computeH {ConvergenceClubs} | R Documentation |
Compute H values
Description
Computes H values (cross-sectional variance) according to the clustering algorithm by Phillips and Sul (2007, 2009)
Usage
computeH(X, quantity = "H", id)
Arguments
X |
matrix or dataframe containing data (preferably filtered, in order to remove business cycles) |
quantity |
string indicating the quantity that should be returned. The options are
|
id |
optional; row index of regions for which H values are to be computed; if missing, all regions are used |
Details
The cross sectional variation is computed as the quadratic
distance measure for the panel from the common limit and under the
hypothesis of the model should converge to zero as t tends towards infinity:
where
Value
A numeric vector, a matrix or a list, depending on the value of quantity
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.
Examples
data("filteredGDP")
h <- computeH(filteredGDP[,-1], quantity="h")
H <- computeH(filteredGDP[,-1], quantity="H")
b <- computeH(filteredGDP[,-1], quantity="both")