|dc.description.abstract||"India is amongst the fastest-growing major economies in the world today. Financing from the organized sector, particularly banking, remains the fulcrum for supporting and sustaining India’s growth. Three aspects, inter alia, in this bankingled development process, are important - a contributive and supportive monetary policy, regulatory reforms addressing public welfare needs, and technological innovation supporting banking access and services. In this thesis, we sequentially examine these intertwined aspects.
In the first essay, I nowcast monthly headline Inflation using Dynamic Factor Models in a mixed-frequency set-up. The study leverages crowdsourced prices of 22 essential commodities collected daily from 75 centers in conjunction with a host of market-based measures like yield spread, crude oil price, money supply, reserve money, stock prices, and exchange rate. The forecast using the proposed
method outperforms the forecast from the Reserve Bank of India’s Survey of Professional Forecasters and forecasts from the conventional methods. I further model asymmetry in monthly retail inflation realization using the Quantile Autoregressive
Distributed Lag Mixed-Frequency Data Sampling (QADL-MIDAS) proposed by Ghysels and Iania. The study shows that the persistence of inflation is quantile dependent and non-extreme quantiles are mean-reverting under the flexible inflation targeting regime adopted by India in 2016. On the other hand, extreme quantiles show a unit-root-like behavior.
In the second essay, I estimate the demand for retail deposits in Indian banks using a discrete-choice structural model of demand. The study models consumer behavior using a variety of bank characteristics and prices viz. service fees anddeposit interest rates. I find that consumers respond favorably to an increase in the deposit rate, decrease in service fees, and improvement in bank characteristics like
employees per branch, number of branches, number of Automatic Teller Machines per branch, and electronic payments infrastructure. Using the estimated structural parameters, I further study the welfare implications of saving rate deregulation in India. The study establishes that the saving rate deregulation of 2011 led to a significant increase in welfare during the years immediately following the deregulation.
In the third essay on FinTech in payments, I study the adoption of digital payment technologies over the last decade. Using a difference-in-differences design, the study assesses if the demonetization exercise of 2016 led to enhanced adoption of digital payments. I further study the evolution of digital payments adoption accounting for exogenous shocks like demonetization and nationwide lockdown in
the wake of the COVID-19 pandemic. The study found insufficient evidence in support of the claim that COVID-19 led to enhanced adoption of digital channels (as measured by the volume of transactions as a percentage of GDP)."||en_US