On the Distributive Costs of Drug-Related Homicides
Crime and violence are serious obstacles to human development, social inclusion, and economic growth (see, among others, Glaeser, 1999). Drug production and trafficking are a major problem in many countries. These activities are often associated with violence, a lack of security and corruption in the police force and in the legal system. In some countries, the sheer number of killings that take place may have a negative impact on economic outcomes. In Mexico, there have been more than 50,000 drug-related homicides (DRHs) since 2006, when President Calderon took office and declared a war on drugs. Compared with the deaths occurring in other recent conflicts, such as the campaigns waged by the Irish National Liberation Army (3,500) or ETA (1,000) in Spain, the number of homicides in Mexico is more than an order of magnitude higher. As a result of this violence, five Mexican cities are among the ten most violent cities in the world, and Mexican citizens consider drug-related violence to be their most important concern. Many analysts and prominent policymakers have estimated that this situation translates into a reduction in GDP of as much as 1 to 2 percentage points. Nevertheless, these estimates are more in the nature of guesses rather than being the result of any rigorous attempt to measure the economic causal effect of drug-related violence.
In a new paper (Ajzenman, Galiani and Seira, 2015), we estimate the causal effect of violence on house prices by drawing on a unique dataset of house prices compiled using information on all the houses and apartments that were appraised in connection with applications for mortgages between 2008 and 2011. House prices are not only important in and of themselves; they also reflect the (dis)amenities of living in given locations. To measure the causal impact of homicides on house prices, we take advantage of a rich dataset that contains more than 1.3 million appraisals. These appraisals are distributed among more than a thousand of the country’s municipalities (out of a total of 2,445) and take various dwelling characteristics into account. For statistics on homicides, we use a national dataset of deaths (in this case, we focus on murders) collected by the Mexican Federal Secretariat of Health. The sharp increase in DRHs allows us to identify the causal effects that are of interest to us here. We contend that the nature of local DRHs is unrelated to local economic conditions, since they are mainly associated with retaliation killings, battles among drug organizations and clashes with the Army.
Our findings indicate that increases in DRHs have a negative effect on house prices, but only in the case of low-quality housing. In other words, this negative impact on house price is borne entirely by the poorer segments of the population. Using a hedonic price equation while conditioning on municipality fixed effects, period effects, secular trends by type of house and specific state trends, as well as controlling for a large set of dwelling characteristics, we estimate that one standard deviation of increase in homicides lowers the price of poor-quality houses by more than 3%. In light of the Rosen (1974) hedonic prices model, where the price of a differentiated good can be described by a vector of characteristics, our parameters of interest could be interpreted as the average marginal willingness to pay for security amenities. Given that many municipalities registered DRH increases of much more than 100% and that housing wealth is typically the largest source of wealth for Mexican families and especially for low-income households, the economic costs of this type of violence could be substantial.
In spite of this large burden on the poor, the willingness to pay to reverse the increase in drug-related crime is not high at the economy level. We estimate it to be approximately 0.1% of Mexico’s GDP. This result because the cost of the violence induced by drug trafficking is all suffered by the extreme poor households. Nevertheless, the cost is high relative to the social transfers made by the national government to the poor in Mexico.
The findings described in our paper are also in line with those of Di Tella et al. (2010), who, while studying another environment and type of conflict, also find that violence places a heavy burden on the poor. These authors exploit the sharp increase in crime that took place during the second half of the 1990s and, in particular, during the year 2001 in Buenos Aires, Argentina. Their main research question is whether the rich or the poor have been the main victims of this rise in crime. In the case of home robberies, they find that the poor have been the main victims of increases in such crimes but, in that case, the channel for this effect is the fact that the rich, unlike the poor, are able to protect their homes by hiring security services and/or installing security devices (see also Levitt, 1999).
References:
Ajzenman, N., Galiani, S., and Seira, E. (2015), "On the Distributive Costs of Drug-Related Homicides", Journal of Law and Economics.
Di Tella, R., Galiani, S., and Schargrodsky, E. (2010), "Crime Distribution and Victim Behavior during a Crime Wave", in The Economics of Crime: Lessons from Latin America, Di Tella, R., Edwards, S., and Schargrodsky, E., (eds.), National Bureau of Economic Research, 2010.
Glaeser, Edward (1999), “An Overview of Crime and Punishment”, Mimeo, Harvard University.
Levitt, Steven (1999), “The Changing Relationship between Income and Crime Victimization”, FRBNY Economic Policy Review, 87-99.
Rosen, S. (1974), “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition”, Journal of Political Economy, 82, 34-55.
