Three essays in macroeconomics
OA Version
Citation
Abstract
This dissertation consists of three chapters pertaining to retail markets and their broader economic implications. In the first chapter, I argue that the multi-product, one-stop shopping nature of retail markets implies significant amplification of nominal shocks while addressing a classic puzzle regarding item-level price volatility. The second chapter explores the properties of retailer pricing zones identified using a machine learning method. In the third chapter, I explore the propensity of households to switch grocery retailers following price increases of several goods.
The first chapter demonstrates that retail-level real rigidity is both quantitatively important and consistent with facts on retail pricing. Motivated by extensive literature on customer markets and retail pricing strategies, I construct a menu cost model in which demand occurs at the store-basket level and stores face incentives to keep their overall ``basket prices" near those of competitors. Calibrating the price concavity of store-level demand to basket price volatility in the NielsenIQ data, the model predicts that full price-level adjustment takes two and a half times as long as in a counterfactual CES model following a small monetary policy shock. Critically, retailer-level real rigidity is compatible with high volatility of item-level prices, a fact shown to be incompatible with item-level real rigidity by Klenow and Willis.
The second chapter, joint with Ian Meeker, develops a clustering method for identifying pricing zones in retail scanner data. We begin by documenting the self-identified pricing zones in the Dominick's Finer Foods data, and compare the efficacy of several different clustering methods in recovering these zones. After validating our method on an independent data set with known pricing zones, we use it to identify several pricing zones in the NielsenIQ Scanner Data. A post-hoc analysis of the identified zones reveals comparable properties to the self-identified Dominick's zones.
In the third chapter, I use high-frequency household and store micro-data from NielsenIQ to test the sensitivity of household exit decisions from grocery stores in response to both absolute and relative price changes at the store. This chapter extends prior empirical analyses by considering multiple retailers and allowing for an outsize influence of individual consumer goods on the exit decision. All specifications reveal that the probability that a household exits increases as prices observed at the store increase. The responses are larger when household-store expenditure shares are smaller.