dh

Perform the Dumitrescu-Hurlin test.

prompt

Force the dialog to appear from within a program.

p

Print output of the test.

@all

Apply to all series in the group.

Column number or letter (e.g., “2”, “B”). Apply to the series corresponding to the column.

first_col[:]last_col

Colon-delimited range of columns (from low to high, e.g., “3:5”). Apply to all series corresponding to the column range.

first_series[:]last_series

Colon-delimited range of columns (from low to high, e.g., “series01:series05”) specified by series names. Apply to all series corresponding to the column range.

cntn, none

Case 1: No deterministic terms.

Corresponding VAR model has no deterministic terms.

cltn

Case 2: Restricted constant.

Constant only in the cointegrating relations.

Corresponding VAR has a constant.

Case 3 (JHJ): Unrestricted constant

Constant included both in the short-run equation and (artificially) in the cointegrating relations via orthogonalization.

Corresponding VAR has a constant and trend.

cstn

Case 3: Unrestricted constant

Constant only in the short-run equation.

Corresponding VAR has a trend.

cbtl

Case 4 (JHJ): Unrestricted constant and restricted trend

Constant included both in the short-run equation and (artificially) in the cointegrating relations via orthogonalization, and trend included only in the cointegrating relations.

Corresponding VAR has a constant and trend.

cstl

Case 4: Unrestricted constant and restricted trend

Constant only in the short-run equation, and trend only in the cointegrating relation.

Corresponding VAR has a trend.

cbtb

Case 5 (JHJ): Unrestricted constant and trend

Constant and trend both included in the short-run equation and (artificially) in the cointegrating relations via orthogonalization.

Corresponding VAR has a constant, linear, and quadratic trend.

csts

Case 5: Unrestricted constant and trend

Constant and trend both included in the short-run equation.

Corresponding VAR has a linear and quadratic trend.

determsummary

Summarize all deterministic trend cases.

restrict

Impose restrictions as specified by the “restspec=” option.

restspec="spec"

Define the restricted VEC specification where spec is a space a space delimited list of VEC coefficient restrictions.

m = integer, maxit = integer

Maximum number of iterations for restricted estimation (only valid if you choose the restrict option).

c = scalar, cvg = scalar

Convergence criterion for restricted estimation. (only valid if you choose the restrict option).

save = mat_name

cvtype=ol

Display 0.05 and 0.01 critical values from Osterwald-Lenum (1992).

This option reproduces the output from version 4. The default is to display critical values based on the response surface coefficients from MacKinnon-Haug-Michelis (1999). Note that the argument on the right side of the equals sign are letters, not numbers 0-1).

cvsize=arg (default=0.05)

Specify the size of MacKinnon-Haug-Michelis (1999) critical values to be displayed. The size must be between 0.0001 and 0.9999; values outside this range will be reset to the default value of 0.05. This option is ignored if you set “cvtype=ol”.

prompt

Force the dialog to appear from within a program.

p

Print results.

method=arg

Test method: Engle-Granger residual test (“eg”), Phillips-Ouliaris residual test (“po”).

trend=arg (default=“const”)

Specification for the powers of trend to include in the cointegrating equation: None (“none”), Constant (“const”), Linear trend (“linear”), Quadratic trend (“quadratic”).

Note that the specification implies all trends up to the specified order so that choosing a quadratic trend instructs EViews to include a constant and a linear trend term along with the quadratic.

regtrend=arg (default=“none”)

Additional trends to include in the regressor equations (but not the cointegrating equation): None (“none”), Constant (“const”), Linear trend (“linear”), Quadratic trend (“quadratic”). Only trend orders higher than those specified by “trend=” will be considered.

Note that the specification implies all trends up to the specified order so that choosing a quadratic trend instructs EViews to include a constant and a linear trend term along with the quadratic.

lag=arg (default=“a”)

Method of selecting the lag length (number of first difference terms) to be included in the regression: “a” (automatic information criterion based selection), or integer (user-specified lag length).

lagtype=arg (default=“sic”)

Information criterion or method to use when computing automatic lag length selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “msaic” (Modified Akaike), “msic” (Modified Schwarz), “mhqc” (Modified Hannan-Quinn), “tstat” (t-statistic).

maxlag=integer

Maximum lag length to consider when performing automatic lag-length selection

lagpval=number (default=0.10)

Probability threshold to use when performing automatic lag-length selection using a t-test criterion. Applicable when both “lag=a” and “lagtype=tstat”.

nodf

Do not degree-of-freedom correct estimates of the variances.

prompt

Force the dialog to appear from within a program.

p

Print results.

trend=arg (default=“const”)

Specification for the powers of trend to include in the cointegrating equation: None (“none”), Constant (“const”), Linear trend (“linear”), Quadratic trend (“quadratic”).

Note that the specification implies all trends up to the specified order so that choosing a quadratic trend instructs EViews to include a constant and a linear trend term along with the quadratic.

regtrend=arg (default=“none”)

Additional trends to include in the regressor equations (but not the cointegrating equation): None (“none”), Constant (“const”), Linear trend (“linear”), Quadratic trend (“quadratic”). Only trend orders higher than those specified by “trend=” will be considered.

