Object Reference : Object View and Procedure Reference : Series
  
 
lrvar
Compute the symmetric, one-sided, or strict one-sided long-run variance of a series.
Syntax
Series View: series_name.lrvar(options)
Options
 
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) prior to whitening.
out=arg
Name of output sym or matrix (optional)
panout=arg
Name of ee output matrix (optional).
prompt
Force the dialog to appear from within a program.
p
Print results.
Whitening Options
 
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
Maximum lag-length for automatic selection (optional) (if “lag=a”). The default is an observation-based maximum of .
Kernel Options
 
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), “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”).
Examples
ser1.lrvar(out=outsym)
computes the symmetric long-run variance of the series SER1 and saves the results in the output sym matrix OUTSYM.
ser1.lrvar(kern=quadspec, bw=andrews)
computes the long-run variance SER1 using the quadratic spectral kernel, Andrews automatic bandwidth.
ser1.lrvar(kern=quadspec, lag=3, bw=andrews)
performs the same calculation but uses AR(3) prewhitening prior to computing the kernel estimator.
ser1.lrvar(kern=none, window=upper, lag=a, infosel=aic, bw=neweywest, rwgt=res)
computes parametric VAR estimates of the upper long-run variance using an AIC based automatic lag-length prewhitening procedure, Newey-West bandwidth selection, and row weight series RES.
Cross-references
See “Long-run Variance”“Panel Long-run Variances”Appendix F. “Long-run Covariance Estimation”. See also Group::lrcov.