[183_203_DF_DICA_ACDP_17] Age class, enterprise age class

Name: Age class, enterprise age class
Creator: DBnomics

Updated on DBnomics on March 31, 2023 (7:00 AM).

[FREQ] Frequency

[A] annual

[REF_AREA] Territory

[IT] Italy
[IT108] Monza e della Brianza
[IT109] Fermo
[IT110] Barletta-Andria-Trani
[IT111] Sud Sardegna
[ITC] Nord-ovest
[ITC1] Piemonte
[ITC11] Torino
[ITC12] Vercelli
[ITC13] Biella
[ITC14] Verbano-Cusio-Ossola
[ITC15] Novara
[ITC16] Cuneo
[ITC17] Asti
[ITC18] Alessandria
[ITC2] Valle d'Aosta / Vallée d'Aoste
[ITC20] Valle d'Aosta / Vallée d'Aoste
[ITC3] Liguria
[ITC31] Imperia
[ITC32] Savona
[ITC33] Genova
[ITC34] La Spezia
[ITC4] Lombardia
[ITC41] Varese
[ITC42] Como
[ITC43] Lecco
[ITC44] Sondrio
[ITC45] Milano
[ITC46] Bergamo
[ITC47] Brescia
[ITC48] Pavia
[ITC49] Lodi
[ITC4A] Cremona
[ITC4B] Mantova
[ITD] Nord-est
[ITD1] Provincia Autonoma Bolzano / Bozen
[ITD10] Bolzano / Bozen
[ITD2] Provincia Autonoma Trento
[ITD20] Trento
[ITD3] Veneto
[ITD31] Verona
[ITD32] Vicenza
[ITD33] Belluno
[ITD34] Treviso
[ITD35] Venezia
[ITD36] Padova
[ITD37] Rovigo
[ITD4] Friuli-Venezia Giulia
[ITD41] Pordenone
[ITD42] Udine
[ITD43] Gorizia
[ITD44] Trieste
[ITD5] Emilia-Romagna
[ITD51] Piacenza
[ITD52] Parma
[ITD53] Reggio nell'Emilia
[ITD54] Modena
[ITD55] Bologna
[ITD56] Ferrara
[ITD57] Ravenna
[ITD58] Forlì-Cesena
[ITD59] Rimini
[ITDA] Trentino Alto Adige / Südtirol
[ITE] Centro (I)
[ITE1] Toscana
[ITE11] Massa-Carrara
[ITE12] Lucca
[ITE13] Pistoia
[ITE14] Firenze
[ITE15] Prato
[ITE16] Livorno
[ITE17] Pisa
[ITE18] Arezzo
[ITE19] Siena
[ITE1A] Grosseto
[ITE2] Umbria
[ITE21] Perugia
[ITE22] Terni
[ITE3] Marche
[ITE31] Pesaro e Urbino
[ITE32] Ancona
[ITE33] Macerata
[ITE34] Ascoli Piceno
[ITE4] Lazio
[ITE41] Viterbo
[ITE42] Rieti
[ITE43] Roma
[ITE44] Latina
[ITE45] Frosinone
[ITF] Sud
[ITF1] Abruzzo
[ITF11] L'Aquila
[ITF12] Teramo
[ITF13] Pescara
[ITF14] Chieti
[ITF2] Molise
[ITF21] Isernia
[ITF22] Campobasso
[ITF3] Campania
[ITF31] Caserta
[ITF32] Benevento
[ITF33] Napoli
[ITF34] Avellino
[ITF35] Salerno
[ITF4] Puglia
[ITF41] Foggia
[ITF42] Bari
[ITF43] Taranto
[ITF44] Brindisi
[ITF45] Lecce
[ITF5] Basilicata
[ITF51] Potenza
[ITF52] Matera
[ITF6] Calabria
[ITF61] Cosenza
[ITF62] Crotone
[ITF63] Catanzaro
[ITF64] Vibo Valentia
[ITF65] Reggio di Calabria
[ITG] Isole
[ITG1] Sicilia
[ITG11] Trapani
[ITG12] Palermo
[ITG13] Messina
[ITG14] Agrigento
[ITG15] Caltanissetta
[ITG16] Enna
[ITG17] Catania
[ITG18] Ragusa
[ITG19] Siracusa
[ITG2] Sardegna
[ITG25] Sassari
[ITG26] Nuoro
[ITG27] Cagliari
[ITG28] Oristano
[ITG29] Olbia-Tempio
[ITG2A] Ogliastra
[ITG2B] Medio Campidano
[ITG2C] Carbonia-Iglesias