Note that the specification implies all trends up to the specified order so that choosing a quadratic trend instructs EViews to include a constant and a linear trend term along with the quadratic.

nodf

Do not degree-of-freedom correct the coefficient covariance estimate.

prompt

Force the dialog to appear from within a program.

p

Print results.

lag=arg (default=0)

Lag specification: integer (user-specified lag value), “a” (automatic selection).

infosel=arg (default=“aic”)

Information criterion for automatic selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn) (if “lag=a”).

maxlag=integer

Maximum lag-length for automatic selection (optional) (if “lag=a”). The default is an observation-based maximum.

kern=arg (default=“bart”)

Kernel shape: “none” (no kernel), “bart” (Bartlett, default), “bohman” (Bohman), “daniell” (Daniel), “parzen” (Parzen), “parzriesz” (Parzen-Riesz), “parzgeo” (Parzen-Geometric), “parzcauchy” (Parzen-Cauchy), “quadspec” (Quadratic Spectral), “trunc” (Truncated), “thamm” (Tukey-Hamming), “thann” (Tukey-Hanning), “tparz” (Tukey-Parzen).

bw=arg (default=“nwfixed”)

Bandwidth: “fixednw” (Newey-West fixed), “andrews” (Andrews automatic), “neweywest” (Newey-West automatic), number (User-specified bandwidth).

nwlag=integer

Newey-West lag-selection parameter for use in nonparametric bandwidth selection (if “bw=neweywest”).

bwoffset=integer (default=0)

Apply integer offset to bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

bwint

Use integer portion of bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

Pedroni (default)

Pedroni (1994 and 2004).

Kao

Kao (1999)

Fisher

Fisher - pooled Johansen

const (default)

Include a constant in the test equation.

Applicable to Pedroni and Kao tests.

trend

Include a constant and a linear time trend in the test equation.

Applicable to Pedroni tests.

none

Do not include a constant or time trend.

Applicable to Pedroni tests.

determ=arg

Indicate deterministic trends as detailed above in “Options for the Johansen Test”.

Applicable to Fisher tests.

hac=arg (default=“bt”)

Method of estimating the frequency zero spectrum: “bt” (Bartlett kernel), “pr” (Parzen kernel), “qs” (Quadratic Spectral kernel).

Applicable to Pedroni and Kao tests.

bw=arg (default=“nw”)

Method of selecting the bandwidth, where arg may be “nw” (Newey-West automatic variable bandwidth selection), or a number indicating a user-specified common bandwidth.

Applicable to Pedroni and Kao tests.

lag=arg

For Pedroni and Kao tests, the method of selecting lag length (number of first difference terms) to be included in the residual regression. For Fisher tests, a pair of numbers indicating lag.

infosel=arg (default=“sic”)

Information criterion to use when computing automatic lag length selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn).

Applicable to Pedroni and Kao tests.

maxlag=int

Maximum lag length to consider when performing automatic lag length selection, where int is an integer. The default is

Applicable to Pedroni and Kao tests.

disp=arg (default=500)

Maximum number of individual results to be displayed.

prompt

Force the dialog to appear from within a program.

p

Print results.

cov

Product moment covariance.

corr

Product moment correlation.

sscp

Sums-of-squared cross-products.

stat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

prob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

rcov

Spearman’s rank covariance.

rcorr

Spearman’s rank correlation.

rsscp

Sums-of-squared cross-products.

rstat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

rprob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

taub

Kendall’s tau-b.

taua

Kendall’s tau-a.

taucd

Kendall’s concordances and discordances.

taustat

Kendall’s score statistic for evaluating whether the Kendall’s tau-b measure is zero.

tauprob

Probability under the null for the score statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

ucov

Product moment covariance.

ucorr

Product moment correlation.

usscp

Sums-of-squared cross-products.

ustat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

uprob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

wgt=name (optional)

Name of series containing weights.

wgtmethod=arg (default = “sstdev”

Weighting method (when weights are specified using “weight=”): frequency (“freq”), inverse of variances (“var”), inverse of standard deviation (“stdev”), scaled inverse of variances (“svar”), scaled inverse of standard deviations (“sstdev”).

Only applicable for ordinary (Pearson) calculations. Weights specified by “wgt=” are frequency weights for rank correlation and Kendall’s tau calculations.

pairwise

Compute using pairwise deletion of observations with missing cases (pairwise samples).

df

Compute covariances with a degree-of-freedom correction to account for estimated means (for centered specifications), and any partial conditioning variables.

multi=arg (default=“none”)

Adjustment to p-values for multiple comparisons: none (“none”), Bonferroni (“bonferroni”), Dunn-Sidak (“dunn”).

outfmt=arg (default=“single”)

Output format: single table (“single”), multiple table (“mult”), list (“list”), spreadsheet (“sheet”). Note that “outfmt=sheet” is only applicable if you specify a single statistic keyword.

out=name

Basename for saving output. All results will be saved in Sym matrices named using keys (“COV”, “CORR”, “SSCP”, “TAUA”, “TAUB”, “CONC” (Kendall’s concurrences), “DISC” (Kendall’s discordances), “CASES”, “OBS”, “WGTS”) appended to the basename (e.g., the covariance specified by “out=my” is saved in the Sym matrix “MYCOV”).

prompt

Force the dialog to appear from within a program.

p

Print the result.

d=integer (default=0)

Compute correlogram for specified difference of the data.

prompt

Force the dialog to appear from within a program.

p

Print the correlograms.

cov

Product moment covariance.

corr

Product moment correlation.

sscp

Sums-of-squared cross-products.

stat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

prob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

rcov

Spearman’s rank covariance.

rcorr

Spearman’s rank correlation.

rsscp

Sums-of-squared cross-products.

rstat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

rprob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

taub

Kendall’s tau-b.

taua

Kendall’s tau-a.

taucd

Kendall’s concordances and discordances.

taustat

Kendall’s score statistic for evaluating whether the Kendall’s tau-b measure is zero.

tauprob

Probability under the null for the score statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

ucov

Product moment covariance.

ucorr

Product moment correlation.

usscp

Sums-of-squared cross-products.

ustat

Test statistic (t-statistic) for evaluating whether the correlation is zero.

uprob

Probability under the null for the test statistic.

cases

Number of cases.

obs

Number of observations.

wgts

Sum of the weights.

wgt=name (optional)

Name of series containing weights.

wgtmethod=arg (default = “sstdev”

Weighting method (when weights are specified using “weight=”): frequency (“freq”), inverse of variances (“var”), inverse of standard deviation (“stdev”), scaled inverse of variances (“svar”), scaled inverse of standard deviations (“sstdev”).

