données locales

Paru le : 21/02/2023

Full set of local data Municipality of La Machine (58151)

Detailed figures
Paru le :Paru le21/02/2023
- February 2023

Growth and structure of the population in 2019

Municipality of La Machine (58151)

POP T0 - Population estimates by age range

POP T0 - Population estimates by age range
2008 % 2013 % 2019 %
Altogether 3 549 100,0 3 435 100,0 3 240 100,0
0 to 14 years old 489 13,8 474 13,8 445 13,7
15 to 29 years old 436 12,3 391 11,4 352 10,9
30 to 44 years old 548 15,4 502 14,6 444 13,7
45 to 59 years old 807 22,7 707 20,6 618 19,1
60 to 74 years old 743 20,9 812 23,6 840 25,9
75 and over 526 14,8 549 16,0 541 16,7
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

POP G2 - Population estimates by age range

POP G2 - Population estimates by age range
2008 2013 2019
0 to 14 years old 13,8 13,8 13,7
15 to 29 years old 12,3 11,4 10,9
30 to 44 years old 15,4 14,6 13,7
45 to 59 years old 22,7 20,6 19,1
60 to 74 years old 20,9 23,6 25,9
75 and over 14,8 16,0 16,7
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

POP G2 - Population estimates by age range

  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

POP T1 - Population since 1968: population and average density (residents per square kilometre)

POP T1 - Population since 1968: population and average density (residents per square kilometre)
1968(*) 1975(*) 1982 1990 1999 2008 2013 2019
Population 5 749 4 999 4 627 4 192 3 735 3 549 3 435 3 240
Average density (inhab / km²) 320,3 278,5 257,8 233,5 208,1 197,7 191,4 180,5
  • (*) 1967 and 1974 for overseas departments (DOM)
  • The data proposed is established for the same geographical scope, in the geography in force on 01/01/2022.
  • Sources: Insee, RP1967 to 1999 counts, RP2008 to RP2019 main holdings.

POP T2M - Demographic indicators since 1968

POP T2M - Demographic indicators since 1968
1968 to 1975 1975 to 1982 1982 to 1990 1990 to 1999 1999 to 2008 2008 to 2013 2013 to 2019
Average annual change in population in % –2,0 –1,1 –1,2 –1,3 –0,6 –0,7 –1,0
due to the natural balance in % 0,1 –0,4 –0,8 –0,8 –0,8 –0,6 –0,7
due to the apparent balance of inflows and outflows in % –2,1 –0,7 –0,4 –0,5 0,2 –0,0 –0,3
Natality rate (‰) 14,3 10,9 7,9 7,4 8,3 8,7 6,2
Mortality rate (‰) 13,1 15,0 16,0 15,4 16,2 15,1 12,8
  • The data proposed is established for the same geographical scope, in the geography in force on 01/01/2022
  • Sources: Insee, RP1968 to 1999 counts, RP2008 to RP2019 main holdings - Civil status

POP T3 - Population by age and sex in 2019

POP T3 - Population by age and sex in 2019
Male % Female %
Altogether 1 552 100,0 1 688 100,0
0 to 14 years old 222 14,3 223 13,2
15 to 29 years old 185 11,9 167 9,9
30 to 44 years old 214 13,8 230 13,6
45 to 59 years old 309 19,9 309 18,3
60 to 74 years old 423 27,3 417 24,7
75 to 89 years old 185 11,9 290 17,2
90 years and over 14 0,9 52 3,1
0 to 19 years old 290 18,7 296 17,5
20 to 64 years old 801 51,6 764 45,3
65 and over 461 29,7 628 37,2
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

POP T4 - Home address 1 year before the study

POP T4 - Home address 1 year before the study
2013 % 2019 %
People one year old and over, previously living: 3 409 100,0 3 213 100,0
In the same house 3 086 90,5 2 952 91,9
In another house in the same town 129 3,8 94 2,9
In another town 193 5,7 167 5,2
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

POP G3 - Home address 1 year before for people living in another house, by age in %

POP G3 - Home address 1 year before for people living in another house, by age in %
In another house in the same town In another town
1 to 14 years old 35,4 64,6
15 to 24 years old 38,3 61,7
25 to 54 years old 37,5 62,5
55 years old and over 32,1 67,9
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

POP G3 - Home address 1 year before for people living in another house, by age in %

  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

POP T5 - Population aged 15 years and over by socioprofessional classification

POP T5 - Population aged 15 years and over by socioprofessional classification
2008 % 2013 % 2019 %
Altogether 3 066 100,0 2 939 100,0 2 830 100,0
Farmer operators 4 0,1 5 0,2 5 0,2
Craftsmen, traders, business leaders 52 1,7 56 1,9 65 2,3
Managers and higher intellectual professions 68 2,2 71 2,4 50 1,8
Middle-level occupations 208 6,8 171 5,8 165 5,8
Services employee 437 14,3 449 15,3 350 12,4
Blue-collar workers 545 17,8 419 14,2 390 13,8
Retirees 1 115 36,4 1 244 42,3 1 220 43,1
Other people with no professional activity 636 20,7 526 17,9 585 20,7
  • Sources: Insee, RP2008, RP2013 and RP2019, additional operations, geography as of 01/01/2022.

POP T6 - Population aged 15 years and over by sex, age and socioprofessional classification in 2019

POP T6 - Population aged 15 years and over by sex, age and socioprofessional classification in 2019
Male Female Share in % of the population aged
15 to 24 years old 25 to 54 years old 55 years and over
Altogether 1 340 1 490 100,0 100,0 100,0
Farmer operators 5 0 0,0 0,5 0,0
Craftsmen, traders, business leaders 45 20 0,0 4,0 1,5
Managers and higher intellectual professions 15 35 0,0 3,5 0,9
Middle-level occupations 85 80 0,0 12,5 2,4
Services employee 85 265 16,2 25,0 4,3
Blue-collar workers 300 90 13,5 32,5 2,4
Retirees 605 615 0,0 0,0 74,2
Other people without professional activity 200 385 70,3 22,0 14,3
  • Source: Insee, RP2019 additional operation, geography as of 01/01/2022.

