[TCRED-SALAIRES-REVENUS-SAM-SEX-CSP] Net average annual wage according to the socio-professional group and sex
Updated on DBnomics on August 18, 2022 (12:44 PM).
[FREQ] Frequency
- [A] Annual
[INDICATEUR] Indicator
- [SALAIRE_ANNUEL_MOYEN] Average annual wage
[NATURE] Nature
- [VALEUR_ABSOLUE] Absolute value
[METIER] Professions
- [4] Technicians and associate professionals
- [5] Employees
- [6] Manual workers
- [CCE] Managers, including employed business leaders
- [SO] Not applicable
[REF_AREA] Reference area
- [D01] 01 - Ain
- [D02] 02 - Aisne
- [D03] 03 - Allier
- [D04] 04 - Alpes-de-Haute-Provence
- [D05] 05 - Hautes-Alpes
- [D06] 06 - Alpes-Maritimes
- [D07] 07 - Ardèche
- [D08] 08 - Ardennes
- [D09] 09 - Ariège
- [D10] 10 - Aube
- [D11] 11 - Aude
- [D12] 12 - Aveyron
- [D13] 13 - Bouches-du-Rhône
- [D14] 14 - Calvados
- [D15] 15 - Cantal
- [D16] 16 - Charente
- [D17] 17 - Charente-Maritime
- [D18] 18 - Cher
- [D19] 19 - Corrèze
- [D21] 21 - Côte-d'Or
- [D22] 22 - Côtes-d'Armor
- [D23] 23 - Creuse
- [D24] 24 - Dordogne
- [D25] 25 - Doubs
- [D26] 26 - Drôme
- [D27] 27 - Eure
- [D28] 28 - Eure-et-Loir
- [D29] 29 - Finistère
- [D2A] 2A - Corse-du-Sud
- [D2B] 2B - Haute-Corse
- [D30] 30 - Gard
- [D31] 31 - Haute-Garonne
- [D32] 32 - Gers
- [D33] 33 - Gironde
- [D34] 34 - Hérault
- [D35] 35 - Ille-et-Vilaine
- [D36] 36 - Indre
- [D37] 37 - Indre-et-Loire
- [D38] 38 - Isère
- [D39] 39 - Jura
- [D40] 40 - Landes
- [D41] 41 - Loir-et-Cher
- [D42] 42 - Loire
- [D43] 43 - Haute-Loire
- [D44] 44 - Loire-Atlantique
- [D45] 45 - Loiret
- [D46] 46 - Lot
- [D47] 47 - Lot-et-Garonne
- [D48] 48 - Lozère
- [D49] 49 - Maine-et-Loire
- [D50] 50 - Manche
- [D51] 51 - Marne
- [D52] 52 - Haute-Marne
- [D53] 53 - Mayenne
- [D54] 54 - Meurthe-et-Moselle
- [D55] 55 - Meuse
- [D56] 56 - Morbihan
- [D57] 57 - Moselle
- [D58] 58 - Nièvre
- [D59] 59 - Nord
- [D60] 60 - Oise
- [D61] 61 - Orne
- [D62] 62 - Pas-de-Calais
- [D63] 63 - Puy-de-Dôme
- [D64] 64 - Pyrénées-Atlantiques
- [D65] 65 - Hautes-Pyrénées
- [D66] 66 - Pyrénées-Orientales
- [D67] 67 - Bas-Rhin
- [D68] 68 - Haut-Rhin
- [D69] 69 - Rhône
- [D70] 70 - Haute-Saône
- [D71] 71 - Saône-et-Loire
- [D72] 72 - Sarthe
- [D73] 73 - Savoie
- [D74] 74 - Haute-Savoie
- [D75] 75 - Paris
- [D76] 76 - Seine-Maritime
- [D77] 77 - Seine-et-Marne
- [D78] 78 - Yvelines
- [D79] 79 - Deux-Sèvres
- [D80] 80 - Somme
- [D81] 81 - Tarn
- [D82] 82 - Tarn-et-Garonne
- [D83] 83 - Var
- [D84] 84 - Vaucluse
- [D85] 85 - Vendée
- [D86] 86 - Vienne
- [D87] 87 - Haute-Vienne
- [D88] 88 - Vosges
- [D89] 89 - Yonne
- [D90] 90 - Territoire de Belfort
- [D91] 91 - Essonne
- [D92] 92 - Hauts-de-Seine
- [D93] 93 - Seine-Saint-Denis
- [D94] 94 - Val-de-Marne
- [D95] 95 - Val-d'Oise
- [D971] 971 - Guadeloupe
- [D972] 972 - Martinique
- [D973] 973 - French Guiana
- [D974] 974 - La Réunion
- [D976] 976 - Mayotte
- [FE] France
- [FM] Metropolitan France
