Al Agung, Ahmad Nadifa
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Journal : PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS

Shadow Economy Estimation Across ASEAN Member States: MIMIC Model Approach Al Agung, Ahmad Nadifa; Agustina, Neli
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.578

Abstract

As a measure of official output, GDP remains incomplete, omitting the substantial economic transactions that occur within the shadow economy. The shadow economy reduces government tax revenues and weakens fiscal capacity. It also contributes to the underestimation of macroeconomic indicators. This study estimates the size of the shadow economy in ASEAN member states (AMS) using the Multiple Indicators and Multiple Causes (MIMIC) model. The model employs three causal variables and two indicator variables to capture the latent construct. Inflation, unemployment rate, and GDP per capita growth are identified as the main causal determinants. Economic growth and M2 growth are validated as significant indicators constructed for the shadow economy. The estimation covers the period from 2000 to 2023 and reveals an upward trend in the shadow economy across ten AMS, with an average size of 37.75 percent of GDP. These findings emphasize the need for policy actions that focus on maintaining price stability, promoting inclusive economic growth, and expanding formal employment opportunities to mitigate the expansion of the shadow economy.