Microfinance Poverty Assessment Tool

Henry, Carla; Sharma, Manohar; Lapenu, Cécile; Zeller, Manfred

doi:10.1596/0-8213-5674-7

Cited by 74 publications

(59 citation statements)

References 1 publication

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“…As a default, the CGAP recommends a sample size of at least 500 and that a 2-to-3 ratio of clients to non-clients is maintained in all clusters in an impact assessment study (Henry, Sharma, Lapenu, and Zeller, 2003).…”

Section: Sampling Proceduresmentioning

confidence: 99%

The Impact of Microfinance on Household Livelihoods: Evidence from Rural Eritrea

Habte

Visser

Ocran

2017

Development Finance

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Eritrea, a relatively young African nation, is one of the least developed countries in the world. Its economy is predominantly dependent on subsistence agriculture and the level and magnitude of poverty is more severe in rural areas. The formal financial sector is underdeveloped, state-owned, far from being competitive, and limited in terms of depth and breadth as measured by the relevant financial sector development indicators. To address the limitations of the formal banking sector and to help fill the financing gap, and improve the general livelihood of those at the lower income group, the Government of Eritrea introduced a Saving and Microcredit Programme (SMCP) in 1996 for which no scientific study measuring its impact has been done at the household level. The study was conducted in rural areas to find out whether the SMCP as a microfinance institution has improved the livelihood of its clients. The specific objectives of the study were to describe the characteristic feature of rural livelihoods in terms of the resources owned, the strategies pursued and outcomes achieved, identify and examine the determinants of household participation in the SMCP and finally assess the impact of participation in SMCP on household livelihoods. The study employed a quasi-experimental cross-sectional survey design involving structured and semistructured questionnaire administered to 500 respondents of whom 200 represented the treated group and 300 the controlled group. Logit regression was employed to identify the factors that determine household participation in the SMCP. In regard to this, age of the client household, household size, marital status, level of education of the client household, the size of first round loan, entrepreneurial experience, type of loan product offered by the institution, ownership of livestock and microenterprise, the perception of the client on involuntary deposits, the occurrence of a negative events (shock) to the household and village access to electricity were found to have statistically significant effect on the household"s probability to participate in the SMCP. Furthermore, the marginal effects were also computed to evaluate the contribution of each of these factors to the likelihood of participating in the SMCP. A propensity score matching model was applied to assess the impact of the programme on the livelihood of its clients. The findings reveal that participation in the SMCP has a significantly higher average treatment effect on the treated (ATT) households.Profits generated from off-farm and small microenterprises, the values of household and livestock assets, food and non-food consumption expenditures and nutrition quality, were ii found to be on average higher for the treated households than for the controlled households.

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Section: Sampling Proceduresmentioning

confidence: 99%

The Impact of Microfinance on Household Livelihoods: Evidence from Rural Eritrea

Habte

Visser

Ocran

2017

Development Finance

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“…Most export market suppliers are members of PMOs (63%) and comply with GlobalGAP standards (56%), which is to be expected. 4 The agricultural and livestock asset indices are based on a principal component analysis following IRUNGU (2002), HENRY et al (2003), RUTSTEIN andJOHNSON (2004), andZELLER et al (2006). Agricultural and livestock assets are two of the five key categories of non-land assets identified as important for the study area.…”

Section: Market Channels and Their Participantsmentioning

confidence: 99%

Smallholder Participation in the Commercialisation of Vegetables: Evidence from Kenyan Panel Data

Muriithi

Matz

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper describes the participation of smallholders in commercial horticultural farming in Kenya and identifies constraints and critical factors that influence their decision to participate in this industry by selling their produce. The study employs panel survey data on smallholder producers of both international (export) and domestic market vegetables and controls for unobserved heterogeneity across farmers. We find that participation of smallholders in both the domestic and export vegetable markets declined and that this trend is associated with weather risks, high costs of inputs and unskilled labour, and erratic vegetable prices, especially in the international market. Different factors are at play in determining a household's market choice for the commercialisation of vegetables: credit is important only when vegetables are (also) exported, livestock ownership is negatively related to production for the domestic market, and distance to the nearest market town positively related to all pathways of commercialisation, for example.

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“…Banerjee and Mullainathan [27] emphasize that the effects of the micro-credit's policy on poverty lowering are ambiguously considered in the short term. In order to check the strength of the obtained results concerning the examined groups, an analysis of their levels of good ranking is carried out [28][29][30]. This criterion is crucial since it is an early detection of the position of the two client groups' ultimately correctly classified.…”

Section: Resultsmentioning

confidence: 99%

Microfinace As An Instrument Against Poverty

Maalej¹

2017

J Glob Econ

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The objective of the current approach is to set out how microfinance institutions (MFIs) are incentives for economic development and as sources of lowering poverty. In this respect, a sample of 197 new and old clients having recourse to MFIs is targeted. The discriminant descriptive analysis which is proposed in this article is useful for mainly meeting the results that microfinance has a highly significant effect on improving people's standards of living as well as lowering poverty rates. The comparison between the new and old clients of MFIs is suggestive of the fact that: the older the MFIs is, the more the opportunity to escape poverty is at reach. It is noted that an ambiguity submerges in the short-term micro-credit. The impacts of microfinance are timely joined. Time as a variable is marked importantly in appreciating microfinance in the long term.

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Microfinance Poverty Assessment Tool

Cited by 74 publications

References 1 publication

The Impact of Microfinance on Household Livelihoods: Evidence from Rural Eritrea

The Impact of Microfinance on Household Livelihoods: Evidence from Rural Eritrea

Smallholder Participation in the Commercialisation of Vegetables: Evidence from Kenyan Panel Data

Microfinace As An Instrument Against Poverty

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