Only applicable for ordinary (Pearson) calculations. Weights specified by “wgt=” are frequency weights for rank correlation and Kendall’s tau calculations.

pairwise

Compute using pairwise deletion of observations with missing cases (pairwise samples).

df

Compute covariances with a degree-of-freedom correction to account for estimated means (for centered specifications), and any partial conditioning variables.

multi=arg (default=“none”)

Adjustment to p-values for multiple comparisons: none (“none”), Bonferroni (“bonferroni”), Dunn-Sidak (“dunn”).

outfmt=arg (default= “single”)

Output format: single table (“single”), multiple table (“mult”), list (“list”), spreadsheet (“sheet”). Note that “outfmt=sheet” is only applicable if you specify a single statistic keyword.

out=name

Basename for saving output. All results will be saved in Sym matrices named using keys (“COV”, “CORR”, “SSCP”, “TAUA”, “TAUB”, “CONC” (Kendall’s concurrences), “DISC” (Kendall’s discordances), “CASES”, “OBS”, “WGTS”) appended to the basename (e.g., the covariance specified by “out=my” is saved in the Sym matrix “MYCOV”).

prompt

Force the dialog to appear from within a program.

p

Print the result.

prompt

Force the dialog to appear from within a program.

p

Print the cross correlogram.

type=arg

Specify which settings to apply. type=trans loads the column group frequency, data display, table default transformation, and table default frequency conversion settings. type=appear loads the table default appearance settings. This includes the table default fonts, color, header options, label options, and formats. By default both types are loaded.

series

Load series specific settings. This option is ignored if type=trans is used.

transform(trans)

Set the transformation method for the row. trans can be: “l”(level), “d”(1 period diff), “yd”(year difference), “pc”(1 period % change), “pca”(1 period % chg-AR), “pcy”(year % chg), “tabdefault” (table default setting), “none” (don’t apply transformation)

freqconv(conv)

Set the frequency conversion method for the row. conv can be “avgtran”(avg then transform), “tranavg”(transform then avg), “sumtran”(sum then transform), “first”(first period), “last”(last period), “tabdefault” (table default setting).

format(fmt= new_format, units=new_units, prefix=” “, suffix=” “, +/-thousand, +/-comma, +/-parens)

Assign a custom prefix/suffix to the number, add a separator (comma or point) to denote thousands, replace a comma with a decimal point, or bracket negative numbers with parenthesis:

fmt can be: “f[.prec]”(fixed decimal), “c[.prec]”(fixed characters), “auto”, “serformat”(series format).

units can be: “N”(native), “P”(percent), “T”(thousands), “M”(millions), “B”(billions), “TR”(trillions)

customrow(“string”)

Add a custom row header containing the quoted text string. To use a blank row, simply leave string empty.

font( “name”, size, +/-b, +/-I, +/-s, +/-u) )

Sets the font, size and style. name should be the name of the font, size should be an integer size value. You may use +b, +i, +s or +u to set bold, italic, strikeout or underline respectively. Use “tabdefault” to use the table default font setting.

textcolor(arg)

Sets the color of the text. arg may be one of the predefined color keywords, or it may be specified using individual red-green-blue (RGB) components using the “@RGB” or “@HEX” functions. The arguments to the @RGB function are a set of three integers from 0 to 255, representing the RGB values of the color. The arguments to the “@HEX” function are a set of six characters representing the RGB values of the color in hexadecimal. Each two character set represents a red, green or blue component in the range '00' to 'FF'. For a description of the available color keywords see “Color definitions”.

rowlabel(label)

Sets a custom row label in place of the series name.

overwrite

Overwrite an existing template with the same name. Without this option naming conflicts will result in an error.

display(arg, n)

Specify the data to display in each table row. arg can be “first”, “last” or “year”.

“first” or “last” will display annual totals, plus the first, or last, n observations in each row.

“year” will display observations for n years of data per row.

firstfreq(freq)

Sets the frequency for the first column grouping: freq can be “n”(native), “a”(annual), “q”(quarterly), “m”(monthly).

secfreq(freq)

Sets the frequency for the second column grouping: freq can be “none” (none), “n”(native), “a”(annual), “q”(quarterly), “m”(monthly).

nalabel(“arg”)

Sets the label for NA values to arg.

