Publisher

ISEIISEI

Journal One moment, please...One moment, please... Abstract

The shadow economy encompasses economic activities that are not recorded in the Gross Domestic Product (GDP), resulting in reporting bias and diminished state revenue. This study estimates the size of the shadow economy across 34 Indonesian provinces from 2015 to 2021 using the Multiple Indicators and Multiple Causes (MIMIC) method. The results indicate that the estimated average shadow economy ranges from 4.73% to 42.64% of the provincial GRDP. Key influencing factors include tax burden, government regulations, regional autonomy, self-employed labor, and economic openness. These findings support policies aimed at reducing the shadow economy through tax efficiency, improved regulations, and enhanced welfare for micro, small, and medium enterprises (MSMEs) backed by local governments.

Conclusion

This study identifies tax burden, government regulations, regional autonomy, self-employment, and economic openness as significant factors influencing the shadow economy in Indonesian provinces between 2015 and 2021.The tax burden emerges as a primary driver of shadow economic activity, suggesting that government tax policies contribute to its expansion.Provinces with high tax burdens may incentivize informal economic activities.Therefore, adaptive local tax reforms and enhanced digitalization are crucial for mitigating the shadow economy and fostering formal economic growth.

Future Research

Further research should investigate the specific mechanisms through which tax policies influence shadow economy participation at the provincial level, potentially employing micro-simulation models to assess the impact of different tax scenarios. Additionally, a comparative study examining the effectiveness of various regulatory simplification strategies across provinces could provide valuable insights for policy design. Finally, exploring the role of digital financial inclusion and access to credit for MSMEs in formalizing the economy, particularly in regions with high shadow economy prevalence, warrants further investigation. These studies should consider the unique socio-economic characteristics of each province to tailor effective interventions. A longitudinal study tracking the impact of government interventions aimed at reducing the shadow economy, coupled with detailed surveys of informal businesses, would provide a more nuanced understanding of the challenges and opportunities in formalizing the Indonesian economy. This research should also explore the relationship between corruption levels and the size of the shadow economy, as perceived corruption may incentivize businesses to operate informally to avoid scrutiny and potential extortion. Furthermore, investigating the impact of social safety nets and unemployment benefits on reducing the incentive to participate in the shadow economy could inform the design of more effective social policies.

References

1. Inequality, Institutions, and Informality. inequality institutions informality https 9p7pzq3jbl execute... publications.iadb.org/en/inequality-institutions-and-informalityInequality Institutions and Informality inequality institutions informality https 9p7pzq3jbl execute publications iadb en inequality institutions and informality
2. Estimating the shadow economy at the provincial level in Indonesia: A MIMIC model approach | Jurnal Ekonomi... doi.org/10.52813/jei.v14i1.561Estimating the shadow economy at the provincial level in Indonesia A MIMIC model approach Jurnal Ekonomi doi 10 52813 jei v14i1 561

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