Endnotes

¹ Real GDP growth fluctuated around 3% throughout the 1990s (Government of Pakistan (2003), p.21), but the head count index using the official poverty line, which is based on calorie consumption rose from 26.1 in 1990-91 to 32.1 in 2000-01 (Government of Pakistan (2003), p.12) and the Gini coefficient, which measures inequality, rose from 28.4% in 1984-85 to 29.6% in 1998-98 (World Bank, 2002, page 26).

² The major NGOs providing microfinance services in Pakistan are Development Action for Mobilization and Emancipation (DAMEN), Sungi Development Foundation (SUNGI), Taraqee Foundation (Taraqee), Orangi Pilot Project (OPP), Sindh Agricultureal and Forestry Workers Coordinating Organization (SAFWCO)¡¢ Asasah and KASHF Foundation (Kashf)

³ National Rural Support Programme (NRSP), Punjab Rural Support Programme (PRSP), Sarhad Rural Support Programme (SRSP) Thardeep Rural Development Programme (TRDP).

⁴ The microfinance division of the Bank of Khyber, the one traditional commercial bank offering microfinancial services, is also not financially sustainable. (Pakistan Microfinance Network Performance Indicators Report 2003)

⁵ The Pakistan Poverty Alleviation Fund (PPAF), for example, a national apex institution wholesaling financial services to eligible institutions ¨C including many of the NGOs and RSPs described above - reports that as of June 2005 its 56 partner organizations had 221,150 active sub-loans.

⁶ The Pakistan Microfinance Network (2001) reports that members had reached a cumulative total of 136,205 borrowers as of June 2001.

⁷ The First Microfinance Bank, Rozgar Bank and Network Microfinance Bank have recently received microfinance banking licenses.

⁸ Some of the difficulties are summarized by Hussein and Hussain (2003) in an overview of the impact of microfinance on poverty and gender equity prepared for the Pakistan Microfinance Network. They mention the difficulties of overcoming selection bias as well as the fact that the factors included in quantitative studies are pre-determined, rather than open-ended as in qualitative approaches.

⁹ Within Pakistan, PPAF (2004), conducted by GALLUP is a nice example of this practitioner-friendly type of quantitative assessment. PPAF (2004) recognizes the issue of bias upfront, but for practical reasons is unable to use any of the techniques described below, instead using client recall to proxy for change in income. Zafar and Abid (1999) is an example of the qualitative approach, using focus group discussions with Kashf clients to assess socio-economic outcomes. Zafar and Abid (1999) also discuss survey data from 55 Kashf households, but the sample includes no control group.

¹⁰ Morduch (1999) also questions the quality and accuracy of some of the data; particularly whether the control groups are truly representative. 11 Although it should be noted that these rates are still much lower than the rate of failure of newlyestablished enterprises in developed countries such as the United States or Japan.

¹² In this sample, the bottom quintile corresponded to those households consuming less than half of caloric levels set for the official poverty line of the Government of Pakistan. Thus it covers very poor households.

¹³ The official poverty line is based on caloric intake and translates into approximately Rs 1,000 per capita per month of food consumption. The author would like to thank Talat Anwar for raising this issue and providing updated poverty line estimates.

Comment(s)

There are [1] comment(s) for this entry. Post a comment.

1. Khan Hidayat Ullah
   (posted 23 November 2006 / 10:14:28 PM)
   
   Econometric Model Selection:
   
   I went through your paper and really liked the approach adopted by you while found your results interesting as well.
   
   I have one comment to make. When it comes the components of microfinance pertaining to the term of loan, e.g., amount, duration and repayment mode, in practice these factors are determined by the both the borrower and lender through negotiation between line staff of MFI and Managers of CBOs. This results into adoption of resolution by members in joint meeting held by field staff MIF and CBO.
   
   Keeping these factors in view, the claim that an explanatory variable relating to terms of micro-credit is exogenous becomes doubtful. This creates endogenity problems in the model and the results which are estimated by this model can not be claimed as unbiased.
   
   In you model you have used variables like amounts of loan and times of loans borrowed in past, which brings in endogenity problem in the model and leads to biased estimates, if I am correct? I would like to know how you addressed this problem in your econometric model. If not what kind of instrumental variable you intend to use in order to deal with situation will.