Declare a var (Vector Autoregression) object.

Syntax

var var_name

var var_name.ls(options) lag_pairs endog_list [@ exog_list]

var var_name.ec(trend, n) lag_pairs endog_list [@ exog_list]

Declare the var as a name, or a name followed by an estimation method and specification.

The Var::ls method estimates an unrestricted VAR using equation-by-equation OLS. You must specify the order of the VAR (using one or more pairs of lag intervals), and then provide a list of series or groups to be used as endogenous variables. You may include exogenous variables such as trends and seasonal dummies in the VAR by including an “@-sign” followed by a list of series or groups. A constant is automatically added to the list of exogenous variables; to estimate a specification without a constant, you should use the option “noconst”.

Options

noconst | Do not include a constant in the VAR specification (when combining declaration with Var::ls method). |

prompt | Force the dialog to appear from within a program. |

p | Print the estimation result if the estimation procedure is specified. |

Examples

var mvar.ls 1 4 8 8 m1 gdp tb3 @ @trend

declares and estimates an unrestricted VAR named MVAR with three endogenous variables (M1, GDP, TB3), five lagged terms (lags 1 through 4, and 8), a constant, and a linear trend.

var jvar.ec(c,2) 1 4 m1 gdp tb3

declares and estimates an error correction model named JVAR with three endogenous variables (M1, GDP, TB3), four lagged terms (lags 1 through 4), two cointegrating relations. The “c” option assumes a linear trend in data but only a constant in the cointegrating relations.

Cross-references