Ecm

Syntax

Ecm(Input: ITimeSeries,
    Period: IMsPeriod,
    Method: ECMType,
    EndogenousVariableAROrder: Integer,
    ExogenousVariableAROrder: Integer,
    Casewise: MsCasewise,
    Explanatories: Array)

Parameters

Input. Output variable

Period. Period, at which the method is calculated. If the parameter value is Null, the method is calculated at the entire time period

Method. Type of error correction model

EndogenousVariableAROrder. Autoregression order of endogenous (output) variable

ExogenousVariableAROrder. Autoregression order of exogenous variables

Casewise. Missing data treatment method

Explanatories. Exogenous (explanatory) variables.

Description

It converts variable using error correction model.

Comments

Use this method only in series calculation mode.

Explanatories. They are specified via comma. Remember, that the number of exogenous variables (m) must satisfy to inequality: 0 < m < n-1 for model with constant and 0 < m < n for model without constant in cointegral equation, where n is the number of observations in the output variable.

Example

Formula	Result	Application
= Ecm({Brazil\|BCA[t]}, SetPeriod("01.01.2002","01.01.2016", ECMType.NoTrendIntercept,1,0, MsCasewise.Yes, {Afghanistan\|BCA},{Canada\|BCA})	For the Brazil\|BCA series the error correction model is calculated by the following parameters: model without trend in autoregression and with constant in cointegration level, the autoregression order in endogenous variable is 1, the order of autoregression of exogenous variables is 0, exogenous (explanatory) variables are Afghanistan\|BCA and Canada\|BCA factors. The calculation is executed at the period of 2002-2016 by the Casewise missing data treatment method.	It can be used in formulas of calculated series of time series database and in formulas of attribute-based models of modeling container.
= Ecm(X1,ECMType.TrendIntercept,0,1, MsCasewise.Yes,X2,X3)	For the X1 factor the error correction model is calculated by the following parameters: model with linear trend in autoregression and with constant in the cointegral equation, the order of autoregression of endogenous variable is 0, order of autoregression of exogenous variables is 1, exogenous (explanatory) variables are the X2 and the X3 factors. Calculation is executed for the whole period using the Casewise missing data treatment method.	It can be used in model variable-based formulas of modeling container.