Approximation of crime, poverty, and misery index across quasi‐democratic and dictatorship regimes in Pakistan: Static and dynamic analysis

Abstract

The study explores the nexus of crime rate, misery indices, and poverty in Pakistan for longer and shorter periods by using time series data (1965–2018). Granger causality and autoregressive distributed lag (ARDL) approaches have been used to examine the long run and short run associations. Results indicate that all variables cause the crime rate unidirectionally, while the ARDL model states that misery index, poverty, and crime rate are cointegrated. Interestingly, any change in the poverty and misery index during the long run makes people violent, which ultimately fosters the crime rate. Finally, the error correction mechanism demonstrates the quick adjustment process and about 72% and 68% disequilibrium in crime rate from its equilibrium path is corrected every year. It is evident through the study results that democratic governments have been less effective than dictatorships to address the socioeconomic aspects of human life; rather functioning as a government of the people, by the people and for the people.

Does the crime rate respond symmetrically or asymmetrically to changes in governance quality and macroeconomic variables? The application of linear and non-linear ARDL

“…Consequently, the country's reported crimes surged from 370,350 (1997) to 802,066 (2020). Before that, Shah et al. (2022) reported that the number of reported crimes in Pakistan almost doubled between 1980 and 1990.…”

“…Consequently, the country's reported crimes surged from 370,350 (1997) to 802,066 (2020). Before that, Shah et al (2022) reported that the number of reported crimes in Pakistan almost doubled between 1980 and 1990. These statistics only include reported crimes; however, 30 to 50% of crimes in Pakistan go unreported (Gillani et al, 2009).…”