of the shadow economy and investigate its effect on the financial sustainability of the public budget. Economic factors such as direct taxes, indirect taxes, government welfare, government spending and unemployment were considered causal variables, while indicators of financial sustainability included budget deficit, public debt and gross domestic product (GDP). The shadow economy served as an intermediary variable.

Based on the findings, the researchers recommend regulating and formalizing legitimate activities within the shadow economy. Additionally, they suggest promoting investment projects to reduce unemployment rates, lowering taxes on essential goods and consumer items and providing support to local producers in Palestine. These measures aim at addressing the challenges posed by the shadow economy and fostering economic stability.

The study reveals that the average size of the shadow economy in Palestine between 1998 and 2021 was 43.80%, fluctuating within the range of 39.92%–46.30%. It further establishes that an increase in direct and indirect taxes as well as unemployment contributes to the expansion of the shadow economy. Conversely, government welfare and spending exert a diminishing effect. Moreover, the study finds that the rise of the shadow economy correlates with an increase in public debt, budget deficit and GDP, indicating a negative impact on the financial sustainability of the public budget.

Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.

This paper uses the data from 27 countries and various estimation strategies to test the arguments presented in this paper. The sample covers the period between 2002 and 2020.

The empirical results suggest that banks headquartered in countries with high shadow banking activity have fewer NPLs than otherwise similar banks headquartered in countries with low shadow banking activity. The findings remain qualitatively the same in different sub-samples and after replacing the main variables with their alternate proxies. The paper also shows that this relationship is sensitive to bank-specific characteristics. Moreover, the paper also indicates that the stringency of banking regulations weakens the relationship between shadow banking and NPLs.

The study’s data limitations prevent a detailed year-by-year analysis of NPLs and shadow banking, restricting insights into their evolving dynamics. In addition, the focus on country-level shadow banking data limits the exploration of how multinational banks’ activities in various jurisdictions impact individual banks’ NPLs.

The paper not only documents the effect of shadow banking on NPLs but also shows that the relationship between shadow banking and NPLs weakens as banking regulations become more stringent.

The effects of government expenditure on the shadow economy have been investigated. However, the effect from a moderating factor that affects this relationship has been largely ignored in the existing literature. This paper investigates how fiscal deficit moderates the effects of government expenditure on the shadow economy for 32 Asian countries for the past two decades since 2000.

The authors use various techniques, which allow cross-sectional dependence and slope homogeneity in panel data analysis, to examine this relationship in both the long run and short run. The analysis also considers the marginal effects of government expenditure on the shadow economy at different degrees of fiscal deficits.

Empirical findings from this paper indicate that an increase in government expenditure and fiscal deficit will increase the shadow economy size. Interestingly, the effects of government expenditure on the shadow economy will intensify with a greater degree of the budget deficit. The authors also find that enhancing economic growth to improve income per capita and extending international trade appears to reduce the shadow economy in the Asian countries.

The authors consider that policies targeting reducing shadow economy should follow conventional economic policies on economic growth, unemployment and inflation.

To the best of the authors’ knowledge, this is the first empirical study conducted to examine the moderating role of fiscal deficit in the government expenditure–shadow economy nexus in Asian countries.

This study builds on the extant research of the authors on illegal rural enterprise (IRE). However, instead of taking a single or micro case approach within specific sections of the farming and food industries we examine the concept holistically from a macro case perspective. Many IRE crimes simply could not be committed without insider knowledge and complicity, making it essential to appreciate this when researching or investigating such crimes.

Using data from published studies, we introduce the theoretical concept of “Shadow infrastructure” to analyse and explain the prevalence and endurance of such criminal enterprises. Using a multiple case approach, we examine data across the cases to provide an analysis of several industry wide crimes—the illicit halal meat trade; the theft of sheep; the theft of tractors and plant; and the supply of illicit veterinary medicines.

We examine IRE crimes across various sectors to identify commonalities in practice and in relation to business models drawing from a multidisciplinary literature spanning business and criminology. Such enterprises can be are inter-linked. We also provide suggestions on investigating such structures.

We identify academic and practical implications in relation to the investigation of IRE crime and from an academic perspective in relation to researching the phenomenon.

This study combines data from numerous individual studies from a macro perspective to provide practical solutions to a multifaceted problem.

High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.

There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.

In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.

The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.

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.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

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