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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-CENSUS / TZA_2002-2003_ASCS_V01_EN_M_V01_A_OCS / variable [V908]
Agricultural-Census

Agriculture Sample Census Survey 2002-2003

United Republic of Tanzania, 2004
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Reference ID
TZA_2002-2003_ASCS_v01_EN_M_v01_A_OCS
Producer(s)
National Bureau of Statistics, Office of Chief Government Statistician-Zanzibar
Collections
Agricultural Censuses
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 24, 2019
Last modified
Oct 24, 2019
Page views
114758
Downloads
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  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • annual crop and
    vegetable
    production-long
    rainy
    seasonR072
  • annual crop and
    vegetable
    production-short
    rainy
    seasonR071
  • Cattle diseases
    R185
  • Cattle intake
    R183
  • Cattle offtake
    R184
  • Cattle
    population,
    intake and
    offtake R182
  • crop extension
    messages R152
  • crop extension
    services R151
  • crop storage
    R092
  • permanentperennial
    crops and fruit
    tree production
    R073
  • Goat diseases
    R195
  • Goat intake
    during 20022003
    R193
  • Goat offtake
    R194
  • Goat
    population,
    intake and
    offtake R192
  • Goat
    population,
    intake and
    offtake R092_1
  • Goat
    population,
    intake and
    offtakeR092_1
  • Livestock
    extension R291
  • Livestock
    extension
    service
    providers R292
  • Livestock Pest
    and Parasite
    control R220
  • Livestock
    product R250
  • marketing
    problem R102
  • marketing
    problem R103
  • Milk production
    R186
  • Milk production
    R196
  • access and use
    of resources
    R061
  • access to farm
    inputs and
    implements R121
  • access to
    functional
    Livestock
    StructuresaccessoriesR270
  • activities of
    the
    householdR022
  • Agroprocessing
    and
    by-productsR082
  • Animal
    contribution to
    crop production
    R171
  • Chicken
    diseases R240
  • credit for
    Agriculture
    purposesR13_1
  • erosion
    controlwater
    harvesting
    facilities R112
  • farm implements
    and assets used
    and owned by
    the household
    during
    2002-2003 R122
  • Fish farming
    R282
  • household
    information
    R031
  • Household
    information,
    Agriculture
    activities,
    Livestock
    informationR00
  • labour use R311
  • land
    accessownershiptenure
    R041
  • land use R051
  • livelihood
    constraints
    R162
  • livelihood
    constraintsR161
  • other Livestock
    R230
  • outlets for the
    sale of
    Livestock R260
  • related to
    respondent and
    household head
    R122_00
  • tree
    farmingagroforestry
    R142
  • use of
    secondary
    products R076
  • Pig
    diseasespestsconditions
    R215
  • Pig increase
    R213
  • Pig offtake
    R214
  • Pig population
    and production
    R212
  • Sheep diseases
    R205
  • Sheep intake
    R203
  • Sheep offtake
    R204
  • Sheep
    population,
    intake and
    offtake R202
  • R321
  • R331
  • R332
  • use of credit
    for agriculture
    purposes R130
  • use of credit
    for agriculture
    purposes R131
  • use of credit
    for agriculture
    purposes R132

District (District)

