There is now plenty of evidences of the impact of microfinance on the lives of the poor borrowers. This study also found such evidence of impact. Different analysis techniques were used to investigate the level of impact where the value of asset holding of the participants was taken up as the major outcome variable. Since the study is based on a panel data set and includes all the households including the dropout clients, it is less prone to the bias of comparing the incoming clients to the older ones.
Looking into the pattern of dropout, we found that poverty status of the clients and their group, availability of alternative services, their loyalty to BRAC along with their satisfaction with the service have significant association with the possibility of dropout. Flexibility in loan
repayment was observed as a major area to work on to improve client retention. However, finding appropriate flexibility that does not impede the financial health and ‘good practices’ of microfinance is a major challenge.
REFERENCES
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Carter M R, Barrett CB. The Economics of Poverty Traps and Persistent Poverty: An Asset-based Approach”. Social Science Research Network: 2005.
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Journal of Microfinance, 2001: 3(2): 75 – 85.
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Department of economics, CSIS, Jakarta: 2005:2:19 (http://www.csis.or.id/papers/wpe093). Accessed on 15 May 2007.
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30 Annexure
Annex-1. Mark Schreiner's poverty score-card derived from BBS HIES
Indicators Attributes Points
1 What type of latrine do you have? Open field pit pucca
sanitary or water seal pacca
Assigned Score 0 7 12
2 How many household members are 11 years old or younger 4 or more 3 2 1 0
Assigned Score 0 7 12 17 26
3 Does any household member work for a daily wage? Yes No
Assigned Score 0 7
4
How many living rooms does the house have (excluding ones used
for business and kitchen)? 1 2 or 3 4 or more
Assigned Score 0 3 9
5 Do all children ages 6 to 17 attend school in your household? No
No children age
6 to 17 Yes
Assigned Score 0 4 6
6 Does the household Own a TV set? No Yes
Assigned Score 0 11
7 How many hectares of cultivable land does the household own? Less than 0.34 0.34 to 0.99 1 to 1.99 2 or more
Assigned Score 0 3 4 9
8 What is the main construction material of the walls of the house? Hemp/hay/bamboo or mud brick C.I. sheet/wood Brick/cement
Assigned Score 0 5 7
9 Does the household own any cattle? No Yes
Assigned Score 0 9
10 Does the house have a separate kitchen? No Yes
Assigned Score 0 4
Total
Annex-2. Steps for instrumental variables (IV) analysis OLS model : Yi =β0+β1LSi+β2HHi+ui
i i 2 i 1 0
i NL HH u
Y =β +β +β +
Condition of IV method: The conditions of instrumental variables to be used are relevance i.e. there must be relationship between IV and endogenous variables to be instrumented (LS in our case), and exogeneity i.e. correlation between IV and error term must be zero.
Relevance: correlation (IVi, LSi) ≠ 0 or, correlation (IVi, NLi) ≠ 0 Exogeneity: correlation (IVi, ei) = 0
Stages of IV: In 2SLS estimation process, amount of last loan is predicted by the instrumental variables and other exogenous variables in the first stage. The predicted amount of last loan instead of actual ones enters at the second stage with other exogenous variables.
i i 2 i 1 o
i IV HH v
LS =α +α +α + or, NLi =αo+α1IVi+α2HHi+vi
i 2 i 1 0
i ˆ ˆ IV ˆ HH
Sˆ
L =α +α +α or, NLˆi=αˆ0+αˆ1IVi+αˆ2HHi
i
* i 2
* i
* 1 0
i LSˆ HH u
Y =β +β +β + or, Yi =β*0+β1*NLˆi+β*2HHi+ui
Justification of IV: To estimate J statistics the number of instrumental variables has to be larger than the number of included endogenous variable what is the case here. In calculating J statistics, using the estimates of 2SLS, the value of asset is predicted3 to estimate the residuals.
* i 2
* i
* 1 0
i LS HH
Yˆ =β +β +β or, Yˆi=β*0+β*1NLi+β*2HHi Yˆ
Y eˆi= −
i i 2 i 1 0
i IV HH
eˆ =π +π +π +ε
The residual is regressed against the instruments and other exogenous variables; and endogenous size of loan is excluded. Partial F-statistics of the instruments from the final regression multiplied by the number of instruments yields the J statistics. Thus, all four instruments satisfy the condition of exogeneity.
3 In calculating the predicted values, actual values of loan size is used instead of predicted ones from the first stage.
Annex-3. Determinants of participation using logit model
Relative economic status (1= better-off 0= otherwise) 0.447
(2.45)**
Female headed HH (1= yes 0= otherwise) 0.460
(0.97)
Highest education of HH member 0.045
(1.97)**
Violence index (0= no violence against women, ... 7= extreme violence) 0.355
(3.21)***
Knowledge index (0= no knowledge on legal issues, ….7= knowledge on all legal issues) -0.061
(1.64)
Improved creditworthiness (1= yes 0= otherwise) 0.105
(0.71)
Improved economic status (1 =yes 0= otherwise) -0.349
(1.68)*
Having mobility outside village (1= yes 0= otherwise) 0.095
(0.33)
Having food security (1= yes 0= otherwise) -0.393
(2.37)**
HH having sanitary latrine (1= yes 0= otherwise) 0.203
(1.45)
Source of cooking water (1= tube-well 0= otherwise) 0.802
(1.20)
HH Having electricity connection (1= yes 0= otherwise) 0.234
(1.24)
Number of HH member 0.112
(2.39)**
HH with at one female earner (1= yes 0= otherwise) -0.411
(2.54)**
Number of income source -0.137
(1.72)*
HH having at least one day labour (1= yes 0= otherwise) 0.250
(1.65)*
Amount of cultivable land (decimal) -0.001
(1.37)
Number of cow 0.072
(1.35)
Number of goat 0.058
-1.33
Number of crisis faced 0.461
(4.30)***
Constant -1.312
(1.76)*
Observations 1038
Pseudo R squire 0.061 Absolute value of z statistics in parentheses
Significant at 10%; ** significant at 5%; *** significant at 1%
Annex-4. Questionnaire for repeat survey
PART A
Sample Status: New Scale up New Comparison ID No
Member name --- --- --- Member No Joining Date
DD MM YY Name of VO and Code ---
Branch Office and Code ---
Village --- Union --- Upazila --- Zila --- Name of interviewer ---Date
DD MM YY Remark of cross checker 1= Satisfied 2= Not satisfied Signature after satisfaction
--- Remark of supervisor 1= Satisfied 2= Not satisfied Signature after satisfaction
--- 1. What is the status of household interview?
1= Household found and interviewed
2= Household found but could not be interviewed 3= Household was not found
2. If 2 and 3 why not found (mention reason)
1 = Respondent was not found by visiting 2-3 different days
2= Death of respondent 3 = merged with other household 4 = permanent migration (10 Km.
away from previous place) 5 = temporary migration
Others (……….………..…………..) 3. Member line No. according to baseline
4. Respondent’s line No. in present survey (see table 5):