Size Of Shadow Economy Research Articles

Macroeconomic fundamentals, institutional quality and shadow economy in OIC and non-OIC countries

PurposeThe purpose of this paper is to analyze the relationship between macroeconomic fundamentals, intuitional quality and shadow economy.Design/methodology/approachBy 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.FindingsThe 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.Originality/valueThe 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.

Shadow economy and foreign direct investment in Nigerian manufacturing industry

In this paper, we investigate the symmetric and asymmetric effect of shadow economy on foreign direct investment (FDI) in Nigerian manufacturing sector using ARDL and NARDL estimation techniques for the period of 1975-2017. We find that an increase in shadow economy reduces FDI net inflow in the short run while this relationship turns to be positive in the long run. This result persists after using NARDL to re-estimate the model. Negative and positive changes in the size of shadow economy have negative and significant effects on FDI in the short run, while in the long run both changes have positive effects on FDI in the sector. The results imply that in the short run, new foreign investors would like to operate in the formal sector due to tax incentives and other financial incentives available for new entrants. However, in the long run, shadow economy attracts FDI, because incentives enjoyed have expired coupled with high cost of doing business in the country. The investors would prefer to either look for loopholes in tax laws or attempt to evade tax and cut down official remittances to the government by operating in the informal sector of the economy.

Investigating and estimating the size of Shadow Economy by using monetary approach: Case study of Malaysia

The purpose of this study is to explore and estimate the size of Shadow Economy of Malaysia. This study used annual Time series data from 1980 to 2018, introduced Lending Interest Rate as additional variable for the first time to estimate the Shadow or dim Economy, and focused on the Currency Demand Approach (CDA) which is the best way of estimation the size of S.E. The results of ARDL, Unit Root Test (ADF) and Bound Test have also generated for the purpose. And this study investigated positive relationship between Currency Circulation to Money Supply Ratio and GDP, Inflation, Interest rate, and Total Tax Revenue through ARDL and estimated the required Shadow Economy, and also explored the Shadow Economy of Malaysia and estimated the size of S.E. Size of tax evasion community has also derived by present research which represent that taxes are not the only measures of Shadow Economy.

CORRUPTION AND THE SHADOW ECONOMY - EFFECTS ON A COUNTRY’S ECOMICAL DEVELOPMENT

Corruption and the shadow economy represent an interesting and current topic in the field of business, because they are responsible for important economic and financial loses, for the governments and the economic and social future of one’s country. Therefore, the current paper aims to underline the concepts of corruption and shadow economy, the main types of corruption and how the shadow economy manifests itself in different economical systems as well as some methods of analysing the shadow economy size. We are presenting some interesting results of a secondary data research developed in order to understand the impact of the corruption phenomena on the economical results of certain European countries, as well as assessing the evolution of the Corruption Perception Index in the EU and its impact in the population perception of corruption, combined with pointing out how the shadow economy reduces the value of the GDP, by providing a comparative analysis of different countries.

Mitigating the shadow economy through financial sector development in Indonesia: some empirical results

We examine the relationship between financial sector development and the shadow economy in Indonesia from 1980 to 2020. We estimate the size of Indonesia's shadow economy using the “Modified Cash to Deposits Ratio” approach. We then construct a long-term model using the size of Indonesia's shadow economy as the dependent variable. We set financial sector development as the main independent variable in our model. We use per capita real gross domestic product, the misery index, and foreign direct investment as control variables in our model. We find that financial sector development and the size of Indonesia's shadow economy have a nonlinear relationship that shows an inverted U-shape curve. The size of the shadow economy expands at the early stages of financial sector development to a turning point and decreases when financial sector development increases further. We also find that foreign direct investment curtails Indonesia's shadow economy. Additionally, increases in income expand Indonesia's shadow economy while misery index shows ambiguous results. We suggest the Indonesian authorities widen access for micro, small, and medium firms to the credit markets and enhance existing programs to reduce poverty and narrow the income gap in the country. These efforts help to narrow the size of Indonesia's shadow economy.

