Working Paper: NBER ID: w23295
Authors: Rema Hanna; Gabriel Kreindler; Benjamin A. Olken
Abstract: In cities worldwide, the widespread use of single occupancy cars often leads to traffic congestion and its associated ill effects. Using high frequency data from Google Maps, we test whether high-occupancy vehicle (HOV) policies can be an effective tool to combat congestion. Using the unexpected lifting of Jakarta’s HOV policy, we show that after the policy was abandoned delays rose about 39 percent on affected roads during the morning peak—and nearly 69% during the evening peak. Importantly, this was not due to simply a substitution from other roads to the former HOV routes: the lifting of the policy led to worse traffic throughout the city, even on roads that had never been restricted or at times of the day when restrictions had never been in place. The increase in traffic persisted long after the policy was lifted. In short, we find that HOV policies can greatly improve traffic conditions.
Keywords: No keywords provided
JEL Codes: O18; R41
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| elimination of the 3-in-1 HOV policy (R48) | increase in traffic delays on affected roads (R48) |
| increase in traffic delays on affected roads (R48) | decline in average speeds (R48) |
| elimination of the 3-in-1 HOV policy (R48) | overall increase in car usage (R48) |
| increase in car usage (R41) | increase in traffic congestion (L91) |
| lifting of the HOV policy (R48) | spillover impacts on non-HOV roads (R48) |
| lifting of the HOV policy (R48) | persistent negative effects on congestion (L91) |
| lifting of the HOV policy (R48) | increased demand for single-occupancy vehicles (R48) |