+/-displayname

Use display names as default labels.

transform(row, trans)

Set the transformation method for row row. trans can be: “l”(level), “d”(1 period diff), “yd”(year difference), “pc”(1 period % change), “pca”(1 period % chg-AR), “pcy”(year % chg).

freqconv(row, conv)

Set the frequency conversion method for the specified row. conv can be “avgtran” (avg then transform), “tranavg” (transform then avg), “sumtran” (sum then transform), “first” (first period), “last”(last period).

format(fmt= new_format, units=new_units, prefix=” “, suffix=” “, +/-thousand, +/-comma, +/-parens)

Assign a custom prefix/suffix to the number, add a separator (comma or point) to denote thousands, replace a comma with a decimal point, or bracket negative numbers with parenthesis:

fmt can be: “f[.prec]”(fixed decimal), “c[.prec]”(fixed characters), “auto”, “serformat”(series format).

units can be: “N”(native), “P”(percent), “T”(thousands), “M”(millions), “B”(billions), “TR”(trillions)

colheader(+/-b, +/- i)

Sets column headers to bold or italic style.

rowheader(+/-b, +/- i)

Sets row headers to bold or italic style.

fillcolor(arg)

Set the table row background color to that specified by arg. arg may be one of the predefined color keywords, or it may be specified using individual red-green-blue (RGB) components using the “@RGB” or “@HEX” functions. The arguments to the @RGB function are a set of three integers from 0 to 255, representing the RGB values of the color. The arguments to the “@HEX” function are a set of six characters representing the RGB values of the color in hexadecimal. Each two character set represents a red, green or blue component in the range '00' to 'FF'. For a description of the available color keywords see “Color definitions”.

altfillcolor(colorspec)

Set the table alternate row background color to colorspec. colorspec may consist of an @rgb(r,g,b) or @hex specification or it may be the name of a basic color such as “white”, “blue”, “red”, “black”, etc.

font(row, “name”, size, +/–b, +/–I, +/–s, +/–u)

Sets the font, size and style. name should be the quoted name of the font, size should be an integer size value. You may use +b, +i, +s or +u to set bold, italic, strikeout or underline respectively.

yrformat(arg)

Sets the date format for year date labels. arg may be “YYYY” (4-digit years) or “YY” (2 digit years).

qtrformat(arg)

Sets the date format for quarterly date labels. arg may be “QR” (upper-case Roman numerals), “qr” (lower-case Roman numerals), “[Q]Q” (“Q” followed by the quarter number), “Q” (quarter number), “Mon” (3 letter month abbreviation for first month in quarter), “Month” (full month name for first month in quarter).

monformat(arg)

Sets the date format for monthly date labels. arg may be “[M]mm” (“M” followed by month number), “mm” (month number), “MM” (month number with preceding zero), “[M]MM” (“M” followed by month number with preceding zero) “Mon” (3 letter month abbreviation), “Month” (full month name), “M” (upper-case first letter of month name), or “m” (lower-case first letter of month name).

qtryrformat(arg)

Sets the joint date format for quarter and year. Only applicable if “Display(first)” or “Display(last)” is used.

arg may be: “YYYY[q]Q]”, “YYYY[Q]Q”, “YYYY:Q”, “YY[q]Q”, “YY[Q]Q”, “YY:Q”, “YYYY QR”, “YYYYqr”, “YYYY qr”, “YY QR”, “YYqr”, “YY qr”, “Mon YYYY”, “Mon YY”, or “Month YYYY”.

See description of “yrformat” and “qtrformat” above for details.

monyrformat(arg)

Sets the joint date format for month and year. Only applicable if “Display(first)” or “Display(last)” is used.

arg may be: “YYYY[m]mm]”, “YYYY[M]mm”, “YYYY[m]MM”, “YYYY:M”, “YY[m]mm”, “YY[M]mm”, “YY[m]MM”, “YY:mm”, “YY:MM”, “Mon YYYY”, “Mon YY”, “Month YYYY”, “Month YY”, “YYMon”, or “YY-Mon”.

See description of “yrformat” and “monformat” above for details on each.

+/– endperiod

Use end of period date labels.

kernfit

Kernel regression (default).

nnfit

Nearest neighbor (local) regression.

empqq

Empirical quantile-quantile plot.

mult = mat_type

Multiple series or column handling: where mat_type may be: “pairs” or “p” - pairs, “mat” or “m” - scatterplot matrix, “lower” or “l” - lower triangular matrix.

prompt

Force the dialog to appear from within a program.

p

Print the report table.

graph

Display observation graph showing duplicates.

sheet

Display spreadsheet view of duplicates.

individ

Display first individual duplicates.

dropna (default) / keepna

[Drop/Keep] NA as a category.

v=integer (default=1000)

Make bins if the number of distinct values or categories exceeds the specified number.

nov

Do not make bins on the basis of number of distinct values; ignored if you set “v=integer.”

a=number

(optional) Make bins if average count per distinct value is less than the specified number.

b=integer (default=50)

Maximum number of categories to bin into if performing automatic binning.

n, obs, count (default)

Display frequency counts.

nocount

Do not display frequency counts.

nolimit

Remove prompt warning for continuing when the total number of cells is very large.

sort=arg (default=“lohi”)

Sort order for entries in the frequency table: high data value to low ("hilo"), low data value to high ("lohi" –default), high frequency to low ("freqhilo"), low frequency to high ("freqlohi").

prompt

Force the dialog to appear from within a program.

p

Print the table.

total (default) / nototal

[Display / Do not display] totals.

pct (default) / nopct

[Display / Do not display] percent frequencies.

cum (default) / nocum

(Display/Do not) display cumulative frequency counts/percentages.

table (default)

Display in table mode.

list

Display in list mode.

rowm (default) / norowm

[Display / Do not display] row marginals.

colm (default) / nocolm

[Display / Do not display] column marginals.

tabm (default) / notabm

[Display / Do not display] table marginals—only for more than two series.

subm (default) / nosubm

[Display / Do not display] sub marginals—only for “l” option with more than two series.

full (default) / sparse

(Full/Sparse) tabulation in list display.

totpct / nototpct (default)

[Display / Do not display] percentages of total observations.

tabpct / notabpct (default)

[Display / Do not display] percentages of table observations—only for more than two series.

rowpct / norowpct (default)

[Display / Do not display] percentages of row total.

colpct / nocolpct (default)

[Display / Do not display] percentages of column total.

exp / noexp (default)

[Display / Do not display] expected counts under full independence.

tabexp / notabexp (default)

[Display / Do not display] expected counts under table independence—only for more than two series.

test (default) / notest

[Display / Do not display] tests of independence.