Couples – Family – Households in 2019

Municipality of La Machine (58151)

FAM T1 - Households by composition

FAM T1 - Households by composition
Number of households Household population
2008 % 2013 % 2019 % 2008 2013 2019
Altogether 1 744 100,0 1 708 100,0 1 650 100,0 3 468 3 362 3 175
One-person households (male and female) 678 38,9 709 41,5 720 43,6 678 709 720
 Single Male 281 16,1 265 15,5 315 19,1 281 265 315
 Single Female 397 22,8 444 26,0 405 24,5 397 444 405
Other households without families 28 1,6 35 2,1 10 0,6 72 76 20
Family households: 1 038 59,5 964 56,4 920 55,8 2 719 2 577 2 435
 Couple with no children 577 33,1 550 32,2 540 32,7 1 163 1 135 1 100
 Couple with children 341 19,5 272 15,9 255 15,5 1 251 1 063 1 010
 Single parent 120 6,9 142 8,3 125 7,6 305 379 325
  • Sources: Insee, RP2008, RP2013 and RP2019, additional operations, geography as of 01/01/2022.

FAM G1 - Households’ size since 1968

FAM G1 - Households’ size since 1968
1968(*) 1975(*) 1982 1990 1999 2008 2013 2019
Average number of occupants per main residence 2,96 2,70 2,52 2,34 2,16 1,99 1,97 1,92
  • (*) 1967 and 1974 for the overseas departments (DOM)
  • The data proposed is established for the same geographical scope
  • in the geography in force on 01/01/2022.
  • Sources: Insee, RP1967 to 1999 counts RP2008 to RP2019 main holdings

FAM G1 - Households’ size since 1968

  • (*) 1967 and 1974 for the overseas departments (DOM)
  • The data proposed is established for the same geographical scope
  • in the geography in force on 01/01/2022.
  • Sources: Insee, RP1967 to 1999 counts RP2008 to RP2019 main holdings

FAM G2 - Share of people aged 15 years and over living alone, by age – household population

FAM G2 - Share of people aged 15 years and over living alone, by age – household population
en % 2008 2013 2019
15 to 19 years old 2,8 1,4 2,2
20 to 24 years old 14,4 11,8 11,5
25 to 39 years old 8,5 10,7 11,9
40 to 54 years old 17,1 16,3 19,4
55 to 64 years old 17,9 22,7 29,3
65 to 79 years old 28,7 31,9 30,4
80 and over 63,5 58,0 53,4
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FAM G2 - Share of people aged 15 years and over living alone, by age – household population

  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FAM G3 - Share of people aged 15 years and over living as a couple, by age

FAM G3 - Share of people aged 15 years and over living as a couple, by age
en % 2008 2013 2019
15 to 19 years old 5,0 3,5 3,5
20 to 24 years old 36,6 25,0 33,7
25 to 39 years old 69,5 67,2 66,9
40 to 54 years old 69,2 67,4 59,9
55 to 64 years old 76,6 70,3 64,0
65 to 79 years old 65,0 63,6 66,7
80 and over 31,1 35,0 41,1
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FAM G3 - Share of people aged 15 years and over living as a couple, by age

  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FAM G4 - Marital status of the population aged 15 years and over in 2019

FAM G4 - Marital status of the population aged 15 years and over in 2019
%
Married 44,7
Civil partnership 3,4
In cohabitation 10,2
Widowed 12,6
Divorced 7,0
Single 22,2
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

FAM G4 - Marital status of the population aged 15 years and over in 2019

  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

FAM T2 - Households by socioprofessional classification of the reference person in 2019

FAM T2 - Households by socioprofessional classification of the reference person in 2019
Number of households % Household population %
Altogether 1 650 100,0 3 175 100,0
Farmer operators 5 0,3 20 0,6
Craftsmen, traders, business leaders 45 2,7 90 2,8
Managers and higher intellectual professions 35 2,1 65 2,0
Middle-level occupations 100 6,1 270 8,5
Services employee 225 13,6 515 16,2
Blue-collar workers 255 15,5 670 21,1
Retirees 820 49,7 1 260 39,7
Other people with no professional activity 165 10,0 285 9,0
  • Sources: Insee, RP2019 additional operation, geography as of 01/01/2022.

FAM G5 - Households by socioprofessional classification of the reference person in 2019

FAM G5 - Households by socioprofessional classification of the reference person in 2019
%
Farmer operators 0,3
Handicrafters, traders, business leaders 2,7
Managers and higher intellectual professions 2,1
Middle-level occupations 6,1
Services employee 13,6
Blue-collar workers 15,5
Retirees 49,7
Unemployed persons 10,0
  • Sources: Insee, RP2019 additional operation, geography as of 01/01/2022.

FAM G5 - Households by socioprofessional classification of the reference person in 2019

  • Sources: Insee, RP2019 additional operation, geography as of 01/01/2022.

FAM T3 - Families by composition

FAM T3 - Families by composition
2008 % 2013 % 2019 %
Altogether 1 047 100,0 969 100,0 925 100,0
Couple with children 341 32,6 272 28,1 255 27,6
Single parent 128 12,3 142 14,6 130 14,1
Male single parent 16 1,5 30 3,1 25 2,7
Female single parent 112 10,7 111 11,5 105 11,4
Couple with no children 577 55,2 555 57,3 540 58,4
  • Sources: Insee, RP2008, RP2013 and RP2019, additional operations, geography as of 01/01/2022.

FAM T4 - Families by number of children under 25 years old

FAM T4 - Families by number of children under 25 years old
2008 % 2013 % 2019 %
Altogether 1 047 100,0 969 100,0 925 100,0
No children 650 62,1 616 63,6 615 66,5
1 child 217 20,7 131 13,6 125 13,5
2 children 128 12,3 171 17,6 130 14,1
3 children 32 3,1 35 3,7 40 4,3
4 children and over 20 1,9 15 1,6 15 1,6
  • Sources: Insee, RP2008, RP2013 and RP2019, additional operations, geography as of 01/01/2022.

Housing in 2019

Municipality of La Machine (58151)

LOG T1 - Number of dwellings by category since 1968

LOG T1 - Number of dwellings by category since 1968
1968(*) 1975(*) 1982 1990 1999 2008 2013 2019
Altogether 2 143 2 116 2 142 2 140 2 032 2 098 2 110 2 120
Main residences 1 940 1 850 1 833 1 768 1 699 1 747 1 707 1 640
Second homes 71 101 145 140 136 182 123 173
Vacant dwellings 132 165 164 232 197 169 281 307
  • (*) 1967 and 1974 for the overseas departments
  • Sources: Insee, RP1967 to 1999 counts, RP2008 to RP2019 main holdings.

