LAUSR

This paper empirically investigates the interplay between buyer search behavior and firm pricing strategy in a commodity market where many firms price compete to sell homogeneous products. We use the heterogeneity in buyers’ search costs to explain why a firm offers periodic price discounts and enjoys a high profit. An estimation method is proposed to recover the non-parametric distribution of the search costs from the price and transaction volume data. With both data, we show that the search cost distribution can be estimated non-parametrically in a sequential search model, and estimation results from a non-sequential search model are robust to the assumption of the maximum number of searches. We also show the commonly observed high-low pricing strategy can be an optimal strategy for firms when buyers search prices sequentially. As an empirical application, we use the proposed method to estimate the search models using data on a commodity product sold by a firm in a B-to-B market. The models predict a high profit margin for the firm that is consistent with the data, but the sequential search model fits with the observed price distributions and supply costs better than the non-sequential search model.