A statistical analysis of inter-state disparities in agricultural development across India
555 / 297 / 90
Authors
-
AMRIT KAUR MAHAL
Punjab Agricultural University, Ludhiana, Punjab 141 004, India
-
PRITPAL SINGH
Punjab Agricultural University, Ludhiana, Punjab 141 004, India
-
SUNNY KUMAR
Punjab Agricultural University, Ludhiana, Punjab 141 004, India
-
SIMRANJIT KAUR
Punjab Agricultural University, Ludhiana, Punjab 141 004, India
Keywords:
Agriculture sector, Composite index, Development, Inter-state variation, Regression analysisAbstract
A comparative analysis of inter-state variations for three years i.e. 2019–20 to 2021–22 in agricultural development across India had been done by using secondary data from the major agricultural states for 28 key development indicators related to agriculture for Triennium Ending (TE) 2022. The composite indices of development based on the optimum combination of indicators related to agriculture had been worked out for four zones and the overall agricultural states of India. The results of Composite Index (CI) showed that Punjab (0.32), West Bengal (0.37), Gujarat (0.52), and Kerala (0.58) ranked highest in the north, east, west, and south zones, respectively. Overall, the state-wise CI ranged from 0.47 in Punjab to 0.83 in Odisha. The states were further ranked and categorised into high (H), high middle (HM), low middle (LM), and low (L) levels of development. Punjab (0.47), Haryana (0.51), Gujarat (0.59), and Madhya Pradesh (0.60) emerged as the most agriculturally developed states. Significant factors, namely gross irrigated area, mechanisation and technical adoption (tube wells), productivity [wheat (Triticum aestivum L.), maize (Zea mays L.), and vegetables], input usage (chemical fertiliser), and economic dimension of agriculture [sugarcane (Saccharum officinarum L.) returns] were identified among the development indicators. Enhancing these factors could improve the socio-economic conditions of Indian farmers. The study suggested that the low-developed states require improvements in various dimensions in most indicators to enhance the overall development of agriculture.
Downloads
References
Ahvo A, Heino M, Sandstrom V, Chrisendo D, Jalava M and Kummu M. 2023. Agricultural input shocks affect crop yields more in the high-yielding areas of the world. Nature Food 4: 1037–46. DOI: https://doi.org/10.1038/s43016-023-00873-z
Breusch T S and Pagan A R. 1979. A simple test for heteroscedasticity and random coefficient variation. Econometrica 47(5): 1287–94. Deshpande T. 2017. The State of Indian Agriculture, pp. 1–29. PRS Legislative Research, New Delhi. DOI: https://doi.org/10.2307/1911963
Draper N R and Smith H. 2003. Applied Regression Analysis. John Wiley and Sons, New York.
Florek K, Lukaszewicz J, Perkal J, Steinhaus H and Zubrzycki S. 1951. Taksonomia wrocławska. Anthropological Review 17: 193–211.
Government of Punjab. 2022. Statistical Abstract of Punjab 2022. Directorate of Statistics. Department of planning, Government of Punjab. www.esopb.gov.in
Huang C and Townshend J R G. 2003. A stepwise regression tree for nonlinear, approximation: Application to estimating sub pixel land over. International Journal of Remote Sensing 24(1): 75–90. DOI: https://doi.org/10.1080/01431160305001
Krasilnikov P, Taboada M A and Amanullah. 2022. Fertiliser use, soil health and agricultural sustainability. Agriculture 12(4): 462. DOI: https://doi.org/10.3390/agriculture12040462
Narain P, Sharma S D, Rai S C and Bhatia V K. 2007. Statistical evaluation of social development at district level. Journal of the Indian Society of Agricultural Statistics 61(2): 216–26.
Nath B D and Nath S D 2023. Crop productivity in hilly areas of north east India: Constraints and strategies. Biological Forum–An International Journal 15(3): 892–98.
Ohlan R. 2013. Pattern of regional disparities in socio-economic development in India: District level analysis. Social Indicators Research 114: 841–73. DOI: https://doi.org/10.1007/s11205-012-0176-8
Shapiro S and Wilk M. 1965. An analysis of variance test for normality. Biometrika 52(3–4): 591–611. DOI: https://doi.org/10.1093/biomet/52.3-4.591
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2026 The Indian Journal of Agricultural Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright of the articles published in The Indian Journal of Agricultural Sciences is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.
How to Cite
