The Concept of Structural Equation Modelling for Measuring the Shadow Economy – International and Polish Perspectives

Katarzyna Brzozowska‑Rup; Mariola Chrzanowska; Agnieszka Piotrowska‑Piątek; Małgorzata Sobieraj; Maciej Kozłowski

doi:10.18778/1508-2008.27.14

Authors

Katarzyna Brzozowska‑Rup Statistical Office in Kielce, Poland; Kielce University of Technology, Kielce, Poland
Mariola Chrzanowska Warsaw University of Life Sciences, Warsaw, Poland; Statistical Office in Kielce, Poland
Agnieszka Piotrowska‑Piątek Statistical Office in Kielce, Poland; Kielce University of Technology, Kielce, Poland
Małgorzata Sobieraj Statistical Office in Kielce, Kielce, Poland
Maciej Kozłowski University of Lodz, Lodz, Poland https://orcid.org/0000-0002-7749-6118

DOI:

https://doi.org/10.18778/1508-2008.27.14

Keywords:

shadow economy, national statistical offices, structural equation models, unobserved variables, international economy

Abstract

The goal of the article is to explore the potential of explicatory Structural Equation Modelling (SEM) and its specifications for measuring the shadow economy (SE). This is done from the perspective of various approaches in selected countries. The article is a review and conceptual paper. The study is divided into three stages: a comprehensive description of the nature of the SE and the difficulties associated with measuring it; a comparative analysis of the approaches applied in selected EU countries (with particular emphasis on Italy and Poland), and finally, the concept of SE estimation based on SEM model is proposed.

One of the most important limitations regarding the SE is that it is not possible to measure the extent of this phenomenon directly. This leads to the use of non‑standard estimation techniques based on latent variable models. The innovation of this approach is that it considers three factors that are not directly observable, i.e., tax morality, concealing salaries, and regulation of the economy.

The proposed model allows us to capture and explain empirical SE phenomena more precisely and effectively than with classical statistical and econometric methods. However, we are aware that it is highly probable that many SEMs will need to be tested and modified to achieve the final result.

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