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Leandro Medina, Mr. Andrew W Jonelis, and Mehmet Cangul
The multiple indicator-multiple cause (MIMIC) method is a well-established tool for measuring informal economic activity. However, it has been criticized because GDP is used both as a cause and indicator variable. To address this issue, this paper applies for the first time the light intensity approach (instead of GDP). It also uses the Predictive Mean Matching (PMM) method to estimate the size of the informal economy for Sub-Saharan African countries over 24 years. Results suggest that informal economy in Sub-Saharan Africa remains among the largest in the world, although this share has been very gradually declining. It also finds significant heterogeneity, with informality ranging from a low of 20 to 25 percent in Mauritius, South Africa and Namibia to a high of 50 to 65 percent in Benin, Tanzania and Nigeria.
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

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

International Monetary Fund

Causes” (MIMIC) approach of Frey and Weck-Hanneman (1984) . 40 This paper draws on Loayza (1997) and uses the MIMIC approach to both estimate the size of the informal economy and gauge its effect on the provision of social security, unionization, and school enrollment. 62. The MIMIC method is based on a structural equation model approach that treats the size of the informal economy as a latent (unobserved) variable with several causes and several indicators (or effects) . The methodology uses associations between the observable causes and the observable effects

Guillermo Javier Vuletin

per capita. The paper is organized as follows. The next section reviews the different methods used by the literature to estimate the size of the informal economy. It also carefully explains the “Multiple Indicators, Multiple Causes” (MIMIC) approach, which is the econometric method used in this study. Section III presents the set of countries and variables used in the analysis. The empirical results are discussed in Section IV , and Section V contains some concluding remarks. II. M ethods for M easuring the S ize of the I nformal E conomy Many

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

is arguable. 8 (vi) Multiple Indicators, Multiple Causes (MIMIC) approach : This method explicitly considers several causes, as well as the multiple effects, of the informal economy. The methodology makes use of the associations between the observable causes and the effects of an unobserved variable, in this case the informal economy, to estimate the variable itself ( Loayza, 1997 ). 9 3. Econometric Strategy Most of the methods described above consider only one (either direct or indirect) indicator of the informal economy, such as electricity

International Monetary Fund

for 158 countries from 1991 to 2015 while addressing early criticism. In particular, when using the MIMIC approach, GDP per capita, growth rate of GDP, or first differences in GDP are often used as cause as well as indicator variables. Instead of GDP, we use a light intensity approach as an indicator variable, then run a variety of robustness tests to further assess the validity of our results. 2 We, in addition to MIMIC, use a fully independent method, the predictive mean matching (PMM) method by Rubin (1987) , which overcomes these calibration problems. This is