We develop efficient computational strategies for inventory liquidation problem, which is characterized by a retailer disposing of a fixed amount of inventory over a period of time. Liquidating end-of-cycle products optimally represents a challenging problem due to its inherent stochasticity....

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed by the inclusion of those...