Working papers

• A Pure Characteristics Approach for Evaluating Welfare Effects from Introducing New Products with Options (Job Market Paper)

Abstract: Structural estimation of welfare effects from new goods largely relies on demand models that include a logit error and the simulation of a counterfactual that removes the new goods. In markets where consumers have both brand preferences and product-type (option) preferences, nested demand models come into play. However, the logit errors in nested logit models not only lead to an inaccurate prediction of shares in the counterfactual but also make welfare estimates sensitive to the number of nests. To deal with these two problems which give rise to implausibly large welfare estimates, I develop an empirical framework to estimate a pure characteristics demand model that allows for option (nest) choices and eliminates the need to rely on logit errors. I then provide an application using scanner data to quantify the welfare effects of four new products simultaneously introduced to the U.S. shampoo market where consumers have strong preferences over options. Results show that consumer welfare increases the most from the shampoo product that offers a niche option. Compared with models featuring logit errors, my approach reduces welfare overestimation by at least 73%. It also provides a better fit and more accurate welfare estimates than the pure characteristics model ignoring options.

Presented at: IIOC 2023 (Rising Stars Session), CEA 2023

• Estimating Pure Characteristics Demand Models with Supply-Side Optimization

Abstract: The pure characteristics demand models are well-suited for analyzing markets with a large number of products or problems involving a changing number of products since they eliminate the need to rely on logit errors. However, it is also challenging to incorporate a supply side due to the fact that the market share functions are set-valued and not continuous. This project fills the gap in the literature by developing estimation strategies for incorporating multiproduct firms' optimization problems into the pure characteristics model. Such a new framework is important to answer a variety of questions regarding firms' optimal decisions when the number of products is changing. Examples include pricing new product lines, optimal product assortment, and product choices in merger analysis. To deal with the major challenge, I utilize a regularization method proposed in the mathematical programming literature to obtain a unique and continuous market share function, which can be estimated feasibly. From my preliminary simulation studies, I find that such a method can provide accurate estimates of firms' marginal costs and new equilibrium prices when the number of products changes.

Presented at: CEA 2024