  This paper analyzes the empirical relationship between the inflation rate and
its proximate determinants in Argentina, using quarterly data over the period
2004-2022 and an error-correction vector model approach. Unlike previous
literature, this paper uses a theoretical framework to motivate the inclusion
of variables that are expected to contribute to explain inflation, thus
reducing the risk of omitting relevant variables and formalizing key
mechanisms. Inference is performed through Granger causality analysis, impulse
response functions and forecast errors variance decomposition. The results
suggest that an anti-inflationary plan for Argentina should take into
consideration both the greater relevance of the inertial component, the
exchange rate and the interest rate in the short-run dynamics of the price
level, and the long-run relationship between prices, interest rate and activity
level.
