EconPapers    
Economics at your fingertips  
 

Estimating the size of the shadow economy in Spain: a structural model with latent variables

Angel Alañon Pardo () and Miguel Gómez-Antonio

Applied Economics, 2005, vol. 37, issue 9, 1011-1025

Abstract: There has recently been a revival of international interest in measuring the size of the shadow economy. The current study adopts an approach to the Spanish case that is based on the theory of unobservable variables. This methodology involves the estimation of structural models (MIMIC) which analyses a set of causes of the shadow economy while simultaneously taking into account its influence upon a series of indicators. The proposed model permits the determination of a relative evolution over time of the size of the shadow economy, which requires the calibration of the model with an exogenous estimation in order to obtain real values. The exogenous estimation employed is that obtained by a monetary method based on a money demand function. The results show a considerable shadow economy, measuring between 8 and 18.8% of GDP in the period 1976-2002, and demonstrate that the shadow economy is significantly influenced by the tax burden, the degree of regulation and unit labour costs. A positive correlation is obtained between GDP, money demand and the level of the shadow economy.

Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/00036840500081788 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:37:y:2005:i:9:p:1011-1025

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036840500081788

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:applec:v:37:y:2005:i:9:p:1011-1025