Analysis of the shadow economy in the Spanish regions

Corruption, the shadow economy and innovation in Spanish regions

“…Regarding values of the variable that approximates the underground economy, the results show the expected negative sign but only when the number of crimes against tax authorities is used as a proxy for the shadow economy and for the OLS and random effects estimation. The estimations for the shadow economy from González-Fernández and González-Velasco (2015) do not provide significant results in any of the models. Thus, the results of the shadow economy are not as robust as those for corruption, but there are traces of the negative influence of the shadow economy on innovation.…”

“…In the first part of the table, we show the Pearson correlations between the variables included in the analysis. We include the dependent variable, i.e., the annual growth of patents along with the rest of right-hand-side variables, namely, public expenditure on R&D relative to GDP, foreign direct investment (FDI) relative to GDP, the total number of patents, the debt/GDP ratio, unemployment, the CPI in the Spanish regions calculated by GONZÁLEZ-FERNÁNDEZ and GONZÁLEZ-VELASCO (2014) and the estimates for the shadow economy related to GDP (SE) for the Spanish regions calculated by GONZÁLEZ-FERNÁNDEZ and GONZÁLEZ-VELASCO (2015).We also estimate the pairwise correlation in the second part of the table, and the results do not differ from those shown in the table.…”

“…As in the previous subsection, we apply different estimation methods and include time dummies in all the models. The explanatory variables are those previously mentioned, and to approximate the shadow economy, we utilize the estimates obtained by González-Fernández and González-Velasco (2015) and the number of crimes against tax authorities (CTA). The table presents the panel data regressions of corruption and other explanatory variables on innovation, for which the growth in the number of patents serves as a proxy.…”

“…We also include as explanatory variables the foreign direct investment (FDI) relative to GDP, the total number of patents, the debt/GDP ratio and unemployment. To approximate the shadow economy relative to GDP (SE), we employ the estimations for Spanish regions (SE) calculated by GONZÁLEZ-FERNÁNDEZ and GONZÁLEZ-VELASCO (2015) as well as the number of crimes against tax authorities (CTA). In the first model, we apply the pooled OLS model, and then, in Columns 3-6, random and fixed effects models are applied.…”

La Economía Sumergida en Tiempos de Crisis: Un Análisis del Trabajo no Declarado en Europa.

“…and Windebank, J., 1995;Mauleón, I. y Sardà. J., 1997;Ahumada, H. et al 2008;Sardà, J., 2011, 2015;González-Fernández, M. and González-Velasco, M.C., 2015). Entre sus limitaciones, destacan (a) el que no todas las operaciones de economía sumergida se pagan en efectivo; (b) que estos modelos presuponen que la carga impositiva es el único factor que provoca la economía sumergida, obviando otros como la regulación, el comportamiento de los ciudadanos o la moral fiscal; y (c) que la velocidad de la circulación del dinero no es igual en ambas economías (Thomas, J.J., 1986(Thomas, J.J., , 1992(Thomas, J.J., , 1999Feige, E.L., 1986).…”