No open-access location is known for this record yet.
No open-access location is known for this record yet.
Retail Price Setting in Uruguay Fernando Borraz (bio) and Leandro Zipitría (bio) In recent years there has been a large increase in the empirical literature on price behavior. As new and detailed data sets become available, we observe a number of important studies on the microeconomic fundamentals of price setting by firms—mainly retailers—and their impact on inflation. This analysis allows a better understanding of the behavior, dispersion, and volatility of prices. In this paper, we use a rich and unique data set of 30 million daily prices in grocery stores and supermarkets across Uruguay to analyze stylized facts about consumer price behavior. Our findings are as follows: — The median duration of prices is two and one-half months. Therefore, retail prices in Uruguay are less sticky than in the United States and Brazil but stickier than in Chile and the United Kingdom. — We do not find evidence of a seasonal pattern in the likelihood of price adjustments. — The frequency of price adjustment is correlated with expected inflation only for the personal care product category. For the food category we find that supermarkets change the percentage points of the adjustment but not their frequency. [End Page 77] — The probability of price change on the first day of the month is nine times higher than on any other day. — The probability of a price change is not constant over time. — There exists a high synchronization of price changes in our database, either at the city level or chain level. Overall, our analysis seems to be consistent with time-dependent models, although the high synchronization of price changes on the first day of the month awaits a better theoretical explanation. A Brief Review of the Empirical Literature Although there are different theoretical models in the literature that explain the microeconomic behavior of prices—such as menu cost models, sticky price and sticky information models, and time- or state-dependent pricing strategies—the stylized facts still avoid a unique theoretical explanation. Klenow and Malin (2010), which provides an up-to-date and concise overview of the empirical evidence, confronts the data with different theoretical models. The authors stress ten facts of the microeconomic behavior of prices. The primary facts are that prices do change at least once a year; that the main instrument for downward price adjustment is sales; that most markets have a stickier reference price; that goods prices differ in frequency of adjustment and the changes are asynchronous for different types of goods; that microeconomic forces explain the behavior of prices that differ from aggregate inflation; and that prices adjust mainly when wages change. Gopinath and Rigobon (2008) studies the stickiness of traded goods using microdata on U.S. import and export prices at the dock for the period 1994-2005. The authors find long price duration for traded goods—10.6 months for imports and 12.8 months for exports; great heterogeneity in price stickiness across goods at the disaggregated level; a declining probability of price adjustment over time for imports; and a rather low exchange rate pass-through into U.S. import prices. Nakamura and Steinsson (2008) uses the consumer price index (CPI) and the producer price index (PPI) from the U.S. Bureau of Labor Statistics (BLS) for the period 1988-2005 to study price stickiness. The results show that there is a duration of regular prices of between eight and eleven months, after excluding sale prices; that temporary sales are an important source of price flexibility—mainly downward price flexibility; that roughly one-third of price changes, excluding sales, are price decreases; that price increases strongly [End Page 78] covary with inflation, but price decreases do not; and that price changes are highly seasonal, mainly in the first quarter. Finally, the study finds that the hazard function of price changes, which estimates the probability of a price change after t periods without changing, is slightly downward sloping, which implies that the probability of a price change occurring decreases the longer the time span since the last change. Some of these conclusions are relativized in Klenow and Kryvtsov (2008). Using monthly price information from the BLS for the period 1988-2004, the authors find that prices...
Loading…
Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.