ConvergenceClubs (version 2.2.5)

mergeDivergent: Merge divergent units

Description

Merges divergent units according the algorithm proposed by von Lyncker and Thoennessen (2017)

Usage

mergeDivergent(clubs, time_trim, estar = -1.65)

Value

A list of Convergence Clubs, for each club a list is return with the following objects: id, a vector containing the row indices of the units in the club; model, a list containing information about the model used to run the t-test on the units in the club; unit_names, a vector containing the names of the units of the club (optional, only included if it is present in the clubs object given in input).

Arguments

clubs

an object of class convergence.clubs (created by findClub or mergeClubs function)

time_trim

a numeric value between 0 and 1, representing the portion of time periods to trim when running log t regression model; if omitted, the same value used for clubs is used.

estar

a numeric value indicating the threshold \(e^*\) to test if divergent units may be included in one of the new convergence clubs. To be used only if mergeDivergent=TRUE.

Details

von Lyncker and Thoennessen (2017) claim that units identified as divergent by the basic clustering procedure by Phillips and Sul might not necessarily still diverge in the case of new convergence clubs detected with the club merging algorithm. To test if divergent units may be included in one of the new convergence clubs, they propose the following algorithm:

1. Run a log t-test for all diverging units, and if \(t_k > -1.65\) all these units form a convergence club (This step is implicitly included in Phillips and Sul basic algorithm);

2. Run a log t-test for each diverging units and each club, creating a matrix of t-values with dimensions \(d \times p\), where each row d represents a divergent region and each column p a convergence club;

3. Take the highest \(t > e^*\) and add the respective region to the respective club and restart from the step 1. the authors suggest to use \(e^* = t = -1.65 \);

4. The algorithm stops when no t-value > e* is found in step 3, and as a consequence all remaining units are considered divergent.

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.

von Lyncker, K.; Thoennessen, R., 2017. Regional club convergence in the EU: evidence from a panel data analysis. Empirical Economics 52 (2), 525-553

See Also

mergeClubs, Merges a list of clubs created by findClubs;

Examples

data("filteredGDP")

#Cluster Countries using GDP from year 1970 to year 2003
clubs <- findClubs(filteredGDP, dataCols=2:35, unit_names = 1, refCol=35,
                   time_trim = 1/3, cstar = 0, HACmethod = "FQSB")
summary(clubs)

# Merge clusters and divergent units
mclubs <- mergeClubs(clubs, mergeDivergent=TRUE)
summary(mclubs)