This paper empirically analyzes the determinants of demand in the German automobile industry. Our primary goal is to refine the existing literature on that topic by exploring the impact of uniqueness seeking behaviour of individuals on the demand schedule. Using a dataset on the segment of...

According to the prospect theory financial investors tend to sell winners too early and ride losers too long. Therefore, demand for financial advise should be high in a bull market and low in a bear market. Thus, we test the hypothesis whether the demand for business magazines is somehow related...

The design of alternative tariff structures can serve as a low-cost and effective tool in achieving higher take-up of basic services among poor households while allowing the provider to recover costs. A contingent valuation survey from the Water Supply and Sanitation Project of the Asian...

This paper outlines recently developed techniques for estimating the primitives needed to empirically analyze equilibrium interactions and their implications in oligopolistic markets. It is divided into an introduction and three sections; a section on estimating demand functions, a section on...

We present empirical techniques that are both familiar to students of industrial organization and useful for modeling of media markets. We first focus on demand estimation with discussion of various discrete choice models. We then turn to estimation of the demand for advertising. We next turn to...

We characterize the dispersion of firm-level productivity and demand shocks over the business cycle using Swedish microdata including prices and analyse the consequences for firms and the aggregate economy. Demand dispersion increases by more than productivity dispersion in recessions....

We propose a tractable method for estimation of a simultaneous search model for differentiated products that allows for observed and unobserved heterogeneity in both preferences and search costs. We show that for type I extreme value distributed search costs, expressions for search and purchase...

We propose a demand estimation method that allows researchers to estimate substitution patterns from unstructured image and text data. We first employ a series of machine learning models to measure product similarity from products' images and textual descriptions. We then estimate a nested logit...