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]
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