[DATA_TYPE] Indicator

[AENTEMPYAA] number of persons employees of the active enterprises (annual average values)
[AENTOUTWAA] number of outworkers of active enterprises (annual average values)
[AENTSEAA] number of self employers of the active enterprises (annual average values)
[AENTTEMPAA] number of temporary workers of active enterprises (annual average values)

[ECON_ACTIVITY_NACE_2007] Economic activity (NACE Rev. 2)

[0010] TOTAL

[PERS_EMPL_SIZE_CLASS] Size classes of persons employed

[TOTAL] total

[LEGAL_FORM] Legal form

[TOT] totale

[AGE_ENTERPRISE] Enterprise age

[TOTAL] total
[Y0-2] 0-2 years
[Y11-15] 11-15 years
[Y3-5] 3-5 years
[Y6-10] 6-10 years
[Y_GE16] 16 years and over

[SEX] Sex

[9] total

[AGE] Age

[NSP] no response
[Y15-29] 15-29 years
[Y30-49] 30-49 years
[Y_GE15] 15 years and over
[Y_GE50] 50 years and over

[COUNTRY_BIRTH] Country of birth

[WORLD] All countries of the world

Search filters

Frequency [FREQ] (1)

Territory [REF_AREA] (139)

Indicator [DATA_TYPE] (4)

Economic activity (NACE Rev. 2) [ECON_ACTIVITY_NACE_2007] (1)

Size classes of persons employed [PERS_EMPL_SIZE_CLASS] (1)

Legal form [LEGAL_FORM] (1)

Enterprise age [AGE_ENTERPRISE] (6)

Sex [SEX] (1)

Age [AGE] (5)

Country of birth [COUNTRY_BIRTH] (1)

This dataset has 14,740 series:

Trim NA Values

Series code	2012	2013	2014	2015	2016	2017
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y11-15.9.NSP.WORLD]	12427.4	13180.01	12594.76	16101.32	3085.75	4032.72
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y11-15.9.Y15-29.WORLD]	328947.44	303429.48	282277.1	256602.18	257332.04	234943.64
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y11-15.9.Y30-49.WORLD]	1049162.21	1014645.73	985789.39	910261.93	838616.23	745312.4
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y11-15.9.Y_GE15.WORLD]	1736808.32	1668841.81	1646146.43	1551938.7	1440774.85	1323086.04
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y11-15.9.Y_GE50.WORLD]	346271.27	337586.59	365485.18	368973.27	341740.83	338797.28
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y3-5.9.NSP.WORLD]	385.87	1912.23	NA	NA	33.22	31.49
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y3-5.9.Y15-29.WORLD]	273412.14	244536.1	214429.4	211491.19	204464.53	234668.49
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y3-5.9.Y30-49.WORLD]	667889.24	602485.79	527321.75	529788.83	509591.94	559600.53
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y3-5.9.Y_GE15.WORLD]	1147684.74	1042301.11	919694.92	930015.28	907183.53	1019922.68
[A.IT.AENTEMPYAA.0010.TOTAL.TOT.Y3-5.9.Y_GE50.WORLD]	205997.49	193366.99	177943.77	188735.26	193093.84	225622.17

Showing results 11 - 20 / 14,740