R/mip.R

Defines functions mip

Documented in mip

#' @title Mean income per person
#'
#' @author A. Berihuete, C.D. Ramos and M.A. Sordo
#'
#' @description Estimates the mean income per person.
#'
#' @param dataset a data.frame containing the variables.
#' @param ipuc a character string indicating the variable name of the income per unit of consumption. Default is "ipuc".
#' @param hhcsw a character string indicating the variable name of the household cross-sectional weight. Default is "DB090".
#' @param hhsize a character string indicating the variable name of the household size. Default is "HX040".
#' @param ehhs a character string indicating the variable name of the equivalised household size. Default is "HX050".
#' @param edi a character string indicating the variable name of the equivalised disposable income (with the modified OECD scale). Default is "HX090".
#' @param ci a scalar or vector containing the confidence level(s) of the required interval(s). Default does not calculate the confidence interval.
#' @param rep a number to make the confidence interval using boostrap technique.
#' @param verbose logical; if TRUE the confidence interval is plotted.
#'
#' @return The value of mean income per person.
#'
#' @references B. Buhmann et al. (1988) Equivalence scales, well-being, inequality and poverty: sensitivity estimates across ten countries using the Luxembourg Income Study (LIS) database, Review of Income and Wealth, 34, 115--142.
#' @references \url{http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Equivalised_disposable_income}
#'
#' @examples
#' data(eusilc2)
#' ATdataset <- setupDataset(eusilc2, country = "AT")
#' mip(ATdataset)
#'
#' @seealso setupDataset.
#' @import boot
#' @export

mip <- function(dataset,
                ipuc = "ipuc", # The income per unit of consumption
                hhcsw = "DB090", # Household cross-sectional weight
                hhsize = "HX040", # Household size
                ehhs = "HX050", #  Equivalised household size
                edi = "HX090", # Equivalised disposable income (with the modified OECD scale)
                ci = NULL, rep = 1000, verbose = FALSE){

  dataset <- dataset[order(dataset[,ipuc]),]
  dataset$wHX040 <- dataset[,hhcsw]*dataset[,hhsize] # household weights taking into account the size of the household

  if(is.null(ci)){
    dataset$acum.wHX040 <- cumsum(dataset$wHX040)
    number.homes <- length(dataset$acum.wHX040)
    number.individuals <- dataset$acum.wHX040[number.homes]
    mip <- sum(dataset[,edi]*dataset[,ehhs]*dataset[,hhcsw])/number.individuals
    return(mip)
  }else{
    mip2 <- function(dataset, i){
      dataset.boot <- dataset[i,]
      dataset.boot$acum.wHX040 <- cumsum(dataset.boot$wHX040)
      number.homes <- length(dataset.boot$acum.wHX040)
      number.individuals <- dataset.boot$acum.wHX040[number.homes]
      sum(dataset.boot[,edi]*dataset.boot[,ehhs]*dataset.boot[,hhcsw])/number.individuals
    }
    boot.mip <- boot::boot(dataset, statistic = mip2, R = rep,
                     sim = "ordinary", stype = "i")
    mip.ci <- boot::boot.ci(boot.mip, conf = ci, type = "basic")
    if(verbose == FALSE){
      return(mip.ci)
    }else{
      plot(boot.mip)
      summary(mip.ci)
      return(mip.ci)
    }
  }
}

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rtip documentation built on April 12, 2018, 5:04 p.m.