A hitchhiker's guide to empirical macro models - Filippo Ferroni; Fabio Canova (Federal Reserve Bank of Chicago, 2021)
This paper describes a package which uses MATLAB functions and routines to estimate VARs, local projections and other models with classical or Bayesian methods. The toolbox allows a researcher to conduct inference under various prior assumptions on the parameters, to produce point and density forecasts, to measure spillovers and to trace out the causal effect of shocks using a number of identification schemes. The toolbox is equipped to handle missing observations, mixed frequencies and time series with large cross-section information (e.g. panels of VAR and FAVAR). It also contains a number of routines to extract cyclical information and to date business cycles. We describe the methodology employed and implementation of the functions with a number of practical examples.
Keywords: E52; E32; C10; 330; VARs; Local Projections; Bayesian Inference; Identification; Forecasts; Missing Values; Filters and Cycles; MATLAB