Inflation

Paired with the borrower score/ rating, a credit resilience score would better equip the fi nancial institutions to account for borrower resilience and make credit decisions accordingly. The requirement for CRS in India helps credit to fl ow uninterruptedly during good and bad times. Recognising the parameters used in the existing credit score for individuals and corporate credit rating, a framework for the development of CRS is suggested.

Machine learning techniques are now very common in many spheres, and there is a growing popularity of these approaches in macroeconomic forecasting as well. Are these techniques really useful in the prediction of macroeconomic outcomes? Are they superior in performance compared to their traditional counterparts? We carry out a meta-analysis of the existing literature in order to answer these questions. Our analysis suggests that the answers to most of these questions are nuanced and conditional on a number of factors identified in the study.

The paper estimates a slew of augmented Taylor rule specifications using call and treasury bill rates. After accounting for break points, we calculate the output gap based on a single-index dynamic factor extracted from monthly high-frequency indicators that are representative of broad sectoral activity. In our study, we found that interest rates in India are mostly in line with the augmented Taylor rule specifications after the Reserve Bank of India started using flexible inflation targeting.

Erratic fiscal and monetary policies tend to slow down growth and fuel inflation.