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    Home / Central Data Catalog / LSMS / TZA_2008-2014_NPS-UPD_V01_M / variable [F8]
lsms

National Panel Survey 2008-2015, Uniform Panel Dataset

Tanzania, 2008 - 2015
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Reference ID
TZA_2008-2014_NPS-UPD_v01_M
DOI
https://doi.org/10.48529/655c-x145
Producer(s)
National Bureau of Statistics
Collection(s)
Living Standards Measurement Study (LSMS)
Metadata
Documentation in PDF DDI/XML JSON
Created on
Nov 10, 2020
Last modified
Mar 17, 2021
Page views
142564
Downloads
5018
  • Study Description
  • Data Description
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  • Data files
  • upd4_hh_a.dta
  • upd4_hh_b.dta
  • upd4_hh_c.dta
  • upd4_hh_d.dta
  • upd4_hh_e.dta
  • upd4_hh_f.dta
  • upd4_hh_g.dta
  • upd4_hh_h.dta
  • upd4_hh_i1.dta
  • upd4_hh_i2.dta
  • upd4_hh_j1.dta
  • upd4_hh_j1_1.dta
  • upd4_hh_j1_2.dta
  • upd4_hh_j1_3.dta
  • upd4_hh_j1_4.dta
  • upd4_hh_j1_5.dta
  • upd4_hh_j1_6.dta
  • upd4_hh_j1_7.dta
  • upd4_hh_j3.dta
  • upd4_hh_j4.dta
  • upd4_hh_k.dta
  • upd4_hh_l.dta
  • upd4_hh_m.dta
  • upd4_hh_n.dta
  • upd4_hh_o1.dta
  • upd4_hh_o2.dta
  • upd4_hh_p.dta
  • upd4_hh_q1.dta
  • upd4_hh_q2.dta
  • upd4_hh_r.dta
  • upd4_hh_s.dta
  • upd4_hh_v.dta
  • upd4_hh_w1.dta
  • upd4_hh_w2.dta
  • upd4_hh_x1.dta
  • upd4_hh_x2.dta
  • upd4_hh_x3.dta
  • upd4_hh_y.dta
  • upd4_hh_z1.dta
  • upd4_hh_z2.dta
  • upd4_hh_z3.dta
  • UPD4_HH_J1_8.dta

What was the cause of this situation [3RD]? (hh_12_3)

Data file: upd4_hh_h.dta

Overview

Valid: 470
Invalid: 22652
Minimum: 1
Maximum: 10
Type: Discrete
Decimal: 0
Start: 156
End: 157
Width: 2
Range: 1 - 10
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 INADEQUATE HOUSEHOLD STOCKS DUE TO DROUGHT/POOR RAINS 33
7%
2 INADEQUATE HOUSEHOLD FOOD STOCKS DUE TO CROP PEST DAMAGE 3
0.6%
3 INADEQUATE HOUSEHOLD FOOD STOCKS DUE TO SMALL LAND SIZE 38
8.1%
4 INADEQUATE HOUSEHOLD FOOD STOCKS DUE TO LACK OF FARM INPUTS 43
9.1%
5 FOOD IN THE MARKET WAS VERY EXPENSIVE 83
17.7%
6 UNABLE TO REACH THE MARKET DUE TO HIGH TRANSPORTATION COSTS 5
1.1%
7 NO FOOD IN THE MARKET 12
2.6%
8 FLOODS/WATER LOGGING/HAILSTORM 8
1.7%
9 NO MONEY 166
35.3%
10 OTHER (SPECIFY) 79
16.8%
Sysmiss 22652
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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