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help for modlpr
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Estimate long memory in a timeseries via Modified Log-Periodogram Regression

        modlpr varname [if exp] [in range] [, powers(numlist) [ notrend ]

    modlpr is for use with time-series data.  You must tsset your data before
    using modlpr; see help tsset.  modlpr supports the by prefix, which may be
    used to operate on each time series in a panel. Alternatively, the if
    qualifier may be used to specify a single time series in a panel.

Description

    modlpr computes a modified form of the Geweke/Porter-Hudak (GPH, 1983)
    estimate of the long memory (fractional integration) parameter, d, of a
    timeseries, proposed by Phillips (1999a, 1999b). If a series exhibits long
    memory, it is neither stationary (I[0]) nor is it a unit root (I[1])
    process; it is an I(d) process, with d a real number. However,
    distinguishing unit-root behavior from fractional integration may be
    problematic, given that the GPH estimator is inconsistent against d>1
    alternatives.

    This weakness of the GPH estimator (see gphudak^) is solved by Phillips'
    Modified Log Periodogram Regression estimator, in which the dependent
    variable is modified to reflect the distribution of d under the null
    hypothesis that d=1. The estimator gives rise to a test statistic for d=1
    which is a standard normal variate under the null. Phillips suggests (p.11)
    that deterministic trends should be removed from the series before
    application of the estimator. By default, a linear trend is extracted from
    the series.  This may be suppressed with the notrend option.

    A choice must be made of the number of harmonic ordinates to be included in
    the spectral regression. The regression slope estimate is an estimate of
    the slope of the series' power spectrum in the vicinity of the zero
    frequency; if too few ordinates are included, the slope is calculated from
    a small sample. If too many are included, medium and high-frequency
    components of the spectrum will contaminate the estimate. A choice of
    root(T), or power = 0.5 is often employed. To evaluate the robustness of
    the estimates, a range of power values (from 0.4 - 0.75) is commonly
    calculated as well.  modlpr uses the default power of 0.5. A numlist of
    powers may be given.

    The command displays the d estimate, number of ordinates, conventional
    standard error and P-value, as well as the test statistic (zd) for the test
    of d=1, and its p-value. These values are returned in a matrix, e(modlpr),
    formatted for display.  ereturn list for details. If modlpr is used in a
    panel context and the returned results are to be saved, the if qualifier
    should be used rather than the by prefix to loop over panels.


Examples

    . use http://fmwww.bc.edu/ec-p/data/Mills2d/fta.dta, clear

    . modlpr ftap

    . modlpr ftap, power( 0.5 0.55:0.8)

    . webuse grunfeld, clear

    . modlpr invest if company==6

    . by company: modlpr invest

Authors

    Christopher F. Baum, Boston College, USA
    baum@bc.edu

    Vince Wiggins, StataCorp LP
    vwiggins@stata.com

References
      
Geweke, J. and Porter-Hudak, S., The Estimation and Application of Long Memory
Time Series Models, J. of Time Series Analysis, 1983, 221-238.

Phillips, Peter C.B., Discrete Fourier Transforms of Fractional Processes,
1999a. Unpublished working paper No. 1243, Cowles Foundation for Research in
Economics, Yale University.  http://cowles.econ.yale.edu/P/cd/d12a/d1243.pdf
      
Phillips, Peter C.B., Unit Root Log Periodogram Regression, 1999b.  Unpublished
working paper No. 1244, Cowles Foundation for Research in Economics, Yale
University.  http://cowles.econ.yale.edu/P/cd/d12a/d1244.pdf
      
Also see

    On-line: regress, time, tsset, ac, corrgram gphudak (if installed), roblpr
             (if installed)