Will inflation increase crime rate? New evidence from bounds and modified wald tests

Global Crime

Volumn 8, Issue 4, 2007, Pages 311-323

  Tang, Chor Foon ^a   Lean, Hooi Hooi ^a  

^a NONE

Author keywords

Cointegration; Crime; Inflation; MWALD

Indexed keywords

EID: 36349026386     PISSN: 17440572     EISSN: 17440580     Source Type: Journal    
DOI: 10.1080/17440570701739694     Document Type: Article

References (60)

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37. We thank the anonymous referee for the suggestion. We note that there are many control variables for crime, but due to the limited availability of data, we include only the unemployment rate in the study.
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40. Pesaran, Shin and Smith23 suggest that the order of integration for the series must be known before any conclusion can be drawn.
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42. The diagnostic tests confirm that the residuals have normal distribution (Jarque-Bera test), no heteroskedasticity problem (ARCH test) and are absent from serial correlation (Breusch-Godfrey LM test). The Ramsey RESET tests show no specification errors for the estimated model.
43. We noted that, in the presence of lagged dependent variables, the confidence lines for the CUSUM andCUSUMof squares tests are incorrect. However, this could not be discarded as a useless stability test.
44. The optimal lag order is chosen based on Schwarz Bayesian criterion (SBC).
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47. We note that the standard Granger causality test uses VAR model to examine the causal link. In this study, we use the ARDL due to the assumption that the non-uniform lag order reflects the relationship better than the uniform lag order. We do not include the current variables in the ARDL model because the present or future cannot cause the past (Granger, 1969).
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55. The optimal lag order for the VAR model is determined by SBC.
56. There is weak bilateral causality evidence (at 10%) between crime and unemployment rates.
57. When the unemployment rate is low, inflation rate tends to be high and vise versa (Phillips, 1958).
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59. We thank the anonymous referee for the suggestion.
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