Growth and diffusion dynamics of tractor in Punjab


Abstract views: 155 / PDF downloads: 130

Authors

  • RAVINDRA SINGH SHEKHAWAT Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • K N SINGH Principal Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • MADHUSUDAN BHATTARAI National Project Manager, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • BISHAL GURUNG Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • ACHAL LAMA Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • KRISHNA PADA SARKAR Research Scholar, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
  • RIPI DONI Research Scholar, ICAR-IARI, New Delhi

https://doi.org/10.56093/ijas.v89i6.90835

Keywords:

Diffusion, Levenberg-Marquardt, Monomolecular, Non-linearmodel, Tractor density

Abstract

Over the last few decades, India has seen an incessant increase of tractor use as well as expansion in its domestic tractor manufacturing industry, in spite of comparatively slow wage growth and a slow decline in the employment share of the agricultural sector. If the present situation is to be accounted, arguably as much as 90% of the country’s farm area may be prepared by tractors. Monomolecular nonlinear growth model methodology was applied to Punjab’s tractor density time-series data to capture the diffusion of tractor. Levenberg-Marquardt iterative method was applied with the help of SAS by using PROC NLIN statement and the obtained results show that the model is a good fit for the data under consideration. Further, Compound annual growth rate (CAGR) of tractor density was also calculated to infer about the changes in tractor density over the time (1982–2015 ) and found that CAGR was high during 80s and 90s than 2000s. Despite of low growth in last decade, Punjab is expected to have more adopters of tractor in coming years. From this empirical study, we also infer that 90 per cent tractor penetration will be achieved by 2032 in Punjab.

Downloads

Download data is not yet available.

References

Bhalla G S and Singh G. 2011. Economic Liberalization and Indian Agriculture: A district level study, 1st edn. New Delhi. SAGE Publications Pvt Ltd.

Bhattarai M, Joshi P K, Shekhawat R S and Takeshima H. 2017. The evolution of tractorization in India’s low-wage economy key patterns and implications. IFPRI Discussion Paper 01675.

Binswanger H. 1978. The Economics of tractors in South Asia: Ananalytical review. Agricultural Development Council, New York. International Crops Research Institute for the Semi-Arid Tropics Hyderabad.

Binswanger H. 1986. Agricultural Mechanization: A comparative historical perspective. World Bank Research Observer 1(1): 27–56. DOI: https://doi.org/10.1093/wbro/1.1.27

CSAM (Centre for Sustainable Agricultural Mechanization). 2014. Country Pages. Accessed June 2, 2017. http://un-csam. org/cp_index.htm.

Gupta R and Jain K. 2012. Diffusion of mobile telephony in India: An empirical study. Technological Forecasting and Social Change 79(4): 709–15. DOI: https://doi.org/10.1016/j.techfore.2011.08.003

Hawkins D M and Khan D M.2009. A procedure for robust fitting in nonlinear regression. Computational Statisticsand Data Analysis 53(12): 4500–7. DOI: https://doi.org/10.1016/j.csda.2009.07.006

Jayasuriya S K, Te A andHerdt R W. 1986. Mechanisation and cropping intensification: economics of machinery use in low wage economies. Journal of Development Studies 22(2): 327–35. DOI: https://doi.org/10.1080/00220388608421983

Ma C and Jiang L. 2007. Some research on Levenberg–Marquardt method for the nonlinear equations. Applied Mathematics and Computation 184(2): 1032–40. DOI: https://doi.org/10.1016/j.amc.2006.07.004

Seber G A and Wild C J. 2003. Nonlinear Regression. Wiley Series in Probability and Statistics.

Singh G. 2015. Agricultural mechanization development in India. Indian Journal of Agricultural Economics 70(1): 64–82.

Transtrum M K, Machta B B andSethna J P. 2010. Why are non-linear fits to data so challenging? Physical Review Letters 104(6): 060201. DOI: https://doi.org/10.1103/PhysRevLett.104.060201

Downloads

Submitted

2019-06-19

Published

2019-06-19

Issue

Section

Short-Communication

How to Cite

SHEKHAWAT, R. S., SINGH, K. N., BHATTARAI, M., GURUNG, B., LAMA, A., SARKAR, K. P., & DONI, R. (2019). Growth and diffusion dynamics of tractor in Punjab. The Indian Journal of Agricultural Sciences, 89(6), 1054–1056. https://doi.org/10.56093/ijas.v89i6.90835
Citation