Description

We propose a novel methodology to track inflation dynamics in Chile by identifying supply and demand shocks at a highly disaggregated level using prices and quantities information from elec-tronic payments data. We estimate SVAR models where supply and demand shocks are identified with sign restrictions. These estimates are then used to group products into categories of CPI inflation. As opposed to similar studies using categorical-level regressions (e.g., Shapiro, 2022), supply and demand shocks may coexist at a given point in time for a particular category, providing a much richer environment for the policymaker. For the Chilean case, our decomposition provides a reasonable narrative to explain the dynamics of inflation since the start of the COVID-19 pandemic and thereafter. The decomposition of headline inflation obtained by adding up the disaggregates is consistent with that coming from a large DSGE model of the Chilean economy. Keywords: Emerging Economy, Electronic Payment Data, COVID-19, inflation, supply and demand shocks, SVAR.