- [F_H_IDF] Metropolitan France excluding Île-de-France
- [R11] Île-de-France
- [R24] Centre-Val de Loire
- [R27] Bourgogne-Franche-Comté
- [R28] Normandie
- [R32] Hauts-de-France
- [R44] Grand Est
- [R52] Pays de la Loire
- [R53] Bretagne
- [R75] Nouvelle-Aquitaine
- [R76] Occitanie
- [R84] Auvergne-Rhône-Alpes
- [R93] Provence-Alpes-Côte d'Azur
- [R94] Corse
[SEXE] Gender
- [0] All
- [1] Men
- [2] Women
- [SO] Not applicable
[UNIT_MEASURE] Unit
- [EUROS] euros
[CORRECTION] Correction
- [BRUT] Uncorrected
[SERIE_ARRETEE] Stopped series
- [FALSE] nO
- [TRUE] yes
Search filters
Frequency [FREQ] (1)
Indicator [INDICATEUR] (1)
Nature [NATURE] (1)
Professions [METIER] (5)
Reference area [REF_AREA] (117)
Gender [SEXE] (4)
Unit [UNIT_MEASURE] (1)
Correction [CORRECTION] (1)
Stopped series [SERIE_ARRETEE] (2)
This dataset has 819 series:
- from
- 2013=NA
- to
- 2019=28,915
- min:
- 27,776
- max:
- 28,915
- avg:
- 28,304.333
- σ:
- 468.625
- from
- 2013=NA
- to
- 2019=28,437
- min:
- 27,214
- max:
- 28,437
- avg:
- 27,775.667
- σ:
- 504.237
- from
- 2013=NA
- to
- 2019=27,516
- min:
- 26,456
- max:
- 27,516
- avg:
- 26,938.667
- σ:
- 437.89
- from
- 2013=NA
- to
- 2019=27,859
- min:
- 27,043
- max:
- 27,859
- avg:
- 27,360.667
- σ:
- 356.786
- from
- 2013=NA
- to
- 2019=26,879
- min:
- 25,585
- max:
- 26,879
- avg:
- 26,185.333
- σ:
- 532.38
- from
- 2013=NA
- to
- 2019=29,413
- min:
- 28,719
- max:
- 29,413
- avg:
- 29,045.333
- σ:
- 284.828
- from
- 2013=NA
- to
- 2019=27,959
- min:
- 27,003
- max:
- 27,959
- avg:
- 27,414
- σ:
- 401.623
- from
- 2013=NA
- to
- 2019=28,038
- min:
- 27,092
- max:
- 28,038
- avg:
- 27,563
- σ:
- 386.213
- from
- 2013=NA
- to
- 2019=27,119
- min:
- 26,075
- max:
- 27,119
- avg:
- 26,538
- σ:
- 434.302
- from
- 2013=NA
- to
- 2019=27,681
- min:
- 26,750
- max:
- 27,681
- avg:
- 27,195
- σ:
- 381.183
Series code | 2017 | 2018 | 2019 |
---|---|---|---|
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D01.SO.EUROS.BRUT.FALSE] | 27776 | 28222 | 28915 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D02.SO.EUROS.BRUT.FALSE] | 27214 | 27676 | 28437 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D03.SO.EUROS.BRUT.FALSE] | 26456 | 26844 | 27516 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D04.SO.EUROS.BRUT.FALSE] | 27043 | 27180 | 27859 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D05.SO.EUROS.BRUT.FALSE] | 25585 | 26092 | 26879 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D06.SO.EUROS.BRUT.FALSE] | 28719 | 29004 | 29413 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D07.SO.EUROS.BRUT.FALSE] | 27003 | 27280 | 27959 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D08.SO.EUROS.BRUT.FALSE] | 27092 | 27559 | 28038 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D09.SO.EUROS.BRUT.FALSE] | 26075 | 26420 | 27119 |
[A.SALAIRE_ANNUEL_MOYEN.VALEUR_ABSOLUE.4.D10.SO.EUROS.BRUT.FALSE] | 26750 | 27154 | 27681 |
Showing results 1 - 10 / 819