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Cover -- Contents -- List of Boxes, Tables and Figures -- List of Abbreviations -- Foreword -- Preface -- Part 1 -- Chapter 1 -- Chapter 2 -- Part 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Part 3 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 -- Chapter 12 -- Part 4 -- Chapter 13 -- Chapter 14 -- Chapter 15 -- Chapter 16 -- Part 5 -- Chapter 17 -- Chapter 18 -- Chapter 19 -- Chapter 20 -- Part 6 -- Chapter 21 -- Chapter 22 -- Bibliography -- About the Author.
Cover -- Contents -- List of Abbreviations -- Foreword -- Preface -- Acknowledgements -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 -- Chapter 12 -- Select Bibliography -- About the Author.
Cover -- Contents -- List of Tables -- List of Figures -- Foreword -- Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 -- Chapter 12 -- Chapter 13 -- Chapter 14 -- Annexure I -- Annexure II -- Annexure III -- Annexure IV -- Annexure V -- Annexure VI -- Annexure VII -- Annexure VIII -- Annexure IX -- Annexure X -- Annexure XI -- Annexure XII -- Annexure XIII -- Annexure XIV -- Annexure XV -- Annexure XVI -- About the Author.
Not Available ; Credit is considered as one of the most important and basic input in agricultural production process. The prime source of agricultural credit in India has drastically shifted from non-institutional (money lenders) to institutional source in the last five decades due to various policy initiatives of Government of India. Grass root level analysis of the dynamic helps in further policy framework. Hence in this study based on district wise average outstanding agricultural credit by scheduled commercial banks (SCBs) for the TE ending 2017-18, three districts from each state indicating high, medium and low exposure categories is selected using clustering technique. For these study districts outstanding agricultural credit by SCBs was extracted (1976-2017) and analysed. From the Bai-Perron test years viz., 1983, 1990, 1997, 2004 and 2011 are identified to be most common structural breaks in the time series data of each district owing to various policy reforms in the field of agricultural finance. Based on these breaks the time series further subdivided into six phases viz., phase-I (1976-1982), phase-II (1983-1989), phase-III (1990-1996), phase-IV (1997-2003), phase-V (2004-2010) and phase-VI (2011-2017). Phase-wise CAGR was calculated for all the districts and Garrett ranking technique is employed for further ranking of phases across six regions of the country. Phase-I is identified as the phase with high rate of growth in agricultural advances in selected districts across all regions except southern where it is ranked second. The policy initiatives of that period i.e. setting of priority sector lending targets and establishment of Regional Rural Banks have played crucial role in this growth phenomenon of agricultural advances. Further recent policies like doubling agricultural package and ground level credit policies have also played crucial role in the growth of agricultural advances at grass root level in all regions except eastern and north-eastern regions. Whereas in the eastern and north-eastern ...
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