We assess the bias and the efficiency of state-of-the-art dynamic panel data estimators by means of model-based Monte Carlo simulations. The underlying data-generating process consists of a standard theoretical growth model of income convergence based on capital accumulation. While we impose a...

We propose a tractable, data-driven demand estimation procedure based on the use maximum entropy (ME) distributions, and apply it a stochastic capacity control problem motivated from airline revenue management. Specifically, we study the two fare-class "Littlewood" problem in a setting where the...