Optimal Price Setting With Observation and Menu Costs

Abstract

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Pricing decisions in an experimental dynamic stochastic general equilibrium economy

“…This means that the likelihood that a firm changes its price in a period is greater the longer it has kept its price constant. This stands in contrast to most empirical studies, but is consistent with the DSGE model with menu costs (see e.g., Alvarez et al, 2011).…”

“…We find that the fraction of prices that change from one period to the next is not highly correlated with inflation, but the average magnitude of changes does exhibit a strong correlation with inflation. However, in contrast to most empirical studies, but in a manner consistent with the theoretical models of Sheedy (2010) and Alvarez et al (2011), the hazard function of price changes is upward sloping. Menu costs, although calibrated in line with the estimations of Nakamura and Steinsson (2008), prove to be too high, and reduce the frequency of price changes considerably below the estimates from the field.…”

“…The hazard function of price changes indicates the probability of a price change, as a function of the length of time that the same price has been in effect. Intuitively, one might anticipate an upward sloping function (see Alvarez et al, 2011;Sheedy, 2010;), i.e. the longer a price has remained unchanged, the greater the probability it is changed in a given period, particularly if there is a positive underlying rate of inflation.…”

“…The time profile of the hazard rate of price changes has been debated in the literature. An upward sloping hazard rate would bring DSGE models more in line with the stylized facts about the behavior of inflation and output gap, see Sheedy (2010) and Alvarez et al (2011). However, the empirical literature has mostly found that the hazard rate is not upward-sloping (see Klenow and Kryvtsov, 2008;Nakamura and Steinsson, 2008).…”

“…In the Menu Cost treatment there are more extreme price changes.22 Ikeda and Nishioka (2007) estimate the hazard function for goods and for services separately. They assume a Weibull distribution, as we do here, but they estimate a model with heterogeneous types Alvarez et al (2011). derive a non-monotonic hazard function from their model.…”