www.gusucode.com > econ 案例源码程序 matlab代码 > econ/RegressionModelwithARErrorsExample.m
%% Regression Model with AR Errors % This example shows how to plot the impulse response function for a regression % model with AR errors. % Copyright 2015 The MathWorks, Inc. %% % Specify the regression model with AR(4) errors: % % $$\begin{array}{l}{y_t} = 2 + {X_t}\left[ \begin{array}{l}5\\ - 1\end{array} \right] + {u_t}\\{u_t} = 0.9{u_{t - 1}} - 0.8{u_{t - 2}} + 0.75{{\rm{u}}_{t - 3}} - 0.6{{\rm{u}}_{t - 4}} + {\varepsilon _t}.\end{array}$$ % Mdl = regARIMA('Intercept',2,'Beta',[5; -1],'AR',... {0.9, -0.8, 0.75, -0.6}) %% % The dynamic multipliers are absolutely summable because the autoregressive % component is stable. Therefore, |Mdl| is stationary. %% % You do not need to specify the innovation variance. %% % Plot the impulse response function. impulse(Mdl) %% % The impulse response decays to 0 since |Mdl| defines a stationary error % process. The regression component does not impact the impulse responses.