Measuring the shadow economy and its drivers: the case of peripheral EMU countries

We adopt a long-run perspective to investigate the size of the shadow economy and explore the trends in this area. The analysis is based on a panel of peripheral EMU countries over the period 1965-2015. Our empirical approach relies on a multiple indicators and multiple causes (MIMIC) framework. Thi...

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Main Authors: Vicent Almenar, José Luis Sánchez, Juan Sapena
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Ekonomska Istraživanja
Subjects:
Online Access:http://dx.doi.org/10.1080/1331677X.2019.1706601
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spelling doaj-91dfa0aa245b433ebff8947b9354137d2021-04-06T13:27:29ZengTaylor & Francis GroupEkonomska Istraživanja1331-677X1848-96642020-01-013312904291810.1080/1331677X.2019.17066011706601Measuring the shadow economy and its drivers: the case of peripheral EMU countriesVicent Almenar0José Luis Sánchez1Juan Sapena2Department of Economics and Business, Catholic University of ValenciaDepartment of Economics and Business, Catholic University of ValenciaDepartment of Economics and Business, Catholic University of ValenciaWe adopt a long-run perspective to investigate the size of the shadow economy and explore the trends in this area. The analysis is based on a panel of peripheral EMU countries over the period 1965-2015. Our empirical approach relies on a multiple indicators and multiple causes (MIMIC) framework. This approach is a variant of structural equation modelling (SEM). We used two sets of variables, (i.e. potential determinants and indicator variables) to estimate an underlying (unobserved) index that measures the evolution of the shadow economy. Ascertaining the relative importance of the shadow economy enabled analysis of its relationship with other institutional and social issues (e.g. corruption, productivity and economic growth), and helped identify the channels through which the shadow economy might negatively influence the performance of different economies. In the sampled countries, shadow activity increased over the study period. It also seemed to be affected by the economic cycle.http://dx.doi.org/10.1080/1331677X.2019.1706601shadow economystructural equation modellingmultiple indicators multiple causes modelseuropean economic and monetary union
collection DOAJ
language English
format Article
sources DOAJ
author Vicent Almenar
José Luis Sánchez
Juan Sapena
spellingShingle Vicent Almenar
José Luis Sánchez
Juan Sapena
Measuring the shadow economy and its drivers: the case of peripheral EMU countries
Ekonomska Istraživanja
shadow economy
structural equation modelling
multiple indicators multiple causes models
european economic and monetary union
author_facet Vicent Almenar
José Luis Sánchez
Juan Sapena
author_sort Vicent Almenar
title Measuring the shadow economy and its drivers: the case of peripheral EMU countries
title_short Measuring the shadow economy and its drivers: the case of peripheral EMU countries
title_full Measuring the shadow economy and its drivers: the case of peripheral EMU countries
title_fullStr Measuring the shadow economy and its drivers: the case of peripheral EMU countries
title_full_unstemmed Measuring the shadow economy and its drivers: the case of peripheral EMU countries
title_sort measuring the shadow economy and its drivers: the case of peripheral emu countries
publisher Taylor & Francis Group
series Ekonomska Istraživanja
issn 1331-677X
1848-9664
publishDate 2020-01-01
description We adopt a long-run perspective to investigate the size of the shadow economy and explore the trends in this area. The analysis is based on a panel of peripheral EMU countries over the period 1965-2015. Our empirical approach relies on a multiple indicators and multiple causes (MIMIC) framework. This approach is a variant of structural equation modelling (SEM). We used two sets of variables, (i.e. potential determinants and indicator variables) to estimate an underlying (unobserved) index that measures the evolution of the shadow economy. Ascertaining the relative importance of the shadow economy enabled analysis of its relationship with other institutional and social issues (e.g. corruption, productivity and economic growth), and helped identify the channels through which the shadow economy might negatively influence the performance of different economies. In the sampled countries, shadow activity increased over the study period. It also seemed to be affected by the economic cycle.
topic shadow economy
structural equation modelling
multiple indicators multiple causes models
european economic and monetary union
url http://dx.doi.org/10.1080/1331677X.2019.1706601
work_keys_str_mv AT vicentalmenar measuringtheshadoweconomyanditsdriversthecaseofperipheralemucountries
AT joseluissanchez measuringtheshadoweconomyanditsdriversthecaseofperipheralemucountries
AT juansapena measuringtheshadoweconomyanditsdriversthecaseofperipheralemucountries
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