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Academic literature on the topic 'AGMARKNET'
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Journal articles on the topic "AGMARKNET"
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Suri, P. K., and Sushil. "E-Governance through Collaborations - A Case of NICNET based Agricultural Marketing Information Network (AGMARKNET)." Management Dynamics 7, no. 1 (April 26, 2022): 33–44. http://dx.doi.org/10.57198/2583-4932.1198.
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Prakash, P., D. Jaganathan, Sheela Immanuel, Achal Lama, J. Sreekumar, and P. S. Sivakumar. "Forecasting of Sweet Potato (Ipomoea batatas L.) Prices in India." Indian Journal of Extension Education 58, no. 2 (2022): 15–20. http://dx.doi.org/10.48165/ijee.2022.58203.
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Due to the semi-perishable nature of sweet potato the price fluctuation occur based on demand and supply. Hence, it becomes necessary to precisely forecast market price of sweet potato. Price forecasting of sweet potato was carried out for six selected states in India using time series monthly market price, collected from AGMARKNET price portal from January 2010 to December 2021. Exponential Smoothing Models (ESM), Seasonal Autoregressive Integrated Moving Average (SARIMA) model and Time Delay Neural Network (TDNN) model were used for forecasting of sweet potato price. It was observed that among the forecasting models, the TDNN model predicted accurate future prices of sweet potato based on the lowest Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) than SARIMA and ESM. The forecast indicated that the average market price of sweet potato in selected states of India viz., Kerala, Odisha, Gujarat, Karnataka, Maharashtra and Telangana, would be in the range of Rs. 684 to Rs. 2757 per quintal during January 2022 to December 2022. The forecasted price of sweet potato would provide valuable information to the sweet potato growers, government institutions and other stakeholders in the sweet potato value chain to take appropriate decisions on production, marketing and consumption of sweet potato.
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Chavan, Sanket D., Virendra Singh, Shyam Mani Tripathi, and Katta Sravan Naga Parimala Kumar. "Analysis of Spatio-Temporal Behaviour of Arrivals and Prices in Major Onion Markets of India." International Journal of Environment and Climate Change 13, no. 10 (August 22, 2023): 822–33. http://dx.doi.org/10.9734/ijecc/2023/v13i102722.
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The present study was an attempt to examine the behaviour of arrivals and prices of onion in major markets of India over the period from 2008 to 2022. The entire investigation relies on data obtained from secondary sources. Data on monthly wholesale prices and arrivals of selected markets was gathered from Agmarknet, Directorate of Marketing & Inspection, Government of India. Six markets were selected purposively, of which one each market was from four top onion producing states (Lasalgaon, Bangalore, Indore and Ahmadabad) and two were from top consuming cities (Mumbai and Delhi). Various statistical measures were such as linear trend analysis, ratio to trend method of seasonality and coefficient of variation were used to examine trend, seasonality, and inter-year prices variation, respectively in onion arrivals and prices in the selected markets. The findings of the trend analysis indicate that all markets experienced a significant increase in both arrivals and prices throughout the study period, except for the Delhi market, which showed a negative trend in arrivals. The seasonality indices reveal that prices tended to be higher from the month of August to January, while they were lower from February to July. Interestingly, an inverse relationship between onion arrivals and prices could not be established.
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PAUL, RANJIT KUMAR, DIPANKAR MITRA, HIMADRI SHEKHAR ROY, A. K. PAUL, and M. D. YEASIN. "Forecasting price of Indian mustard (Brassica juncea) using long memory time series model incorporating exogenous variable." Indian Journal of Agricultural Sciences 92, no. 7 (April 6, 2022): 825–30. http://dx.doi.org/10.56093/ijas.v92i7.103633.
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The objective of present study was to investigate the efficiency of Autoregressive fractionally integrated movingaverage model with exogenous input (ARFIMAX) in forecasting price of Indian mustard [Brassica juncea (L.) Czern.& Coss]. The daily modal price and arrival data of mustard for two major markets of India, viz. Bharatpur and Agrawere collected during 2008–2018 from AGMARKNET and used for the present investigation. It was observed thateach of the price series under consideration is stationary but autocorrelation function of both the series decay in ahyperbolic pattern. This indicates possible presence of long memory in the price data. Moreover, the significant result of correlation between price and arrival indicate that arrival data could be used as exogenous variable to model and forecast the price for both markets. Accordingly, Autoregressive fractionally integrated moving average (ARFIMA) and ARFIMAX models were applied to obtain the forecasts. The forecast evaluation was carried out with the help of Relative mean absolute percentage error (RMAPE) and Root mean square error (RMSE). The residuals of the fitted models were used for diagnosis checking as well as to investigate the adequacy of developed model. To this end, a comparative study has also been made between the fitted ARFIMAX model and ARFIMA model for both in-sample and out-of-sample data to identify the best fitted model in order to forecast future prices. The model has demonstrated a good performance in terms of explained variability and predicting power.
