Ron Yang

This paper studies how long-haul truck drivers’ preferences to return home affect U.S. interstate trucking costs. I develop a model where drivers are differentiated by their home locations and how they make sequential driving decisions. I estimate drivers’ preference and cost parameters using data on trucking trips and highway inspections, and I find that home preference raises overall shipping prices, particularly in states with fewer drivers. Counterfactual simulations show that policies to increase the number of drivers can lower costs but, due to home preference, the states with the largest incentives to add drivers also generate the fewest positive spillovers.

Note: Sections of this paper were previously circulated as "(Don't) Take Me Home: Home Preference and the Effect of Self-Driving Trucks on Interstate Trade."

To what extent do transportation costs depend on the amount shipped, and how does infrastructure investment shape these costs? We model railroads as multiproduct firms and estimate the link between capacity utilization and costs using firm choices, the network structure of production, and publicly available routing data. We find a U-shaped relationship between marginal costs and rail utilization: As utilization increases, costs decrease by 30% to a low point at 55% utilization, before increasing by another 30%. Increased congestion in the rail network can explain a third of the 50% increase in real rail prices observed since 2004. We use our framework to study two normative and one positive policy questions: First, we estimate the network externalities of rail infrastructure investment, finding that investment in Arizona provides the highest returns, but only 3% are captured by Arizona itself. Next, we evaluate the cost efficiencies that would arise from a merger between Union Pacific and Burlington Northern Santa Fe. We find that such a merger would reduce costs by 17.1% due to reduced misallocation and process innovation. Lastly, we study the effect of the China shock on freight costs. We show that the reallocation of imports toward the West Coast led to a 3% increase in shipment costs in Los Angeles and Chicago, with heterogeneous effects across space and firms.

How prevalent are empty miles in freight trucking markets, and what are the economic frictions that contribute to empty miles? This study collected estimates of empty trips, empty miles, and backhaul probabilities from the economics and transportation literature, covering 40 years and 27 countries. A meta-analysis provides an average empty mile share of 29 percent, with significant variation across settings. High-income countries tend to have lower shares of empty miles than low- and middle-income countries. This study reviews empirical evidence behind three potential mechanisms behind empty trips, geographic imbalances in freight demand, search and matching frictions, and regulatory barriers, and develops a stylized model to capture these sources and evaluate potential policies.