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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.

The purpose of this paper is to analyze the relationship between macroeconomic fundamentals, intuitional quality and shadow economy.

By utilizing data setspanning from 2004 to 2015 of 141 countries, the study has employed advanced panel technique, i.e. Generalized Method of Moments (GMM) method. In order to check consistency of the results, the study also used fixed effect and random effect for robustness.

The study finds that for the full sample, institutional quality has negative effect on shadow economy while macroeconomic fundaments effect shadow economy differently. After splitting the sample into Organization of Islamic Cooperation (OIC) and non-OIC countries subsamples, it observes same influence of macroeconomic fundaments and institutional quality on shadow economy, but the effect of macroeconomic fundaments and institutional quality on shadow economy is less observed for OIC countries. The results are found consistence by using different estimation methods.

The current literature has focused on estimating the size of shadow economy and literature linking the macroeconomic fundaments, institutional quality and shadow economy is scarce. Additionally, this study provides the evidence for cross comparison between OIC economies and non-OIC economies.

The purpose of this paper is to investigate the nonlinear relationship between shadow economy and income inequality and determine whether the size of shadow economy can influence the level of income inequality.

Both parametric (panel OLS) and nonparametric/semiparametric regression suggested by Robinson (1988) will be used to capture the dynamic nonlinear relationship between these variables using unbalanced panel data of 154 countries from 2000 to 2007. Additionally, the relationship between income inequality and shadow economy on both developed and developing countries will be analyzed and compared.

First, semiparametric analysis and nonparametric analysis are significantly different than parametric analysis and better in nonlinear analysis between income inequality and shadow economy. Second, income inequality and shadow economy resemble an inverted-N relationship. Third, the relationship between income inequality and shadow economy is different in developed countries (OECD countries) and developing countries, where OECD countries have similar inverted-N relationship as before. However, for developing countries, income inequality and shadow economy show an inverted-U relationship, similar to the original Kuznets hypothesis.

This study suggests that there is a possible trade-off between income inequality and shadow economy and helps policy makers in solving both problems effectively.

Despite the growing importance of income inequality and shadow economy, literature linking the two variables is scarce. To the best of the authors’ knowledge, there is no literature that nonlinearly links these two variables. Furthermore, the dynamics of the relationship between these two variables in developed countries and developing countries will be explored as well.

In this paper, the authors examine how economic growth shapes the shadow economy in the long and short run.

Using annual time series data from Uganda, drawn from various data sources, covering the period from 1991 to 2017, the authors apply the ARDL modeling approach to cointegration.

This paper finds that an increase in economic growth significantly reduces the size of the shadow economy, in both the long and short run, all else equal. However, the long-run relationship between the shadow economy and growth is non-linear. The results suggest that the rise of the shadow economy could partially be attributed to the slow and sluggish rate of economic growth.

These findings imply that addressing informality requires addressing underlying factors of underdevelopment since improvements in economic growth also translate into a reduction in the size of the shadow economy in the short and long run.

These findings reveal that the low level of economic growth is an issue because it spurs informal sector activities in the short run. However, as the economy improves, it becomes an incentive for individuals to operate in the informal sector. Additionally, tackling shadow activities in the short run could help improve tax revenue collection.

The purpose of this paper is to empirically investigate the determinants and the impact of financial development on shadow economy in OIC countries and then compared with non-OIC countries.

The study applies advanced panel GMM technique.

The study finds that macro-variables (unemployment, economic growth, money supply and foreign trade) and institutional variables reduce shadow economy both in OIC and non-OIC countries. The study also explores that financial development mitigates shadow economy; however, its impact is significantly less in case of OIC economies compared to the non-OIC countries.

Since the focus of this study is OIC countries vs non-OIC countries, the research only includes discussion about shadow economy in 42 OIC member states and 99 non-OIC economies. The decision to restrict the study to 42 OIC economies and 99 non-OIC nations is due to the availability of data.

The study suggests that free market and good business environment in the formal economy are the keys to have less shadow economy. Good institutional setup and ease in regulations can attract firms and businesses from informal sector to the official economy, while political instability is one of the main factors for having large size of shadow economy.

The OIC member countries should implement policies which improve accessibility to finance of every citizen of the country.

Despite the growing importance of shadow economy, the literature investigating determinants and the role of financial development in shadow economy is scarce. To the best of the authors' knowledge, there is no literature that examined the shadow economy in the context of OIC member countries. Furthermore, this study has covered a large number of OIC and non-OIC economics over time and across different groups using largest data and advanced panel GMM techniques.