LOG T2 - Types and categories of dwellings

LOG T2 - Types and categories of dwellings
2008 % 2013 % 2019 %
Altogether 2 098 100,0 2 110 100,0 2 120 100,0
Main residences 1 747 83,3 1 707 80,9 1 640 77,4
Second homes 182 8,7 123 5,8 173 8,2
Vacant dwellings 169 8,0 281 13,3 307 14,5
Houses 1 770 84,4 1 786 84,6 1 784 84,2
Flats 322 15,3 266 12,6 282 13,3
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

LOG T3 - Main residences by number of rooms

LOG T3 - Main residences by number of rooms
2008 % 2013 % 2019 %
Altogether 1 747 100,0 1 707 100,0 1 640 100,0
1 room 64 3,7 62 3,6 52 3,2
2 rooms 176 10,1 182 10,7 161 9,8
3 rooms 526 30,1 476 27,9 468 28,5
4 rooms 558 32,0 531 31,1 507 30,9
5 rooms and over 422 24,2 456 26,7 452 27,6
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

LOG T4 - Average number of rooms in main residences

LOG T4 - Average number of rooms in main residences
2008 2013 2019
All main residences 3,8 3,8 3,9
Houses 3,9 4,0 4,0
Flats 2,8 3,3 3,3
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

LOG G0 - Main residences by over-occupation (except one room dwellings occupied by one person)

LOG G0 - Main residences by over-occupation (except one room dwellings occupied by one person)
%
Over-occupied 1,6
Non-over-occupied 98,4
  • Source: Insee, RP2019 additional operation, geography as of 01/01/2022.

LOG G0 - Main residences by over-occupation (except one room dwellings occupied by one person)

  • Source: Insee, RP2019 additional operation, geography as of 01/01/2022.

LOG T5 - Main residences in 2019 by completion period

LOG T5 - Main residences in 2019 by completion period
Number %
Principal residences build before 2016 1 629 100,0
before 1919 352 21,6
from 1919 to 1945 401 24,6
from 1946 to 1970 318 19,5
from 1971 to 1990 438 26,9
from 1991 to 2005 75 4,6
from 2006 to 2015 45 2,8
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG G1 - Main residences in 2019 by completion period and housing category

LOG G1 - Main residences in 2019 by completion period and housing category
House Flat
before 1919 312 38
from 1919 to 1945 358 43
from 1946 to 1970 272 43
from 1971 to 1990 340 51
from 1991 to 2005 73 2
from 2006 to 2015 45 0
  • Main residences built before 2016.
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG G1 - Main residences in 2019 by completion period and housing category

  • Main residences built before 2016.
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG T6 - Main residence tenure in 2019

LOG T6 - Main residence tenure in 2019
Number of households Share of households in % Household population Average number of rooms
per dwelling per person
Altogether 1 640 100,0 3 155 3,9 2,0
Less than 2 years 129 7,9 287 3,8 1,7
From 2 to 4 years 217 13,2 472 3,6 1,7
From 5 to 9 years 253 15,4 525 3,7 1,8
10 years and over 1 041 63,5 1 871 4,0 2,2
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG G2 - Households by main residence tenure in 2019

LOG G2 - Households by main residence tenure in 2019
Share of households in%
Less than 2 years 7,9
From 2 to 4 years 13,2
From 5 to 9 years 15,4
From 10 to 19 years 21,6
From 20 to 29 years 10,4
30 years and over 31,5
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG G2 - Households by main residence tenure in 2019

  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

LOG T7 - Main residences by occupational status

LOG T7 - Main residences by occupational status
2008 2013 2019
Number % Number % Number % Number of persons Average moving in age in year (s)
Altogether 1 747 100,0 1 707 100,0 1 640 100,0 3 155 21,6
Homeowner 1 320 75,6 1 280 75,0 1 231 75,1 2 423 25,5
Tenant 410 23,5 396 23,2 387 23,6 692 9,3
(including social sector housing) 138 7,9 122 7,2 78 4,8 127 11,2
Housed for free 17 1,0 30 1,8 22 1,3 40 20,2
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

LOG T8M - Main residences by material comfort

LOG T8M - Main residences by material comfort
2008 % 2013 % 2019 %
Altogether 1 747 100,0 1 707 100,0 1 640 100,0
Bathroom including a shower or a bath 1 663 95,2 1 648 96,6 1 589 96,9
Collective central heating 83 4,8 116 6,8 84 5,1
Individual central heating 875 50,1 840 49,2 776 47,3
Individual electric heating 484 27,7 381 22,3 422 25,7
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

LOG T9 - Households’ automotive equipment

LOG T9 - Households’ automotive equipment
2008 % 2013 % 2019 %
Altogether 1 747 100,0 1 707 100,0 1 640 100,0
At least one parking spot 1 000 57,3 978 57,3 1 013 61,8
At least one car 1 303 74,6 1 310 76,8 1 271 77,5
1 car 838 48,0 829 48,6 808 49,3
2 cars and over 465 26,6 481 28,2 463 28,2
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

Education and training in 2019

Municipality of La Machine (58151)

FOR T1 - Enrollment by age and sex in 2019

FOR T1 - Enrollment by age and sex in 2019
Total Enrolled population Enrolled population in %
Altogether Male Female
2 to 5 years old 109 88 80,7 73,3 89,8
6 to 10 years old 169 165 97,6 98,9 96,1
11 to 14 years old 118 114 96,6 98,0 95,5
15 to 17 years old 96 85 88,5 84,4 92,2
18 to 24 years old 140 32 22,9 19,8 27,1
25 to 29 years old 116 0 0,0 0,0 0,0
30 years old and over 2 443 23 0,9 1,1 0,8
  • Source: Insee, RP2019 principal exploitation, geography at the 01/01/2022.