Data file: crop extension messages R152

Overview

Valid: 253521
Invalid: 0
Type: Discrete
Width: 3
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
011 Kondoa 1691
0.7%
012 Mpwapwa 1980
0.8%
013 Kongwa 3405
1.3%
014 Dodoma Rural 3553
1.4%
015 Dodoma Urban 3180
1.3%
021 Monduli 1513
0.6%
022 Arumeru 2457
1%
023 Arusha 555
0.2%
024 Karatu 1215
0.5%
025 Ngorongoro 600
0.2%
031 Rombo 3570
1.4%
032 Mwanga 3265
1.3%
033 Same 3225
1.3%
034 Moshi Rural 6480
2.6%
035 Hai 3530
1.4%
036 Moshi Urban 0
0%
041 Lushoto 4372
1.7%
042 Korogwe 5640
2.2%
043 Muheza 3938
1.6%
044 Tanga 690
0.3%
045 Pangani 2039
0.8%
046 Handeni 1485
0.6%
047 Kilindi 1650
0.7%
051 Kilosa 1860
0.7%
052 Morogoro Rural 870
0.3%
053 Kilombero 1881
0.7%
054 Ulanga 2250
0.9%
055 Morogoro Urban 583
0.2%
056 Mvomero 2145
0.8%
061 Bagamoyo 1973
0.8%
062 Kibaha 2625
1%
063 Kisarawe 3720
1.5%
064 Mkuranga 1845
0.7%
065 Rufiji 1485
0.6%
066 Mafia 210
0.1%
071 Kinondoni 2354
0.9%
072 Ilala 1455
0.6%
073 Temeke 3690
1.5%
081 Kilwa 1260
0.5%
082 Lindi Rural 1050
0.4%
083 Nachingwea 720
0.3%
084 Liwale 1305
0.5%
085 Ruangwa 1170
0.5%
086 Lindi Urban 375
0.1%
091 Mtwara Rural 1338
0.5%
092 Newala 525
0.2%
093 Masasi 1635
0.6%
094 Tandahimba 1620
0.6%
095 Mtwara Urban 165
0.1%
101 Tunduru 2010
0.8%
102 Songea Rural 1424
0.6%
103 Mbinga 3150
1.2%
104 Songea Urban 1545
0.6%
105 Namtumbo 3326
1.3%
111 Iringa Rural 5279
2.1%
112 Mufindi 1845
0.7%
113 Makete 7341
2.9%
114 Njombe 3104
1.2%
115 Ludewa 2658
1%
116 Iringa Urban 765
0.3%
117 Kilolo 5121
2%
121 Chunya 5565
2.2%
122 Mbeya Rural 4575
1.8%
123 Kyela 480
0.2%
124 Rungwe 2595
1%
125 Ileje 2099
0.8%
126 Mbozi' 3540
1.4%
127 Mbarali 750
0.3%
128 Mbeya Urban 4095
1.6%
131 Iramba 4769
1.9%
132 Singida Rural 3315
1.3%
133 Manyoni 2010
0.8%
134 Singida Urban 1500
0.6%
141 Nzega 1632
0.6%
142 Igunga 1155
0.5%
143 Uyui 1770
0.7%
144 Urambo 1710
0.7%
145 Sikonge 1601
0.6%
146 Tabora Urban 4350
1.7%
151 Mpanda 1290
0.5%
152 Sumbawanga Rural 1770
0.7%
153 Nkansi 360
0.1%
154 Sumbawanga Urban 885
0.3%
161 Kibondo 2895
1.1%
162 Kasulu 2835
1.1%
163 Kigoma Rural 5340
2.1%
164 Kigoma Urban 1065
0.4%
171 Bariadi 1440
0.6%
172 Maswa 345
0.1%
173 Shinyanga Rural 1860
0.7%
174 Kahama 3209
1.3%
175 Bukombe 921
0.4%
176 Meatu 2790
1.1%
177 Shinyanga Urban 1665
0.7%
178 Kishapu 3420
1.3%
181 Karagwe 195
0.1%
182 Bukoba Rural 3060
1.2%
183 Muleba 1928
0.8%
184 Biharamulo 990
0.4%
185 Ngara 690
0.3%
186 Bukoba Urban 825
0.3%
191 Ukerewe 1349
0.5%
192 Magu 2607
1%
193 Nyamagana 0
0%
194 Kwimba 1230
0.5%
195 Sengerema 1005
0.4%
196 Geita 660
0.3%
197 Misungwi 1470
0.6%
198 Ilemela 2669
1.1%
201 Tarime 1635
0.6%
202 Serengeti 1362
0.5%
203 Musoma Rural 3165
1.2%
204 Bunda 3630
1.4%
205 Musoma Urban 165
0.1%
211 Babati 1845
0.7%
212 Hanang 1845
0.7%
213 Mbulu 870
0.3%
214 Simanjiro 1845
0.7%
215 Kiteto 1170
0.5%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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