Semantic alignment and professional formation in shaping expert perceptions of the shadow economy’s size
Omer Gokcekus, Elshan Bagirzadeh, Ibrahim NiftiyevPurpose
This study examines whether semantic alignment with a standardized definition and professional formation are associated with expert perceptions of the shadow economy’s size. It addresses a neglected measurement issue in perception-based shadow economy research: whether respondents who appear to answer the same question are in fact applying the same conceptual boundary.
Design/methodology/approach
The study uses original survey data from 87 experts in Azerbaijan drawn from academic, financial, managerial and other policy-relevant sectors (response rate: 55.4%). Guided by the semantic theory of survey response (STSR), the analysis compares subgroup means and dispersion and estimates clustered OLS models with robustness checks using alternative codings, log specifications, and ordered and interval-censored models.
Findings
Definitional alignment is consistently associated with higher perceived shadow economy estimates, and this association is stronger among academically trained respondents. In the baseline specification, academic affiliation and definitional alignment are associated with increases of about 7.4 and 6.8% points, respectively, relative to a sample mean of 31.35%. These are economically meaningful shifts. By contrast, evidence for variance convergence is mixed: subgroup dispersion differs, but variance estimates are imprecise and do not support a definitive convergence claim.
Originality/value
The study extends STSR to shadow economy measurement by showing that semantic alignment functions as a structured correlate of perception-based estimates rather than as random noise. It demonstrates that expert-based macroeconomic indicators may partly reflect conceptual coordination among respondents, making semantic structure an empirical and methodological issue in survey-based economic measurement.