had significant impact on the number of registered urban mortgages but not sales and that stamp duty reductions had a spatially less differentiated and quantitatively larger effect on the number of registered transactions. It suggests that, if property rights reforms are undertaken, all elements of the system will need to be considered.

# **4.1 Did computerization increase credit supply?**

Results from the credit supply regression in table 2 are of interest in two respects. First, inclusion of time and location fixed effects is critical to avoid erroneous conclusions. This is visible from comparison of columns 1 and 3 where addition of the relevant indicator variables not only improves the regression’s fit but also illustrates that what might be interpreted as a significant and large effect of computerization on credit supply (almost a doubling as per column 1) is due largely to changes over time that affected all _taluks_ and, to a lesser extent, location-specific factors. Once relevant controls are included, the point estimate for computerization becomes insignificantly different from zero and even turns negative, suggesting that this intervention had little effect on credit supply overall.

At the same time, the significant and positive coefficient of interacting the computerization variable with the share of urban population that points towards a positive impact of computerization on credit supply in urban but not rural areas. In urban SROs, computerization of land registries would, according to the point estimate, have increased credit supply by 15%. Interactions of computerization variables with indicators of the time elapsed since this intervention support the above conclusions; there is no evidence for lagged effects in the aggregate and the relevant coefficients are individually and jointly not significantly different from zero. By contrast, in urban areas, the effects appear to be persistent and tend to grow stronger over time, increasing from a significant point estimate of 5% to 18% five quarters after computerization, possibly as a result of banks learning about the uses of the information provided by computerized registries or adjusting their business process to take advantages of it more routinely.

How to interpret these results? It is well known that changes in security of land tenure or availability of land ownership information will affect credit supply only if agents are credit constrained and have sufficient illiquid wealth that can be foreclosed upon at reasonable cost (Besley and Ghatak 2009). In rural India, these conditions may not hold for a number of reasons. First, India’s commercial banks are already required by law to direct 18% of their loan portfolio to rural areas so that there may be few creditworthy projects left that would benefit from credit access with reduced transaction cost from loan processing. Second, in rural Andhra Pradesh, the outreach of land registration is limited as both owners and banks prefer to use land records as the basis for processing credit applications. A main reason for this is that land records continue to be maintained manually by village-based representatives of the revenue department, implying lower transactions cost for updating them. Failure of officials or land owners to 12