272—Appendix B. Command Reference

Define cross section members (identifiers) in a pool.

Syntax

List the cross section identifiers after the define keyword.

Examples

pool spot uk jpn ger can

spot.def uk ger ita fra

The first line declares a pool object named SPOT with cross section identifiers UK, JPN, GER, and CAN. The second line redefines the identifiers to be UK, GER, ITA, and FRA.

Cross-references

See Chapter 27, “Pooled Time Series, Cross-Section Data”, on page 823 of the User’s Guide for a discussion of cross-section identifiers.

See also add (p. 198), drop (p. 281) and pool (p. 408).

Deletes objects from a workfile or a database, or removes identifiers from a pool.

Syntax

Command: delete arg1 [arg2 arg3 ...]

Follow the keyword by a list of the names of any objects you wish to remove from the current workfile. Deleting does not remove objects that have been stored on disk in EViews database files.

You can delete an object from a database by prefixing the name with the database name and a double colon. You can use a pattern to delete all objects from a workfile or database with names that match the pattern. Use the “?” to match any one character and the “*” to match zero or more characters.

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When used as a pool procedure, delete allows you to delete series from the workfile using pool series names. You may use the cross-section identifier placeholder “?” in the series names.

If you use delete in a program file, EViews will delete the listed objects without prompting you to confirm each deletion.

Examples

To delete all objects in the workfile with names beginning with “TEMP”, you may use the command:

delete temp*

To delete the objects CONS and INVEST from the database MACRO1, use:

delete macro1::cons macro1::invest

To delete all series in the workfile with names beginning with “CPI” that are followed by identifiers in the pool object MYPOOL.

mypool.delete cpi?

Cross-references

See Chapter 4, “Object Basics”, on page 71 of the User’s Guide for a discussion of working with objects, and Chapter 10, “EViews Databases”, on page 259 of the User’s Guide for a discussion of EViews databases.

Examine derivatives of the equation specification.

Display information about the derivatives of the equation specification in tabular, graphical, or summary form.

The (default) summary form shows information about how the derivative of the equation specification was computed, and will display the analytic expression for the derivative, or a note indicating that the derivative was computed numerically. The tabular form shows a spreadsheet view of the derivatives of the regression specification with respect to each coefficient (for each observation). The graphical form of the view shows this information in a multiple line graph.

Syntax

Equation View: equation_name.derivs(options)

274—Appendix B. Command Reference

Options

gDisplay multiple graph showing the derivatives of the equation specification with respect to the coefficients, evaluated at each observation.

tDisplay spreadsheet view of the values of the derivatives with respect to the coefficients evaluated at each observation.

Note that the “g” and “t” options may not be used at the same time.

Examples

To show a table view of the derivatives:

eq1.derivs(t)

To display and print the summary view:

eq1.derivs(p)

Cross-references

See “Derivative Computation Options” on page 952 of the User’s Guide for details on the computation of derivatives.

See also makederivs (p. 351) for additional routines for examining derivatives, and grads (p. 315), and makegrads (p. 353) for corresponding routines for gradients.

Computes and displays descriptive statistics for the pooled data.

Syntax

List the name of pool series for which you wish to compute descriptive statistics. You may use the cross-section identifier “?” in the series names.

By default, statistics are computed for each stacked pool series, using only common observations where all of the cross-sections for a given series have nonmissing data. A missing observation for a series in any one cross-section causes that observation to be dropped for

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all cross-sections for the corresponding series. You may change the default treatment of NAs using the “i” and “b” options.

EViews also allows you to compute statistics with the cross-section means removed, statistics for each cross-sectional series in a pool series, and statistics for each period, taken across all cross-section units.

Options

mStack data and subtract cross-section specific means from each variable—this option provides the within estimators.

cDo not stack data—compute statistics individually for each cross-sectional unit.

tTime period specific—compute statistics for each period, taken over all cross-section identifiers.

iIndividual sample—includes every valid observation for the series even if data are missing from other series in the list.

bBalanced sample—constrains each cross-section to have the same observations. If an observation is missing for any series, in any cross-section, it will be dropped for all cross-sections.

Examples

pool1.describe(m) gdp? inv? cpi?

displays the “within” descriptive statistics of the three series GDP, INV, CPI for the POOL1 cross-section members.

pool1.describe(t) gdp?

computes the statistics for GDP for each period, taken across each of the cross-section identifiers.

Cross-references

See Chapter 27, “Pooled Time Series, Cross-Section Data”, on page 823 of the User’s Guide for a discussion of the computation of these statistics, and a description of individual and balanced samples.