@all

Apply to all series in the group.

Column number or letter (e.g., “2”, “B”). Apply to the series corresponding to the column.

first_col[:]last_col

Colon delimited range of columns (from low to high, e.g., “3:5”). Apply to all series corresponding to the column range.

first_series[:]last_series

Colon delimited range of columns (from low to high, e.g., “series01:series05”) specified by the series names. Apply to all series corresponding to the column range.

c

Clears all text fields in the label.

d

Sets the description field to text.

s

Sets the source field to text.

u

Sets the units field to text.

r

Appends text to the remarks field as an additional line.

p

Print the label view.

window=arg

Type of long-run covariance to compute: “sym” (symmetric), “lower” (lower - lags in columns), “slower” (strict lower - lags only), “upper” (upper - leads in columns), “supper” (strict upper - leads only)

noc

Do not remove means (center data).

rwgt=arg

Row weights.

out=arg

Name of output sym or matrix (optional).

panout=arg

Name of panel output matrix (optional).

prompt

Force the dialog to appear from within a program.

p

Print results.

lag=arg (default=0)

Lag specification: integer (user-specified number of lags), “a” (automatic selection).

infosel=arg (default=“aic”)

Information criterion for automatic selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn) (if “lag=a”).

maxlag=integer

kern=arg (default=“bart”)

Kernel shape: “none” (no kernel), “bart” (Bartlett, default), “bohman” (Bohman), “daniell” (Daniell), “parzen” (Parzen), “parzriesz” (Parzen-Riesz), “parzgeo” (Parzen-Geometric), “parzcauchy” (Parzen-Cauchy), “quadspec” (Quadratic Spectral), “trunc” (Truncated), “thamm” (Tukey-Hamming), “thann” (Tukey-Hanning), “tparz” (Tukey-Parzen), “user” (User-specified; see “kernwgt=” below).

kernwgt=vector

User-specified kernel weight vector (if “kern=user”).

bw=arg (default=”nwfixed”)

Bandwidth: “fixednw” (Newey-West fixed), “andrews” (Andrews automatic), “neweywest” (Newey-West automatic), number (User-specified bandwidth).

nwlag=integer

Newey-West lag-selection parameter for use in nonparametric bandwidth selection (if “bw=neweywest”).

bwoffset=integer (default=0)

Apply integer offset to bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

bwint

Use integer portion of bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

scale=arg (default=“normload”)

Diagonal matrix scaling of the loadings and the scores: normalize loadings (“normload”), normalize scores (“normscores”), symmetric weighting (“symmetric”), user-specified (arg=number).

cpnorm

Compute the normalization for the score so that cross-products match the target (by default, EViews chooses a normalization scale so that the moments of the scores match the target).

eigval=vec_name

Specify name of vector to hold the saved the eigenvalues in workfile.

eigvec=mat_name

Specify name of matrix to hold the save the eigenvectors in workfile.

prompt

Force the dialog to appear from within a program.

cov=arg (default=“corr”)

Covariance calculation method: ordinary (Pearson product moment) covariance (“cov”), ordinary correlation (“corr”), Spearman rank covariance (“rcov”), Spearman rank correlation (“rcorr”), uncentered ordinary correlation (“ucorr”). Note that Kendall’s tau measures are not valid methods.

wgt=name (optional)

Name of series containing weights.

wgtmethod=arg (default = “sstdev”

Weighting method: frequency (“freq”), inverse of variances (“var”), inverse of standard deviation (“stdev”), scaled inverse of variances (“svar”), scaled inverse of standard deviations (“sstdev”).

Only applicable for ordinary (Pearson) calculations where “weights=” is specified. Weights for rank correlation and Kendall’s tau calculations are always frequency weights.

pairwise

Compute using pairwise deletion of observations with missing cases (pairwise samples).

partial=arg

Compute partial covariances conditioning on the list of series specified in arg.

df

Compute covariances with a degree-of-freedom correction accounting for the mean (for centered specifications) and any partial conditioning variables.

name=name

Specify name for the system object.

ytrans=arg

Dependent variable transformation: none (default), log (“log”), difference (“d”), difference of logs (“dlog”), one percentage change in decimal (“pch”), one-period percentage change—annualized, in percent (“pcha”), one-year percentage change in decimal (“pchy”).

prompt

Force the dialog to appear from within a program.

grp=arg

Name of group to hold output series (optional).

lag=arg (default=1)

Lag specification: integer (user-specified number of lags), “a” (automatic selection).

noc

Do not remove means (center data) prior to whitening.

infosel=arg (default=“aic”)

Information criterion for automatic selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn).

maxlag=integer

prompt

Force the dialog to appear from within a program.

out=arg (default=“table”)

Output type: eigenvector/eigenvalue table (“table”), eigenvalues graph (“graph”), loadings graph (“loadings”), scores graph (“scores”), biplot (“biplot”).

eigval=vec_name

Specify name of vector to hold the saved the eigenvalues in workfile.

eigvec=mat_name

Specify name of matrix to hold the save the eigenvectors in workfile.

prompt

Force the dialog to appear from within a program.

p

Print results.

fsmethod=arg (default=“simple”)

Component retention method: “bn” (Bai and Ng (2002)), “ah” (Ahn and Horenstein (2013)), “simple” (simple eigenvalue methods), “user” (user-specified value).

