Predicting Risks of Anchor Store Openings and Closings

Abstract

The US retail industry has undergone enormous restructuring resulting in construction of new retail space, abandonment of nearby space, bankruptcies, mergers and acquisitions. This paper estimates discrete choice models of opening and closing probabilities of anchors at a given time and location. A probit model with location fixed effects estimates opening and closing probabilities over time and a conditional logit model (CLM) estimates the odds that a given location will be chosen over a competitor. Probabilities are evaluated from the perspective of a given type of anchor classified as low-, mid- or high-price. New findings include the trade-off between competition from same type anchors and localization benefits (different type) associated with comparison shopping in a retail cluster. We develop a new tool for evaluating risks to any existing retail cluster: risks associated with opening a new anchor and with closures of existing anchors. We demonstrate out-of-sample predictive accuracy.