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Abinaya, R., R. Salvadi Easwaran, K. M. Shivakumar, M. Prahadeeswaran, and N. Raja. "Spatial Market Integration of Major Copra Markets in India." Asian Journal of Agricultural Extension, Economics & Sociology 41, no. 9 (July 22, 2023): 568–74. http://dx.doi.org/10.9734/ajaees/2023/v41i92078.
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Aim: The main aim of the study is to estimate the degree of market integration among the selected major Copra markets in India.
Place and Duration of Study: The study was carried out using the secondary data of average monthly prices of copra obtained from the AGMARKNET website from the period of 2014-2021 for Tamil Nadu and Karnataka. Copra price series data of Tamil Nadu (Anaimalai, Avalpoondurai, and Vellakoil markets) and Karnataka (Tiptur market) has been utilized for the study.
Methodology: The time-series econometric tools including the Augmented Dickey-Fuller (ADF) test, Johansen cointegration test, and Granger causality test were used for analyzing the level of market integration. E-views software has been utilized to perform the entire analysis.
Results: The unit root effects were applied to the price series for copra in the selected markets, and they were stationary at their first difference. The long-run equilibrium relationship among the copra markets revealed that the selected markets were integrated with each other. Tiptur market exhibited a bidirectional causational relationship with Anaimalai, Avalpoondurai, and Vellakoil markets. The Granger Causality test revealed the Tiptur market as the lead market, as it influenced the prices of Anaimalai, Avalpoondurai, and Vellakoil Copra markets.
Conclusion: India's coconut market is prone to volatility and uncertainty due to frequent price fluctuations. Price changes typically result from altered market conditions brought on by seasonal and annual variations in output, in addition to competition from other edible oils. The government can put measures into place to lessen price fluctuations with the aid of integrated market information and the information would also benefit the Copra producers and other market players to select the most effective market.
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Mamatha, Narayanaswamy, K. M. Shivakumar, A. Vidhyavathi, and D. Murugananthi. "Assessment of Level of Market Integration in Indian Cotton Markets." Asian Journal of Agricultural Extension, Economics & Sociology, July 28, 2022, 534–39. http://dx.doi.org/10.9734/ajaees/2022/v40i1031109.
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The current study is aimed at using co-integration in assessing the level of market integration among selected cotton markets in India. Monthly cotton price data were collected for the period 2008-09 and 2016-17 from the AGMARKNET website. The advanced time series econometric tools like Augmented Dickey-Fuller (ADF) test, Johansen co-integration test and Granger Causality test were used to study market integration using E-Views software. The price series for cotton in selected markets were subjected to the consequences of unit root and were stationary at first difference. The long-run equilibrium relationship among the cotton markets indicated that these markets were integrated with each other. This implied that prices in Indian cotton markets tend together in response to changes in the demand and supply of cotton. Granger Causality test revealed that the Salem market was the lead cotton market because it influenced the prices of Kurnool and Warangal cotton markets.
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"Seasonality Analysis of Onion with Special Reference to Wholesale Markets of Gujarat." Indian Journal of Economics and Development, March 17, 2023, 188–94. http://dx.doi.org/10.35716/ijed/22103.
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The study was conducted about the wholesale markets of Gujarat state with a study period of seventeen years for onion crops (January 2004 to December 2020). These data were collected from various portals such as NHRDF, Agmarknet, and NHB. The data collected were subjected to statistical analysis using different software such as R and E-views. Twelve monthly moving average was used to analyze the seasonal behaviour in arrivals and prices of onions. Seasonal indices of onion explained onion arrivals were higher in the first half of the year but relatively declined during the second half of the year in the Mahuva, Ahmedabad and Gondal markets. The variation between the lowest and highest intra-year price rise aligned between the lowest (11.79 per cent) in the Mahuva market to the highest (71.08 per cent) in the Gondal market for onion. The maximum value of the coefficient of variation (CV) for onion was witnessed in Gondal (92.94 per cent) market, followed by Ahmedabad (82.78 per cent) and Mahuva (82.16 per cent). Proper transmission of price signals from one market to another assist in price stabilization and foster healthy competition. It would also aid in defending the interests of producer sellers.