FOR G1 - Enrollment rate by age (in %)

FOR G1 - Enrollment rate by age (in %)
2008 2013 2019
2 to 5 years old 72,5 69,9 80,7
6 to 10 years old 96,3 92,7 97,6
11 to 14 years old 96,3 91,3 96,6
15 to 17 years old 94,8 91,9 88,5
18 to 24 years old 23,4 31,2 22,9
25 to 29 years old 3,1 3,1 0,0
30 years old and over 0,4 0,4 0,9
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FOR G1 - Enrollment rate by age (in %)

  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

FOR T2 - Highest level of education for population aged 15 years and over by sex in 2019

FOR T2 - Highest level of education for population aged 15 years and over by sex in 2019
Altogether Male Female
Proportion of unschooled aged 15 years or above 2 655 1 263 1 392
Proportion of graduates in percentage
No diploma or primary education certificate 35,5 31,5 39,2
BEPC brevet des collèges or DNB 6,0 4,8 7,1
CAP, BEP or equivalent 33,8 40,1 28,0
Baccalauréat, brevet professionnel or equivalent 14,5 14,7 14,4
2 years at university 5,5 5,0 6,0
3 to 4 years at university 3,1 2,4 3,7
5 years and over at university 1,6 1,4 1,7
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

FOR G2 - Highest level of education for not enrolled population aged 15 years and over (in %)

FOR G2 - Highest level of education for not enrolled population aged 15 years and over (in %)
2008 2019
No diploma or primary education certificate 47,0 35,5
BEPC brevet des collèges or DNB 6,4 6,0
CAP, BEP or equivalent 29,1 33,8
Baccalauréat, brevet professionnel or equivalent 10,7 14,5
2 years and over at university 6,8 10,1
  • Note: As the response methods have changed during the census surveys, the values cannot be obtained for the 2013 vintage.
  • Sources: Insee, RP2008, RP2019, main operations, geography as of 01/01/2022.

FOR G2 - Highest level of education for not enrolled population aged 15 years and over (in %)

  • Note: As the response methods have changed during the census surveys, the values cannot be obtained for the 2013 vintage.
  • Sources: Insee, RP2008, RP2019, main operations, geography as of 01/01/2022.

Labor force, employment and unemployment within the sense of the census in 2019

Municipality of La Machine (58151)

EMP T1 - Population aged 15 to 64 by economic activity status

EMP T1 - Population aged 15 to 64 by economic activity status
2008 2013 2019
Altogether 2 041 1 939 1 706
Labor force in % 61,5 61,1 62,0
 including people in work in % 51,3 50,3 52,2
 including unemployed workers in % 10,1 10,7 9,7
Economically inactive people in % 38,5 38,9 38,0
 including pupils, students or interns in % 5,3 5,9 5,9
 including retirees in % 15,5 15,2 13,2
 including other economically inactive people in % 17,8 17,7 19,0
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

EMP T2 - Economic activity and employment of the population aged 15 to 64 by sex and by age in 2019

EMP T2 - Economic activity and employment of the population aged 15 to 64 by sex and by age in 2019
Population Labor force Activity rate in % People in work Employment rate in %
Altogether 1 706 1 057 62,0 891 52,2
 15 to 24 years old 236 110 46,6 72 30,5
 25 to 54 years old 962 766 79,6 666 69,2
 55 to 64 years old 508 181 35,6 153 30,1
Male 869 561 64,6 476 54,8
 15 to 24 years old 126 68 54,0 46 36,5
 25 to 54 years old 473 400 84,6 348 73,6
 55 to 64 years old 270 93 34,4 82 30,4
Female 837 496 59,3 415 49,6
 15 to 24 years old 110 42 38,2 26 23,6
 25 to 54 years old 489 366 74,8 318 65,0
 55 to 64 years old 238 88 37,0 71 29,8
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

EMP G1 - Population aged 15 to 64 by economic activity status in 2019

EMP G1 - Population aged 15 to 64 by economic activity status in 2019
Population (%)
People in work 52,2
Unemployed workers 9,7
Retirees 13,2
Pupils, students or interns 5,9
Other economically inactive people 19,0
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

EMP G1 - Population aged 15 to 64 by economic activity status in 2019

  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

EMP T3 - Labor force aged 15 to 64 by socioprofessional classification

EMP T3 - Labor force aged 15 to 64 by socioprofessional classification
2008 including people in work 2013 including people in work 2019 including people in work
Altogether 1 315 1 127 1 165 989 1 020 850
including
 Farmer operators 4 4 0 0 5 5
 Handicrafters, traders and business leaders 52 52 56 56 60 60
 Managers and higher intellectual professions 68 64 66 66 45 45
 Middle-level occupations 208 184 166 156 165 140
 Services employee 437 365 449 363 335 305
 Blue-collar workers 545 457 413 349 385 295
  • Sources: Insee, RP2008, RP2013 and RP2019, additional operations, geography as of 01/01/2022.

EMP T4 - Unemployment of the 15-64 aged population

EMP T4 - Unemployment of the 15-64 aged population
2008 2013 2019
Number of unemployed workers 206 208 166
Unemployment rate in % 16,5 17,6 15,7
Unemployment of the 15-24 aged 35,5 43,6 34,5
Unemployment of the 25-54 aged 14,2 14,2 13,1
Unemployment of the 55-64 aged 13,2 16,5 15,5
  • Sources: Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

EMP G2 - Unemployment rate (within the sense of the census) of the 15-64 aged population by level of education in 2019

EMP G2 - Unemployment rate (within the sense of the census) of the 15-64 aged population by level of education in 2019
Unemployment rate in %
No diploma or primary education certificate 23,2
BEPC brevet des collèges or DNB 20,3
CAP, BEP or equivalent 16,4
Baccalauréat, brevet professionnel or equivalent 14,2
2 years at university 10,0
3 to 4 years at university 10,2
5 years and over at university 3,3
  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

EMP G2 - Unemployment rate (within the sense of the census) of the 15-64 aged population by level of education in 2019

  • Source: Insee, RP2019 main operation, geography as of 01/01/2022.

EMP T5 - Employment and activity

EMP T5 - Employment and activity
2008 2013 2019
Number of jobs in the area 807 695 646
People in work living in the area 1 051 987 908
Employment concentration indicator 76,8 70,4 71,1
Activity rate of 15 years old and over in % 41,1 40,4 38,5
  • The employment concentration indicator is equal to the number of jobs in the area per 100 people in work living in the area.
  • Sources: Insee, RP2008, RP2013 and RP2019, main holdings, place of residence and place of work, geography as of 01/01/2022.

EMP T6 - Employment by working status

EMP T6 - Employment by working status
2008 % 2013 % 2019 %
Altogether 807 100,0 695 100,0 646 100,0
Employee 711 88,1 601 86,5 553 85,6
 including women 353 43,8 344 49,5 298 46,2
 including part-time workers 149 18,5 154 22,2 122 18,9
Non-employee 96 11,9 94 13,5 93 14,4
 including women 19 2,4 24 3,5 37 5,7
 including part-time workers 9 1,1 7 1,0 13 2,0
  • Sources: Insee, RP2008, RP2013 and RP2019, main workplaces, geography as of 01/01/2022.

