program intensity discussed above, this can happen when the program coverage in most of the villages is close to the minimum viable scale.

# **2.3. DATA**

The village level data for the econometric estimation of the impact of MFI coverage on informal interest rates come from the baseline survey conducted during 2006-2007 by the Institute of Microfinance (InM) for the Programmed Initiative for Monga Eradication (PRIME) of Palli Karma Sahayak Fundation (PKSF). We call the data set the InM-PKSF survey. The baseline survey consists of a census of all households meeting certain income, employment and land ownership criteria as well as a village level survey.<sup>18</sup> The village level survey collected information on moneylender interest rates and availability of infrastructure and services. Empirical analysis of this paper is based on this village level data set supplemented with MFI coverage rates calculated from the household survey.<sup>19</sup> The data set covers three districts (Lalmonirhat, Nilphamary and Gaibandha) in Rangpur division where the earliest baseline surveys of the PRIME program were conducted. Out of 18 upazilas (sub-districts) in these districts, the survey was undertaken in 12 upazilas. There are 804 villages in our dataset.<sup>20</sup> To make sure that our estimates are not unduly influenced by a few outliers, we exclude a small number of villages reporting unusually high interest rate (above 180 percent) from our sample giving us a final sample of 793 villages.<sup>21</sup> However, none of the qualitative conclusions from the empirical analysis are affected if we use the full sample (results are available from the authors).

The InM-PKSF survey is particularly suitable for our empirical analysis for a number of reasons. First, the survey was primarily targeted to poor households which are usually more dependent on the moneylenders in the absence of MFIs. Second, interest rate data were collected for a standardized loan product. The interest rate analyzed in this paper is the money lender interest in normal times (not the lean season) for loans of duration up to one year.<sup>22</sup> We do not include interest rates on longer maturity loans, because the maturity of the standard MFI loans in Bangladesh is one year. The standardized rates ensure that variations in interest rates across villages are not due to heterogeneity in loan duration or seasonality.

> than the standard IV estimates (Lewbel (2012)). The inefficiency of the estimator implies that if we find a statistically significant effect, it should be interpreted as strong evidence.

> 18 Households meeting any of the following three conditions were included in the survey: households should have monthly income of Tk. 1,500 or below, or are dependent on day-labor, or have less than 50 decimal of land. 19 The household level dataset available to us does not contain the interest rate information on informal loans.

> 20 To appreciate the richness of the data set, recall that the only available study on the effects of MFIs on moneylender interest rate is based on 106 villages (see Mallick (2012)).

> 21 There is however no village which reported an informal interest rate between above 120 percent and below 180 percent.

> 22 The questionnaire clearly asked about moneylender interest rate (“Mohajoni Rin” in Bengali). So it is highly unlikely, if not impossible, that the households confused moneylender loans with loans from friends and family.

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