Debashis Acharya

An alternative approach to monetary aggregation in DEA

This paper proposes a set of alternative DEA-based money indices that are proved to be both theoretically and empirically competing monetary aggregates since they perform as good as the Divisia aggregates. Based on all the results concerning causality, forecasting and money demand, we conclude that DEA money aggregates prove to be at least competing alternatives to the Divisia aggregates, and hence, suggest that these new aggregates may be considered along with the existing weighted monetary aggregates like the Divisia ones. Given the inherent benefit of the doubt weighting mechanism underlying the DEA models where the optimal weight assigned by DEA to each monetary asset reflects the ongoing financial innovation and the Reserve Bank of Indias policy priority in the distribution of total liquidity, we feel that the DEA money indices can truly capture the liquidity better with ongoing financial innovations in the economy.

Price discovery and volatility spillovers in futures and spot commodity markets: Some Indian evidence

Purpose - – The purpose of this paper is to investigate empirically the price discovery and volatility spillovers in Indian spot-futures commodity markets. Design/methodology/approach - – The study has used four futures and spot indices of Multi-Commodity Exchange, Mumbai. The study also employs vector error correction model (VECM) and bivariate exponential Garch model (EGARCH) to analyze the price discovery and volatility spillovers in Indian spot-futures commodity market. Findings - – The VECM shows that agriculture future price index (LAGRIFP), energy future price index (LENERGYFP) and aggregate commodity index (LCOMDEXFP) effectively serve the price discovery function in the spot market implying that there is a flow of information from future to spot commodity markets but the reverse causality does not exist. There is no cointegrating relationship between metal future price index (LMETALFP) and metal spot price index (LMETALSP). Besides the bivariate EGARCH model indicates that although the innovations in one market can predict the volatility in another market, the volatility spillovers from future to the spot market are dominant in the case of LENERGY and LCOMDEX index while LAGRISP acts as a source of volatility toward the agri-futures market. Research limitations/implications - – The results are aggregate in nature. Further study at disaggregated level will provide further insights on behavior of specific commodity prices and the price discovery process. Originality/value - – The paper provides useful information about the evolution and structures of futures commodity trading in India, related literature and relevant methodology concerning the hypotheses.

Inflation Model for India in the Context of Open Economy

In this article, an atheoretic model is built to explain and forecast inflation, using variables that capture domestic as well as foreign influences on inflation. In all, five specifications of models are estimated, one with only domestic variables and four with one of the foreign price variables, namely, Commodity Price Index (COMM), US Producer Price Index (USPPI), crude oil price (CRUDE), industrial countries’ Consumer Price Index (CPI) (INDCPI). It is found that models with foreign price indicators provide better in-sample fit than the baseline model with only domestic variables. Among the models with foreign price variables, the Commodity Price Index (COMM) performs as the best foreign price variable among the set used, in terms of both in-sample and out-of-sample root mean squared errors (RMSE).

Commodity Prices and Domestic Inflation in India

In this article, the relationship between international prices of primary commodities and domestic inflation in India has been explored empirically for the period 1994 to 2007. For this purpose a commodity price index with international price quotations and domestic WPI weights has been constructed. The empirical results show that cointegration between international and domestic prices has grown stronger in the period since 2000. The co-movement is found at both aggregate indices as also the sub-groups viz. fuel and manufactured products. While carrying out this analysis, it was found that it is necessary to use an appropriate index, in order to capture the country-specific exposure, rather than using the aggregate indices published by international agencies, whose coverage and weights may not represent the risks and exposures of specific countries.

Dynamic Macroeconomic Performance of Indian States: Some Post-Reform Evidence

This chapter makes an attempt to assess the dynamic macroeconomic performance (DMEP) of fifteen major Indian States using three macro indicators viz., gross state domestic product (GSDP), fiscal deficit as percentage of the GSDP and price measured by the GSDP deflator. Keeping in mind consistency in data availability and the post-liberalization period, our study period spans over 1993–94 to 2014–15. All the three indicators are measured in 2004–05 prices. Our finding reveals that States that exhibit higher macroeconomic performance are less poverty ridden and also face less inequality.

