Abstract:
Metro Manila runs on malls, providing both benefits and costs to one of the world’s largest developing-country megacities. Where should optimal public policy incentivize construction of such malls, and how suboptimal are the locations in the status quo? To answer this, I use smartphone location data from 1.05 million devices and traffic data from all roads in Metro Manila to show that barangays with malls experience many more visits and much higher traffic volume than those without. I also find that malls near city borders are associated with lower speeds in neighboring cities, an externality caused by the decentralized mall construction process in the status quo. I then create a theoretical model of mall demand and supply which explains the conditions under which a city becomes dominated by malls. To concretize these mechanisms for Metro Manila and derive policy implications, I build a structural model of a city following the quantitative urban modeling literature, where residents choose daily itineraries, and their route choices endogenously determine congestion on each road in Metro Manila. I estimate the parameters of this model using the aforementioned smartphone and traffic data, then simulate building a mall in different candidate barangays. I first find a large political fragmentation effect that already exists in pure partial equilibrium: because each LGU optimizes for its preferred construction sites, it doesn’t account for externalities onto other LGUs, meaning that malls constructed in the status quo systematically diverge from the Metro Manila-wide optimum. Then about general equilibrium, I compare a naive approach to mall construction that simply maximizes people’s current consumption access to malls (based on home and work locations) to a more sophisticated approach accounting for GE effects on wages, rents, floor space prices, traffic, and people shifting their home and workplace choices. I find that the naive approach, which directly maximizes consumption access, ends up choosing one of the worst locations in GE due to congestion impacts. Meanwhile, the optimal choice in GE would have been one of the worst choices under the naive approach, yet is optimal in GE because it provides very large offsetting agglomeration benefits.
Meeting ID: 471 089 748 908 359
Passcode: gA6F5Xy3
#Philippine Competition Commission #PCC


