Does more crime mean fewer jobs? An ARDL model
This paper analyses how a set of economic variables and a deterrence variable affect criminal activity. Furthermore, it highlights the extent to which crime is detrimental for the economic activity. The case study is Italy for the time span 1970 up to 2004. An Autoregressive Distributed Lags approach is employed to assess the cointegration status of the variables under investigation. A Granger causality test is also implemented to establish temporal interrelationships. The main finding is that all crime typologies, but homicides and fraud, have a crowding-out effect on legal economic activity, reducing the employment rate.
|Date of creation:||2009|
|Date of revision:|
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