EMP T7 - Employment by socioprofessional activity in 2019

EMP T7 - Employment by socioprofessional activity in 2019
Number %
Altogether 555 100,0
Farmer operators 5 0,9
Handicrafters, traders, business leaders 75 13,5
Managers and higher intellectual professions 53 9,6
Middle-level occupations 91 16,3
Services employee 223 40,1
Blue-collar workers 109 19,6
  • Source: Insee, RP2019 additional operation at the workplace, geography as of 01/01/2022.

EMP G3 - Employment by socioprofessional activity

EMP G3 - Employment by socioprofessional activity
2008 2013 2019
Farmer operators 0,5 1,6 0,9
Handicrafters, traders, business leaders 7,3 8,7 13,5
Managers and higher intellectual professions 6,0 8,9 9,6
Middle-level occupations 15,3 16,2 16,3
Services employee 33,5 38,7 40,1
Blue-collar workers 37,5 25,9 19,6
  • Sources: Insee, RP2008, RP2013 and RP2019, additional work place of work, geography as of 01/01/2022.

EMP G3 - Employment by socioprofessional activity

  • Sources: Insee, RP2008, RP2013 and RP2019, additional work place of work, geography as of 01/01/2022.

EMP T8 - Employment by economic sectors

EMP T8 - Employment by economic sectors
2008 2013 2019
Number % Number % Number % including women in % including employees %
Altogether 868 100,0 646 100,0 555 100,0 55,1 84,7
Agriculture 12 1,4 10 1,6 10 1,8 0,0 50,0
Industry 281 32,3 191 29,6 149 26,8 13,4 79,9
Construction 80 9,2 41 6,4 35 6,3 28,8 42,7
Wholesale and retail trade/transports/accommodations and food service activities 167 19,3 142 22,0 75 13,5 46,6 60,1
Public administration/education/healthcare/social work 328 37,8 261 40,4 286 51,5 84,1 100,0
  • Sources: Insee, RP2008, RP2013 and RP2019, additional work place of work, geography as of 01/01/2022.

EMP G4 - Feminisation rate of employment by status and economic sectors in 2019

EMP G4 - Feminisation rate of employment by status and economic sectors in 2019
Employees Non-employees
Agriculture 0,0 0,0
Industry 8,4 33,3
Construction 33,3 25,4
Wholesale and retail trade, transports, accommodations and food service activities 55,5 33,3
Public administration, education, healthcare, social work 84,1
  • Source: Insee, RP2019 additional operation at the workplace, geography as of 01/01/2022.

EMP G4 - Feminisation rate of employment by status and economic sectors in 2019

  • Source: Insee, RP2019 additional operation at the workplace, geography as of 01/01/2022.

Characteristics of employment in the sense of the census in 2019

Municipality of La Machine (58151)

ACT T1 - Population aged 15 years or over having a job by status in 2019

ACT T1 - Population aged 15 years or over having a job by status in 2019
Number % of which% part-time of which% women
Altogether 908 100,0 17,4 46,8
Employees 815 89,8 17,4 47,1
Non-employees 93 10,2 17,2 44,1
  • Source : Insee, RP2019 main operation, geography as of 01/01/2022.

ACT T2 - Status and employment conditions of 15 years or over by sex in 2019

ACT T2 - Status and employment conditions of 15 years or over by sex in 2019
Male % Female %
Altogether 483 100 425 100
Employees 431 89,2 384 90,4
 Tenured personnel and open-ended employment contracts 351 72,7 314 73,9
 Fixed-term employment contracts 34 7,0 52 12,2
 Temporary employment 34 7,0 6 1,4
 Assisted jobs 3 0,6 6 1,4
 Apprentice ship contract - Traineeship 9 1,9 6 1,4
Non-employees 52 10,8 41 9,6
 Independents 27 5,6 25 5,9
 Employers 24 5,0 14 3,3
 Caregivers 1 0,2 2 0,5
  • Source : Insee, RP2019 main operation, geography as of 01/01/2022.

ACT T3 - Employees aged 15 to 64 by sex, age, and partial time jobs in 2019

ACT T3 - Employees aged 15 to 64 by sex, age, and partial time jobs in 2019
Male of which% part-time Female of which% part-time
Altogether 425 4,0 377 30,8
15 to 24 years old 44 9,1 24 37,5
25 to 54 years old 310 2,9 291 29,9
55 to 64 years old 71 5,6 62 32,3
  • Source : Insee, RP2019 main operation, geography as of 01/01/2022.

ACT G1 - Proportion of partial time employees aged 15 years or over by sex

ACT G1 - Proportion of partial time employees aged 15 years or over by sex
2008 2013 2019
Male 3,3 5,7 4,9
Female 32,4 34,5 31,5
  • Sources : Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

ACT G1 - Proportion of partial time employees aged 15 years or over by sex

  • Sources : Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

ACT T4 - Workplace of workers aged 15 years or over depending on their principal residence zones

ACT T4 - Workplace of workers aged 15 years or over depending on their principal residence zones
2008 % 2013 % 2019 %
Altogether 1 051 100 987 100 908 100
working :
in their residential zone 432 41,1 373 37,8 325 35,8
in another zone 618 58,9 614 62,2 583 64,2
  • Sources : Insee, RP2008, RP2013 and RP2019, main operations, geography as of 01/01/2022.

ACT G2 - Proportion of transports used to go to work in 2019

ACT G2 - Proportion of transports used to go to work in 2019
Percentage
None 4,2
Walking 5,4
Bicycle 0,4
Motorized two-wheeled vehicles 1,5
Car or truck 85,0
Public transports 3,4
  • Scope : workers aged 15 or over with a job.
  • Source : Insee, RP2019 main operation, geography as of 01/01/2022.

ACT G2 - Proportion of transports used to go to work in 2019

  • Scope : workers aged 15 or over with a job.
  • Source : Insee, RP2019 main operation, geography as of 01/01/2022.

Births and Deaths of people with usual residence in the area, 2014-2021

Municipality of La Machine (58151)

RFD G1 - Births and Deaths of people with usual residence in the area

RFD G1 - Births and Deaths of people with usual residence in the area
2014 2015 2016 2017 2018 2019 2020 2021
Domiciled deaths 39 43 45 46 39 65 51 58
Domiciled births 28 17 22 15 21 15 15 22
  • Source: Insee, civil status statistics in geography as of 01/01/2022.

RFD G1 - Births and Deaths of people with usual residence in the area

  • Source: Insee, civil status statistics in geography as of 01/01/2022.

