Media Briefings

TIGHT IMMIGRATION POLICIES BOOST THE SHADOW ECONOMY: Evidence from Italy

  • Published Date: March 2016

Immigration and tax evasion are closely linked, according to research by Emanuele Bracco and Luisanna Onnis, to be presented at the Royal Economic Society's annual conference in Brighton in March 2016.

The study analyses 12 years worth of data (1995-2006) on both immigration and the shadow economy in several Italian states. Many undocumented immigrants are barred from working legally, so they end up not declaring their income. This means that they do not pay their taxes and that they fuel the shadow economy in the area.

The authors find that a 1% increase in the immigrant population led to a 5% larger shadow economy. But the link almost entirely disappeared when a major amnesty happened in 2002. This suggests that restrictive immigration policies may have unintended side effects, since by encouraging undocumented migration they also boost the shadow economy.

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• Tax (and social security) evasion is affected by the presence of immigrants.

• This is particularly true for illegal immigrants, who are barred from working legally.

• The presence of illegal immigrants in a locality also increases the propensity to evade of the whole local job market.

• Restrictive immigration policies need to consider the effects they may have on the level of illegal immigration: they may have the unintended effect of increasing tax evasion.

This study analyses the link between the presence of immigrants, both legal and illegal, in a locality, and the incidence of tax evasion. The results suggest that a 1% increase in immigrant population in a locality is correlated with an increase in the share of undeclared economic activity of about 5%. This effect almost totally disappears after a large-scale immigration amnesty in 2002, indicating that it is the presence of illegal immigrants who contributes the most to this link.

The analysis is based on a 12-year dataset (1995-2006) of immigration and shadow economy statistics of Italian provinces.

The reasons behind this phenomenon are varied. First and foremost, illegal immigrants are barred from participating in the legal labour market, naturally fuelling the shadow economy. This not only implies that illegal immigrants work illegally, but also that localities with a larger presence of illegal immigrants have job markets that rely relatively more on illegal work, irrespective of the legal status of each worker.

The researchers also distinguish the effect of legal and illegal workers on the shadow economy, exploiting a large immigration amnesty that came into force at the end of 2002. This amnesty increased by almost 50% the stock of legal immigrants, and regularised over 600,000 illegal immigrants who were already residing and working in Italy.

The study finds that the link between tax evasion and immigration declines and almost disappears after the amnesty, suggesting that there is no detectable difference in the propensity to work illegally between indigenous population and legal immigrants.

As tax evasion is difficult to measure, the analysis relies on a number of measures and statistical techniques.

First, the researchers measure the propensity to evade through the Survey of Household Income and Wealth. This survey, run by the Bank of Italy, relies on subjects declaring the years in their work history in which no social security payments were corresponded.

Second, the researchers measure tax evasion via the regional-level share of irregular jobs as measured by the National Statistical Office (ISTAT).

Third, they build their own measure of tax evasion, which is based on the Physical Input Approach, and in particular on electricity consumption. This method assumes that growth in (local) electricity consumption that cannot be explained by growth in (local, official) GDP is to be imputed to the growth of the shadow economy.

All of the measures of tax evasion show a very strong correlation with the official ISTAT one, reassuring us on the reliability of our own measures. The findings are also very consistent across measures of tax evasion, showing a remarkable level of robustness.

The main finding is that an increase by 1% of the immigrant population leads to a 0.5% increase in the propensity to evade, according to the survey-based analysis, to a 5% increase in the overall share of the shadow economy and to a 7% increase in the share of irregular jobs using our aggregate dataset.

This has interesting implications for immigration policies: restrictive immigration policies are often unable to stop completely the flow of illegal immigrants, and deportation is always a costly and lengthy procedure. This implies that immigration policies that – more or less intentionally – increase the stock of illegal immigrants also have the unintended effect of increasing tax and social security evasion.

ENDS


Immigration, Amnesties and the Shadow Economy
Emanuele Bracco and Luisanna Onnis

Dr Luisanna Onnis
Department of Economics
University of Sheffield
Email: l.onnis@sheffield.ac.uk

Dr Emanuele Bracco
Department of Economics
Lancaster University Management School
Email: e.bracco@lancaster.ac.uk