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Aswini Kumar Mishra

Researcher at Birla Institute of Technology and Science

Publications -  49
Citations -  379

Aswini Kumar Mishra is an academic researcher from Birla Institute of Technology and Science. The author has contributed to research in topics: Emerging markets & Economic inequality. The author has an hindex of 10, co-authored 48 publications receiving 247 citations. Previous affiliations of Aswini Kumar Mishra include Birla Institute of Technology & Science, Pilani - Goa & Indian Institute of Management Ahmedabad.

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Household Income Inequality and Income Mobility: Implications Towards Equalizing Longer-Term Incomes in India

TL;DR: In this article, the authors address three important questions: what are the trends, levels and sources of income inequality in India? Second, how have been the patterns of income mobility? And fina...
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Does corporate governance characteristics influence firm performance in India? Empirical evidence using dynamic panel data analysis

TL;DR: In this paper, the authors examined the empirical relationship between corporate governance and financial performance of Indian firms by developing a corporate governance index (CGI) based on a variety of corporate governance characteristics.
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Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India

TL;DR: In this paper, the authors investigated empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets using Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH).
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Horizontal Equity and the Thirteenth Finance Commission: Issues and Ponderables

TL;DR: In this paper, the parameters/criteria on which basis awards are finalized are analyzed and the scope for possible improvement in the working of fiscal federalism and policy implications have also been deliberated upon.
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Forecasting spot prices of agricultural commodities in India: Application of deep-learning models

TL;DR: In this article, the authors examined the performance of deep learning models for predicting the spot prices of five major agricultural commodities (cotton seed, castor seed, rape mustard seed, soybean seed, and guar seed) on the National Commodity and Derivatives Exchange.