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International Monetary Fund

, requirements to be a taxpayer in the previous year, to demonstrate evidence of the lockdown’s effect on business). Also, closures and restrictions may have incentivized some activities to operate informally. Taking into account the size and nature of shadow activities and employment in specific jurisdictions will be important when designing policy responses to the pandemic. 13 Annex 2.1. Mimic Estimation Results for European Shadow Economies Annex Table 2.1.1. Shadow Economy Estimates, Europe, 2000–06 (Percentage of GDP) Country 2000 2001

Mr. Ben Kelmanson, Koralai Kirabaeva, Leandro Medina, and Jason Weiss
This paper examines the drivers, and reestimates the size of shadow economies in Europe, with a focus on the emerging economies, and recommends policies to increase formality. The size of shadow economies declined across Europe in recent years but remains significant, especially in Eastern Europe. In the emerging European economies, the key determinants of shadow economy size are regulatory quality, government effectiveness, and human capital. The paper argues that a comprehensive package of reforms, focused on country-specific drivers, is needed to successfully combat the shadow economy. The menu of policies most relevant for Europe’s emerging economies include: reducing regulatory and administrative burdens, promoting transparency and improving government effectiveness, as well as improving tax compliance, automating procedures, and promoting electronic payments.
Mr. Ben Kelmanson, Koralai Kirabaeva, Leandro Medina, and Jason Weiss

, tax revenues, trade volume and agriculture value-added as causal variables, and GDP growth and labor force participation rate as indicator variables. The input variables in Hassan and Schneider (2016) are government spending as a percent of GDP, unemployment rate, self-employment rate, Economic and Business Freedom Indices from the Heritage Foundation as causal variables and M1/M2 and labor force participation rate as indicator variables. The MIMIC approach allows us to compare shadow economy estimates across countries and to conduct panel data analysis

Mr. Ben Kelmanson, Koralai Kirabaeva, Leandro Medina, and Jason Weiss
International Monetary Fund

: The Impact of the Georgian Anti-Corruption Drive A. Introduction B. Background: Driving Out Endemic Corruption C. Shadow Economy: Survey-Based Estimates D. Shadow Economy: The Demand for Cash E. Conclusions References Figures III.1. Georgia and Selected CIS Countries: Sales Reported for Tax Purposes, 2002 and 2005 III.2. Shadow Economy Estimates (SDS Survey Method), 2001–05 III.3. Comparing Shadow Economy Estimates, 2003–05 III.4. Domestic and Foreign Currency Deposits, 2001–05 IV. Legal Entities of Public Law in Georgia

International Monetary Fund

2003 and the first quarter of 2004 (i.e., between the first quarter of the last year before and the first quarter after the revolution). Figure III.2. Georgia: Shadow Economy Estimates (SDS Survey Method), 2001–05 (In percent of (sectoral) GDP) Sources: State Department for Statistics of Georgia (SDS); and Fund staff estimates. 63. Although the size of the shadow economy shrunk through the fourth quarter of 2004, some sectors show recent signs of a rebound in underground activities . In some sectors, this could be related to seasonal effects that

Mr. Friedrich Schneider and Dominik Enste

unreported work related to legal services and goods Employee discounts, fringe benefits. Barter of legal services and goods. All do-it-yourself work and neighbor help. Structure of table from Lippert and Walker, The Underground Economy: Global Evidence of its Size and Impact . Vancouver, B.C., The Frazer Institute, 1997. How Large Is the Shadow Economy? Estimating the size of the shadow economy is difficult. After all, people engaged in underground activities do their best to avoid detection. But policymakers and government administrators

International Monetary Fund

light intensity approach; and (3) presents estimates of the size of the shadow economy for 158 countries over 25 years. We have three concrete goals: 1. To extensively evaluate and discuss the latest developments regarding estimation methods, such as the System of National Accounts (SNA) approach and new micro and macro methods, and the crucial evolution of the macro methodologies—namely the currency demand approach (CDA) and the multiple indicators, multiple causes (MIMIC) model—in tackling the problem of double counting. 2. To present shadow economy estimates

Emilio Colombo, Davide Furceri, Pietro Pizzuto, and Patrizio Tirelli

the period 1995–2015. Shadow economy estimates are from MIMIC and DGE models. Figure 3. The role of the shadow economy and level of economic development Note: The chart shows the impulse response functions and the associated 90 percent confidence bands; t = 0 is the year of shock. Estimates based on equation (2) using a sample of 141 countries over the period 1995–2015. Shadow economy estimates are from MIMIC and DGE models. Figure 4. The role of the shadow economy and level of institutional quality Note: The chart shows the impulse response