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    Home / Central Data Catalog / LSMS / ETH_2018_ESS_V03_M / variable [F47]
lsms

Socioeconomic Survey 2018-2019

Ethiopia, 2018 - 2019
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Reference ID
ETH_2018_ESS_v03_M
DOI
https://doi.org/10.48529/k739-c548
Producer(s)
Central Statistics Agency of Ethiopia
Collection(s)
Living Standards Measurement Study (LSMS) Fragility, Conflict and Violence
Metadata
Documentation in PDF DDI/XML JSON
Created on
Dec 18, 2020
Last modified
Feb 24, 2021
Page views
470908
Downloads
86169
  • Study Description
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  • Data files
  • sect_cover_hh_w4.dta
  • sect1_hh_w4.dta
  • sect2_hh_w4.dta
  • sect3_hh_w4.dta
  • sect4_hh_w4.dta
  • sect5a_hh_w4.dta
  • sect5b1_hh_w4.dta
  • sect5b2_hh_w4.dta
  • sect6a_hh_w4.dta
  • sect6b1_hh_w4.dta
  • sect6b2_hh_w4.dta
  • sect6b3_hh_w4.dta
  • sect6b4_hh_w4.dta
  • sect7a_hh_w4.dta
  • sect8_hh_w4.dta
  • sect9_hh_w4.dta
  • sect10a_hh_w4.dta
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  • sect10d1_hh_w4.dta
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  • sect11b1_hh_w4.dta
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  • sect12a_hh_w4.dta
  • sect12b1_hh_w4.dta
  • sect12b2_hh_w4.dta
  • sect14_hh_w4.dta
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  • sect_cover_ls_w4.dta
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  • sect8_2_ls_w4.dta
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  • sect_cover_ph_w4.dta
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  • sect10_ph_w4.dta
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  • sect_cover_pp_w4.dta
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  • sect2_pp_w4.dta
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  • sect4_pp_w4.dta
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  • sect7_pp_w4.dta
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  • sect01a_com_w4.dta
  • sect01b_com_w4.dta
  • sect02_com_w4.dta
  • sect03_com_w4.dta
  • sect04_com_w4.dta
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  • cons_agg_w4.dta
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  • sect10b_com_w4.dta
  • ETH_HouseholdGeovariables_Y4.dta
  • ETH_PlotGeovariables_Y4.dta
  • Crop_CF_Wave4.dta
  • ET_local_area_unit_conversion.dta
  • Food_CF_Wave4.dta
  • sect10a_com_w4.dta

33d.What is the crop code for the second harvest? (Crop #2 Code) (s3q33d)

Data file: sect3_pp_w4.dta

Overview

Valid: 142
Invalid: 19197
Minimum: 1
Maximum: 74
Type: Discrete
Decimal: 0
Start: 746
End: 748
Width: 3
Range: 1 - 74
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 1. BARLEY 4
2.8%
2 2. MAIZE 16
11.3%
3 3. MILLET 0
0%
4 4. OATS 8
5.6%
5 5. RICE 0
0%
6 6. SORGHUM 0
0%
7 7. TEFF 3
2.1%
8 8. WHEAT 0
0%
9 9. Mung Bean/ MASHO 0
0%
10 10. CASSAVA 0
0%
11 11. CHICK PEAS 20
14.1%
12 12. HARICOT BEANS 2
1.4%
13 13. HORSE BEANS 2
1.4%
14 14. LENTILS 4
2.8%
15 15. FIELD PEAS 1
0.7%
16 16. VETCH 28
19.7%
17 17. GIBTO 0
0%
18 18. SOYA BEANS 2
1.4%
19 19. RED KIDENY BEANS 7
4.9%
20 20. FENNEL 0
0%
21 21. CASTOR BEANS 0
0%
22 22. COTTON SEED 0
0%
23 23. LINESEED 0
0%
24 24. GROUND NUTS 0
0%
25 25. NUEG 0
0%
26 26. RAPE SEED 1
0.7%
27 27. SESAME 0
0%
28 28. SUNFLOWER 6
4.2%
29 29. MEGO 0
0%
30 30. SAVORY 0
0%
31 31. BLACK CUMIN 0
0%
32 32. BLACK PEPPER 0
0%
33 33. CARDAMON 0
0%
34 34. CHILIES 1
0.7%
35 35. CINNAMON 0
0%
36 36. FENUGREEK 2
1.4%
37 37. GINGER 0
0%
38 38. RED PEPPER 2
1.4%
39 39. TUMERIC 0
0%
40 40. WHITE LUMIN 0
0%
41 41. APPLES 0
0%
42 42. BANANAS 0
0%
43 43. GRAPES 0
0%
44 44. LEMONS 0
0%
45 45. MANDARINS 0
0%
46 46. MANGOS 1
0.7%
47 47. ORANGES 0
0%
48 48. PAPAYA 0
0%
49 49. PINAPPLES 0
0%
50 50. CITRON 0
0%
51 51. BEER ROOT 0
0%
52 52. CABBAGE 0
0%
53 53. CARROT 1
0.7%
54 54. CAULIFLOWER 0
0%
55 55. GARLIC 1
0.7%
56 56. KALE 6
4.2%
57 57. LETTUCE 1
0.7%
58 58. ONION 14
9.9%
59 59. GREEN PEPPER 0
0%
60 60. POTATOES 4
2.8%
61 61. PUMPKINS 0
0%
62 62. SWEET POTATO 0
0%
63 63. TOMATOES 1
0.7%
64 64. GODERE 0
0%
65 65. GUAVA 0
0%
66 66. PEACH 0
0%
67 67. MUSTARD 0
0%
68 68. FETO 0
0%
69 69. SPINACH 0
0%
70 70. GREEN BEANS 0
0%
71 71. CHAT 2
1.4%
72 72. COFFEE 1
0.7%
73 73. COTTON 0
0%
74 74. ENSET 1
0.7%
75 75. GESHO 0
0%
76 76. SUGAR CANE 0
0%
77 77. TEA 0
0%
78 78. TOBACCO 0
0%
79 79. CORIANDER 0
0%
80 80. SACRED BASIL 0
0%
81 81. RUE 0
0%
82 82. GISHITA 0
0%
83 83. WATERMELON 0
0%
84 84. AVOCADOS 0
0%
85 85. GRAZING LAND 0
0%
86 86. TEMPORARY GR 0
0%
97 97. PIJAPIN 0
0%
98 98. OTHER ROOT C 0
0%
99 99. OTHER LAND 0
0%
108 108. AMBOSHIKA 0
0%
110 110. GIRAMTA 0
0%
112 112. KAZMIR 0
0%
113 113. STRAWBERRY 0
0%
114 114. SHIFERAW 0
0%
115 115. OTHER FRUITS 0
0%
116 116. TIMIZ KIMEM 0
0%
117 117. OTHER SPICES 0
0%
118 118. OTHER PULSES 0
0%
119 119. OTHER OIL SEED 0
0%
120 120. OTHER CEREAL 0
0%
121 121. OTHER CASE CROPS 0
0%
123 123. OTHER VEGETABLE 0
0%
Sysmiss 19197
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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