The Dismal Science

Narco Economics

A new study that could help Mexico win its war on drug traffickers.

Soldiers of the Mexican Army escort Alfredo Aleman Narvaez, aka 'El Comandante Aleman', an alleged member of the drug cartel 'Los Zetas', during his presentation in Mexico City on November 17, 2011.
Mexican soldiers escort Alfredo Aleman Narvaez, aka “El Comandante Aleman,” an alleged member of the drug cartel Los Zetas.

Photo by Yuri Cortez/AFP/Getty images.

“It’s not personal, Sonny. It’s strictly business.” Al Pacino’s classic line from The Godfather nicely sums up the economics profession’s basic view of human enterprise, criminal and otherwise: Human beings make decisions based on rational cost-benefit calculations, not passion or emotion. And it captures the approach employed by MIT Ph.D. student Melissa Dell in her recent work, which strips the seemingly senseless violence of the Mexican Drug War to its cold, rational essentials. Viewing Mexico’s drug cartels as calculating, profit-maximizing business operations, Dell’s model provides a framework for understanding how traffickers have adjusted their operations in response to President Felipe Calderón’s war on the drug trade. According to Dell, the cartels have behaved like textbook economic actors, shifting their trafficking routes in predictable ways to circumvent towns where the government has cracked down and raiding towns where competing cartels have been weakened by government efforts. By providing a basis for analyzing how traffickers react to government efforts, Dell’s work might help Calderón’s administration design a better strategy for defeating Mexico’s drug lords.

Dell’s study is part of the emerging field of forensic economics, which aims to shed light on shadowy corners of the economic world, where there is much speculation but few verifiable facts. Assessing how drug traffickers react to interdiction efforts is complicated by the fact that the government is unlikely to direct its military and policing resources at random. For example, if the government works to secure areas where the cartels are gaining strength, we may observe an increase in violence—not because of anything that government forces did, but simply because it’s an area where the drug trade is on the rise. So Dell looks at places where the strength of anti-trafficking efforts is essentially the result of a coin flip. She compares towns where a mayor from Calderón’s law-and-order Partido Acción Nacional (PAN) barely won the election (that is, by a margin of less than 5 percent) to towns where a mayor from a different party won by a similarly slim margin. She argues that before the votes were tallied, the two types of towns were essentially identical. But following the election, the PAN-ruled towns are more aligned with the drug war waged by the federal government.

What happens when a law-and-order mayor gets elected? All hell breaks loose: Dell estimates that the drug-related homicide rate almost doubles relative to “control” towns where the PAN wasn’t elected. And it’s not the result of traffickers warring with police, but rather traffickers fighting with each other. Dell conjectures—based on anecdotal evidence about the drug war—that police efforts tend to weaken a cartel’s grip on a town just enough that competing traffickers see an opening to come in and fight for control of the town. Indeed, when a rival cartel controls a neighboring town, the effect of a PAN win on the drug-related homicide rate is several times higher.

A trafficker’s job is shipping Mexican-produced heroin, marijuana, and methamphetamines north to the U.S. from drug-producing regions at the lowest possible cost. When a PAN-backed mayor succeeds in making the roads in his town impassable to traffickers, a rational trafficker will often respond by cutting his losses and skipping town, shifting his routes to run around the obstruction and through more smuggler-friendly communities. The smuggler’s problem, it turns out, was solved by a Dutch computer scientist, Edsger Dijkstra, in the 1950s, who figured out how to calculate the shortest distance between any two points connected via road networks. (If that sounds simple, you’re probably thinking of a simple road network with just a few branches rather than the intricate web of roadways the connect Mexico’s 2,456 municipalities.)

Dell uses Dijkstra’s algorithm first to model the routes that cost-minimizing traffickers would take on Mexico’s roadways and then to predict how these paths would change if disrupted by PAN victories along a route. It turns out that this model—combining simple assumptions about traffickers’ transport costs with an exercise in using Google Maps—is remarkably predictive of how trafficking routes are affected by PAN-led crackdowns that effectively sever paths on the road network: Drug confiscations in the communities where Dell predicts traffickers will relocate to following a crackdown increase by about 20 percent in the months following close PAN victories. It’s a reminder that crime fighting is a bit like Whac-A-Mole—smothering traffickers’ activities in one locale merely causes them to shift their operations elsewhere. Dell finds that drug-related homicides also go up in places that her model predicts will lie on traffickers’ new paths from Mexican drug labs to the U.S. border. (And she finds tentative evidence that towns on newly created routes see a decline in informal sector wages, presumably since drug traffickers also run protection rackets along their smuggling routes, which primarily victimize small shopkeepers and others in the informal economy.)

So at least in the short run, the war on drugs doesn’t lead to a happy outcome for anyone—wars break out on the streets of PAN-controlled towns between newly warring factions, and violence spikes in neighboring communities that had been relatively free of drug violence.

Once you add up these various effects, it’s easy to see how Mexico’s drug war has cost more than 40,000 lives over nearly five years, and counting. It’s also easy to understand calls to bring the war to a halt: For all the human tragedy and billions in economic cost, traffickers merely reroute their smuggling operations around the piecemeal interventions of the police and military. Yet that is precisely the point of drug-interdiction efforts—not to eliminate all drug trafficking, but to raise its costs. Raising costs squeezes the margins of Mexican smugglers who, like all good businessmen, will scale back their operations, thus reducing the supply that reaches the U.S. market.

And even the rise in local violence may ultimately have a silver lining. The increased factional violence that has accompanied government crackdowns may ultimately weaken all of the government’s adversaries. And it’s not just rival cartels that take advantage of weakness to attack—it’s also led to a splintering among the dominant cartels as lower-level commandants split off to compete with their former bosses.

Dell has spoken with Mexican government officials, who believe her approach holds promise for mapping probable trafficking routes and identifying locations in the road network where interdiction efforts would force the costliest redirection of drug shipments. In years past, Mexico has relied more on qualitative analysis of cartel strategy—Dell heard that apparently at one point Mexican analysts tried to predict trafficking routes literally by “connecting the dots” by hand among towns where confiscations had taken place—a far cry from Google Maps and Dijkstra’s algorithm.  The comparison provides a stark indication of the critical ammunition that economists like Dell can provide in the wars on drugs, terrorism, and other worldly ills, if given the chance.