Have a personal or library account? Click to login
The impact of loan accessibility on household welfare: An empirical analysis in Lesotho Cover

The impact of loan accessibility on household welfare: An empirical analysis in Lesotho

By: Mussa Deme and  Paikene Mangani  
Open Access
|Jun 2025

Figures & Tables

Figure 1:

Distribution of Covariates before and after matching
Both estimation methods (IPWRA and MDM) are consistent with the PSM method. The two techniques indicate that access to credit significantly increases household expenditure and income.
Distribution of Covariates before and after matching Both estimation methods (IPWRA and MDM) are consistent with the PSM method. The two techniques indicate that access to credit significantly increases household expenditure and income.

Impact of access to credit on expenditures

Outcomes VariableNearest neighbor MatchingCaliper MatchingKernel Matching
Transport Expenditure63.75***66.56***66.59***
Food Expenditure150.27***157.02***157.04***
Household income816.52***850.97***851.26***
Health Expenditure28.87***28.56***28.56***
Closing Expenditure36.68***37.68***37.68***
Education Expenditure50.88***52.06***52.06***
Rent Expenditure57.35***63.01***63.03***

Outcome Variables and Covariates

VariablesDescription
Outcome variables
Food expenditure(Amount of food expenses)
Transport expenditure(Amount of transport expenditure)
Household income(Household income)
Health expenditure(Amount of health expenditure)
Clothing expenditure(Amount of closing expenditure)
Education expenditure(Amount of education expenditure)
Rent Expenditure(Amount of rent expenditure)
Independent variable
Access to Credit=1 if a household has access to credit and =0 if no access to credit
Covariates
Hhage (years)Age of the respondent
HHsizeHousehold size
FemaleDummy (1= female and 0 =male)
EducatedDummy (1=primary school and above and 0 =not educated
SingleDummy (1= single and 0 =otherwise)
RuralDummy for the area (1=Rural and 0 =Urban)

Covariates Balance Check

Mean
Before matchingTreatedControlBias reduction (%)P-value
Female .41.40 0.000
Educated .86.87 0.000
Single .15.22 0.000
HHsize 4.073.86 0.011
Rural .59.63 0.078
HHage 49.6851.21 0.017
After matching
Female .41.4144.30.561
Educated .86.8691.20.938
Single .15.1484.10.340
HHsize 4.073.8696.90.886
Rural .59.6070.60.951
HHage 49.6850.1395.00.426

Summary Statistics

VariablesTreatment groupControl groupDifference
Treatment variable
Access to credit10
Outcomes variable
Transport Expenditure184.72113.9870.74
Food Expenditure644.12470.19173.93
Household income2324.871420.33904.54
Health Expenditure100.0471.4128.63
Closing Expenditure54.4715.9038.57
Education Expenditure86.7132.4654.25
Rent Expenditure131.7364.5467.19
Covariates
Rural.59.63-0.04
Hhage49.6851.21-1,53
Hhsize4.073.860,21
Female.41.400.01
Educatwed.86.87-0.01
Single.15.22-0.07
Observations1,8051,1942,999

Inverse Probability weighting regression adjustment estimation

Outcomes variableIPWRA estimationMDM estimation
Transport Expenditure64.39***56.28***
Food Expenditure 157.33*** 157.98***
Household income 844.77*** 785.08***
Health Expenditure27.21***25.37***
Closing Expenditure38.09***38.40***
Education Expenditure 51.78*** 36.64***
Rent Expenditure 60.62*** 43.91***
DOI: https://doi.org/10.2478/rsep-2025-0001 | Journal eISSN: 2547-9385 | Journal ISSN: 2149-9276
Language: English
Page range: 1 - 14
Submitted on: Feb 7, 2025
Accepted on: Mar 28, 2025
Published on: Jun 9, 2025
Published by: BC Group
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Mussa Deme, Paikene Mangani, published by BC Group
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.