Determinants of shadow economy in OIC and non-OIC countries: the role of financial development

PurposeThe 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.Design/methodology/approachThe study applies advanced panel GMM technique.FindingsThe 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.Research limitations/implicationsSince 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.Practical implicationsThe 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.Social implicationsThe OIC member countries should implement policies which improve accessibility to finance of every citizen of the country.Originality/valueDespite 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.

Oil price shocks, protest, and the shadow economy: Is there a mitigation effect?

AbstractIn this study, we look at how oil price shocks affect the incidence of protests in a country and how the size of a country's shadow economy influences this relationship. Using panel data from 144 countries, from the period of 1991–2015, we find evidence that negative oil price shocks significantly increase protests in countries with small shadow economies. The effect dissipates as the size of the shadow economy increases and eventually vanishes in countries with a shadow economy representing more than 35% of gross domestic product. Our analysis departs from existing literature by emphasizing the moderating role of a shadow economy on the effects of negative oil shocks on the incidence of protests in oil‐dependent economies. The results are robust to various specifications and their broader implications are discussed.

Shadow economy in Africa: how relevant is financial inclusion?

PurposeThis study aims to investigate the possible relationship between financial inclusion and shadow economy in selected African countries.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThis 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.

ICT development and shadow economy: Empirical evidence from the EU transition economies

The substantial improvements in development information and communication technologies led many economic and non-economic implications for the countries and in turn motivated the researchers to question the various effects of ICT especially in the light of economic crime. This study explores the short and long run influence of information and communication technologies on the shadow economy in 11 post-transition EU members over 1996-2015 period through second generation panel cointegration and causality tests regarding the cross-sectional dependence. The economic analyses disclosed that ICT indicators and human development had significant effects on the size of shadow economy in both short and long run. It was found that growing ICTs lead to reduction on the size of the shadow economy; in addition, human capital improvement policies serve as an important factor when tackling the shadow economy.

Impacts of Political Stability on Shadow Economy: Evidence from Bay of Bengal Initiative for Multi-sectoral Technical and Economic Cooperation Countries

The issue of political stability and the shadow economy is the most vital concern for sustainable development. However, the relationship between them is yet to be explored. Particularly, in the context of Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation Countries (BIMSTEC) countries, there are no studies that have examined the influence of political stability on shadow economy. This study fills these gaps. Using panel data from 1998 to 2015, this study empirically investigated whether and how political stability affects shadow economy. Findings indicate that political stability has significant negative effects on the size of shadow economy. We also observed that regulation freedom, fiscal freedom, business freedom, trade freedom, government integrity, government spending and gross domestic product (GDP) growth have significant negative effects, while unemployment has significant positive effects on the shadow economy. Findings of this study imply that governments and policymakers should make efforts to ensure greater political stability in their countries, which will lessen the size of shadow economy that, in turn, will accelerate economic growth. The present study adds to empirical literature of the analogous issue by confirming (or else) the findings of past studies carried out across the world. The findings indicate that there exists a positive association between the extent of political stability and the shadow economy for BIMSTEC countries.

Tax evasion, corruption and COVID-19 health risk exposure: a cross country analysis

PurposeThe purpose of this study is to examine the relationship between tax evasion and COVID-19 public health risk exposure in both high-corruption countries and low-corruption countries.Design/methodology/approachThis study uses cross-sectional data from 138 countries. Tax evasion is measured using the shadow economy size (light intensity approach) as calculated by (Medina and Schneider, 2018). The SolAbility COVID-19 public health risk exposure index (CPHRE) is used to measure COVID-19 health risk. Also, the corruption perception index from transparency international is used for measuring the level of corruption.FindingsThis study finds that the level of tax evasion is positively related to CPHRE. Also, the results revealed a positive relationship between corruption and CPHRE. Furthermore, this study examined the moderation effect of corruption. The results indicate that the positive relationship between tax evasion and public health risk exposure is significant in low-corruption countries, but it is insignificant in high-corruption countries. These results imply that the severity of corruption can increase COVID-19 health risk exposure more than tax evasion.Practical implicationsOur findings are alerting the policymakers for the negative noneconomic consequences of tax evasion and corruption. It provides evidence that tax evasion and corruption can increase CPHRE.Originality/valueAccording to the author’s knowledge, this is the first study that examines the relationship between tax evasion and COVID-19 risk and that tests the moderation effect of corruption.