Household income and poverty in 2020

Municipality of La Machine (58151)

REV T1 - Tax households in 2020

REV T1 - Tax households in 2020
2020
Number of tax households 1 610
Number of people in tax households 3 093
Median disposable income (per consumption unit in euros) 19 320
Share of actually taxed tax households (in %) 35
  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV G1 - Poverty rate by age range of the reference fiscal person in 2020

REV G1 - Poverty rate by age range of the reference fiscal person in 2020
Rate in %
Altogether 17
Less than 30 years old
30 to 39 years old
40 to 49 years old
50 to 59 years old
60 to 74 years old
75 and over
  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV G1 - Poverty rate by age range of the reference fiscal person in 2020

  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV G2 - Poverty rate by tenure of the reference fiscal person in 2020

REV G2 - Poverty rate by tenure of the reference fiscal person in 2020
Rate in %
Altogether 17
Homeowner 12
Tenant 37
  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV G2 - Poverty rate by tenure of the reference fiscal person in 2020

  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV T2 - Disposable income components in 2020

REV T2 - Disposable income components in 2020
share in %
Altogether 100,0
Work income 46,5
including wages 42,5
including unemployment pensions 2,6
including self-employed income 1,4
Retirement pension or annuity 49,7
Capital income (real estate, financial, others) 5,7
Social benefits 8,3
including child benefit 2,0
including income support 4,7
including housing benefit 1,6
Tax –10,2
  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

REV T3 - Disposable income distribution in 2020

REV T3 - Disposable income distribution in 2020
2020
Median disposable income (per consumption unit in euros) 19 320
Inter-decile ratio 2,5
1st decile (in euros) 11 250
9th decile (in euros) 28 630
  • Scope: tax households - excluding communities and homeless.
  • Source: Insee-DGFiP-Cnaf-Cnav-Ccmsa, Localised disposable income system (FiLoSoFi) in geography as of 01/01/2022.

Wages and work income in 2020

Municipality of La Machine (58151)

SAL G1 - Average net hourly wage (in euros) by socioprofessional category in 2020

SAL G1 - Average net hourly wage (in euros) by socioprofessional category in 2020
Altogether Female Male
Altogether 12,7 11,6 13,4
Managerial staff* 23,5 19,3 25,6
Middle-level occupations 15,8 13,7 17,0
Services employee 10,8 10,7 11,2
Blue-collar workers 12,0 11,3 12,1
  • * Managerial staff, higher intellectual professions and salaried business leaders.
  • Scope: Private sector and public enterprises excluding agriculture, socioprofessional activity
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL G1 - Average net hourly wage (in euros) by socioprofessional category in 2020

  • * Managerial staff, higher intellectual professions and salaried business leaders.
  • Scope: Private sector and public enterprises excluding agriculture, socioprofessional activity
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL G3 - Average net hourly wage (in euros) difference between male and female by socioprofessional category in 2020

SAL G3 - Average net hourly wage (in euros) difference between male and female by socioprofessional category in 2020
Difference (in %)
Altogether –13,1
Managerial staff* –24,9
Middle-level occupations –19,7
Services employee –3,9
Blue-collar workers –7,1
  • * Managerial staff, higher intellectual professions and salaried business leaders.
  • Scope: Private sector and public enterprises excluding agriculture, socioprofessional activity of the reference person's main position during the year.
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL G3 - Average net hourly wage (in euros) difference between male and female by socioprofessional category in 2020

  • * Managerial staff, higher intellectual professions and salaried business leaders.
  • Scope: Private sector and public enterprises excluding agriculture, socioprofessional activity of the reference person's main position during the year.
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL T1 - Average net hourly wage (in euros) by age in 2020

SAL T1 - Average net hourly wage (in euros) by age in 2020
Altogether Female Male
15 to 25 years old 11,0 10,6 11,2
26 to 50 years old 12,6 11,3 13,3
50 years old or over 13,4 12,3 14,1
  • Scope: Private sector and public enterprises excluding agriculture.
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL G4 - Average net hourly wage (in euros) difference between male and female by age in 2020

SAL G4 - Average net hourly wage (in euros) difference between male and female by age in 2020
Gender pay gap (in%)
15 to 25 years old –4,6
26 to 50 years old –15,0
50 years old and over –12,9
  • Scope: Private sector and public enterprises excluding agriculture.
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

SAL G4 - Average net hourly wage (in euros) difference between male and female by age in 2020

  • Scope: Private sector and public enterprises excluding agriculture.
  • Source: Insee, All employees database, file of employees at place of residence in geography as of 01/01/2022.

Business and establishment set-ups in 2021

Municipality of La Machine (58151)

DEN T1 - Business set-ups by sector of activity in 2021

DEN T1 - Business set-ups by sector of activity in 2021
Company set-ups Of which sole proprietorships
Number % Number %
Altogether 11 100,0 9 81,8
Industry 2 18,2 2 100,0
Construction 7 63,6 5 71,4
Wholesale and retail trade/transports/accommodations and food service activities 0 0,0 0
Information/communication 0 0,0 0
Finance and insurance activities 0 0,0 0
Real estate activities 0 0,0 0
Professional/scientific/technical activites/administrative and support service activities 1 9,1 1 100,0
Public administration/education/healthcare/social work 1 9,1 1 100,0
Other service activities 0 0,0 0
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography at 01/01/2022.

DEN G1 - Business set-ups

DEN G1 - Business set-ups
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Altogether 13 8 14 6 11 17 7 9 9 11
Sole proprietorship 13 8 14 5 11 10 6 9 5 9
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN G1 - Business set-ups

  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN T3 - Number of legal units by economic sector on the 31st of December 2020

DEN T3 - Number of legal units by economic sector on the 31st of December 2020
Number %
Altogether 129 100,0
Industry 12 9,3
Construction 20 15,5
Wholesale and retail trade/transports/accommodations and food service activities 49 38,0
Information/communication 3 2,3
Finance and insurance activities 4 3,1
Real estate activities 2 1,6
Professional/scientific/technical activites/administrative and support service activities 9 7,0
Public administration/education/human health/social work 15 11,6
Other service activities 15 11,6
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN T4 - Business set-ups by economic sectors in 2021

