The BLP demand model for differentiated products is the workhorse model for demand
estimation with market-level data. This model uses random coefficients to account for …

We propose a likelihood-based estimator for random coefficients discrete choice demand
models that is applicable in a broad range of data settings. Intuitively, it combines the …

Beschreibung: The causal relation between a product's purchased quantity and observable
characteristics of the product itself or its substitutes lies at the heart of many economic …

The logit model is the most popular tool in estimating demand for differentiated products. In
this model, the outside good plays a crucial role because it allows consumers to stop buying …

Despite the importance of Berry et al.(1995)'s model of demand for differentiated products
(BLP hereafter), there are few results about its finite sample behavior. In theory, simulation …

Demand estimation is a crucial step in structural modeling. In order to catch fundamentals
when simulating counterfactuals and provide welfare-enhancing policy advice, the present …

The logit model is the most popular tool for estimating demand in differentiated products
markets. However, in its aggregate version, practitioners have to “guess” the size outside …

Abstract We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients
discrete-choice demand model, which underlies much recent empirical work in IO. We add …

We develop a semi-nonparametric approach to identify and estimate the demand for
differentiated products. The proposed method adopts a random coefficients discrete choice …

Empirical exercises in economics frequently involve estimation of highly nonlinear models.
The criterion function may not be globally concave or convex and exhibit many local …