Note the following:

(1) If using simple methods, the minimum eigenvalue and cumulative proportions may be specified using “minigen=” and “cproport=”.

(2) If setting “fsmethod=user” to provide a user-specified value, you must specify the value with “r=”.

r=arg (default=1)

User-specified number of components to retain (for use when “fsmethod=user”).

mineigen=arg (default=0)

Minimum eigenvalue to retain component (when “fsmethod=simple”).

cproport=arg (default=1.0)

Cumulative proportion of eigenvalue total to attain (when “fsmethod=simple”).

mfmethod=arg (default=“user”)

(1) For use with all components retention methods apart from user-specified (“fsmethod=user”).

(2) If setting “mfmethod=user”, you may specify the maximum number of components using “rmax=”.

(3) Schwert’s rule sets the maximum number of components using the rule: let

n=arg or rmax=arg (default=all)

User-specified maximum number of factors to retain (for use when “mfmethod=user”).

fsic=arg (default=avg)

Component selection criterion (when “fsmethod=bn”): “icp1” (ICP1), “icp2” (ICP2), “icp3” (ICP3), “pcp1” (PCP1), “pcp2” (PCP1), “pcp3” (ICP3), “avg” (average of all criteria ICP1 through PCP3).

Component selection criterion (when “fsmethod=ah”): “er” (eigenvalue ratio), “gr” (growth ratio), “avg” (average of eigenvalue ratio and growth ratio).

Component selection (when “fsmethod=simple”): “min” (minimum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “max” (maximum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “avg” (average the optimal number of factors as specified by the min and max rule, then round to the nearest integer).

demeantime

Demeans observations across time prior to component selection procedures, when “n=bn” or “n=ah”.

sdizetime

Standardizes observations across time prior to component selection procedures, when “n=bn” or “n=ah”.

demeancross

Demeans observations across cross-sections prior to component selection procedures, when “n=bn” or “n=ah”.

sdizecross

Standardizes observations across cross-sections prior to component selection procedures, when “n=bn” or “n=ah”.

scree

Display a scree plot of the eigenvalues (if “output=graph).

diff

Display a graph of the eigenvalue differences (if “output=graph).

cproport

Display a graph of the cumulative proportions (if “output=graph).

scale=arg, (default= “normload”)

Diagonal matrix scaling of the loadings and the scores: normalize loadings (“normload”), normalize scores (“normscores”), symmetric weighting (“symmetric”), user-specified (arg=number).

cpnorm

Compute the normalization for the scores so that cross-products match the target (by default, EViews chooses a normalization scale so that the moments of the scores match the target).

nocenter

Do not center the elements in the graph.

mult=arg (default=”first”)

Multiple graph options: first versus remainder (“first”), pairwise (“pair”), all pairs arrayed in lower triangle (“lt”)

labels=arg (default=“outlier”)

Scores label options: identify outliers only (“outlier”), all points (“all”), none (“none”).

labelprob=arg (default=0.1)

Outlier label probability (if “labels=outlier”).

autoscale=arg (default=1.0)

Rescaling factor for auto-scaling.

userscale=arg

User-specified scaling.

cov=arg (default=“corr”)

Covariance calculation method: ordinary (Pearson product moment) covariance (“cov”), ordinary correlation (“corr”), Spearman rank covariance (“rcov”), Spearman rank correlation (“rcorr”), uncentered ordinary correlation (“ucorr”). Note that Kendall’s tau measures are not valid methods.

wgt=name (optional)

Name of series containing weights.

wgtmethod=arg (default = “sstdev”)

Weighting method: frequency (“freq”), inverse of variances (“var”), inverse of standard deviation (“stdev”), scaled inverse of variances (“svar”), scaled inverse of standard deviations (“sstdev”).

Only applicable for ordinary (Pearson) calculations where “weights=” is specified. Weights for rank correlation and Kendall’s tau calculations are always frequency weights.

pairwise

Compute using pairwise deletion of observations with missing cases (pairwise samples).

partial=arg

Compute partial covariances conditioning on the list of series specified in arg.

df

Compute covariances with a degree-of-freedom correction accounting for the mean (for centered specifications) and any partial conditioning variables.

@first

Order the group members based upon their first value (ignoring NAs).

@firstna

Order the group members based upon their first value (treating NAs as a value).

@last

Order the group members based upon their last value (ignoring NAs).

@lastna

Order the group members based upon their last value (treating NAs as a value).

@max

Order the group members based upon their maximum value.

@mean

Order the group members based upon their mean.

@median

Order the group members based upon their median value.

@min

Order the group members based upon their minimum value.

@obs

Order the group members based upon the number of non-NA observations.

@rand

Randomize the ordering.

@reverse

Reverse the current ordering.

r

Reverse the sort order.

outsmpl= smpl_spec

Sample to fill the new series. Either provide the sample range in double quotes or specify a named sample object. The default is the current workfile sample.

name= group_name

Name of group to hold created series.

permute

Draw from rows without replacement. Default is to draw with replacement.

weight= series_name

Name of series to be used containing values proportional to the desired row probabilities (importance sampling). The weight series must have non-missing non-negative values in the input sample, but the weights need not add up to 1, as EViews will normalize the weights.