DEN T4 - Business set-ups by economic sectors in 2021
Altogether %
Altogether 15 100,0
Industry 2 13,3
Construction 7 46,7
Wholesale and retail trade/transports/accommodations and food service activities 2 13,3
Information/communication 0 0,0
Finance and insurance activities 0 0,0
Real estate activities 1 6,7
Professional/scientific/technical activites/administrative and support service activities 2 13,3
Public administration/education/healthcare/social work 1 6,7
Other service activities by the number of business creations including free lancers 0 0,0
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN G3 - Establishment set-ups

DEN G3 - Establishment set-ups
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Establishment set-ups 14 10 17 9 11 18 9 13 10 15
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN G3 - Establishment set-ups

  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

DEN T5 - Number of legal units by economic sector on the 31st of December 2020

DEN T5 - Number of legal units by economic sector on the 31st of December 2020
Number %
Altogether 153 100,0
Industry 15 9,8
Construction 20 13,1
Wholesale and retail trade/transports/accommodations and food service activities 56 36,6
Information/communication 3 2,0
Finance and insurance activities 8 5,2
Real estate activities 5 3,3
Professional/scientific/technical activites/administrative and support service activities 14 9,2
Public administration/education/human health/social work 17 11,1
Other service activities 15 9,8
  • Scope: market activities outside agriculture.
  • Source: Insee, Directory of companies and establishments (Sirene) in geography as of 01/01/2022.

Tourism in 2023

Municipality of La Machine (58151)

TOU T1 - Number and capacity of hotels on the 1st of January 2023

TOU T1 - Number and capacity of hotels on the 1st of January 2023
Hotels Rooms
Altogether 1 11
1 star 0 0
2 stars 0 0
3 stars 0 0
4 stars 0 0
5 stars 0 0
Non-ranked 1 11
  • Source: Insee, territorial partners in geography as of 01/01/2022.

TOU T2 - Number and capacity of campsites on the 1st of January 2023

TOU T2 - Number and capacity of campsites on the 1st of January 2023
Campsites Pitch
Altogether 1 10
1 star 0 0
2 stars 0 0
3 stars 0 0
4 stars 0 0
5 stars 0 0
Non-ranked 1 10
  • Source: Insee, territorial partners in geography as of 01/01/2022.

TOU T3 - Number of other tourist collective accommodations on the 1st of January 2023

TOU T3 - Number of other tourist collective accommodations on the 1st of January 2023
Accommodation Number of bed places (1)
Altogether 0 0
Tourist accommodations 0 0
Holiday villages or private homes 0 0
Youth hostels 0 0
  • (1) rooms, apartments, dormitories ...
  • Source: Insee, territorial partners in geography as of 01/01/2022.

Définitions

Declarative judgments of birth: Any birth occurring on French territory must be the subject of a declaration to the Civil register within three days of giving birth, giving rise to an act. If this declaration has not been made within this legal period, it is the subject of a declaration of birth giving rise to a transcription in the civil status registers.

Declarations of death: When death is insured but the body could not be found (plane crash, disappearance at sea ...), a declaratory judgment of death is drawn up which results in transcription on the civil status registers.

Tax household: Household made up of the grouping of tax households listed in the same dwelling. Its existence in a given year is due to the fact that at least an independent declaration of income coincides with the occupation of a dwelling known to the Housing Tax. Households made up of people who do not have their fiscal independence (mainly students) are counted in households where they declare their income even if they occupy independent accommodation.

Average hourly net salary: Result of the quotient of the mass of net wages compared to the number of salaried hours calculated on all the positions carried out by the employee during the year (excluding unemployment benefits). The number of paid hours takes into account paid overtime and all the periods during which the employee remains linked to an establishment due to the employment contract (leave, period of illness and accident at work), at the exception of periods of unpaid leave.

Market activity: The activity of a company is qualified as market if its operating expenses are normally covered for more than 50 % through the sale of its production. The activity of an establishment is market if this establishment contributes essentially to the production of a good or service considered to be market, either by nature or because its selling price exceeds 50 % of its production costs.

Public domain: An establishment belongs to this area if it is part of a legal category 7 enterprise (legal person or body subject to administrative law) or if more than half of its workforce is part of the State civil service.

The definitions of other concepts allowing a better understanding of the variables are accessible on insee.fr.

Champ

Population censuses

The data are offered to users in particular for comparing municipalities, grouping variable categories or obtaining results on personalized sets of municipalities.

Derived from calculations linked to sampling techniques, the data in terms of numbers are provided with several decimal places; these must be used for all calculations carried out, in order to avoid rounding errors.

For more information on the population census, consult the page of presentation of the population census.

The data come either from the main farm (princ.) or from the complementary farm (compl).

For more methodological information, you can consult the sheets "Tips on using census results".

These sheets present the characteristics of the population census and deal with their consequences on the use of the data. They specify in particular the changes affecting the main statistical variables and their comparability with previous censuses.

Civil register

Annual statistics concerning domiciled births are drawn up from the statistical bulletins of civil status, drawn up by the mayors, at the time and in the municipality where the births take place. They relate to births having taken place in all the municipalities of France. Births that took place abroad or in the overseas communities (COM) are not counted.

The "commune" variable corresponds to the commune of the mother's domicile in France.

The statistics include declarative judgments of birth, but do not take into account stillbirths.

Annual statistics concerning domiciled deaths are drawn up from civil status statistics bulletins drawn up by the mayors, at the time and in the municipality where the deaths took place. They relate to deaths that have occurred in all municipalities in France. Deaths having occurred abroad or in overseas communities (COM) are not counted.

The "commune" variable corresponds to the commune of the deceased's domicile in France.

The statistics include declarative judgments of deaths.

Localised disposable income system (FiLoSoFi)

The scope covered is that of all ordinary tax households: it excludes people who are homeless or living in institutions (prison, home, retirement home, etc.).

The share of taxed households is calculated on the basis of households whose declared income is positive or zero.

Other indicators are calculated on the basis of households with positive or zero disposable income.

Municipalities without inhabitant or without inhabitant subject to the housing tax are not in the list of municipalities.

All employees databases

The statistics are compiled from information collected on private sector companies and public companies located in France.

Statistics on socio-professional categories relate to the main position occupied by the employee during the year, excluding agriculture and undefined socio-professional category.

People whose age is not indicated and minors are also excluded from the statistical field.

Register of enterprises and establishments (REE)

The indicators relate to the number of businesses and legal units and the creation of businesses and establishments of all non-agricultural market activities. This field includes financial activities.

When a company has several establishments, it is located at its head office.

The number of companies or legal units in year N corresponds to the number of companies or legal units active on December 31, N-1.

