PANELDOLS - Pedroni(2001) DOLS

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PANELDOLS - Pedroni(2001) DOLS

Postby TomDoan » Sun May 06, 2012 8:02 pm

This is a revised procedure for estimating the cointegrating vectors using the multivariate group mean panel DOLS from Pedroni(2001) "Purchasing Power Parity Tests in Cointegrated Panels," Review of Economics and Statistics, 83, 727-731.

paneldols.src
Procedure file - requires RATS 8.0 or later
(14.44 KiB) Downloaded 164 times


Compared with earlier versions, this adds the option for DET=TREND (not just CONSTANT), a SMPL option for excluding data points, defines global variables for the individual coefficients and covariance matrices and defines residuals from the mean group estimates.

@paneldols( options ) start end
# list of variables (list dependent variable first)


Options
DET=NONE/[CONSTANT]/TREND
TDUM/[NOTDUM] Use TDUM to subtract out common time effects
LAGS=number of lags to use in the Bartlett kernel (for computing the variance) [5]
DLAGS=number of lags and leads on the differences [2]
SMPL=Dummy series with 0's in entries to skip [include all]
PRINT=NONE/SHORT/[FULL] Sets the level of printed output. PRINT=FULL includes the estimates for the individuals, while PRINT=SHORT just does the full sample estimates.
TITLE=title of report ["Mean Group Panel FM Estimation"]
BVEC=VECTOR with hypothesized slope coefficients [all zeros]. The t-statistics reported are for tests against this vector.

AVERAGE=[SIMPLE]/SQRT/PRECISION
Determines how the individual estimates are combined to compute the full sample estimate. AVERAGE=SIMPLE takes a simple arithmetic average. This is the default, and the behavior of Pedroni's original program. AVERAGE=SQRT weights each individual by the diagonal matrix formed by taking the square roots of the precision matrix (inverse covariance matrix) of the estimates for that individual. This matches up with the averaging done in computing the t-statistics, that is, the coefficients and covariance matrix from AVERAGE=SQRT will reproduce the average t-statistics. AVERAGE=PRECISION weights each individual by the precision of its estimates.

Variables Defined
%BETA group estimates of coefficients
%STDERRS group estimates of standard errors
%TSTATS group estimates of t-statistics (for testing BVEC if you include it)
%XX estimates of covariance matrix of group estimates
%%IBETAS individual coefficients
%%ISTDERRS individual standard errors
%%ITSTATS individual t-statistics (for testing BVEC if you include it)
%%IXX individual covariance matrices. This is a VECTOR[SYMM] with %%IXX(i) as the covariance matrix for individual i


A companion procedure for estimating with FM OLS rather than DOLS is at
http://www.estima.com/forum/viewtopic.php?f=7&t=1055

An example of its use is at
http://www.estima.com/forum/viewtopic.php?f=8&t=1057


Last bumped by TomDoan on Sun May 06, 2012 8:02 pm.
TomDoan
 
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