Computes dynamic forecasts of the default equation.
forecast computes the forecast using the default equation 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.
(Note that we recommend that you instead use the equation proc
Equation::forecast since it explicitly specifies the equation of interest.)
Syntax
forecast(options) yhat [y_se]
You should enter a name for the forecast series and, optionally, a name for the series containing the standard errors. 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. |
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. |
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
forecast con_d
plot con_d
estimate a linear regression over the period 1970Q1–1990Q4, computes dynamic forecasts for the period 1991Q1–1995Q4, and plots the forecast as a line graph.
equation eq1.ls m1 gdp ar(1) ma(1)
forecast m1_bj bj_se
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, see
fit.
See
“Forecasting from an Equation” for a discussion of forecasting in EViews and
“Discrete and Limited Dependent Variable Models” for forecasting from binary, censored, truncated, and count models.
See
“Forecasting” for a discussion of forecasting from sspace models.
See
Equation::forecast and
Equation::fit for the equivalent object commands.
See
Equation::makemodel and
Model::solvefor forecasting from systems of equations or ordered equations.