**OPTION** |
**DESCRIPTION** |

afcse |
Used with the BLUP or IBLUP options to get Asymptotic Forecast Standard Errors as described above. |

beg= |
Specifies the BEGinning observation to be used in estimation. This option overrides the SAMPLE command and defaults to the sample range in effect. |

blup |
Used in autoregressive models when the user wishes the predicted values to be adjusted with the lagged residual, to give the Best Linear Unbiased Predictions. BLUP only uses information from the first observation specified. Note, that correct forecast standard errors are only available for the first-order autoregressive model as described above. |

coef= |
Gives an input vector of model coefficients. If this is not specified then the estimated coefficients from the previous SHAZAM command are used. |

csnum= |
Specifies which cross-section to use on a Pooled Cross-Section Time-Series model for POOL models. |

dynamic |
Performs DYNAMIC forecasts for models with a lagged dependent variable. It is assumed that the lag variable is the first independent variable listed. |

end= |
Specifies the ENDing observation to be used in estimation. This option overrides the SAMPLE command and defaults to the sample range in effect. |

estend= |
Specifies the last observation of the estimation for AUTO and POOL models. |

fcse= |
Saves the ForeCast Standard Errors in the variable specified. The option is only available when the coefficients from the previous regression are used for forecasting. The variable to be used for the forecast standard errors must be defined before the estimation with the DIM command. Note that if the HETCOV or AUTCOV= options were used on the previous OLS command, the forecast standard errors are incorrect. |

fixed |
Performs forecasts for FIXED effects POOL models. Also, see the CSNUM= and NCROSS= options. |

gf |
Prints Goodness of Fit tests for normality of residuals. Coefficients of skewness and excess kurtosis and the Jarque-Bera test for normality of the residuals are also computed. |

iblup |
Used in autoregressive models when the user wishes the predicted values to be adjusted with the lagged residual, to give the Best Linear Unbiased Predictions. IBLUP uses information from the Immediately preceding observation. Note, that correct forecast standard errors are only available for the first-order autoregressive model as described above. |

list |
LISTs and plots the residuals and predicted values of the dependent variable and residual statistics. When LIST is specified RSTAT is automatically turned on. |

max |
This option is equivalent to the LIST and GF options. |

meanpred |
Calculate the forecast standard errors for the case of mean prediction. The default method is to calculate forecast standard errors for the case of individual prediction. |

ncross= |
Specifies the Number of CROSS-sections in a Pooled Cross-Section Time-Series model for POOL models. |

nogf |
Specifies not to print Goodness of Fit tests for normality of residuals, skewness, kurtosis and the Jarque-Bera test |

percent |
This option adds one line to every observation listing to display the PERCENTage change in the actual and predicted values (measured as the ratio of the current year to the previous year). In addition, it reports the ratio of the residual to the actual value. These ratios are printed in parentheses below the usual listing of actual, predicted, and residual values. |

predict= |
Saves the PREDICTed values of the dependent variable in the variable specified. |

resid= |
Saves the values of the RESIDuals from the regression in the variable specified. |