METHOD OF ESTIMATING THE VOLUME OF THE SHADOW ECONOMY

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.

Relationship Between Unemployment Rate and Shadow Economy in Nigeria: A Tado-Yamamoto Approach

This study assessed the nature of the relationship between the size of the shadow economy and unemployment rate in Nigeria using the Tado-Yamamoto approach over the period 1980Q1 to 2018Q4. The size of the shadow economy in Nigeria was determined using the parsimonious model of MIMIC (4-1-2) having four multiple causes (tax burden, self-employment, social benefits paid by the government and unemployment rate) and two indicators (index of real Gross Domestic Product and currency ratio (M1/M2)). The estimated relationship of the size of shadow economy as percentage of official GDP recorded 13.78% at the beginning of the first quarter of 1980 before fluctuating to 8.23% in the third quarter of 2009. The existence of a strong and positive association between the unemployment rate and shadow economy is affirmed by the estimated coefficient of determination (0.89) which confirmed the capacity of the shadow economy to absorb the unemployed workers from the official economy in Nigeria. Evidence exists from the Tado and Yamamoto (1995) causality test which revealed a causal relationship emanating from unemployment rate to the size of shadow economy. This was confirmed by the Modified Wald (MWald) test which demonstrated that a strong unidirectional causality running from unemployment rate to the size of shadow economy exists at 1% level of significance.

Shadow economy and foreign direct investment in Nigerian manufacturing industry

In this paper, we investigate the symmetric and asymmetric effect of shadow economy on foreign direct investment (FDI) in Nigerian manufacturing sector using ARDL and NARDL estimation techniques for the period of 1975-2017. We find that an increase in shadow economy reduces FDI net inflow in the short run while this relationship turns to be positive in the long run. This result persists after using NARDL to re-estimate the model. Negative and positive changes in the size of shadow economy have negative and significant effects on FDI in the short run, while in the long run both changes have positive effects on FDI in the sector. The results imply that in the short run, new foreign investors would like to operate in the formal sector due to tax incentives and other financial incentives available for new entrants. However, in the long run, shadow economy attracts FDI, because incentives enjoyed have expired coupled with high cost of doing business in the country. The investors would prefer to either look for loopholes in tax laws or attempt to evade tax and cut down official remittances to the government by operating in the informal sector of the economy.

Corruption, Shadow Economy And Economic Growth: Evidence From Emerging And Developing Asian Economies

This paper investigates the interactions of corruption and the shadow economy with economic growth in 17 selected Asian countries with emerging and developing economies. These countries are categorized according to International Monetary Fund sources and chosen based on available data. This paper analyzes the annual data over the period 2000 – 2015 from the World Bank, Transparency International and from International Monetary Fund to estimate whether corruption and shadow economy affect economic growth. Generalized Methods of Moments (GMM) method is used in this research. The results show that corruption index has a statistically significant and positive impact on economic growth while the shadow economy has a significant negative impact. These findings suggest that corruption does not sand but greases on the wheel of economic growth. Further, a reduction in the size of shadow economy could be more beneficial for emerging markets and developing economies in Asia to develop economy. Additionally, the results also indicate that in these countries, foreign direct investment, public expenditure, tax revenue and inflation have a positive impact on the growth while remittances have no relationship.

Empirical analysis of the interplay between shadow economy and pollution: With panel data across the provinces of China

This paper provides a pioneering study of the interactive relationship between shadow economy and environmental pollution by applying the data of the 31 provinces in China from 2005 to 2015. Side effects of shadow economy including environment pollution have been proved by plenty of articles, yet still have not attracted enough public attentions. If the severe pollution will in turn further increase the size of the shadow economy, then the environmental situation in the present will lead to an even worse unhealthy economy growth path. This paper firstly adopts MIMIC (Multiple Indicators Multiple Causes) method to calculate the size of shadow economy, then uses the Generalized Method of Moments (GMM) specification to analyze the interplay between shadow economy and pollution in association with environmental regulation, economic growth, foreign direct investment and educational level. The results show that shadow economy and pollution do have a positive interaction between each other, statistically significant at 1% level. Also, both pollution and shadow economy have a U-shaped non-linear relationship with environmental regulation, but an inverse U-shaped non-linear relationship with economic growth. Finally, foreign direct investment (FDI) and education level have positive linear impacts on both pollution and shadow economy, too. But the effect from FDI is weak and less significant.

