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
3152
Downloads
40
- 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
E.35 How much did the household spend on hired labor during ${agr_season}? (season_labor_cost)
Data file: agricultural_season.dta
Overview
Valid:
66
Invalid:
947
Minimum:
2000
Maximum:
175000
Type:
Discrete
Decimal:
0
Start:
329
End:
334
Width:
6
Range:
2000 - 175000
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 2000 | 2 |
3%
|
|
| 3000 | 2 |
3%
|
|
| 3500 | 1 |
1.5%
|
|
| 4000 | 2 |
3%
|
|
| 8000 | 1 |
1.5%
|
|
| 9000 | 1 |
1.5%
|
|
| 10000 | 2 |
3%
|
|
| 14000 | 1 |
1.5%
|
|
| 15000 | 4 |
6.1%
|
|
| 18000 | 1 |
1.5%
|
|
| 20000 | 7 |
10.6%
|
|
| 24000 | 3 |
4.5%
|
|
| 25000 | 3 |
4.5%
|
|
| 28000 | 1 |
1.5%
|
|
| 29000 | 1 |
1.5%
|
|
| 30000 | 7 |
10.6%
|
|
| 35000 | 2 |
3%
|
|
| 36000 | 1 |
1.5%
|
|
| 37000 | 1 |
1.5%
|
|
| 39000 | 1 |
1.5%
|
|
| 40000 | 4 |
6.1%
|
|
| 45000 | 3 |
4.5%
|
|
| 50000 | 5 |
7.6%
|
|
| 70000 | 1 |
1.5%
|
|
| 78000 | 1 |
1.5%
|
|
| 80000 | 2 |
3%
|
|
| 95000 | 1 |
1.5%
|
|
| 100000 | 2 |
3%
|
|
| 120000 | 2 |
3%
|
|
| 175000 | 1 |
1.5%
|
|
| Sysmiss | 947 |
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.