Impact Evaluation of the Social Support for Resilient Households Project 2023-2024
Baseline
Malawi, 2023 - 2024
Get Microdata
Reference ID
MWI_2023-2024_SSRLPIE-BL_v01_M
Producer(s)
Emily Beam, Benedetta Lerva
Created on
Feb 19, 2025
Last modified
Feb 19, 2025
Page views
65573
Downloads
448
- Data files
- sslrp_baseline.dta
- hh_roster.dta
- demographics.dta
- migration.dta
- education_roster.dta
- health_roster.dta
- asset_list.dta
- labour_roster.dta
- agricultural_season.dta
- agr_act_hhmbr.dta
- livestock.dta
- lvtk_product_sales.dta
- livestock_raising_member.dta
- nfe_roster.dta
- nfe_purch_assets.dta
- nfe_sold_assets.dta
- nfe_hh_roster.dta
- oth_income.dta
- food_consumption.dta
- nonfood_consumption_week.dta
- nonfood_consumption_month.dta
- nonfood_consumption_three_month.dta
- nonfood_consumption_year.dta
- food_security.dta
- saving_account.dta
- financial_vlsa.dta
- outstanding_loans.dta
- financial_loan.dta
- financial_insurance.dta
- perm_crops.dta
- seasonal_crops.dta
- seasonal_lab_agr_act.dta
- sslrp_baseline_e2.dta
- hh_roster.dta
- demographics.dta
- migration.dta
- education_roster.dta
- health_roster.dta
- asset_list.dta
- labour_roster.dta
- perm_crops.dta
- seasonal_crops.dta
- agricultural_season.dta
- seasonal_lab_agr_act.dta
- agr_act_hhmbr.dta
- livestock.dta
- lvtk_product_sales.dta
- livestock_raising_member.dta
- nfe_roster.dta
- nfe_purch_assets.dta
- nfe_sold_assets.dta
- nfe_hh_roster.dta
- oth_income.dta
- food_consumption.dta
- nonfood_consumption_week.dta
- nonfood_consumption_month.dta
- nonfood_consumption_three_month.dta
- nonfood_consumption_year.dta
- food_security.dta
- saving_account.dta
- financial_vlsa.dta
- outstanding_loans.dta
- financial_loan.dta
- financial_insurance.dta
B.32 How many days was ${health_name} sick or injured over the past 30 days? (health_sick_days)
Data file: health_roster.dta
Overview
Valid:
7426
Invalid:
12475
Minimum:
1
Maximum:
30
Type:
Discrete
Decimal:
0
Start:
267
End:
268
Width:
2
Range:
1 - 30
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 1 | 193 |
2.6%
|
|
| 2 | 646 |
8.7%
|
|
| 3 | 1356 |
18.3%
|
|
| 4 | 778 |
10.5%
|
|
| 5 | 402 |
5.4%
|
|
| 6 | 121 |
1.6%
|
|
| 7 | 2145 |
28.9%
|
|
| 8 | 58 |
0.8%
|
|
| 9 | 30 |
0.4%
|
|
| 10 | 78 |
1.1%
|
|
| 11 | 11 |
0.1%
|
|
| 12 | 25 |
0.3%
|
|
| 13 | 7 |
0.1%
|
|
| 14 | 650 |
8.8%
|
|
| 15 | 31 |
0.4%
|
|
| 16 | 6 |
0.1%
|
|
| 17 | 6 |
0.1%
|
|
| 18 | 6 |
0.1%
|
|
| 19 | 2 |
0%
|
|
| 20 | 51 |
0.7%
|
|
| 21 | 172 |
2.3%
|
|
| 23 | 1 |
0%
|
|
| 24 | 11 |
0.1%
|
|
| 25 | 18 |
0.2%
|
|
| 26 | 1 |
0%
|
|
| 27 | 6 |
0.1%
|
|
| 28 | 9 |
0.1%
|
|
| 29 | 6 |
0.1%
|
|
| 30 | 600 |
8.1%
|
|
| Sysmiss | 12475 |
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.