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Agricultural Market Intelligence Center–A Case Study of Chilli Crop Price Forecasting Intelangana


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1 Department of Agricultural Economics (A.M.I.C.), College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad (Telangana), India
     

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Indian is an agriculture based country, where more than 50 per cent of population is depend on agriculture. This structures the main source of income. The commitment of agribusiness in the national income in India is all the more, subsequently, it is said that agriculture in India is a backbone for Indian Economy. The majority of the rural producers are unable to understand and interpret the market and price behaviour to their advantages. Hence, market information and intelligence are crucial to enable farmers and traders to make informed decisions about what to grow, when to sell, and where to sell. The price forecasts are made by analyzing the prices of agricultural commodities concerned over 17 years using advanced statistical tools like ARIMA, ARCH, GARCH models, comparing the same with prices of futures markets and national and international reports of trade surveys besides conducting state level trade surveys. Under the project price forecasts were made for chilli twice once during Kharif season for 2 years fromKharif 2017-18 and 2018-19. Thus, out of total 4 price forecasts 3 price forecasts with more than 90 per cent precision were developed and disseminated through various means like university website, university magazine “Vyavasayam”, SMS to contact farmers, All India radio, farmers’ trainings and meetings, etc.

Keywords

Agricultural Market, Intelligence Center, Chilli Crop.
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  • Bharathi, R., Havaldhar, Y.N., Megeri, S.N. and Patil, G.M. (2009). Forecasting of arrivals and prices in Ramnagar and Siddlagatta market. J. Indian Society Agric. Stat., 63(3). 247-257.
  • Box, G.E.P. and Jenkin, G.M. (1976). Time series of analysis. Forecasting and Control, Sam Franscico, Holden Day, California, USA.
  • Haridev Singh, E. (2013). Forecasting tourist Inflow in Bhutan using seasonal ARIMA. Internat. J. Sci. & Res., 9 (2) : 242 - 245.
  • Meyler, Aidan, Kenny, Geoff and Quinn, Terry (1998). Forecasting Irish inflation using ARIMA models, Central Bank and Financial Services Authority of Ireland Technical Paper Series, Vol. 1998, No. 3/RT/98 (December 1998), pp.1-48.
  • Paul, R. K., Alam, Wasi and Paul, A.K. (2014). Prospects of livestock and dairy production in India under time series framework. Indian J.Anim. Sci., 84 (4): 462–466.
  • Prajneshu and Venugopalan, R. (1998). On non-linear procedure for obtaining length - weight relationship. Indian J. Anim. Sci., 68 (1) : 452-456.
  • Singh, S., Ramasubramanian,V. and Mehta, S.C. (2007). Statistical models for forecasting rice production of India. J. Indian Soc. Agric. Statist., 61(2) : 80- 83.
  • WEBLIOGRAPHY
  • http://agrimarketing.telangana.gov.in/indexnew.jsp.

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  • Agricultural Market Intelligence Center–A Case Study of Chilli Crop Price Forecasting Intelangana

Abstract Views: 647  |  PDF Views: 0

Authors

R. Vijaya Kumari
Department of Agricultural Economics (A.M.I.C.), College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad (Telangana), India
Panasa Venkatesh
Department of Agricultural Economics (A.M.I.C.), College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad (Telangana), India
G. Ramakrishna
Department of Agricultural Economics (A.M.I.C.), College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad (Telangana), India
A. Sreenivas
Department of Agricultural Economics (A.M.I.C.), College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad (Telangana), India

Abstract


Indian is an agriculture based country, where more than 50 per cent of population is depend on agriculture. This structures the main source of income. The commitment of agribusiness in the national income in India is all the more, subsequently, it is said that agriculture in India is a backbone for Indian Economy. The majority of the rural producers are unable to understand and interpret the market and price behaviour to their advantages. Hence, market information and intelligence are crucial to enable farmers and traders to make informed decisions about what to grow, when to sell, and where to sell. The price forecasts are made by analyzing the prices of agricultural commodities concerned over 17 years using advanced statistical tools like ARIMA, ARCH, GARCH models, comparing the same with prices of futures markets and national and international reports of trade surveys besides conducting state level trade surveys. Under the project price forecasts were made for chilli twice once during Kharif season for 2 years fromKharif 2017-18 and 2018-19. Thus, out of total 4 price forecasts 3 price forecasts with more than 90 per cent precision were developed and disseminated through various means like university website, university magazine “Vyavasayam”, SMS to contact farmers, All India radio, farmers’ trainings and meetings, etc.

Keywords


Agricultural Market, Intelligence Center, Chilli Crop.

References