We study the problem of finding an optimal assortment of products maximizing the expected revenue, in which customer preferences are modeled using a Nested Logit choice model. This problem is known to be polynomially solvable in a specific case and NP-hard otherwise, with only approximation...

In this paper, we propose a two-step semi-nonparametric estimator for the widely used random coefficient logit demand model. In the first step, exploiting the structure of logit choice probabilities, we transform the full demand system into a partial linear model and estimate the fixed...

We present novel identification and estimation results for a mixed logit model of demand for bundles with endogenous prices given bundle-level market shares. Our approach hinges on an affine relationship between the utilities of single products and of bundles, on an essential real analytic...

Full paper available at "https://ssrn.com/abstract=3141041" https://ssrn.com/abstract=3141041We first present simulations investigating some properties of the Inverse Product Differentiation Logit (IPDL) model. Next, we provide a range of general methods for building Generalized Logit (GL)...

We describe an efficient estimation method for large-scale tree logit models, using a novel change-of-variables transformation that allows us to express the negative log-likelihood as a difference of strictly convex functions. Exploiting this representation, we design a fast iterative method...

I develop the flexible inverse logit (FIL) model, which is a structural inverse demand model which is able to describe the behavior of heterogeneous, utility-maximizing consumers choosing from a choice set of (possibly many) products that are differentiated in a way that is both observed and...

We present the constrained assortment optimization problem under the mixed logit model (MXL) with design options and deterministic customer segments. The rationale is to select a subset of products of a given size and decide on the attributes of each product such that a function of market share...

We study two random choice models that explain behavioural patterns suggesting that the outside option is often chosen by decision makers who find it hard to decide between the otherwise desirable market alternatives available to them. The decision-conflict logit extends the logit model with an...

This study seeks to answer whether it is possible to design an early warning system framework that can signal the risk of fiscal stress in the near future, and what shape such a system should take. To do so, multiple models based on econometric logit and the random forest models are designed and...

We provide two characterizations, one axiomatic and the other neuro-computational, of the dependence of choice probabilities on deadlines in the softmax form, with time independent utility function, time dependent noise parameter, that measures the unit cost of information, and...