that tries to identify specific shocks to wealth in order to identify credit constraints.11
In Banerjee and Duflo we test these predictions by taking advantage of a recent change in the so-called “priority sector” rules in India: all banks in India are required to lend at least 40 percent of their net credit to the priority sector, which includes small scale industry (SSI), at an interest rate that is required to be no more than 4 percentage points above their prime lending rate.12 If banks do not satisfy the priority sector target, they are required to lend money to specific government agencies at low rates of interest. In January, 1998, the limit on total investment in plants and machinery for a firm to be eligible for inclusion in the small scale industry category was raised from Rs. 6.5 million to Rs. 30 million. Our empirical strategy focuses on the firms that became newly eligible for credit in this period, and uses firms that were always eligible for priority sector credit as a control. The results from our analysis are reported briefly in the next sub-section.
The evidence for under-lending
Data: The data we use were obtained from one of the better-performing Indian public sector banks. We use data from the loan folders maintained by the bank on profit, sales, credit lines and utilization, and interest rates. The loan folders also report all numbers that the banker was required to calculate (e.g. his projection of the bank’s future turnover, his calculation of the bank’s credit needs, etc.) in order to determine the amount to be lent. We also record these, and will make use of them in the analysis described in the next section. We have data on 253 firms (including 93 newly eligible firms). The data is available for the entire 1997 to 1999 period for 175 of these firms.
Specification Through much of this section we will estimate an equation of the form
yit − y
= α y B I G i + β y P O S T t + γ y B I G i ∗ P O S T t + ² y i t
with y taking the role of the various outcomes of interest (credit, revenue, profits, etc.) and the dummy P OST representing the post January 1998 period. We are in effect comparing how the outcomes change for the big firms after 1998, with how they change for the small firms. Since
11 See inter alia, Blanchflower and Oswald (1998), Lamont (1997). 12 Banerjee and Duflo (2002).