TIME SERIES ANALYSIS OF PADDY (DHAN) ON THE BASIS OF ARRIVAL & PRICES & BUILDING A DIAGNOSTIC TOOL

Abstract

The AGMARKNET website (http://www.agmarknet.nic.in) is an initiative taken by the Directorate of Marketing and Inspection, Ministry of Agriculture and Farmer Welfare, Government of India, with the aim of collecting and disseminating marketing related information of agricultural commodities throughout the country. It is an online G2C e- governance portal which caters to the needs of various stakeholders such as farmers, policy makers, industry, & academic institutions by providing agricultural marketing related information from a single Platform. The portal has helped to reach farmers who do not have sufficient resources to get adequate market information. It facilitates web- based information flow, of the daily arrivals and prices of commodities in the agricultural produce markets spread across the country. Such information will enable the farmers to obtain fair returns on their produce. For consumers, it means that they will be able to obtain agricultural produce at fair and affordable prices. To achieve these objectives, it is necessary that the information being recorded and disseminated by the AGMARKNET portal be of accurate and reliable nature. The fact that this information is also intended to be used for national level agricultural policy decisions makes it even more crucial for the information to be highly accurate and complete in all aspects. This study aims to forecast the modal prices of Paddy(Dhan) for a particular variety (Paddy fine) using time series modeling, data cleansing, filtering, soring, are the essential tasks conducted as a part of this process. The time series modeling has been attempted to forecast Paddy prices in 2017. Microsoft Excel 2013 & E views 9.5 Lite have been used for time for time series analysis. The second objective of the study is to develop a diagnostic tool for major markets where paddy(dhan) arrivals are high. The diagnostic tool will help the data quality by monitoring the data reporting process continuously. Microsoft Excel was used for developing the diagnostic tool