MCCExtExampleData: An Extended MCC/DMC Example Data Set Including Covariates

In bayesMCClust: Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering

Description

An extended MCC/DMC example data set including covariates and response variables – a data set for demonstration purposes...

This small data set is from data from the Austrian Social Security Database (ASSD), which combines detailed longitudinal information on employment and earnings of all private sector workers in Austria since 1972. The IEW Working Paper Zweimueller et al. (2009) (see Source) gives an overview and a description of the main characteristics of the Austrian Social Security Database.

The ASSD was made available for the Austrian Center of Labor Economics and the Analysis of the Welfare State (http://www.labornrn.at/). This small sample consists of N=9402 male Austrian workers, who enter the labor market for the first time in the years 1975 to 1985 and are less than 25 years old at entry. The cohort analysis is based on an observation period from 1975 to 2005.

Usage

data(MCCExtExampleData)

Format

The format is:

List of 4
 $ Njk.i     : num [1:6, 1:6, 1:9402] 0 0 0 0 0 0 0 0 0 0 ...
  ..- attr(*, "dimnames")=List of 3
  .. ..$ : chr [1:6] "0" "1" "2" "3" ...
  .. ..$ : chr [1:6] "0" "1" "2" "3" ...
  .. ..$ : NULL
 $ covariates:'data.frame': 9402 obs. of  4 variables:
  ..$ alrateBezNew        : num [1:9402] 5.97 2.1 2.47 4.26 5.05 ...
  ..$ angStart            : num [1:9402] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ skilled             : int [1:9402] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ unskilled           : int [1:9402] 0 0 0 0 0 0 0 0 0 0 ...
 $ NjkiMat   : num [1:9402, 1:36] 0 0 3 0 1 0 0 1 0 2 ...
 $ obsList   :List of 9402
  ..$ SVNR2166110217: int [1:9] 0 2 2 2 2 2 2 2 2
  ..$ SVNR1924158211: int [1:10] 1 0 3 2 3 2 3 4 4 2
  ..$ SVNR1982609045: int [1:10] 1 0 2 3 0 0 0 4 0 0
  .. [list output truncated]
 $ MNLresponse2gr: int [1:9402] 2 2 2 2 1 2 2 2 2 1 ...
 $ MNLresponse3gr: int [1:9402] 3 2 2 3 1 3 3 2 3 1 ...
 $ MNLresponse4gr: int [1:9402] 2 4 3 4 1 2 4 4 4 4 ...
 

Details

MCCExtExampleData is a list containing the following objects:

Njk.i

A 3-dimensional array of dimension 6x6x9402 containing the transition frequencies (6 x 6-matrices) of 9402 individuals. These represent the counts of transitions between wage categories from year to year with varying observation periods. Categories 1 to 5 correspond to the wage quintiles and 0 to no income.

covariates

contains the data.frame with the covariates used in the logit regression model. It contains the following variables:

		alrateBezNew	unemployment rate in the district
		angStart	dummy for white collar workers
		skilled	dummy for skilled workers
		unskilled	dummy for unskilled workers

NjkiMat

contains the Njk.i-data in matrix format of dimension 9402x36 (each row corresponds to the columns of the matrices in Njk.i).

obsList

A list of 9402 numeric vectors (of integers with variable lengths) representing wage categories. Wage mobility time series with variable lengths describing (transitions between) wage categories (from year to year) of 9402 individuals where categories 1 to 5 correspond to the wage quintiles (in the income distribution of the corresponding year) and 0 to no income. Each positive number represents the position in the income distribution in terms of quintiles of a particular year.

MNLresponse2gr,...,MNLresponse4gr

vectors containing the response variable for h=2,3,4 clusters/groups, (necessary) for use in MNLAuxMix (for demonstration purposes).

Note

Note, that in contrast to the literature (see References), the numbering (labelling) of the states of the categorical outcome variable (time series) in this package is sometimes 0,...,K (instead of 1,...,K), however, there are K+1 categories (states)!

Source

The following IEW Working Paper gives an overview and a description of the main characteristics of the Austrian Social Security Database:

Zweimueller, Josef, Winter-Ebmer, Rudolf, Lalive, Rafael, Kuhn, Andreas, Wuellrich, Jean-Philippe, Ruf, Oliver and Buechi, Simon, Austrian Social Security Database (May 4, 2009). Available at SSRN: http://ssrn.com/abstract=1399350 or at http://www.labornrn.at/wp/wp0903.pdf.

References

Sylvia Fruehwirth-Schnatter, Christoph Pamminger, Andrea Weber and Rudolf Winter-Ebmer, (2011), "Labor market entry and earnings dynamics: Bayesian inference using mixtures-of-experts Markov chain clustering". Journal of Applied Econometrics. DOI: 10.1002/jae.1249 http://onlinelibrary.wiley.com/doi/10.1002/jae.1249/abstract

Christoph Pamminger and Sylvia Fruehwirth-Schnatter, (2010), "Model-based Clustering of Categorical Time Series". Bayesian Analysis, Vol. 5, No. 2, pp. 345-368. DOI: 10.1214/10-BA606 http://ba.stat.cmu.edu/journal/2010/vol05/issue02/pamminger.pdf

See Also

LMEntryPaperData, MCCExampleData, mcClustExtended, dmClustExtended, MNLAuxMix

Examples

data(MCCExtExampleData)
str(MCCExtExampleData) 

# see example(s) in mcClustExtended, dmClustExtended, MNLAuxMix or LMEntryPaperData

bayesMCClust documentation built on May 29, 2017, 3:31 p.m.