Learn Timeseries Quantile ARDL for Non-Normal, Non-Stationary and Outlier Variables in EViews

In #timeseries data #ARDL model is used when the variables are expected to have mixed order of #integration as a result of #unitroot tests. Further if the variables are #non-normal or have #outliers, it will make standard #OLS based estimates #redundant. In this video we learn how to #estimate #quantile ARDL in #eviews using #two-step #ECM model. Further it includes some #diagnostics tests and the #quantileplots of the #coefficients.

• #education
• #ecm
• #unit_root
• #ardl
• #quantile
• #non_normal
• #outliers
• #extreme_values
• #robust
• #median
• #percentile
• #distribution
• #quantile_regression
• #long_run
• #short_run
• #autoregressive_distributed_lag_model
• #who_to_estimate_long_run_coefficients_at_median
• #quantile_convergence_coefficient
• #coefficient_estimation_at_different_percentiles
• #eviews_analysis
• #eviews_tutorial
• #timeseries_quantile_ardl
• #non_stationary
• #outlier_variables
• #eviews
• #noman_arshed
• #econistics