The number of business or establishment creations corresponds to the number of businesses or establishments created during year N.

Pay and salaried employment localized file (Flores)

The Flores system (Pay and salaried employment localized file) covers establishments that have employed at least one employee during the year, in France excluding Mayotte. In this municipal database, the data made available is also restricted to establishments active at the end of the year (last week of December), which excludes establishments which ceased their activity during the year.

The salaried workforce at the end of the year corresponds to the number of positions present in the last week of December in the employing establishment. The workforce at the end of the year in some establishments may therefore be zero, if the employee (s) during the year were no longer employed at the end of December.

Flores covers all salaried employment, regardless of the sector of activity and the type of employer (public or private, including individual employers). Establishments under the Ministry of the Armed Forces (military personnel as well as civilians) are excluded from the scope.

The Flores device succeeds Clap, whose last vintage described the year 2015. The results from Flores and Clap are not comparable, and therefore should not be the subject of evolving comparative analyzes.

Specifically:

-Clap covered all active establishments, employers and non-employers. The number of establishments with zero staff at the end of the year was therefore much higher in Clap, because of this difference in field.

- Conversely, Clap only counted so-called non-ancillary jobs, that is to say those exceeding a certain threshold of remuneration and / or duration. This restriction has been removed in Flores, which counts all workstations.

Hotel occupancy survey

The scope covers tourist hotels, classified or not, with more than 5 bedrooms and campsites with more than 10 pitches, classified or not, including residential campsites. It also covers other collective tourist accommodation.

Statistics on the accommodation offer are established in conjunction with the regional tourism committees (CRT) and the general management of enterprises (DGE). They are offered at municipal level for France (excluding Mayotte).

The statistics concerning the outdoor hotel business relate to the campsites offering sites for transient customers intended for tourists who do not choose to live there as well. only on campsites offering pitches rented year-round, that is to say to a single customer for the entire period when the campsite is open.

Classified hotels and campsites are classified according to the new classification nomenclature implemented by the operator Atout France. The distribution by star is not available for the 2013 vintage for hotels, because the classification being paid, the distribution by star was not significant.

The information on other collective accommodation in the overseas departments is of lower quality. Since 2018, the field concerning other collective accommodation in the overseas departments has been deleted. The workforce from other collective accommodation has been transferred to hotels.

Géographie

Population censuses 2008, 2013, 2019: dissemination in the municipalities of France outside Mayotte in geography on 01/01/2022;

Vital statistics: distribution to all municipalities in France in geography as of 01/01/2022;

Localized social and fiscal file (Filosofi): dissemination in the municipalities of mainland France, Martinique and Reunion, in geography as of 01/01/2022;

All employees databases, file of employees at the place of residence: dissemination in the municipalities of France excluding Mayotte with more than 2,000 inhabitants, respecting specific thresholds, in geography as of 01/01/2022;

Localized Compensation and Employee Employment File (Flores): dissemination in the municipalities of France outside Mayotte, in geography as of 01/01/2022;

Directory of businesses and establishments (Sirene) - Business demography: distribution to all municipalities in France, in geography as of 01/01/2022;

Insee, territorial partners for tourism data: dissemination to all municipalities in France, geography as of 01/01/2022

Release threshold for the population census

The population census makes it possible to know the diversity and evolution of the population of France. Insee thus provides statistics on inhabitants and dwellings, their number and their characteristics: distribution by sex and age, occupations, housing conditions, modes of transport, commuting, etc.

Data from additional census holdings are not disseminated for areas less than 2 000 inhabitants. In addition, numbers below 200 should be handled with care, as it cannot be significant.

Particularity of Civil register data

The data, for the municipalities of Paris (75056), Lyon (69123) and Marseille (13055), are presented for the entire municipality and for each municipal district.

For these municipalities, the municipal district of the domicile is not systematically informed about the statistical bulletin. Births are therefore only counted in the database at the level of the municipality and not of the municipal district. The sum of births in the arrondissements of Lyon (Marseille and Paris respectively) is therefore not always equal to the number of births in the municipality of Lyon (Marseille and Paris respectively).

Dissemination threshold and statistical confidentiality of the Localized Social and Fiscal File (FiLoSoFi)

Data from FiLoSoFi are subject to statistical confidentiality. No statistics are disseminated on very small areas (less than 50 households and less than 100 people).

Three indicators (median standard of living, counts in number of households and number of people) are proposed for areas with more than 50 households or more than 100 people.

In the largest areas (more than 1,000 households or more than 2 000 people), all indicators are generally offered. They are also disseminated on the sub-populations associated with a socio-demographic criterion (for example under 30 years) having a minimum number of at least 200 people and at least 11 households.

Poverty rates are disseminated for areas with more than 1,000 households or more than 2 000 ppeople in which there are at least 200 people and 11 poor households, as well as at least 200 people and 11 households above the poverty line.

They are distributed to sub-populations associated with a socio-demographic criterion (for example under 30s) with a minimum workforce of at least 200 people. and at least 11 poor households and at least 200 people and at least 11 households above the poverty line.

When the rates are in the ranges [0; 5] and [95; 100], the exact value is not displayed, it is replaced by the values ​​5 % and 95 % respectively.

The components of disposable income are disseminated over areas over 1 000 households or more than 2 000 people, provided that for each of the income components there are at least 11 households for which the component is non-zero.

Statistical confidentiality of the Bases All employees

Data from the All Employees Bases are subject to statistical confidentiality. No statistics are released for areas less than 2 000 inhabitants. Moreover, each box in the table must contain at least 5 employees and no employee must represent more than 80 % of the box payroll. These constraints lead to excluding from the dissemination the results of certain areas of more than 2 000 inhabitants.

Warning on the nature of municipal data and their use for the localized file of remunerations and salaried employment (Flores)

INSEE makes localized data from Flores available to the municipal level. However, at this geographic scale, the results of this data warehouse have not been validated by experts. Each user is therefore called upon to exercise good judgment concerning the plausibility and relevance of the results, in particular in limited geographic or sectoral fields. As far as possible, the analyzes should focus on areas "of sufficient size" (several thousand salaried positions), in order to limit errors that could be due to occasional erroneous declarations by certain establishments.

Status of municipal data from Flores differs in particular from that of Employment Estimates, which are subject to full validation by experts and which are disseminated at a more aggregate level (department and employment area at the finest). In other words, the municipal data, in return for their finesse, do not benefit from the same validation and adjustment framework.