punbalancedness {plm}R Documentation

Measures for Unbalancedness of Panel Data

Description

This function reports unbalancedness measures for panel data as defined in Ahrens/Pincus (1981) and Baltagi/Song/Jung (2001).

Usage

punbalancedness(x, ...)
## S3 method for class 'panelmodel'
punbalancedness(x, ...)
## S3 method for class 'data.frame'
punbalancedness(x, index = NULL, ...)
## S3 method for class 'pdata.frame'
punbalancedness(x, ...)

Arguments

x

a panelmodel, a data.frame, or a pdata.frame object,

index

only relevant for data.frame interface, for details see pdata.frame,

...

further arguments.

Details

punbalancedness returns measures for the unbalancedness of a panel data set.

An application of the measure "gamma" is found in e. g. Baltagi/Song/Jung (2002), pp. 488-491, and Baltagi/Chang (1994), pp. 78–87, where it is used to measure the unbalancedness of various unbalanced data sets used for Monte Carlo simulation studies. Measures c1, c2, c3 are used for similar purposes in Baltagi/Song/Jung (2001).

In the two-dimensional case, punbalancedness uses output of pdim to calculate the two unbalancedness measures, so inputs to punbalancedness can be whatever pdim works on. pdim returns detailed information about the number of individuals and time observations (see pdim).

Value

A named numeric containing either two or three entries, depending on the panel structure inputted:

*

For the two-dimensional panel structure, the entries are called gamma and nu,

*

For a nested panel structure, the entries are called c1, c2, c3.

Note

Calling punbalancedness on an estimated panelmodel object and on the corresponding (p)data.frame used for this estimation does not necessarily yield the same result (true also for pdim). When called on an estimated panelmodel, the number of observations (individual, time) actually used for model estimation are taken into account. When called on a (p)data.frame, the rows in the (p)data.frame are considered, disregarding any NA values in the dependent or independent variable(s) which would be dropped during model estimation.

Author(s)

Kevin Tappe

References

Ahrens, H.; Pincus, R. (1981), “On two measures of unbalancedness in a one-way model and their relation to efficiency”, Biometrical Journal, 23(3), pp. 227–235.

Baltagi, Badi H.; Chang, Young-Jae (1994), “Incomplete panels: A comparative study of alternative estimators for the unbalanced one-way error component regression model”, Journal of Econometrics, 62(2), pp. 67–89.

Baltagi, Badi H.; Song, Seuck Heun; Jung, Byoung Cheol (2001), “The unbalanced nested error component regression model”, Journal of Econometrics, 101(2), pp. 357–381.

Baltagi, Badi H.; Song, Seuck H.; Jung, Byoung C. (2002), “A comparative study of alternative estimators for the unbalanced two-way error component regression model”, Econometrics Journal, 5(2), pp. 480–493.

See Also

nobs, pdim, pdata.frame

Examples

# Grunfeld is a balanced panel, Hedonic is an unbalanced panel
data(list=c("Grunfeld", "Hedonic"), package="plm")

# Grunfeld has individual and time index in first two columns
punbalancedness(Grunfeld) # c(1,1) indicates balanced panel
pdim(Grunfeld)$balanced   # TRUE

# Hedonic has individual index in column "townid" (in last column)
punbalancedness(Hedonic, index="townid") # c(0.472, 0.519)
pdim(Hedonic, index="townid")$balanced   # FALSE

# punbalancedness on estimated models
plm_mod_pool <- plm(inv ~ value + capital, data = Grunfeld)
punbalancedness(plm_mod_pool)

plm_mod_fe <- plm(inv ~ value + capital, data = Grunfeld[1:99, ], model = "within")
punbalancedness(plm_mod_fe)

# replicate results for panel data design no. 1 in Ahrens/Pincus (1981), p. 234
ind_d1  <- c(1,1,1,2,2,2,3,3,3,3,3,4,4,4,4,4,4,4,5,5,5,5,5,5,5)
time_d1 <- c(1,2,3,1,2,3,1,2,3,4,5,1,2,3,4,5,6,7,1,2,3,4,5,6,7)
df_d1 <- data.frame(individual = ind_d1, time = time_d1)
punbalancedness(df_d1) # c(0.868, 0.887)

# example for a nested panel structure with a third index variable
# specifying a group (states are grouped by region) and without grouping
data("Produc", package = "plm")
punbalancedness(Produc, index = c("state", "year", "region"))
punbalancedness(Produc, index = c("state", "year")) 

[Package plm version 1.6-6 Index]