Competition in Indian life insurance industry: post liberalisation evidence

This paper makes an attempt to assess the state of competition in the Indian life insurance industry for the period 2000-01 to 2014-15 highlighting the nature of competition after the economic reforms in the economy. The study is based on secondary data of the insurance companies for the period 2000-01 to 2014-15. A set of concentration measures such as the k-concentration ratio (CRk), Herfindahl-Hirschman index (HHI), the Hall-Tideman index (HTI), Horvath index (HOV), Entropy index (ENT), Ginevicius index, and GRS index is estimated to assess the state of competition. Accuracy of these indices is also tested along with use of concentration curves and indices. Among all the concentration measures, HHI, HTI and GIN indices depict the low market concentration of life insurance companies, compared to other indices. The index value indicates that though the concentration in the market has declined but still it remains at a relatively higher level.

Perverse liquidity effect of monetary policy: some evidence for India

The liquidity effect of money supply increases, as policy-oriented measures, would generally lead to a decline in interest rates. This is the direct effect. However, such money supply increases lead to a sum of the direct effect plus the positive indirect price and income effects. In sum, the net effect may be positive leading to a net increase and not a decrease in the interest rate. The regular money demand function is suitably modified to capture the structural changes of the Indian economy to verify the net effect of monetary policy-induced money supply movements. The empirical evidence indicates the presence of a perverse liquidity effect.

Can a Disinflationary Policy Have a Differential Impact on Sectoral Output? A Look at Sacrifice Ratios in OECD and Non-OECD Countries

This article examines the sectoral impact of disinflationary monetary policy by calculating the sacrifice ratios for several Organisation for Economic Co-operation and Development (OECD) and non-OECD countries. Sacrifice ratios calculated through the episode method reveal that disinflationary monetary policy has a differential impact across three sectors in both OECD and non-OECD countries. Of the three sectors, the industry and service sectors show significant output loss due to a tight monetary policy in OECD and non-OECD countries. But the agricultural sector shows a differential impact of disinflation policy: It shows a negative sacrifice ratio in OECD countries indicating that output growth is insignificantly affected by a tight monetary policy while non-OECD countries yield positive sacrifice ratios, suggesting that the output loss is significant. Further, it is observed that sacrifice ratios calculated from aggregate data are different from ratios calculated from sectoral data. JEL Classification: E52, E58, C14, O50

Corporate Performance during Business Cycles: Evidence from Indian Manufacturing Firms:

The present study is an attempt to assess the ‘probability of incurring loss’ of manufacturing firms in India during different phases of business cycles. We use data on a sample of 87 manufacturing companies for the period from 2002 to 2014 (comprising 1131 firm years). We use the panel logit model with the dependent variable derived from the return on assets to empirically test the hypothesis. Besides, we use firm-specific variables and macroeconomic variables as independent variables in the model. Firm-specific variables, namely size of the firm and interest coverage ratio and macroeconomic variables namely exchange rate, bank credit, inflation, interest rate and index of industrial production are statistically significant in predicting the probability of incurring loss of the firms during the study period. The results are important for investors, corporate houses, managers, lenders, policymakers and the research community as business cycles have a visible impact on all functional areas of an organization. Our study assumes significance because of the importance of macroeconomic variables in the strategic decision-making of the corporate sector in general and manufacturing firms in particular.

Life Insurance in India: Origin, Evolution and the Present State

This chapter traces the origin of Indian life insurance and discusses its evolution in different phases, distinguishing the pre-liberalization era from the post-liberalization phase. The present state of life insurance in India is discussed in terms of indicators like insurance penetration and density. A comparative picture is drawn with reference to global life insurance. The state of life microinsurance and postal life insurance is briefly discussed followed by the challenges before the future of the industry.