Relationship between crimes and economic conditions in Pakistan: a time series approach

Using the time series data from 1990-2011, this paper is an attempt to explore the relationship between economic conditions and criminal activities in Pakistan. Three variables are being used for economic conditions like increasing female employment in labor market, CPI which denotes inflation and income inequality. We check their relationship with total reported crime with reference to Pakistan. The Augmented Dicky Fuller test is used for unit root process which suggested that all the variables are stationary at the 1st level. For the long run relationship Johanson-Cointegration technique has been applied. After statistical procedure results suggested that female employment, inflation and the Gini index are strongly related with crime. Coefficient of Gini index is high which means that in long-run income inequality affects the crime more than other two because income inequality is a long-run phenomenon so it affect the criminal activities with great magnitude. Vector Correction Model (VCM) has been applied to check the short-run relationship between variables. VCM results suggested that the model we estimate is divergent. Divergent model mean that there is no adjustment from long-run to short-run between variables as they are going away from equilibrium. If we increase the lag length, the model can become divergent but due to crime data unavailability it was difficult to increase the observations and the lags as well. Research paper gives evidence that economic conditions have significant impact on crimes and increasing female employment which is considered as labor market improvement is positively related with crime in Pakistan. This relationship may be the result of market imperfections. Moreover inflation by decreasing purchasing power and income inequality by increasing the gap between social classes is also the cause of increasing crime and they contribute significantly in crime situation of country.