Introduction to vector error-correction models and cointegration basics

Apuntes

Title stata.com vec intro — Introduction to vector error-correction models Description Remarks and examples References Also see Description Stata has a suite of commands for fitting, forecasting, interpreting, and performing inference on vector error-correction models (VECMs) with cointegrating variables. After fitting a VECM, the irf commands can be used to obtain impulse–response functions (IRFs) and forecast-error variance decompositions (FEVDs). The table below describes the available commands. Fitting a VECM vec [TS] vec Fit vector error-correction models Model diagnostics and inference vecrank [TS] vecrank Estimate the cointegrating rank of a VECM veclmar [TS] veclmar Perform LM test for residual autocorrelation after vec vecnorm [TS] vecnorm Test for normally distributed disturbances after vec vecstable [TS] vecstable Check the stability condition of VECM estimates varsoc [TS] varsoc Obtain lag-order selection statistics for VARs and VECMs Forecasting from a VECM fcast compute [TS] fcast compute Compute dynamic forecasts after var, svar, or vec fcast graph [TS] fcast graph Graph forecasts after fcast compute Working with IRFs and FEVDs irf [TS] irf Create and analyze IRFs an...