Uncovering criminal economy
Uncovering criminal economy
Thursday, 4 April 2013: 5:50 PM
This paper gives a theoretical contribution to modelize criminal economy. A criminal firm not only evades taxes and social security contributions, as an underground firm, but also produces an illegal good. Unlike underground economy, that is indirectly estimated by the statistical offices in GDP calculation, criminal economy is not included in main economic indicators. This happens both for the difficulty to detect entrepreneurs and workers belonging to criminal sector and for the scarcity of data on illegally produced goods.
Our work is an attempt to bridge this gap. Following the literature which uses economic theory to construct time series for those economic variables unknown to official statistics, we build a DSGE model with two goods, the legal good and the criminal good. The former can be produced either by the sunlight firm and by the underground firm. The sunlight firm is risk-adverse, is subject to distortionary taxation on sales, on labor wages and on earned profits. The underground firm is risk-neutral, evades any form of taxation, and hence profits are higher than for the sunlight firm, but only if it is not discovered evading; if, instead, the underground firm is detected evading, it is fined with same amount of taxation as the sunlight firm plus a civil penalty factor proportional to firm size. The criminal good is produced only by the criminal firm, that is a risk-lover firm, which evades any form of taxation and violates penal law if it is not discovered; if, instead, the criminal firm is detected evading and committing criminal offenses, it is fined with two penalty factors: the civil one for tax evasion and the penal one for not conforming to penal law. When discovered, the criminal firm is forced to close.
All sectors are subject to stochastic incorrelated technology shocks on total factor productivity.
The demand side of the economy is populated by an infinite number of households with preferences defined over legal good consumption, criminal good consumption, public expenditure and labor services on a period-by-period basis. Total labor services can be allocated either in the legal sector or in the underground and the criminal sector.
The first order conditions together with an appropriate parametrization are able to characterize criminal economy as a function of regular economy, whose data are known, and of underground economy, whose data are estimated. Hence, the first result of the model is the construction of an high frequency estimated time series for criminal economy.
We perform this analysis for Italy, the European Union and the US on quarterly data, over the sample 2000:01-2010:04.
We find that criminal economy has a greater weight on GDP in Italy than in the European Union and the US.
Then we dynamically simulate the model under the technology shocks that hit the three sectors of this economy.
Main findings are that: 1) criminal production has a grater relative volatility than underground production and regular production; 2) both underground and criminal production appear to be negatively correlated with GDP, showing that they conserve as a sort of buffer for the economy, whenever the business cycle is in downturn phases.
Our work is an attempt to bridge this gap. Following the literature which uses economic theory to construct time series for those economic variables unknown to official statistics, we build a DSGE model with two goods, the legal good and the criminal good. The former can be produced either by the sunlight firm and by the underground firm. The sunlight firm is risk-adverse, is subject to distortionary taxation on sales, on labor wages and on earned profits. The underground firm is risk-neutral, evades any form of taxation, and hence profits are higher than for the sunlight firm, but only if it is not discovered evading; if, instead, the underground firm is detected evading, it is fined with same amount of taxation as the sunlight firm plus a civil penalty factor proportional to firm size. The criminal good is produced only by the criminal firm, that is a risk-lover firm, which evades any form of taxation and violates penal law if it is not discovered; if, instead, the criminal firm is detected evading and committing criminal offenses, it is fined with two penalty factors: the civil one for tax evasion and the penal one for not conforming to penal law. When discovered, the criminal firm is forced to close.
All sectors are subject to stochastic incorrelated technology shocks on total factor productivity.
The demand side of the economy is populated by an infinite number of households with preferences defined over legal good consumption, criminal good consumption, public expenditure and labor services on a period-by-period basis. Total labor services can be allocated either in the legal sector or in the underground and the criminal sector.
The first order conditions together with an appropriate parametrization are able to characterize criminal economy as a function of regular economy, whose data are known, and of underground economy, whose data are estimated. Hence, the first result of the model is the construction of an high frequency estimated time series for criminal economy.
We perform this analysis for Italy, the European Union and the US on quarterly data, over the sample 2000:01-2010:04.
We find that criminal economy has a greater weight on GDP in Italy than in the European Union and the US.
Then we dynamically simulate the model under the technology shocks that hit the three sectors of this economy.
Main findings are that: 1) criminal production has a grater relative volatility than underground production and regular production; 2) both underground and criminal production appear to be negatively correlated with GDP, showing that they conserve as a sort of buffer for the economy, whenever the business cycle is in downturn phases.