Object Reference : Object View and Procedure Reference : Equation
  
 
forecast
Computes dynamic forecasts of an estimated equation.
forecast computes the forecast for all observations in a specified sample. In some settings, you may instruct forecast to compare the forecasted data to actual data, and to compute summary statistics.
Syntax
eq_name.forecast(options) yhat [y_se]
eq_name.forecast(options) yhat [y_se y_var]
Enter a name for the forecast series and, optionally, a name for the series containing the standard errors. For ARCH specifications, you may use the second form of the command, and optionally enter a name for the conditional variance series. Forecast standard errors are currently not available for binary or censored models. forecast is not available for models estimated using ordered methods.
Options
 
d
In models with implicit dependent variables, forecast the entire expression rather than the normalized variable.
u
Substitute expressions for all auto-updating series in the equation.
g
Graph the forecasts together with the ±2 standard error bands.
ga
Graph the forecasts along with the actuals (if available).
e
Produce the forecast evaluation table.
i
Compute the forecasts of the index. Only for binary, censored and count models.
s
Ignore ARMA terms and use only the structural part of the equation to compute the forecasts.
n
Ignore coef uncertainty in standard error calculations that use them.
b =arg
MA backcast method: “fa” (forecast available). Only for equations estimated with MA terms. This option is ignored if you specify the “s” (structural forecast) option.
The default method uses the estimation sample.
forcsmpl=smpl
Forecast sample (optional). If forecast sample is not provided, the workfile sample will be employed
f = arg (default= “actual”)
Out-of-forecast-sample fill behavior: “actual” (fill observations outside the forecast sample with actual values for the fitted variable), “na” (fill observations outside the forecast sample with missing values).
stochastic
Perform stochastic simulation for dynamic equations estimated using least squares.
streps=integer (default=1000)
Number of stochastic repetitions (for threshold regression or stochastic simulation).
stfrac=number (default=.02)
Fraction of failed repetitions before stopping (for threshold regression or stochastic simulation).
prompt
Force the dialog to appear from within a program.
p
Print view.
Examples
The following lines:
smpl 1970q1 1990q4
equation eq1.ls con c con(-1) inc
smpl 1991q1 1995q4
eq1.fit con_s
eq1.forecast con_d
plot con_s con_d
estimate a linear regression over the period 1970Q1–1990Q4, compute static (fitted) and dynamic forecasts for the period 1991Q1–1995Q4, and plot the two forecasts in a single graph.
equation eq1.ls m1 gdp ar(1) ma(1)
eq1.forecast m1_bj bj_se
eq1.forecast(s) m1_s s_se
plot bj_se s_se
estimates an ARMA(1,1) model, computes the forecasts and standard errors with and without the ARMA terms, and plots the two forecast standard errors.
Cross-references
To perform static forecasting with equation objects see Equation::fit. For multiple equation forecasting, see Equation::makemodel, and Model::solve.
For more information on equation forecasting in EViews, see “Forecasting from an Equation”.