In the data, a sizable fraction of price changes are temporary price reductions referred to as sales. Existing models include no role for sales. Hence, when confronted with data in which a large fraction of price changes are sales related, the models must either exclude sales from the data or leave them in and implicitly treat sales like any other price change. When sales are included, prices change frequently and standard sticky price models with this high frequency of price changes predict small effects from money shocks. If sales are excluded, prices change much less frequently and a standard sticky price model with this low frequency of price changes predict much larger effects of money shocks. This paper adds a motive for sales in a parsimonious extension of existing sticky price models. We show that the model can account for most of the patterns of sales in the data. Using our model as the data generating process, we evaluate the existing approaches and find that neither well approximates the real effects of money in our economy in which sales are explicitly modeled.
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Paper provided by Federal Reserve Bank of Minneapolis in its series Working Papers with number
652.
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