This study aims to investigate the possible relationship between financial inclusion and shadow economy in selected African countries.

The study uses panel data estimation technique and Toda and Yamamoto causality approach. The data of selected African counties over a period of 2005–2015 are sourced from World Bank Development Indicators, International Monetary Fund International Financial statistics database and International Country Risk Guide.

The results show that financial inclusion reduces the size of shadow economy. The causality results show that there is a unidirectional causality moving from financial inclusion to shadow economy. The results demonstrate that a country with lower level of corruption and higher level of growth can benefit more in reducing the size of shadow economy through financial inclusion.

This study provides the first evidence of the link between financial inclusion and shadow economy from the Sub-Saharan Africa perspective. The study suggests that financial inclusion may be useful in affecting the size of shadow economy in Africa.

This study investigates the effect of shadow economy on environmental pollution and the role of institutional quality in moderating the impact in African countries between 1991 and 2015.

The study employs three pollutant variables namely: carbon dioxide emissions per capita, methane emission and nitrous oxide emission as robustness check. Also, battery of methodologies; ordinary least squares, fixed effects and system generalised method of moments are used to drive out the conclusions of this study.

The findings reveal that shadow economy and institutional quality contribute significantly to environmental pollution in Africa. Further, the interactive effect of shadow economy and institutional quality worsens environmental quality in the region. This reveals that weak institutional quality recorded in the region increases the level of shadow economy, thereby intensifying environmental pollution.

The study concludes that weak institutional framework in the region reinforces shadow economy and environmental pollution. Hence, findings from this study can help policymakers in the region to better understand the role of institutional quality in reducing shadow economy and environmental pollution.

This study enriches one’s understanding on the role of institutional quality in the relationship between environmental quality and shadow economy in African context. It investigates the direct and indirect impact of institutions and shadow economy on environmental quality. The study also uses three different robust variables to measure environmental pollution (carbon dioxide (CO₂) emissions per capita, methane emission and nitrous oxide emission) for sensitivity analysis.

Using state-level data on productive and unproductive entrepreneurship, shadow economy size, and public official corruption, the purpose of this paper is to examine whether formal sector productive (unproductive) entrepreneurial activity is associated with lower (higher) levels of informal economic activity.

Additionally, the author aims to connect US state-level entrepreneurship, shadow economy size, and corruption by asking whether corruption affects entrepreneurial outcomes primarily through its effects on the shadow economy. The author contends that if this is the case, then estimates of corruption should serve as a good instrument for shadow economy size in regressions on formal sector entrepreneurial outcomes.

Results from OLS regressions suggest that shadow economy size shares a strong, negative (positive), and statistically significant relationship with productive (unproductive) entrepreneurship. These results are fairly robust to GMM estimation. Additionally, the author finds that corruption is a strong instrument for shadow economy size; one for which validity cannot be rejected in regressions on productive, and net entrepreneurship scores.

However, the author cannot safely assert that the author finds evidence of the shadow economy serving as a primary channel through which corruption affects observed entrepreneurial outcomes. Failure to reject validity of the corruption instrument is, at best, suggestive of the primacy of the entrepreneurial choice between formal and informal sector participation.

This study, to the author’s knowledge, is the first to attempt “connecting the dots” between entrepreneurship, corruption, and shadow economy size.

The purpose of this paper is to examine the impact of corruption on the size of the shadow economy in countries that differ with respect to income level or geographical location. The underlying idea is that the primary manifestation of corruption might be associated with country characteristics and that different types of corruption might have different consequences.

IV regressions and bootstrapping are applied to a cross‐section of countries to show that geographical location of a country impacts on the relationship between corruption and the shadow economy. An interaction term of the level of corruption and geography is used to capture the differences in the types and consequences of corruption between countries.

Corruption does not seem to affect the size of the shadow economy outside the tropics. Instead, the higher the tropical area fraction of a country, the more a certain level of corruption enlarges the unofficial economy. Moreover, corruption and the shadow economy seem to be substitutes in the tropics.

Different types of corruption may have different consequences.

Unlike most of the previous literature, the paper accounts for the fact that some corrupt practices tend to be commonplace in some parts of the world, while other countries may be plagued by other types of corruption. Therefore, the consequences of corruption might also differ.