Estimating Information Rigidity using Firms’ Survey Data

The slope of the sticky information Phillips curve proposed by Mankiw and Reis (2002) is based on the degree of information rigidity on the part of firms. Carroll (2003) uses an epidemiology model of expectations and finds evidence for the U.S. of a one-year lag in the transmission of information from professional forecasters to households. Using financial institutions? and firms? survey data from Peru and the model proposed by Carroll, I estimate the degree of information rigidity for the Peruvian economy. This paper also considers heterogeneous responses and explores the cross-sectional dimension of these survey forecasts. I find that the degree of information stickiness is such that it takes between one and three quarters for updating information, a result that is robust to different specifications.