This paper aims at assessing the causal and temporal relationships between crime and the economic indicators related to the aggregated demand function. The case study is Italy and a quarterly frequency is used (1981:1 - 2005:4). A Vector Autoregressive Correction Mechanism (VECM) is employed after having assessed the integration and cointegration status of the variables under investigation. Long and short run dynamics are estimated. A Granger causality test is also implemented to establish temporal interrelationships. The main findings are that, in the short run, crime positively effects GDP and government expenditure, while has a crowding out effect on exports. In the long run, crime positively leads imports and inflation, whereas negatively investments and government expenditure.
Testing the effects of crime on the Italian economy
DETOTTO, CLAUDIO;
2010-01-01
Abstract
This paper aims at assessing the causal and temporal relationships between crime and the economic indicators related to the aggregated demand function. The case study is Italy and a quarterly frequency is used (1981:1 - 2005:4). A Vector Autoregressive Correction Mechanism (VECM) is employed after having assessed the integration and cointegration status of the variables under investigation. Long and short run dynamics are estimated. A Granger causality test is also implemented to establish temporal interrelationships. The main findings are that, in the short run, crime positively effects GDP and government expenditure, while has a crowding out effect on exports. In the long run, crime positively leads imports and inflation, whereas negatively investments and government expenditure.
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