| dc.description.abstract | The non-banking sector’s existence is based on its ability to meet the un-met need by providing banking facilities to the non-banked and difficult to cater segments. Housing being a basic need after food and clothing, is a major focus area for the government as historically it has been seen that when there is development in the housing sector, the economy also was in a upcycle. But access to finance is limited due to limits set for the financial system to lend money. The pillars of the financial systems – the banks are not eligible to lend to the unbanked segment (no data on the creditworthiness) or to the first time borrower as there is not data to assure that the loan would not end up being a non-performing asset. But the shadow banks have taken up this task and is trying to bridge the gap by lending to this segment. But as this is a challenging task, even their undesirable output is expected to be higher than the banks. Keeping that in mind, is it possible to evaluate the efficiency of the non-banks with the banks and say that they are inefficient due to their rising NPAs? The comparative efficiency analysis should be run on systems working with similar set of inputs and producing a similar set of outputs. (A. Das, 2012) Therefore, it is useful to look at the efficient entities within the HFC universe, and study their best practices. This study would be around conducting a parametric and non-parametric analysis of the HFCs while incorporating the effects of undesirable output (A.R.Jayaramana, 2014) and hence see how efficient are our housing sector units. Additionally, we can run similar tests on housing sectors in other countries and benchmark our performance to check for avenues for improvement by looking at their best practices. (K, 2010). | en_US |
