Talking About Crime: Why Are We Focusing On Enforcement?

I was listening to BFM radio this morning with some bemusement – there was a fairly long discussion regarding the latest crime statistics report from Pemandu (excerpt):

Pemandu: Crime index down by 10.1% from January to May

KUALA LUMPUR: Malaysia's crime index fell by 10.1% between January and May this year, Pemandu said on Thursday.

According to figures released by Pemandu's Reducing Crime NKRA director Eugene Teh, there were 63,221 cases between January and May this year compared to 70,343 cases recorded in the corresponding period last year.

“The NKRA's focus on bringing down the crime rate in the last three years has achieved big wins yearly since we first began the Government Transformation Programme and the trend seems to be continuing,” he said.

Teh added that Index Crime dropped by 11.1% from 177,520 in 2010 to 157,891 in 2011. Index Crime are classified as Property Crimes which include theft, snatch theft, vehicle theft, machinery theft and house break-ins and Violent Crimes which are robbery, assault, rape and murder.

Street Crimes have also seen a noticeable drop with 38,030 in 2009 dropping by 39.7% to 22,929 in 2011...

Crime, Income Inequality, And The Economy: It’s All Related

In the mailbox today (abstract):

Skill-biased Technological Change, Earnings of Unskilled Workers, and Crime
Naci H. Mocan, Bulent Unel

This paper investigates the impact of unskilled workers' earnings on crime. Following the literature on wage inequality and skill-biased technological change, we employ CPS data to create state-year as well as state-year-and (broad) industry specific measures of skill-biased technological change, which are then used as instruments for unskilled workers' earnings in crime regressions. Regressions that employ state panels reveal that technology-induced variations in unskilled workers' earnings impact property crime with an elasticity of -1, but that wages have no impact on violent crime. The paper also estimates, for the first time in this literature, structural crime equations using micro panel data from NLSY97 and instrumenting real wages of young workers. Using state-year-industry specific technology shocks as instruments yields elasticities that are in the neighborhood of -2 for most types of crime, which is markedly larger than previous estimates. In both data sets there is evidence for asymmetric impact of unskilled workers' earnings on crime. A decline in earnings has a larger effect on crime in comparison to an increase in earnings by the same absolute value.

Crime Rates Are Down, But It Isn’t All Due To Policy

Cutting subsidies isn’t the only thing the Government has been working on. One of the National Key Result Areas (NKRAs) that the administration of Dato’ Sri Najib has committed to is reducing street crime, and it seems that the fairly innovative approach (*cough*) of putting more policemen on the beat, and in identified crime hotspots is bearing fruit (excerpt):

Najib’s fight against crime showing good results

The hurdle was to get a large number of “men in blue” in a relatively short time, given the fact that recruitment and months of training was needed before a policeman could start duty.

Chief Secretary to the Government Tan Sri Sidek Hassan said Najib, who wanted to try new things using existing and available resources had suggested that desk-bound police personnel be reassigned to go to the ground and their place in offices be taken over by civilians.

The result: an additional 7,402 police personnel including officers on the ground today to fight crime. The move has seen some impressive results.

Home Minister Datuk Seri Hishammuddin Hussein recently revealed that the street crime index and the total crime index had fallen by 39% and 15% respectively in the first quarter of the year – well beyond the 20% and 5% target set for the end of the year.

More details on the reduction in crime are available here. I’m not intending here to belittle this achievement, but I have to ask: How much of this reduction is due to the changes in deployment of police personnel, and how much is due to the fact that the economy has improved?

I stumbled upon this unpublished working paper last year and have been meaning to post on it for quite a while (abstract, emphasis mine):

Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach

Economists recognized that economic conditions have an impact on crime activities. In this study we employed the Autoregressive Distributed Lag (ARDL) bounds testing procedure to analyze the impact of economic conditions on various categories of criminal activities in Malaysia for the period 1973-2003. Real gross national product was used as proxy for economic conditions in Malaysia. Our results indicate that murder, armed robbery, rape, assault, daylight burglary and motorcycle theft exhibit long-run relationships with economic conditions, and the causal effect in all cases runs from economic conditions to crime rates and not vice versa. In the long-run, strong economic performances have a positive impact on murder, rape, assault, daylight burglary and motorcycle theft, while on the other hand, economic conditions have negative impact on armed robbery.

Causality has a very specific meaning in econometrics, so don’t take this to mean that poor economic conditions literally “cause” crime in the dictionary sense of the word. Nevertheless, you can construct a fairly common sense rationale for why crime goes up when the economy goes down – higher unemployment and reduced income in economic downturns means that individuals on the margin have an incentive to resort to crime, and the opposite happens when the economy turns northward.

Juxtapose this reasoning against the drop in crime that has been registered for the first quarter of 2010 relative to last year. Since 1Q 2009 was the bottom of the recession and we’ve seen considerable improvement in economic activity since then, it shouldn’t be all too surprising to find crime rates dropping in the past year.

The trick is to disentangle the various influences on crime rates, from the change in deployment (possible), to the change in economic conditions (definite), to changes in income and wealth inequality (no relationship apparently), to the growth in the supply of potential criminals via population growth (I’d argue for this one). As a modelling approach, I’d treat the latter three as explanatory variables, while the change of deployment would be represented by a dummy variable (i.e. as a potential structural break), either within a Vector Error Correction Model (VECM) or an ARDL framework.

Since I don’t have the time series on crime rates or their breakdown, this is all sheer conjecture on my part, but I would say the structural break would test as significant, but so would economic growth and population growth. But that’s just a guess.

On the other hand, I don’t see why there’s any particular reason to ascribe all the credit to changes in crime rates to government policy or police deployment – just as there is no reason to assign them all the blame when things go wrong.

Technical Notes:

1. Habibullah, M.S. and Baharom, A.H. (2008): “Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach”. Unpublished.
2. Baharom, A.H. and Habibullah, M.S. (2008): “Crime and Income Inequality: The Case of Malaysia”. Unpublished.

And some further reading on crime economics from the same source:

1. Baharom, A.H. and Habibullah, M.S. (2008): “Is crime cointegrated with income and unemployment?: A panel data analysis on selected European countries”. Unpublished.
2. Habibullah, M.S. and Law, Siong-Hook (2008): “Property crime and macroeconomic variables in Malaysia: Some empirical evidence from a vector error-correction model”. Unpublished.
3. Puah, Chin-Hong, Voon, Sze-Ling and Entebang, Harry (2008): “Factors stimulating corporate crime in Malaysia”. Unpublished.