Object Reference : Object View and Procedure Reference : Series
  
 
pancov
Compute covariances, correlations, and other measures of association for a panel series.
You may compute measures related to Pearson product-moment (ordinary) covariances and correlations, Spearman rank covariances, or Kendall’s tau along with test statistics for evaluating whether the correlations are equal to zero.
Syntax
series_name.pancov(options) [keywords]
By default, EViews will compute the contemporaneous (between cross-section) covariances, correlations and related statistics for the panel series. You may use the “period” option to instruct EViews to compute the between period (within cross-section) measures.
You should specify keywords indicating the statistics you wish to display from the list below.
You may specify keywords from one of the four sets (Pearson correlation, Spearman rank correlation, Kendall’s tau, Uncentered Pearson) corresponding the computational method you wish to employ. (You may not select keywords from more than one set.)
If you do not specify keywords, EViews will assume “cov” and compute the Pearson covariance matrix.
Pearson Correlation
 
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.
Spearman Rank Correlation
 
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.
Kendall’s tau
 
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.
Uncentered Pearson
 
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.
Note that cases and obs are available for each of the methods.
 
Options
 
period
Compute period (within cross-section) panel covariances and related statistics. The default is to compute contemporaneous (between cross-section) measures.
pairwise
Compute using pairwise deletion of observations with missing cases (pairwise samples).
df
Compute covariances with a degree-of-freedom correction for the mean (for centered specifications).
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.
Examples
ser1.pancov
displays the contemporaneous Pearson covariance matrix of SER1 using the cross-sections in sample.
ser1.pancov corr stat prob
displays a table containing the contemporaneous Pearson correlation matrix for SER1, along with t-statistics for testing for zero correlation, and associated p-values,.
smpl 1990 2010
ser1.pancov(period, pairwise) taub taustat tauprob
computes the between period Kendall’s tau-b, score statistic, and p-value for the score statistic, for the periods in the sample “1990 2010” using samples with pairwise missing value exclusion.
ser1.pancov(out=aa, list) cor
computes the contemporaneous Pearson correlation for the series SER1, displays it in list form, and saves the results in the symmetric matrix object AACORR.
Cross-references
See “Covariance Analysis”for discussion.
To display the results of the panel principal components decomposition, see Series::panpcomp.
See Group::cor for the command to compute these measures across series.