Price Search and Periodic Price Discounts

This paper empirically investigates the interplay between buyer search behavior and firm pricing strategy in a commodity market where many firms compete in price to sell homogeneous products. We use the heterogeneity in buyer search cost to rationalize why a firm offers periodic price discounts and enjoys a high profit in such a market. An estimation method is proposed to recover the nonparametric distribution of buyer search cost from the price and transaction volume data. With both data, we show that the search cost distribution can be estimated nonparametrically in a sequential search model, and estimation results from a nonsequential search model are robust to the assumption on the maximum number of searches. We also show that the commonly observed high-low pricing strategy can be an optimal strategy for firms when buyers search for price information sequentially. As an empirical application, we use the proposed method to estimate the two search models using data on a commodity product sold by a firm in a business-to-business market. The models predict a high profit margin for the firm, which is consistent with the data, but the sequential search model fits with the observed price distributions and supply costs better than the nonsequential search model. The online appendix is available at https://doi.org/10.1287/mnsc.2016.2641 . This paper was accepted by Matthew Shum, marketing.