R/get_tech_intensity.R

In altay-oz/WIODnet: Creates long tables from WIOD data and carry network calculations

#' Create a data frame for technology intensity.
#'
#' @description Create a data frame of technology intensity as defined
#'     by EUROSATAT for all NACE coded industries in WIOD files.
#'
#' @param yearly.raw yearly raw data from the downloaded zip such as WIOT2011_October16_ROW.RData
#'
#' @param isic parameter to be given for the aggregation of the industries.
#' 
#' @import dplyr
#'
#' @import magrittr
#'
#' @import stringr
#' 
getTechIntensity <- function(yearly.raw, isic) {

    ## get the industry and RNr code 
    industry.RNr <- yearly.raw %>% select(RNr, IndustryCode) %>% unique

    ## adding 57 to 61 the code Z. this is done to group them later
    ## 57 to 61 are final consumption
    ## we are using/keeping it for network score calculations.
    RNr <- c(57:61)
    IndustryCode <- "Z"
    df <- data.frame(RNr, IndustryCode, stringsAsFactors = FALSE)

    industry.RNr <- rbind(industry.RNr, df)

    if (isic == 1) {
        ## creating 1 digit industry code
        industry.RNr %<>% mutate(NewIndustryCode = ifelse(RNr < 62,
                                                         str_sub(IndustryCode,
                                                                 start = 1,
                                                                 end = 1),
                                                         IndustryCode)) %>%
            select(-IndustryCode)

    } else if (isic == 2) {
        ## changing the name of the manufacturing industry ISIC code into
        ## their technology intensity. Then we will aggregate according to
        ## their technology intensity.
        IndustryCode <- c("C10-C12","C13-C15","C16","C17","C18","C19","C20","C21","C22","C23","C24",
                          "C25","C26","C27","C28","C29","C30","C31_C32","C33")
        tech.type <- c("Low Tech","Low Tech","Low Tech",
                       "Low Tech","Low Tech",
                       "Medium-Low Tech","Medium-High Tech",
                       "High Tech","Medium-Low Tech",
                       "Medium-Low Tech","Medium-Low Tech",
                       "Medium-Low Tech","High Tech",
                       "Medium-High Tech","Medium-High Tech",
                       "Medium-High Tech","Medium-High Tech",
                       "Low Tech","Low Tech")
        man.table <- data.frame(IndustryCode, tech.type, stringsAsFactors = FALSE)

        industry.RNr  <- left_join(industry.RNr, man.table, by = "IndustryCode")

        industry.RNr %<>% mutate(IndustryCode = ifelse(!is.na(tech.type),
                                                       tech.type, IndustryCode)) %>%
            select(-tech.type)

        names(industry.RNr) <- c("RNr", "NewIndustryCode")
    } else if (isic == 0) {
        ## changing the column name, keeping all industries identical,
        ## there is no change in industry column 
        names(industry.RNr) <- c("RNr", "NewIndustryCode")
    }

     return(industry.RNr)
}