The impact of loan accessibility on household welfare: An empirical analysis in Lesotho
Mussa Deme
Graduate School of Social Sciences and Humanities, International Economics Development Program, Hiroshima UniversityJapan
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und Paikene Mangani
Graduate School of Innovation and Practice for Smart Society, Hiroshima UniversityJapan
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09. Juni 2025
Über diesen Artikel
Artikel-Kategorie: Research Papers
Online veröffentlicht: 09. Juni 2025
Seitenbereich: 1 - 14
Eingereicht: 07. Feb. 2025
Akzeptiert: 28. März 2025
DOI: https://doi.org/10.2478/rsep-2025-0001
Schlüsselwörter
© 2025 Mussa Deme et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1:
Impact of access to credit on expenditures
| Outcomes Variable | Nearest neighbor Matching | Caliper Matching | Kernel Matching |
|---|---|---|---|
| Transport Expenditure | 63.75*** | 66.56*** | 66.59*** |
| Food Expenditure | 150.27*** | 157.02*** | 157.04*** |
| Household income | 816.52*** | 850.97*** | 851.26*** |
| Health Expenditure | 28.87*** | 28.56*** | 28.56*** |
| Closing Expenditure | 36.68*** | 37.68*** | 37.68*** |
| Education Expenditure | 50.88*** | 52.06*** | 52.06*** |
| Rent Expenditure | 57.35*** | 63.01*** | 63.03*** |
Outcome Variables and Covariates
| Variables | Description |
|---|---|
| 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) |
| Access to Credit | =1 if a household has access to credit and =0 if no access to credit |
| Hhage (years) | Age of the respondent |
| HHsize | Household size |
| Female | Dummy (1= female and 0 =male) |
| Educated | Dummy (1=primary school and above and 0 =not educated |
| Single | Dummy (1= single and 0 =otherwise) |
| Rural | Dummy for the area (1=Rural and 0 =Urban) |
Covariates Balance Check
| Mean | |||||
|---|---|---|---|---|---|
| Before matching | Treated | Control | Bias reduction (%) | P-value | |
| Female | .41 | .40 | 0.000 | ||
| Educated | .86 | .87 | 0.000 | ||
| Single | .15 | .22 | 0.000 | ||
| HHsize | 4.07 | 3.86 | 0.011 | ||
| Rural | .59 | .63 | 0.078 | ||
| HHage | 49.68 | 51.21 | 0.017 | ||
| Female | .41 | .41 | 44.3 | 0.561 | |
| Educated | .86 | .86 | 91.2 | 0.938 | |
| Single | .15 | .14 | 84.1 | 0.340 | |
| HHsize | 4.07 | 3.86 | 96.9 | 0.886 | |
| Rural | .59 | .60 | 70.6 | 0.951 | |
| HHage | 49.68 | 50.13 | 95.0 | 0.426 | |
Summary Statistics
| Variables | Treatment group | Control group | Difference |
|---|---|---|---|
| Access to credit | 1 | 0 | |
| Transport Expenditure | 184.72 | 113.98 | 70.74 |
| Food Expenditure | 644.12 | 470.19 | 173.93 |
| Household income | 2324.87 | 1420.33 | 904.54 |
| Health Expenditure | 100.04 | 71.41 | 28.63 |
| Closing Expenditure | 54.47 | 15.90 | 38.57 |
| Education Expenditure | 86.71 | 32.46 | 54.25 |
| Rent Expenditure | 131.73 | 64.54 | 67.19 |
| Rural | .59 | .63 | -0.04 |
| Hhage | 49.68 | 51.21 | -1,53 |
| Hhsize | 4.07 | 3.86 | 0,21 |
| Female | .41 | .40 | 0.01 |
| Educatwed | .86 | .87 | -0.01 |
| Single | .15 | .22 | -0.07 |
| 1,805 | 1,194 | 2,999 | |
Inverse Probability weighting regression adjustment estimation
| Outcomes variable | IPWRA estimation | MDM estimation |
|---|---|---|
| Transport Expenditure | 64.39*** | 56.28*** |
| Food Expenditure | 157.33*** | 157.98*** |
| Household income | 844.77*** | 785.08*** |
| Health Expenditure | 27.21*** | 25.37*** |
| Closing Expenditure | 38.09*** | 38.40*** |
| Education Expenditure | 51.78*** | 36.64*** |
| Rent Expenditure | 60.62*** | 43.91*** |