SHADOW ECONOMY, AEOI, DAN KEPATUHAN PAJAK

This research develops a broad conceptual framework of shadow economy transactions in Indonesia based on the previous research and finds the correlation with the current tax regulation on automatic exchange of information and tax compliance. Shadow economy is the activity of individuals, households, and/or firms that evade, avoid, or not report its transaction to the government. Based on the previous research, by using monetary approach, the average size of shadow economy in Indonesia equals to 8 – 19% of GDP. Based on this data, the government uses automatic exchange of information (AEOI) to minimize the effect of shadow economy to increase tax revenue and to boost tax compliance.

How Does the Shadow Economy Affect Environmental Quality in Sub-Saharan Africa? Evidence from Heterogeneous Panel Estimations

This paper empirically examines how the size of the shadow economy affects environmental quality in sub-Saharan Africa (SSA). We apply the autoregressive distributed lag (ARDL) methodology to a panel of 22 SSA countries over the 1991–2015 period. Findings show that there is a negative relationship between the size of the shadow economy (in percentage of GDP) and CO2 emission both in the long and short run. Also, the size of shadow economy is found to be inversely related to CO2 emission in the long run for all income groups, but this effect is statistically significant only within the subpanel of lower-middle-income countries. Consistent with the scale effect, our findings suggest that there is no evidence that the shadow economy increases environmental degradation in SSA.

Tax evasion and public governance before and after the European “big bang”: a red flag for policymakers

PurposeThe purpose of this study is to examine the impact of public governance quality on tax evasion levels in old (pre-2004) and new (post-2004) European Union (EU) members before and after the 2004 EU-enlargement.Design/methodology/approachThis study uses panel data of 28 EU countries over the period 1996-2015. Tax evasion is measured using an updated version of the shadow economy size based on the light intensity, as calculated by (Medina and Schneider, 2018). The World Bank’s worldwide governance indicators are used as a measure of public governance.FindingsThe results indicate that new EU members have higher tax evasion levels compared to the old ones before and after the 2004 EU enlargement. The findings also report that the public governance quality is superior in old members throughout the 1996-2015 period. Furthermore, the authors found that after the EU enlargement, tax evasion levels decreased in both EU groups; however, the authors noticed an improvement in the public governance quality in new members and a deterioration in old ones. Additional analysis confirms the impact of public governance quality as an effective tool for reducing tax evasion behavior in both EU groups before and after the EU enlargement.Practical implicationsThe findings are potentially useful for EU policymakers in identifying the most effective tools that can minimize tax evasion levels in EU countries. Additionally, the results are alarming as they show the negative consequences of the EU enlargement in old EU members. Thus, policymakers should consider them when setting their rules and regulations to reduce the significant differences between both EU groups to prevent member states from potentially exiting the EU.Originality/valueTo the best of the knowledge, this is the first study that examines the tax evasion behavior and public governance quality in the EU before and after the EU enlargement.

Modelling the shadow economy of South Africa: Using the currency demand and MIMIC approach

Abstract. This paper estimates the size and development of the South African shadow economy (SE) using two indirect approaches namely, the Multivariate Indicator Multivariate Causes (MIMIC) model and the Currency Demand Approach (CDA). The study uses time series from 2000 to 2019 (using quarterly data) to estimate the SE of South Africa for the period 2004 to 2018. The average estimated size of the SE from the CDA and MIMIC model are 22.47% and 25.45% respectively. Overall, the MIMIC and CDA models are both showing a slight decreasing trend for the same period. The study recommends further analysis to be conducted on economic segments in order to explore the SE activity distribution between different economic sectors; resulting in an easier way to identify, locate and monitor unrecorded businesses and also increase revenue collections and minimise non-compliance for different sectors. Keywords. Shadow Economy of South Africa, GDP, CDA, MIMIC. JEL. C32, H26, I2, O17, P48.