A Structural Analysis of Freight Delays in the Indian Railway Network

Abstract

Indian Railways, the world's fourth-largest in size, operates one of the world's slowest freight networks. The slow pace of freight trains is because passenger trains, which share the same infrastructure, get prioritized in dispatch by railway section managers (also known as section controllers). In this paper, we study how section controllers make freight train stop and hold decisions while managing the movement of freight trains. Subsequently, we propose policies to reduce freight delays and, thus, increase trains' speed through the network. We use detailed high-frequency network congestion data and estimate a structural model to reverse engineer the key parameters underlying the controllers' decisions. The estimated parameters provide empirical evidence for (i) the priority accorded to passenger trains over freight trains, (ii) the push effects in the freight train queue, and (iii) the strategic behavior of section controllers in holding trains at larger stations. Using the estimated model, we conduct a set of counterfactual analyses to address the problem of slow freight train speeds. First, we evaluate the impact of constructing Dedicated Freight Corridors (DFCs), high-capacity corridors reserved for freight transport. We find that the DFCs lead to about a 29% reduction in train delays and a 12% improvement in speeds. Then, we also evaluate non-capacity-investment-based alternatives to DFCs, like threshold-based releases and freight capacity consolidation. Interestingly, we find that our non-capacity interventions can provide benefits similar to those of DFCs while being nearly costless. Specifically, a 45-minute threshold release policy leads to around 31% reduction in dwell times. Similarly, consolidating freight capacity by about 25% leads to around a 10% increase in speed, comparable to the improvement achievable with the DFC.

Keywords: Freight Operations, Indian Railways, Empirical Analysis, Choice Models, Wait times, Structural Estimation