Harmonized Host and Refugee Labor Market Survey 2022
Ethiopia, 2022
Get Microdata
Reference ID
ETH_2022_HHR-LMS_v01_M
Producer(s)
Fafo Institute for Labor and Social Research
Metadata
Created on
Dec 17, 2024
Last modified
Dec 17, 2024
Page views
4602
Downloads
23
Please select the specific economic activity the person is engaged in (LM623)
Data file: eth_rsi_main_user_weights.sav
Overview
Valid:
1224
Invalid:
2677
Minimum:
11
Maximum:
710
Type:
Discrete
Decimal:
0
Start:
475
End:
477
Width:
3
Range:
11 - 710
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 11 | Farming own plot | 36 |
2.9%
|
| 12 | Farming another person’s plot for money | 5 |
0.4%
|
| 13 | Farming a shared plot | 0 |
0%
|
| 14 | Middleman for farming crops | 1 |
0.1%
|
| 15 | Animal/livestock husbandry/Fishing | 28 |
2.3%
|
| 21 | Hawking (not owning any shops) | 37 |
3%
|
| 22 | Stalls (no physical shop) | 45 |
3.7%
|
| 23 | Small shop | 102 |
8.3%
|
| 24 | Medium/Large shop | 70 |
5.7%
|
| 25 | Brokerage | 14 |
1.1%
|
| 26 | Selling firewood/ charcoal | 5 |
0.4%
|
| 27 | Online shop (and do not have a physical shop) | 3 |
0.2%
|
| 31 | Restaurant | 25 |
2%
|
| 32 | Bar/Cafe | 21 |
1.7%
|
| 33 | Fast-food stand | 29 |
2.4%
|
| 34 | Cooking for others/NGOs, catering | 18 |
1.5%
|
| 35 | Brewery | 5 |
0.4%
|
| 36 | Butchery | 4 |
0.3%
|
| 37 | Fishery | 0 |
0%
|
| 38 | Dairy | 4 |
0.3%
|
| 39 | Bakery | 7 |
0.6%
|
| 41 | Barber/Beauty/Hairsalon/henna tattoo | 26 |
2.1%
|
| 42 | Hair plaiting/beauty services (without shop) | 9 |
0.7%
|
| 43 | Nail art | 1 |
0.1%
|
| 51 | Cinema | 0 |
0%
|
| 52 | Music shop | 3 |
0.2%
|
| 53 | DVD shop | 0 |
0%
|
| 54 | Artist | 2 |
0.2%
|
| 55 | Gambling / Sport Pesa | 6 |
0.5%
|
| 61 | Tailoring | 32 |
2.6%
|
| 62 | Selling clothing/ textiles/ shoes/accessories | 26 |
2.1%
|
| 71 | Construction workers/Brick makers | 52 |
4.2%
|
| 72 | Cleaners/housemaid | 33 |
2.7%
|
| 73 | Security guards/watch-man | 11 |
0.9%
|
| 74 | Shoe-shining /repairing | 3 |
0.2%
|
| 75 | Doing HH chores for others | 9 |
0.7%
|
| 76 | Daily casual labour | 75 |
6.1%
|
| 77 | Porters | 13 |
1.1%
|
| 78 | Factory workers | 2 |
0.2%
|
| 79 | Garbage collection | 0 |
0%
|
| 81 | Electrician | 14 |
1.1%
|
| 82 | Plumber | 4 |
0.3%
|
| 83 | Carpenter | 7 |
0.6%
|
| 84 | Auto mechanic | 13 |
1.1%
|
| 85 | Bicycle mechanic | 0 |
0%
|
| 86 | General mechanic | 17 |
1.4%
|
| 87 | Carwash | 0 |
0%
|
| 88 | Craft-making | 22 |
1.8%
|
| 91 | Selling mobile phone credit | 0 |
0%
|
| 92 | Phone charging | 0 |
0%
|
| 93 | Internet cafe | 0 |
0%
|
| 94 | Computer-related services and programming | 12 |
1%
|
| 101 | Money transfer | 22 |
1.8%
|
| 102 | Forex bureau | 1 |
0.1%
|
| 103 | Money lender | 4 |
0.3%
|
| 104 | Gold/silver/Jewelry seller | 0 |
0%
|
| 111 | Photography shop | 0 |
0%
|
| 112 | Computer/Hardware | 3 |
0.2%
|
| 113 | Travel agency | 4 |
0.3%
|
| 121 | Bajaj/Boda-boda/tuk-tuk | 36 |
2.9%
|
| 122 | Taxi/mini-bus/Matatu | 53 |
4.3%
|
| 123 | Parking | 1 |
0.1%
|
| 124 | Commercial goods transportation | 26 |
2.1%
|
| 125 | Petro station | 2 |
0.2%
|
| 131 | Hotel /Guesthouse | 13 |
1.1%
|
| 141 | Teacher/School (elementary, secondary school, religious) | 40 |
3.3%
|
| 142 | Language instructor/Translator | 1 |
0.1%
|
| 143 | Professor/Lecturer (university level) | 2 |
0.2%
|
| 144 | Research assistant/Researcher | 2 |
0.2%
|
| 145 | Tutoring | 6 |
0.5%
|
| 151 | Pharmacy | 10 |
0.8%
|
| 152 | Doctors/Nurse | 21 |
1.7%
|
| 161 | Architect/ Lawyer/Engineer | 6 |
0.5%
|
| 162 | Office worker (clerk, bookkeeper…) | 23 |
1.9%
|
| 171 | Government/community official | 44 |
3.6%
|
| 172 | Utility (provision of electricity/water) | 1 |
0.1%
|
| 173 | Police officer/Military service | 7 |
0.6%
|
| 174 | Community worker/mobilization | 16 |
1.3%
|
| 175 | Paid community work | 13 |
1.1%
|
| 181 | Religion (priest, pastor, imam, evangelist) | 13 |
1.1%
|
| 310 | Milling | 1 |
0.1%
|
| 710 | Fetching water for money | 2 |
0.2%
|
| Sysmiss | 2677 |
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.