club: Find a club

In ConvergenceClubs: Finding Convergence Clubs

Find a club

Description

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.

Usage

club(
  X,
  dataCols,
  core,
  time_trim,
  HACmethod = c("FQSB", "AQSB"),
  cstar = 0,
  cstar_method = c("fixed", "incremental"),
  cstar_increment = 0.1,
  cstar_cap = 3
)

Arguments

X	dataframe containing data (preferably filtered data in order to remove business cycles). Data must not contain any NA or NaN values, otherwise the clustering procedure will be stopped with an error.#' @param dataCols integer vector with the column indices of the data
core	an integer vector containing the id's of units in core group
time_trim	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.
HACmethod	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".
cstar	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.
cstar_method	a string specifying whether cstar should be mantained fixed (cstar_method="fixed") or increased iteratively until the whole club satisfies the condition tvalue>-1.65 (cstar_method="incremental"). Default is cstar_method="fixed" (see Details).
cstar_increment	a positive value specifying the increment to cstar, only valid if cstar_method="incremental" (see Details).
cstar_cap	scalar indicating the maximum value up to which cstar can be increased

Value

A list of three objects: id, a vector containing the row indices of club units 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 units in the club.

References

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.

ConvergenceClubs documentation built on June 14, 2022, 1:06 a.m.