Modelling the Shadow Economy: An Econometric Study of Technology Development and Institutional Quality

This econometric analysis models the conditional expectation of Europe’s shadow economy size as a function of technologization and institutional quality indicators, using a balanced panel of 29 countries from 2007 to 2022. Technologization is measured through the four dimensions of Desai’s Technological Achievement Index, and institutional quality via core World Government Indicators variables. Rigorous diagnostics select a random-effects model with year dummies and Driscoll-Kraay standard errors, explaining 61% of the variance in informality. Development of Human Skills delivers the largest individual reduction (−7.2 pp), strongly supporting the core hypothesis. Control of Corruption is also highly significant (−2.8 pp). While New Technology Creation showed a negative association, its statistical significance proved unstable across model specifications. Technology diffusion becomes insignificant when common global time shocks are absorbed, implying that mere adoption has limited independent effect. Furthermore, the impact of human skills intensifies significantly in countries with high New Technology Diffusion (−12,489), revealing a potent synergy between human capital and technological advancement. Policy priorities therefore include anti-corruption enforcement, Research and Development incentives, and sustained investment in skills, especially where technology diffusion is high, to draw hidden activity into the formal sector.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2025-12-07
DOI
https://doi.org/10.3390/math13243914
Primary Topic
Taxation and Compliance Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling the Shadow Economy: An Econometric Study of Technology Development and Institutional Quality

Anamaria Mișa, Lavinia Mastac
Mathematics
Taxation and Compliance Studies
article

Modelling the Shadow Economy: An Econometric Study of Technology Development and Institutional Quality

Anamaria Mișa, Lavinia Mastac
article en

Abstract

This econometric analysis models the conditional expectation of Europe’s shadow economy size as a function of technologization and institutional quality indicators, using a balanced panel of 29 countries from 2007 to 2022. Technologization is measured through the four dimensions of Desai’s Technological Achievement Index, and institutional quality via core World Government Indicators variables. Rigorous diagnostics select a random-effects model with year dummies and Driscoll-Kraay standard errors, explaining 61% of the variance in informality. Development of Human Skills delivers the largest individual reduction (−7.2 pp), strongly supporting the core hypothesis. Control of Corruption is also highly significant (−2.8 pp). While New Technology Creation showed a negative association, its statistical significance proved unstable across model specifications. Technology diffusion becomes insignificant when common global time shocks are absorbed, implying that mere adoption has limited independent effect. Furthermore, the impact of human skills intensifies significantly in countries with high New Technology Diffusion (−12,489), revealing a potent synergy between human capital and technological advancement. Policy priorities therefore include anti-corruption enforcement, Research and Development incentives, and sustained investment in skills, especially where technology diffusion is high, to draw hidden activity into the formal sector.

MathematicsVol. 13(24)
Bucharest University of Economic Studies (RO)
Openalex Percentile: Top 54%
Taxation and Compliance Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.