Indian Journal of Economics and Development

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Comparative Evaluation of Different Statistical Models for Explaining Productivity Trend of Rice and Wheat Crops in North Gujarat Zone


Affiliations
1 Department of Agricultural Statistics, B. A. College of Agriculture, Anand Agricultural University, Anand- 388110 (Gujarat), India
 

Objective: To identify the appropriate trend equations, compound growth rates and instability indices of productivity of rice and wheat crops in North Gujarat zone in India.

Methods: The present study was made through fitting of different linear, non-linear and time series models. The time-series data from 1960-61 to 2012-13 on productivity of rice and wheat crops for North Gujarat zone were collected from Directorate of Agriculture, Gujarat state, Gandhinagar.

Findings: It was found that among different polynomial models, linear model for rice and cubic model for wheat were best fitted for productivity trend and in case of ARIMA models, ARIMA (0,1,1) was evolved as the best fitted trend functions for productivity of both rice and wheat crop. The compound growth rates for productivity were 6.65% and 3.99 % annually in rice and wheat crop, respectively. The instability indices were observed 24.72 with 44.49% CV in rice and 14.18 with 25.47% CV in wheat crop.

Improvements: The trend of productivity for different crops is important factor for successful planning and decision making for the policy makers. Forecasting also plays a crucial role in agricultural, business, industrial, government and institutional planning because many important decisions depend on the anticipated future values of certain variables.


Keywords

ARIMA, Polynomial Models, Compound Growth Rates, Instability Indices, Trend.
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  • Anonymous. District-wise area, production and yield of important food and non-food crops in Gujarat state. Directorate of Agriculture, Gujarat state, Gandhinagar. 2012-13.

  • V. K. Boken. Forecasting spring wheat using time series analysis: A case study for the Canadian prairies. Agronomy Journal, 2000; 92(6), 1047-1053.

  • Anonymous. The drought of 1987, Response and management. Department of Agriculture and Co- operation, ministry of Agriculture, GOI, New Delhi. 1990; 1.

  • A. D. Kalola, J. S. Patel, R. Lakshminarayana. Trends and variability in area, production and productivity of tobacco in Gujarat. Tobacco Development Journal. 1995; 3(4), 37-43.

  • R. C. Hasija, L. S. Kausik, K. S. Suhag, D. R. Aneja. Growth and trend in area, production and productivity of wheat in Hariyana. Agriculture Science Digest. 2004; 24(2), 91-94.

  • P. C. Padhan. Applications of ARIMA model for forecasting agricultural productivity in India. Journal of Agriculture and Social Science. 2012; 8, 50-56.


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  • Comparative Evaluation of Different Statistical Models for Explaining Productivity Trend of Rice and Wheat Crops in North Gujarat Zone

Abstract Views: 271  |  PDF Views: 175

Authors

R. L. Yadav
Department of Agricultural Statistics, B. A. College of Agriculture, Anand Agricultural University, Anand- 388110 (Gujarat), India
A. D. Kalola
Department of Agricultural Statistics, B. A. College of Agriculture, Anand Agricultural University, Anand- 388110 (Gujarat), India

Abstract


Objective: To identify the appropriate trend equations, compound growth rates and instability indices of productivity of rice and wheat crops in North Gujarat zone in India.

Methods: The present study was made through fitting of different linear, non-linear and time series models. The time-series data from 1960-61 to 2012-13 on productivity of rice and wheat crops for North Gujarat zone were collected from Directorate of Agriculture, Gujarat state, Gandhinagar.

Findings: It was found that among different polynomial models, linear model for rice and cubic model for wheat were best fitted for productivity trend and in case of ARIMA models, ARIMA (0,1,1) was evolved as the best fitted trend functions for productivity of both rice and wheat crop. The compound growth rates for productivity were 6.65% and 3.99 % annually in rice and wheat crop, respectively. The instability indices were observed 24.72 with 44.49% CV in rice and 14.18 with 25.47% CV in wheat crop.

Improvements: The trend of productivity for different crops is important factor for successful planning and decision making for the policy makers. Forecasting also plays a crucial role in agricultural, business, industrial, government and institutional planning because many important decisions depend on the anticipated future values of certain variables.


Keywords


ARIMA, Polynomial Models, Compound Growth Rates, Instability Indices, Trend.

References