Marriage Transitions in Malawi 2007-2009, Panel Data
Malawi, 2007 - 2009
Get Microdata
Reference ID
MWI_2007-2009_MTM_v01_M
Producer(s)
Kathleen Beegle
Created on
Jun 05, 2019
Last modified
Jun 06, 2019
Page views
185225
Downloads
1066
- Data files
- hh2_cmty
- hh2_divorce
- hh2_mkts_foodprices
- hh2_mkts_hlthfac
- hh2_mkts_location
- hh2_mortality
- hh2_tf
- hh2_vct
- hh2p1_cs
- hh2p1_s1
- hh2p1_s2
- hh2p1_s3
- hh2p1_s4
- hh2p1_s5
- hh2p1_s6
- hh2p1_s7
- hh2p1_s8
- hh2p2_cs
- hh2p2_s9
- hh2p2_s10
- hh2p2_s11
- hh2p2_s12
- hh2p2_s13
- hh2p2_s13a
- hh2p2_s14
- hh2p3_cs
- hh2p3_s15
- hh2p3_s16
- hh2p3_s17
- hh2p3_s18
- hh2p3_s19
- hh2p3_s19a
- hh2p3_s20
- hh3_cmty
- hh3_health
- hh3_market_mids
- hh3_market_ms1
- hh3_mortality
- hh3_tf
- hh3_vct
- hh3p1_cs
- hh3p1_s1
- hh3p1_s2
- hh3p1_s3
- hh3p1_s4
- hh3p1_s4b
- hh3p1_s5
- hh3p1_s6
- hh3p1_s8
- hh3p2_cs
- hh3p2_s9
- hh3p2_s10
- hh3p2_s11
- hh3p2_s11b
- hh3p2_s12
- hh3p2_s12b
- hh3p2_s12c
- hh3p2_s13a
- hh3p2_s13b
- hh3p2_s13c
- hh3p2_s13c2
- hh3p2_s14
- hh3p3_cs
- hh3p3_s15
- hh3p3_s16
- hh3p3_s17
- hh3p3_s17b
- hh3p3_s18
- hh3p3_s18b
- hh3p3_s18c
- hh3p3_s19
- hh3p3_s19b
- hh3p3_s20
- mkts_foodprices
- mkts_hlthfac
- mkts_location
- p1_cs
- p1_s1
- p1_s2
- p1_s3
- p1_s4
- p1_s5
- p1_s6
- p1_s7
- p1_s8
- p2_cs
- p2_s9
- p2_s10
- p2_s11
- p2_s12
- p2_s13
- p2_s14
- p2_s14a
- p2_s15
- pi_cs
- pi_mortality
- pi_s1
- pi_s2
- pi_s3
- pi_s4
- pi_s5
- pi_s5a
- pi_s6
- pi_tf
- pi2_cs
- pi2_s1
- pi2_s2
- pi2_s3
- pi2_s3b
- pi2_s4
- pi2_s5
- pi2_s5a
- pi2_s6a
- pi2_s6b
- pi2_s7
- pi2_s7check
- pi2_tf
- ptrack_public
What would you say your partner does for work? (s13bq53a)
Data file: hh3p2_s13c
Overview
Valid:
531
Invalid:
750
Minimum:
10
Maximum:
97
Type:
Discrete
Decimal:
0
Start:
273
End:
274
Width:
2
Range:
10 - 99
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 10 | Field preparation | 9 |
1.7%
|
| 11 | Ridging | 0 |
0%
|
| 12 | Planting | 0 |
0%
|
| 13 | Transplanting/Supply | 0 |
0%
|
| 14 | Fertilizing/Manuring | 0 |
0%
|
| 15 | Weeding | 0 |
0%
|
| 16 | Harvest | 0 |
0%
|
| 17 | Animal care | 0 |
0%
|
| 18 | Gathering vegetables | 0 |
0%
|
| 19 | Agricultural - general | 44 |
8.3%
|
| 20 | Other operations (agriculture) | 0 |
0%
|
| 21 | Other operations (agriculture) | 0 |
0%
|
| 30 | Agricultural wage-labor (for cash) | 3 |
0.6%
|
| 31 | Agricultural wage-labor (in-kind labor) | 0 |
0%
|
| 32 | Group field labor | 0 |
0%
|
| 33 | Salaried employment | 34 |
6.4%
|
| 39 | Non-farm ganuy (day labor) | 12 |
2.3%
|
| 40 | Marketing work/sales | 19 |
3.6%
|
| 41 | Handicraft production | 2 |
0.4%
|
| 42 | Alcohol production | 0 |
0%
|
| 43 | Transporting goods | 0 |
0%
|
| 44 | Metal work | 1 |
0.2%
|
| 45 | Basket/mat weaving | 1 |
0.2%
|
| 46 | Carpentry | 0 |
0%
|
| 47 | Charcoal/firewood preparation | 0 |
0%
|
| 48 | Water collection for sale | 0 |
0%
|
| 49 | Other cash activity | 72 |
13.6%
|
| 50 | Making food/cooking | 81 |
15.3%
|
| 51 | Fetching water | 8 |
1.5%
|
| 52 | Fetching/splitting firewood | 3 |
0.6%
|
| 53 | Child care | 0 |
0%
|
| 54 | Washing clothes | 1 |
0.2%
|
| 55 | Repairing/building house/farm | 1 |
0.2%
|
| 56 | Cleaning inside/outside house | 18 |
3.4%
|
| 57 | Caring for an ill HH/family member | 0 |
0%
|
| 88 | Don't know | 0 |
0%
|
| 90 | Religious activities | 2 |
0.4%
|
| 91 | Attending a funeral | 0 |
0%
|
| 92 | Village help/community work | 0 |
0%
|
| 93 | Attending school/studying/school related work | 211 |
39.7%
|
| 94 | Political meeting | 0 |
0%
|
| 95 | Visiting with friends | 5 |
0.9%
|
| 96 | Resting/sleeping | 0 |
0%
|
| 97 | Other leisure activities | 4 |
0.8%
|
| 99 | Missing | 0 |
0%
|
| Sysmiss | 750 |
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.