Spatial characteristics and dynamic modeling of informal economies

Joseph Emmanuel Fantcho () and Patrick Konin N’Gouan ()
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Joseph Emmanuel Fantcho: Université Des Montagnes
Patrick Konin N’Gouan: Centre Ivoirien de Recherches Economiques Et Sociales

International Economics and Economic Policy, 2024, vol. 21, issue 2, No 10, 483-514

Abstract: Abstract This study identifies the factors that describe informal economies and summarizes them into indices measuring informality. We use data from 189 countries for the years 2015 and 2020. We carry out a factor analysis to identify the variables which structure informal economies and use the scores from a logistic regression to measure the degree of informality for each country. The results show that the degree of informality is related to the level of development. Thus, developing countries are generally those with the highest degree of informality while developed countries are generally characterized by a low level of informality. One of the important contributions of this paper is the method used to derive and then determine the depth of the informal economy in each country from the logistic regressions. Since the informal economy is not directly measurable, we first construct a binary variable named “prior informality.” It is this variable that will be used in the logistic regression to measure the magnitude of the informal economy in each country. Thus, we construct a synthetical indicator that takes into account all dimensions of the informal economy with their particularity depending on whether we are in developed countries, in middle-income countries, or in underdeveloped countries. Mathematically, the principal component analysis gives us the best graphical representations of informal economies according to their characteristics. Likewise, the study enables us to classify countries into groups according to the variables that determine informality and draw dynamic charts representing the countries according to their level of informality.

Keywords: Informal economy; Factor analysis; Aggregate index; Logistic regression; Classification; Maps (search for similar items in EconPapers)
JEL-codes: C38 C51 C82 E26 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10368-024-00609-9

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