If no weights are provided, rows will be drawn with equal probability weights.

block=integer

Block length for each draw. Must be a positive integer. The default block length is 1.

withna (default)

[Draw / Do not draw] from all rows in the current sample, including those with NAs.

dropna

Do not draw from rows that contain missing values in the current workfile sample.

fixna

Excludes NAs from draws but copies rows containing missing values to the output series.

nopanel

Ignore panel structure when resampling. By default, EViews will resample within each cross-section and assign to the corresponding cross-section.

prompt

Force the dialog to appear from within a program.

type = arg

Type of fill coloring for spreadsheet cells: “single” (single color), “posneg” (positive-negative single threshold), “range” (single range coloring), “hilo” (high-low-median), “custom” (custom coloring).

s = arg

cright

closed on the right only

cboth

closed on both sides

cleft

closed on the left only

oboth

open on both sides

cright

closed on the right

cleft

closed on the left

solid color specification

@grad(color_arg)

gradient using color specification

@trans

transparent

cright

closed on the right only

cboth

closed on both sides

cleft

closed on the left only

oboth

open on both sides

solid color specification

@grad(color_arg1, color_arg2)

gradient using color specification, where color_arg1 and color_arg2 are the low and high colors, respectively.

@trans

transparent

solid color specification

@grad(color_arg)

gradient using color specification

@trans

transparent

@all

Apply to all series in the group.

Column number or letter (e.g., “2”, “B”). Apply to the series corresponding to the column.

first_col[:]last_col

Colon delimited range of columns (from low to high, e.g., “3:5”). Apply to all series corresponding to the column range.

first_series[:]last_series

Colon delimited range of columns (from low to high, e.g., “series01:series05”) specified by the series names. Apply to all series corresponding to the column range.

top / middle / bottom

Vertical justification setting.

auto / left / center / right

Horizontal justification setting. Strings are left-justified and numbers are right-justified under “auto”.

type = arg

Type of fill coloring for spreadsheet cells: “single” (single color), “posneg” (positive-negative single threshold), “range” (single range coloring), “hilo” (high-low-median), “custom” (custom coloring).

s = arg

cright

closed on the right only

cboth

closed on both sides

cleft

closed on the left only

oboth

open on both sides

cright

closed on the right

cleft

closed on the left

solid color specification

@grad(color_arg)

gradient using color specification

transparent

cright

closed on the right only

cboth

closed on both sides

cleft

closed on the left only

oboth

open on both sides

solid color specification

@grad(color_arg1, color_arg2)

gradient using color specification, where color_arg1 and color_arg2 are the low and high colors, respectively.

transparent

solid color specification

@grad(color_arg)

gradient using color specification

transparent

w

Wide. In a panel this will switch to the unstacked form of the panel (dates along the side, cross-sections along the top).

t

Transpose.

a

All observations (ignore sample)

nl

Do not display labels.

tform=arg (default= “level”

Display transformed data: raw data (“level”), one period difference (“dif” or “d”), annual difference (“dify” or “dy”), one period percentage change (“pch” or “pc”), annualized one period percentage change (“pcha” or “pca”), annual percentage change (“pchy” or “pcy”), natural logarithm (“log”), one period difference of logged values (“dlog”).

c

Compare view. Display the compare view of the group.

p

Print the spreadsheet view.

i

Use individual sample for each series after removing missing values for the individual series.

By default, EViews computes the statistics using a common sample after removing observations with missing values for any series in the group.

p

Print the stats table.

mean (default)

Test equality of mean.

med

Test equality of median.

var

Test equality of variance.

c

Use common sample.

i (default)

Use individual sample.

prompt

Force the dialog to appear from within a program.

p

Print the test results.

const (default)

Include a constant in the test equation.

trend

Include a constant and a linear time trend in the test equation.

none

Do not include a constant or time trend (only available for the ADF and PP tests).

dif=integer (default=0)

Order of differencing of the series prior to running the test. Valid values are {0, 1, 2}.

sum (default)

Summary of the first five panel unit root tests (where applicable).

llc

Levin, Lin, and Chu.

breit

Breitung.

ips

Im, Pesaran, and Shin.

adf

Fisher - ADF.

pp

Fisher - PP.

hadri

Hadri.

balance

Use balanced (across cross-sections or series) data when performing test.

lagmethod=arg (default=“sic”)

Method for selecting lag lengths (number of first difference terms) to be included in the Dickey-Fuller test regressions:

“aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “tstat” (Ng-Perron first backward significant t-statistic).

lag=arg

Specified lag length (number of first difference terms) to be included in the regression: integer (user-specified common lag length), vector_name (user-specific individual lag length, one row per cross-section).

maxlag=arg

Maximum lag length to consider when performing automatic lag length selection: integer (common maximum lag length), or vector_name (individual maximum lag length, one row per cross-section). The default setting produces individual maximum lags of,

lagpval=arg (default=0.1)

Probability value for use in the t-statistic automatic lag selection method (when “lagmethod = tstat”).

hac=arg (default=“bt”)

Method of estimating the frequency zero spectrum: “bt” (Bartlett kernel), “pr” (Parzen kernel), “qs” (Quadratic Spectral kernel),

band = arg, b=arg (default=“nw”)

Method of selecting the bandwidth: “nw” (Newey-West automatic variable bandwidth selection), “a” (Andrews automatic selection), number (user-specified common bandwidth), vector_name (user-specified individual bandwidths, one row for each cross-section).

prompt

Force the dialog to appear from within a program.

p

Print output from the test.

type=arg (default=“panic”)

Type of unit root test: PANIC - Bai and Ng (2004) (“panic”), CIPS - Pesaran (2007) (“cips”).

Note:

(1) when performing PANIC testing, factor selection, MQ, ADF lag selection, VAR lag selection (possibly), long-run variance (possibly), and p-value simulation options are relevant.

