New Evidence on the Size and Drivers of the Shadow Economy in Spain: A Model Averaging Approach
Vicente Orts Ríos
Abstract
Open-access reader
Vicente Orts Ríos
Abstract
Open-access reader
This study investigates the evolution of the shadow economy in Spain during the period 1986-2016 using the Currency Demand Approach by means of Bayesian Model Averaging econometric techniques. The results of the empirical analysis suggest that the average share of the underground economy as a percentage of the GDP during 1986-2016 was the 18.2% whereas in 2016, the estimated size was the 11.95%. The estimated figures for the period under consideration are in line with the averaged estimates of previous studies for the same time frame. Nevertheless, a remarkable difference between previous analysis and the estimated pattern stemming from this study is that the size of the shadow economy depicts an inverted U shape time profile, with a marked reduction in the years after the Great Recession. With the estimates of the shadow economy in hand, the importance of the drivers of the shadow economy in Spain is investigated by means of Bayesian Model Averaging methods. The main finding of this analysis is that the key factors driving variations in the size of the shadow economy are the taxes, the level of education and the distribution of employment across sectors.
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This study investigates the evolution of the shadow economy in Spain during the period 1986-2016 using the Currency Demand Approach by means of Bayesian Model Averaging econometric techniques. The results of the empirical analysis suggest that the average share of the underground economy as a percentage of the GDP during 1986-2016 was the 18.2% whereas in 2016, the estimated size was the 11.95%. The estimated figures for the period under consideration are in line with the averaged estimates of previous studies for the same time frame. Nevertheless, a remarkable difference between previous analysis and the estimated pattern stemming from this study is that the size of the shadow economy depicts an inverted U shape time profile, with a marked reduction in the years after the Great Recession. With the estimates of the shadow economy in hand, the importance of the drivers of the shadow economy in Spain is investigated by means of Bayesian Model Averaging methods. The main finding of this analysis is that the key factors driving variations in the size of the shadow economy are the taxes, the level of education and the distribution of employment across sectors.
Key concepts: Economy, Economics, Shadow (psychology), Recession, Econometrics, Econometric model, Macroeconomics, Psychology