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Leandro Medina and Mr. Friedrich Schneider
We undertake an extended discussion of the latest developments about the existing and new estimation methods of the shadow economy. New results on the shadow economy for 158 countries all over the world are presented over 1991 to 2015. Strengths and weaknesses of these methods are assessed and a critical comparison and evaluation of the methods is carried out. The average size of the shadow economy of the 158 countries over 1991 to 2015 is 31.9 percent. The largest ones are Zimbabwe with 60.6 percent, and Bolivia with 62.3 percent of GDP. The lowest ones are Austria with 8.9 percent, and Switzerland with 7.2 percent. The new methods, especially the new macro method, Currency Demand Approach (CDA) and Multiple Indicators Multiple Causes (MIMIC) in a structured hybrid-model based estimation procedure, are promising approaches from an econometric standpoint, alongside some new micro estimates. These estimations come quite close to others used by statistical offices or based on surveys.
Guillermo Javier Vuletin

Front Matter Page Western Hemisphere Department Authorized for distribution by Paul Cashin Contents I. Introduction II. Methods for Measuring the Size of the Informal Economy III. Data A. Cause Variables B. Indicator Variables IV. Empirical Results A. Preliminary Evidence B. MIMIC Estimation Results C. Estimation of the Size of the Informal Economy D. Relative Contribution of Each Cause Variable to the Size of the Informal Economy V. Concluding Remarks References Appendix Data Construction and Sources Figures

Leandro Medina, Mr. Andrew W Jonelis, and Mehmet Cangul

Contents Abstract 1. I ntroduction 2. L iterature Review 3. E conometric Strategy 4. V ariables 5. R esults A.MIMIC Estimation Results B.Estimation of the Size of the Informal Economy 6. Robustness Tests A. Estimating the Size of the Informal Economy Using Predictive Mean Matching B. Estimating the Size of the Informal Economy Using Traditional MIMIC Approach (a la Schneider, 2010) C. Comparison with Countries’ National Accounts Statistics 7. C onclusions 8. R eferences

Mr. Yasser Abdih and Leandro Medina

Front Matter Page Middle East and Central Asia Department Contents I. Introduction II. Empirical Methodology III. Data IV. Main Results and Discussion A. MIMIC Model Estimation B. The Size of the Informal Economy C. Policy Implications V. Conclusion References Figures MIMIC Estimation Results Estimated Size of the Informal Economy (in percent of GDP), 2008 Contribution of Each Cause Variable to the Size of the Informal Economy (in percent), 2008 Tables Size of the Informal Economy, 2008 Relative Contribution

Leandro Medina and Mr. Friedrich Schneider

Front Matter Page African Department Contents Abstract 1. I ntroduction 2. T heoretical C onsiderations A. Causes and Signs/Indicators of Informality 3. E stimation M ethods and MIMIC E stimation R esults Error! Bookmark not defined A. Measuring the Shadow Economy B. MIMIC Estimation Results C. Addressing Potential Shortcomings D. Results on the Size of the Shadow Economy of 158 Countries using the MIMIC Approach 4. A C omparison of the MIMIC (M acro and A djusted ) R esults with M icro S urvey R esults and N

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

@imf.org ; jweiss@imf.org Content Abstract I. Introduction II. Defining and Measuring the Shadow Economy III. Size, Evolution, and Costs of the Shadow Economy IV. Determinants of the Shadow Economy V. Empirical Results VI. Re-estimating the Size of Shadow Economies for European Countries VII. Policy Options VIII. Conclusion BOX 1. Estimating Kosovo’s Shadow Economy FIGURES 1. Shadow Economy in Europe 2. Shadow Economy Estimation: The MIMIC Model TABLES 1. Summary of Empirical Results 2. Summary of MIMIC Estimations

International Monetary Fund

informal economy in the context of the MIMIC estimation strategy, is presented in Box III.1 and Box III.2 , and in Appendices I and II. The estimation period is the early 2000s, using data on the previously-listed 32 Caribbean, Latin American and island countries. 45 Box III.1. Representation of the “Multiple Indicators, Multiple Causes” (MIMIC) Methodology The MIMIC methodology is a structural equation-based modeling approach that treats the size of the informal economy as a latent variable. While the measure of the informal economy is unobservable , many of

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.
International Monetary Fund

night lights (that is, light intensity) as a proxy for the size of an economy, and discuss additional robustness tests. We also cover the econometric results of the MIMIC estimations of the size of the shadow economy for 158 countries and critically evaluate them. Later on we compare the MIMIC results with micro survey results and SNA discrepancy method results before summarizing our findings and providing a conclusion. Theoretical Considerations Individuals are rational calculators who weigh costs and benefits when considering breaking the law. Their

Guillermo Javier Vuletin
This paper estimates the size of the informal economy for 32 mainly Latin American and Caribbean countries in the early 2000s. Using a structural equation modeling approach, we find that a stringent tax system and regulatory environment, higher inflation, and dominance of the agriculture sector are key factors in determining the size of the informal economy. The results also confirm that a higher degree of informality reduces labor unionization, the number of contributors to social security schemes, and enrollment rates in education.