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Plotting

MacroModelling.jl integrates a comprehensive plotting toolkit based on StatsPlots.jl. The plotting API is exported alongside the modelling macros, enabling visualization of impulse responses, simulations, conditional forecasts, model estimates, variance decompositions, and policy functions immediately after model definition. All plotting functions are implemented in the StatsPlotsExt extension, which loads automatically when importing or using StatsPlots.

Available Plotting Functions

MacroModelling.jl provides several plotting functions for analyzing and visualizing model behavior:

  • Impulse Response Functions (IRF): Visualize the dynamic response of endogenous variables to exogenous shocks using plot_irf
  • Policy Functions: Plot the relationship between state variables and endogenous variables using plot_solution
  • Conditional Forecasting: Generate model projections conditional on future paths for endogenous variables or exogenous shocks using plot_conditional_forecast
  • Conditional Variance Decomposition: Visualize the forecast error variance decomposition (FEVD) showing shock contributions to variable variance using plot_conditional_variance_decomposition (also available as plot_fevd)
  • Model Estimates: Display filtered or smoothed estimates of endogenous variables and exogenous shocks, with optional shock decomposition and unconditional forecasts using plot_model_estimates (also available as plot_shock_decomposition)