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.Shadow economy of 162 countries, tax burden, quality of state institutions, regulation, MIMIC model,

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

This paper is a first attempt to study the impact of enforcement on the shadow economy. Using a MIMIC model, we find that a higher share of sub-national government employment and the aspiration of public employees to follow rules significantly deter shadow economic activities. Our results also confirm previous findings: Increased burdens of taxation and regulation as well as the state of the "official" economy are important determinants of the shadow economy. The estimated weighted average informality in 162 countries around the world, including developing, Eastern European, Central Asian, and high-income OECD countries, is 17.1% of "official" GDP.Keywords Shadow economies · Quality of institutions · Enforcement · MIMIC Model JEL Classification O17 · O5 · D78 · H11 · H26

From a theoretical point of view, the relationship between corruption and the shadow economy is ambiguous: They can either be substitutes or complements. This paper contributes to this debate by using a structural equation model with two latent variables to extract information on various dimensions of corruption and the shadow economy. Analyzing a sample of 51 countries around the world over the period 2000 to 2005, we present empirical evidence for a complementary (positive) relationship of corruption and the shadow economy.

This paper presents various methods used for estimating the size of the shadow economy. Each method is evaluated and its strengths and weaknesses are discussed, as well as results each method yields. The purpose of the paper is threefold: Firstly, to demonstrate that there is no single infallible method for estimating the size and development of the shadow economy and results can differ significantly between different approaches. The MIMIC approach, discussed in greater detail, is often used due to its flexibility. Secondly, the paper discusses the very definition of the shadow economy and factors contributing to its growth. Finally, latest estimations of the size of the shadow economies of 143 countries over the period 1996 to 2014 are presented. JEL-Classification: D78, E26, H2, H11, H26, K42, O5, O17Keywords: shadow economy estimates, MIMIC approach, methods to estimate the shadow economy, advantages and disadvantages of the methods, MIMIC-method, calibration procedure, light intensity approach IntroductionEmpirical research about the size and development of the shadow economy all over the world has grown rapidly. Nowadays, there are so many studies,1 which use different methods in order to estimate the size and development of the shadow economy, that it is quite difficult to judge the reliability of various methods. Hence, the goal of this paper is to critically review the various methods for estimating the size of the shadow economy and to discuss their strengths and weaknesses. This will enable an interested reader to evaluate the advantages and disadvantages of the different methods.The paper is structured as follows: In the next section some theoretical considerations are presented, starting with a definition of the shadow economy and a brief discussion of its main causes. In section 3 the various measurement methods, as well as their strengths and weaknesses, are described. This section also presents estimates of the size of the shadow economy in Germany using different estimation methods. Section 4 presents some latest developments, new measurement methods, the concept of digital shadow economy, and latest results from 143 countries between 1996 and 2014. Finally, section 5 presents a summary and some concluding remarks.1 See e.g. Feld and Schneider (2010), Gerxhani (2003), Schneider (2015), and Schneider and Williams (2013), Schneider (2016, Schneider (2016), andSauka, Schneider and Defining the shadow economyResearchers attempting to measure the size of shadow economy face the first and difficult question of how to define it.2 One commonly used working definition encompasses all currently unregistered economic activities that would contribute to the officially calculated (or observed) Gross National Product if observed.3 Smith (1994, p. 18) uses the definition "market-based production of goods and services, whether legal or illegal, that escapes detection in the official estimates of GDP." One of the broadest definitions includes "those economic activities and the income derived from them ...

We analyse the determinants of trade misinvoicing using data on 86 countries from 1980 to 2005. In a simple microeconomic framework, we derive the determinants of four different types of trade misinvoicing taking into account that only the financial incentives determine whether and how much exports/imports to underinvoice or overinvoice, whereas the deterrents only affect the extent of misinvoicing. The hypothesised determinants are tested using data on discrepancies in bilateral trade with the United States. We find that the black market premia and tariffs motivate illegal trading activities. Higher financial penalties effectively act as a deterrent to this crime.

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This paper studies the impact of decentralization on the shadow economy. We argue that decentralization may decrease the size of the shadow economy mainly through two transmission channels: (1) Decentralization enhancing public sector efficiency (efficiency effect), and (2) decentralization reducing the distance between bureaucrats and economic agents, which increases the probability of detection of shadow economic activities (deterrence effect). Using various measures of fiscal, political and government employment decentralization in a cross-section of countries, we find the deterrence effect to be of more importance. The deterrence effect is stronger, the lower the degree of institutional quality. Remarkably, we find no robust evidence of the efficiency effect.