makestats |

Create and save series of descriptive statistics computed from a pool object.

Syntax

pool_name.makestats(options) pool_series1 [pool_series2 ...] @ stat_list

You should provide options, a list of series names, an “@” separator, and a list of command names for the statistics you wish to compute. The series will have a name with the cross-section identifier “?” replaced by the statistic command.

Options

Options in parentheses specify the sample to use to compute the statistics

i | Use individual sample. |

c (default) | Use common sample. |

b | Use balanced sample. |

o | Force the overwrite of the computed statistics series if they already exist. The default creates a new series using the next available names. |

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

Command names for the statistics to be computed

obs | Number of observations. |

mean | Mean. |

med | Median. |

var | Variance. |

sd | Standard deviation. |

skew | Skewness. |

kurt | Kurtosis. |

jarq | Jarque-Bera test statistic. |

min | Minimum value. |

max | Maximum value. |

Examples

pool1.makestats gdp_? edu_? @ mean sd

computes the mean and standard deviation of the GDP_? and EDU_? series in each period (across the cross-section members) using the default common sample. The mean and standard deviation series will be named GDP_MEAN, EDU_MEAN, GDP_SD, and EDU_SD.

pool1.makestats(b) gdp_? @ max min

Computes the maximum and minimum values of the GDP_? series in each period using the balanced sample. The max and min series will be named GDP_MAX and GDP_MIN.

Cross-references

See
“Pooled Time Series, Cross-Section Data” for details on the computation of these statistics and a discussion of the use of individual, common, and balanced samples in pool.

See also
Pool::describe.