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

independent study to calibrate from standardized values to size of informal economy in percent of GDP, and (iii) the estimated coefficients are sensitive to alternative specifications, the country sample and time span chosen. This paper contributes to the literature and addresses the concerns of endogeneity as well as using predictive mean matching as a robustness check for measuring the size of the informal economy in Sub-Saharan African countries. Specifically, by: (a) using a modified version of the standard Multiple Indicator-Multiple Cause (MIMIC) model. This

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.
Céline Allard

opportunities for those working in the informal sector to maintain or improve their living standards. To assess and identify the steps required to create such an environment, this chapter first examines the size of the informal economy in sub-Saharan Africa and how it compares to other regions. As there is considerable variation in the estimated sizes of the informal economies in sub-Saharan African countries, this chapter then seeks to identify factors that are associated with their relative sizes. It also investigates the interaction between informality and economic

International Monetary Fund. Research Dept.

: What Are the Data Needs? Robert M. Heath, Evrim Bese Goksu Working Paper No. 17/154 Exchange Rate Choices with Inflexible Markets and Costly Price Adjustments Tara Iyer Working Paper No. 17/155 IMF Lending in an Interconnected World Jean-Guillaume Poulain, Julien Reynaud Working Paper No. 17/156 The Informal Economy in Sub-Saharan Africa: Size and Determinants Leandro Medina, Andrew W. Jonelis, Mehmet Cangul Working Paper No. 17/157 A License to Issue (Anywhere): Patterns and Drivers of Corporate Bonds in Latin

International Monetary Fund. African Dept.

Peralta-Alva , 2017 , Macro-Structural Policies and Income Inequality in Low-Income Developing Countries . SDN/17/01 . January Institut National de la Statistique et de l’Analyse Economique , 2015 , Enquete Modulaire Integree sur les Conditions de Vie des Menages . Octobre . Medina , Leandro , Andrew Jonelis , and Mehmet Cangul , 2017 , The Informal Economy in Sub-Saharan Africa: Size and Determinants , International Monetary Fund . WP/17/156 Tang , Xin , A Tutorial of the Toolkit for Solving a Multisector Heterogeneous Agents

International Monetary Fund. African Dept.

Working Paper 13/108 . IMF , 2014a , “ Sustaining Long-Run Growth and Macroeconomic Stability in Low-Income Countries—The Role of Structural Transformation and Diversification .” IMF Policy Paper , March . Imbs , Jean , and Romain Wacziarg . 2003 . “ Stages of Diversification .” American Economic Review , 93 ( 1 ): 63 – 86 . Medina , Leandro ; Andrew W Jonelis , and Mehmet Cangul , 2017 , “ The Informal Economy in Sub-Saharan Africa: Size and Determinants ,” Working Paper No. 17/156 Papageorgiou , Chris , Fidel Perez

International Monetary Fund. African Dept.

Pohl. 2 Global Financial Inclusion (Global Findex) data represents the population aged 15 and older. 3 Further information on the SSA experience maybe found in the Spring 2017 AFR REO, Chapter 3: The Informal Economy in Sub-Saharan Africa as well as the IMF book The Global Informal Workforce: Priorities for Inclusive Growth . 4 For more information on trends in financial inclusion, refer to: Delechat, Corinne, and Leandro Medina, eds. 2021 . The Global Informal Workforce: Priorities for Inclusive Growth . Washington, D.C.: International

Zidong An, Tayeb Ghazi, Nathalie Gonzalez Prieto, and Mr. Aomar Ibourk

. Jones , Benjamin , and Benjamin Olken , 2008 , “ The Anatomy of Start-Stop Growth ,” Review of Economics and Statistics , 90 ( 3 ): 582 – 587 . Singhm , Anoop , Join-Chandre , Sonali and Mohommad , Adil ( 2012 ). “ Inclusive growth, institutions, and the Underground Economy ” IMF Working paper . Medina , Jonelis , and Cangul , 2017 , “ The Informal Economy in Sub-Saharan Africa: Size and Determinants ”, IMF Working paper 17/156 . OECD , 2009 , “ Is Informal Normal? Towards More and Better Jobs in Developing Countries

International Monetary Fund

’s overrepresentation in the informal sector in sub-Saharan Africa in more detail. Women Are Less Educated Than Men Informal jobs are disproportionally held by low-skilled workers with no or little formal education. According to the ILO (2018) , more than 90 percent of low-skilled workers are employed in the informal economy in sub-Saharan Africa. Among workers with no education, 95 percent are employed in the informal sector, and for workers with only primary education, 90 percent are in the informal sector. In stark contrast, only 27 percent of workers with tertiary