Add units to core group according to step 3 of the clustering algorithm by Phillips and Sul (2007, 2009), in order to find the enlarged club.
club(X, dataCols, core, time_trim, HACmethod = c("FQSB", "AQSB"), cstar = 0)matrix or dataframe containing data (preferably filtered data in order to remove business cycles)
integer vector with the column indices of the data
an integer vector containing the id's of units in core group
a numeric value between 0 and 1, representing the portion of time periods to trim when running log t regression model. Phillips and Sul (2007, 2009) suggest to discard the first third of the period.
string indicating whether a Fixed Quadratic Spheric Bandwidth (HACmethod="FQSB") or
an Adaptive Quadratic Spheric Bandwidth (HACmethod="AQSB") should be used for the truncation
of the Quadratic Spectral kernel in estimating the \(log t\) regression model
with heteroskedasticity and autocorrelation consistent standard errors.
The default method is "FQSB".
numeric scalar, indicating the threshold value of the sieve criterion \(c^*\) to include units in the detected core (primary) group (step 3 of Phillips and Sul (2007, 2009) clustering algorithm). The default value is 0.
A list of three objects: id, a vector containing the row indices
of club regions in the original dataframe (input of function findClubs);
rows, a vector of row indices of club units in the current dataset
(input of function club); model, a list containing information
about the model used to run the t-test on the regions in the club.
Phillips, P. C.; Sul, D., 2007. Transition modeling and econometric convergence tests. Econometrica 75 (6), 1771-1855.
Phillips, P. C.; Sul, D., 2009. Economic transition and growth. Journal of Applied Econometrics 24 (7), 1153-1185.