Abhiman Das

Efficiency of Indian commercial banks during the reform period

This article contributes to the banking efficiency literature by measuring technical efficiency of banks in four different ownership groups in India during the reform period, 1992–1999. It employs the stochastic frontier function methodology for panel data. The results indicate that the efficiency of raising interest margin is time invariant while the efficiencies of raising other outputs-non-interest income, investments and credits are time varying. The state bank group and foreign banks are more efficient than their counterparts. The reform period witnessed a relatively high efficiency for augmenting investments, which is consistent with economic growth objective of the reform measures. However, there are still larger gaps between the actual and potential performances of banks.

Distribution of cost and profit efficiency: Evidence from Indian banking

This paper uses the nonparametric DEA methodology to estimate cost and profit efficiency of Indian banks during the post-reform period. The results show considerable variation in average levels of profit efficiency across various ownership categories of banks. In general, state owned banks are found to be more efficient than their private counter parts. Further, efficiency tends to be low among the small banks (assets up to Rs. 50 billion), indicating that at the existing scale of operations, these banks are operating far below the efficient frontier. We also examine the distribution of efficiency using nonparametric kernel density estimates. The analysis reveals a rightward-shift of the efficiency distribution over the years. A major part of this shift comes from the state owned banks. Based on the conditional distribution, the study finds strong evidence of ownership explaining the efficiency differential of banks. Additionally, bank size and product-mix are also found to be important, although to a lesser extent.

Scale economies, cost complementarities and technical progress in Indian banking: evidence from fourier flexible functional form

This article uses a multi-product Fourier flexible cost function specification to investigate scale economies, cost complementarities and technical progress of Indian banks during the post reform period 1992 to 2003. The empirical results indicate that there exist significant economies of scale for all size classes of banks and there is no evidence of diseconomies of scale, even for larger banks. In particular, for small and medium-size banks, there is enough opportunity to increase output by either increasing the scale or merging with other banks to improve the average cost curve. The evidence is fairly robust even after controlling the impact of asset quality and overall risk exposure in the cost function specification. In addition, the statistical test confirms that the industry cost function does not have a Translog form. The results do not find any empirical evidence of cost complementarities between outputs. In terms of technical progress, Indian banks have experienced significant cost reduction which is as high as 5% for the recent period. However, the effects due to the scale augmenting and nonneutral components are found to be negligible. 1 Opinions expressed in this article are the sole responsibility of the authors and do not necessarily reflect the views of the institutions with which they are affiliated.

Nowcasting sales growth of manufacturing companies in India

ABSTRACT The performance of private corporate sector is used as an important demand indicator for monetary policy making. As these data are received with a lag, assessing and monitoring of corporate sales on a real-time basis poses a significant challenge to policy makers in India. In this context, this article attempts to nowcast quarterly sales growth of Indian manufacturing companies and GDP growth of India using dynamic factor modelling framework. A multiple-level framework through turning point analysis and elastic net structure is used to overcome the overfitting problem during variable selection. Empirical results show improvement in forecast accuracy for one quarter ahead nowcast using 3-factor and 4-factor models over the benchmark model. However, absolute dominance of 3-factor models over 4-factor models was not established. As such, the article has proposed a forecast combination technique to nowcast sales growth of manufacturing companies in India.

Financial Intermediation Services Indirectly Measured (FISIM): The role of reference rate

Adoption of SNA2008 for measurement of financial sector’s output has brought about several conceptual issues and practical challenges. The proposed reference rate approach plays a vital role in computation and the choice of which affects the FISIM, and thereby financial sector’s output. Depending on the reference rate, it can take a value as low as interest spread times the quantum of loans or as high as interest spread times the quantum of deposits. As there is no consensus on the reference rate, much of the debate among national accountants community over the measurement of FISIM has been confined to the appropriate choice of reference rate. In this context, this paper presents the issues and challenges of implementing the FISIM methodology of SNA2008 with respect to the commercial banking sector in India.

Forecasting Inflation with Mixed Frequency Data in India

In the standard approach of building prediction models, macroeconomic data is matched with monthly or quarterly or annual aggregates of financial series, since macroeconomic data are typically available at those frequencies. Such aggregation leads to the loss of useful forward-looking information of financial data. This is so because financial data are usually observed with higher periodicity than monthly data. Recent empirical evidence suggests that a Mixed Data Sampling (MIDAS) regression technique improves the predictive power of the models that incorporates data of different frequencies. In this article, we propose an autoregressive MIDAS model for forecasting monthly inflation in India using daily treasury yield information. Empirical results show that the proposed model has better predicting power over forecasting inflation in India.