vardpoor (version 0.2.0.8.1)

lingpg: Linearization of the gender pay (wage) gap.

Description

Estimate the gender pay (wage) gap and its linearization.

Usage

lingpg(inc, gender = NULL, id, weight=NULL, sort = NULL,
         Dom = NULL, period=NULL, dataset = NULL, 
         na.rm=FALSE, var_name="lin_gpg")

Arguments

inc

either a numeric vector, 1 column data.frame, matrix, data.table giving the equivalized disposable income, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'datase

gender

either a factor giving the gender, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dataset' column count) specifying the corresponding column of dataset

id

optional; either 1 column data.frame, matrix, data.table with column names giving the personal IDs, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dataset' colu

weight

optional; either a numeric vector, 1 column data.frame, matrix, data.table giving the personal sample weights, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dat

sort

optional; either a numeric vector, 1 column data.frame, matrix, data.table giving the personal IDs to be used as tie-breakers for sorting, or (if dataset is not NULL) a character string, an integer or a logical vector

Dom

optional; either a data.frame, matrix, data.table with column names giving different domains, or (if dataset is not NULL) character strings, integers or a logical vectors (length is the same as 'dataset' column count)

period

optional; either a data.frame, matrix, data.table with column names giving different periods, or (if dataset is not NULL) character strings, integers or a logical vectors (length is the same as 'dataset' column coun

dataset

an optional; name of the individual dataset data.frame.

na.rm

a logical indicating whether missing values should be removed.

var_name

a character string specifying the name of the linearized variable.

Value

• The function returns two values:
• value
  a data.frame containing the estimate(s) the gender pay (wage) gap coeffients (in percentage) by domain, or (if Dom is NULL) totals, using Eurostat definition.
• lin
  a data.frame containing the values of linearized variables of of the gender pay (wage) gap (in precentage) by domains or (if Dom is NULL) totals.

References

Working group on Statistics on Income and Living Conditions (2004) Common cross-sectional EU indicators based on EU-SILC; the gender pay gap. EU-SILC 131-rev/04, Eurostat. Guillaume Osier (2009). Variance estimation for complex indicators of poverty and inequality. Journal of the European Survey Research Association, Vol.3, No.3, pp. 167-195, ISSN 1864-3361, URL https://ojs.ub.uni-konstanz.de/srm/article/view/369. Deville, J. C. (1999). Variance estimation for complex statistics and estimators: linearization and residual techniques. Survey Methodology, 25, 193-203, URL http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?lang=eng&catno=12-001-X19990024882.

See Also

linqsr, lingini, varpoord, var_srs

Examples

data(ses)
dati=data.frame(1:nrow(ses),ses)
colnames(dati)[1]<-"ID"
gpgs2<-lingpg("earningsHour", gender="sex", id="ID", weight="weights",
               Dom="education", dataset=dati)
gpgs2$value