Sex of main income earner [32_292_DF_DCCV_REDNETFAMFONTERED_5]

Updated on DBnomics on July 21, 2023 (8:11 AM)

Frequency [FREQ]
Territory [REF_AREA]
Indicator [DATA_TYPE]
Measure [MEASURE]
Including or not including imputed rents [IMPUTED_RENTS]
Households main income source [FAM_MAIN_INCOME_SOURCE]
Household number of components [NUMBER_HOUSEHOLD_COMP]
Household typology [HOUSEHOLD_TYPOLOGY]
Number of children [NUMB_OF_CHILDREN]
Number of elderly [NUMB_OF_ELDERLY]
Sex of main income earner [SEX_MAIN_PERCEPTOR]
Age of main income earner [AGE_MAIN_EARNIER]
Educational level of main income earner [EDU_LEV_MAIN_EARN]
Professional status of main income earner [LABPROF_STATUS_C_MAIN_EARNER]

Dataset has 136 series. Add search filters to narrow them.

Dimension codes and labels
[FREQ] Frequency
  • [A] annual
[REF_AREA] Territory
  • [IT] Italy
  • [ITC] Nord-ovest
  • [ITD] Nord-est
  • [ITE] Centro (I)
  • [ITF] Sud
  • [ITG] Isole
[DATA_TYPE] Indicator
  • [REDD_MEDIANO_FAM] annual median households income
  • [REDD_MEDIO_FAM] annual average households income
[MEASURE] Measure
  • [9] absolute values
[IMPUTED_RENTS] Including or not including imputed rents
  • [1] including imputed rents
  • [2] not including imputed rents
[FAM_MAIN_INCOME_SOURCE] Households main income source
  • [1] employee income
  • [2] self-employed income
  • [3] public transfers income
  • [4] other type
  • [9] total
[NUMBER_HOUSEHOLD_COMP] Household number of components
  • [99] total
[HOUSEHOLD_TYPOLOGY] Household typology
  • [99] total
[NUMB_OF_CHILDREN] Number of children
  • [9] total
[NUMB_OF_ELDERLY] Number of elderly
  • [9] total
[SEX_MAIN_PERCEPTOR] Sex of main income earner
  • [1] males
  • [2] females
  • [9] total
[AGE_MAIN_EARNIER] Age of main income earner
  • [TOTAL] total
[EDU_LEV_MAIN_EARN] Educational level of main income earner
  • [99] total
[LABPROF_STATUS_C_MAIN_EARNER] Professional status of main income earner
  • [99] total
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