(2) when perform CIPS testing, ADF lag selection options are relevant.

exog=arg (default=“constant”)

Exogenous deterministic variables to include for each cross-section: “none” (no deterministic variables), “constant” (only a constant), “trend” (both a constant and trend).

prompt

Force the dialog to appear from within a program.

p

Print results.

adflagmethod=arg (default=“sic”)

Method for selecting lag length (number of first difference terms) to be included in the Dickey-Fuller test regression or number of lags in the AR spectral density estimator:

“aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “msaic” (Modified Akaike), “msic” (Modified Schwarz), “mhqc” (Modified Hannan-Quinn), “tstat” (Ng-Perron first backward significant t-statistic).

adflag=integer

Use-specified fixed lag.

adfmaxlag=integer

Maximum lag length to consider when performing automatic lag length selection.

Note: default is Schwert’s rule: let

adflagpval=arg (default=0.1)

Probability value for use in the t-statistic automatic lag selection method (“lagmethod = tstat”).

fsmethod=arg (default=“bn”)

Factor retention selection method: “bn” (Bai and Ng (2002)), “ah” (Ahn and Horenstein (2013)), “simple” (simple eigenvalue methods), “user” (user-specified value).

Note the following:

(1) If using simple methods, the minimum eigenvalue and cumulative proportions may be specified using “minigen=” and “cproport=”.

(2) If setting “fsmethod=user” to provide a user-specified value, you must specify the value with “r=”.

r=arg (default=1)

User-specified number of factors to retain (for use when “fsmethod=user”).

mineigen=arg (default=0)

Minimum eigenvalue to retain factor (when “fsmethod=simple”).

cproport=arg (default=1.0)

Cumulative proportion of eigenvalue total to attain (when “fsmethod=simple”).

mfmethod=arg

(1) For use with all factor retention methods apart from user-specified (“fsmethod=user”).

(2) If setting “mfmethod=user”, you may specify the maximum number of factors using “rmax=”.

(3) Schwert’s rule sets the maximum number of factors using the rule: let

rmax=arg (default=all)

User-specified maximum number of factors to retain (for use when “mfmethod=user”).

fsic=arg (default=avg)

Factor selection criterion (when “fsmethod=bn”): “icp1” (ICP1), “icp2” (ICP2), “icp3” (ICP3), “pcp1” (PCP1), “pcp2” (PCP1), “pcp3” (ICP3), “avg” (average of all criteria ICP1 through PCP3).

Factor selection criterion (when “fsmethod=ah”): “er” (eigenvalue ratio), “gr” (growth ratio), “avg” (average of eigenvalue ratio and growth ratio).

Factor selection criterion (when “fsmethod=simple”): “min” (minimum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “max” (maximum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “avg” (average the optimal number of factors as specified by the min and max rule, then round to the nearest integer).

demeantime

Demeans observations across time prior to component selection procedures, when “n=bn” or “n=ah”.

sdizetime

Standardizes observations across time prior to component selection procedures, when “n=bn” or “n=ah”.

demeancross

Demeans observations across cross-sections prior to component selection procedures, when “n=bn” or “n=ah”.

sdizecross

Standardizes observations across cross-sections prior to component selection procedures, when “n=bn” or “n=ah”.

varlagmethod=arg (default=“sic”)

Method for selecting lag length (number of first difference terms) to be included in the test statistic VAR:

“aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “msaic” (Modified Akaike), “msic” (Modified Schwarz), “mhqc” (Modified Hannan-Quinn), “tstat” (Ng-Perron first backward significant t-statistic).

varlag=integer

Use-specified fixed lag.

varmaxlag=integer

Maximum lag length to consider when performing automatic lag length selection.

Note: default is Schwert’s rule: let

lag=arg

Lag specification: integer (user-specified number of lags), “a” (automatic selection).

infosel=arg (default=“aic”)

Information criterion for automatic selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn) (if “lag=a”).

maxlag=integer

kern=arg (default=“bart”)

Kernel shape: “none” (no kernel), “bart” (Bartlett), “bohman” (Bohman), “daniell” (Daniel), “parzen” (Parzen), “parzriesz” (Parzen-Riesz), “parzgeo” (Parzen-Geometric), “parzcauchy” (Parzen-Cauchy), “quadspec” (Quadratic Spectral), “trunc” (Truncated), “thamm” (Tukey-Hamming), “thann” (Tukey-Hanning), “tparz” (Tukey-Parzen), “user” (User-specified; see “kernwgt=” below).

kernwgt=vector

User-specified kernel weight vector (if “kern=user”).

bw=arg (default=”nwfixed”)

Bandwidth: “fixednw” (Newey-West fixed), “andrews” (Andrews automatic), “neweywest” (Newey-West automatic), number (User-specified bandwidth).

nwlag=integer

Newey-West lag-selection parameter for use in nonparametric bandwidth selection (if “bw=neweywest”).

bwoffset=integer (default=0)

Apply integer offset to bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

bwint

Use integer portion of bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”).

mcreps=integer

Number of Monte Carlo replications.

asymplen=integer

Asymptotic length of series.

seed=number

Specifies the random number generator seed

rng=arg

Specifies the type of random number generator. The key can be; improved Knuth generator (“kn”), improved Mersenne Twister (“mt”), Knuth’s (1997) lagged Fibonacci generator used in EViews 4 (“kn4”) L’Ecuyer’s (1999) combined multiple, recursive generator (“le”), Matsumoto and Nishimura’s (1998) Mersenne Twister used in EViews 4 (“mt4”).