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Published in: Journal of Quantitative Economics 1/2017

08-06-2016 | Original Article

Spatial Convergence and Growth in Indian Agriculture: 1967–2010

Author: Tirtha Chatterjee

Published in: Journal of Quantitative Economics | Issue 1/2017

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Abstract

Inter-state disparity has been a perennial feature of Indian agriculture. The study probes if per capita income from agriculture has converged across states and finds evidence in favour of beta convergence. Spatial econometric techniques used indicate significant spatial dependence in agricultural growth. Infrastructure like roads, irrigation, and electricity, diversification in cropping pattern and quality of human capital are found to aid in growth. However, excessive rainfall tends to decrease growth rate in India. The spill-over across states are found to be primarily driven by roads, irrigation and rural literacy and we also find significant impact of spatial income growth providing evidence in favour of agglomeration effects. Hence, investments in human capital, physical infrastructure specially water management and incentives towards growing crops which yield higher returns will aid agriculture growth in India.

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Footnotes
1
For details on absolute and relative location, refer Abreu et al. (2004).
 
2
These 17 states contribute more than 96 % of the national Net Domestic Product (NDP) from agriculture. The states are Andhra Pradesh (AP), Assam, Bihar \(+\) Jharkhand, Gujarat, Haryana, Himachal Pradesh (HP), Jammu & Kashmir (JK), Karnataka, Kerala, Maharashtra, Madhya Pradesh \(+\) Chhattisgarh (MP), Orissa, Punjab, Rajasthan, Tamil Nadu (TN), Uttar Pradesh \(+\) Uttarakhand (UP) and West Bengal (WB).
 
3
Lesage and Pace (2009).
 
4
The 17 states are Andhra Pradesh (AP), Assam, Bihar \(+\) Jharkhand, Gujarat, Haryana, Himachal Pradesh (HP), Jammu & Kashmir (JK), Karnataka, Kerala, Maharashtra, Madhya Pradesh \(+\) Chhattisgarh (MP), Orissa, Punjab, Rajasthan, Tamil Nadu (TN), Uttar Pradesh \(+\) Uttarakhand (UP) and West Bengal (WB).
 
5
The rise in share of gross fixed capital in the 3rd sub-phase has been controlled in the study through year dummies as number of years post rise in investment was very low to accommodate a separate sub-phase and perform a robust statistical analysis.
 
6
Expenditure on agriculture and allied activities include expenditure on crop husbandry, soil and water conservation, animal husbandry, dairy development, fisheries, forestry and wild life, plantations, food storage and warehousing, agriculture research and development, food and nutrition, community development and other agricultural programmes. Both revenue and capital expenditure have been included. This data is available from 1972.
 
7
Rey and Montouri (1999).
 
8
Results of local Moran’s I for other years have not been shown in the table owing to paucity of space. They can be shared on request.
 
9
Rey and Montouri (1999) also find a statistically significant positive correlation between standard deviation and Moran’s I statistic of per capita income of US.
 
10
Fertilizer consumed per unit of cropped area is not significant in any of the models and hence has been dropped from the analysis.
 
11
At the all India level, from 1966 to 2007, on an average bovines account for approximately 65 % of all livestock, and within bovines, animals in milk constitute only approximately 35 %.
 
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Metadata
Title
Spatial Convergence and Growth in Indian Agriculture: 1967–2010
Author
Tirtha Chatterjee
Publication date
08-06-2016
Publisher
Springer India
Published in
Journal of Quantitative Economics / Issue 1/2017
Print ISSN: 0971-1554
Electronic ISSN: 2364-1045
DOI
https://doi.org/10.1007/s40953-016-0046-3

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