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"Impact of Pandemic Covid-19 on Vegetable Marketing in Punjab: An Analysis of Prices and Arrivals." Indian Journal of Economics and Development, June 12, 2021, 331–38. http://dx.doi.org/10.35716/ijed/20215.
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Covid-19 has had a very massive impact on the lives of the people and the economy. This study attempted to look at the vegetable markets in Punjab for 14 weeks, from the first week of March to the second week of June . The data were 2020 collected for four main vegetables of the Rabi crop, namely capsicum, bottle gourd, brinjal, and potato, for which the data was taken from the agmarknet website. A total of 115 mandis were covered, and the data for arrivals and prices were taken for this period. The results showed that leaving bottle gourd, the output for all the other three crops went down. In the case of bottle guard, the arrival went up by 10.6 percent, whereas for brinjal, it went down by 30.1 percent, capsicum by 16.5 percent, and potato by 44.4 percent. The weighted average for the price was taken to calculate the loss from the sales. It was noticed that in absolute terms, the loss was to the tune of 23.8 crores than the previous year. A look at the total traded volume for this period, and the loss came out to be around 23.5 percent of the losses have just come from these four crops.
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THAKUR, AMIT, POULAMI RAY, KAMLESH KUMAR ACHARYA, ABHIJIT DAS, RAJ JAISWAL, UNNI RAVISHANKAR, RAJU R, and SENDHIL R. "Price dynamics in Indian wholesale wheat markets: Insights and implications." Indian Journal of Agricultural Sciences 91, no. 8 (September 24, 2021). http://dx.doi.org/10.56093/ijas.v91i8.115880.
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Wheat is an integral part of food as well as nutrition security holding a significant share in the consumption basket. Hence, any extreme deviations in the staple food price will affect the prospects of the economy. In the context, we analysed the price dynamics and price volatility in Indian wholesale wheat markets using compound annual growth rate, instability indices, and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) model. The study sourced monthly data (July 2002 to June 2019) from the AGMARKNET portal for 15 states. Research findings indicated that the wholesale price, as well as divergence between maximum and minimum price, was highest in the case of Kerala implying the non-production region. Monthly price indices (highest as well as lowest in Haryana respectively during December: 109.90 and July: 91.48) exhibited a clear-cut seasonality attributed to the wheat arrivals post-crop harvest. Barring Maharashtra, the growth and variation in seasonal price indices were positive and relatively low respectively across markets. Corroborating the price trend, Kerala exhibited the highest volatility as evident by the GARCH model estimates, followed by Gujarat, Haryana and Chhattisgarh. Inter alia, volatility in wheat prices is directly linked to regional production. The study advocates for effective dissemination of market information such as price forecast, demand and supply to counter the price volatility as well as decision making for profitable agri-business.
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Kumar, Mohit, A. S. Shaikh, and Rohit Kumar Sharma. "Market Integration and Price Transmission Analysis of Onion in Wholesale Markets of India." Asian Journal of Agricultural Extension, Economics & Sociology, December 20, 2022, 164–71. http://dx.doi.org/10.9734/ajaees/2022/v40i121778.
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The present study was done in seven major onion wholesale markets in India, namely Pimpalgaon, Lasalgaon, Solapur, Pune, Bangalore, Hyderabad and Indore to explore the interdependence of wholesale prices amongst Indian onion markets. The study was conducted in all India perspective and the study period involves the seventeen years data of onion wholesale prices (January 2004 to December 2020). The study was majorly based on the prices of onion obtained through secondary source. These data were collected from various portals such as FAO, NHRDF, Agmarknet and NHB. The current study employs co-integration analysis of wholesale monthly onion prices in selected marketplaces to determine the degree of market integration. The Trace and Maximum Eigen-value tests results showed that the onion prices in India moves together in the long run equilibrium. As a result, it may be stated that India's onion markets are well-functioning. The direction of information flow was determined by using Granger Causality test. It was found that in few markets pairs, price transmissions were bi-directional whereas between Bangalore and Pune market, no transmission was found. The study reveals that Lasalgaon market is dominating in terms of price determination. The empirical study also recommends keeping a careful eye on diverse market behavioural patterns, since "news" in one market might have an influence on other markets due to the numerous interdependencies.
Dissertations / Theses on the topic "AGMARKNET"
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BAKSHI, SOHAIL. "DEVELOPING A DIAGNOSTIC TOOL AND TIME SERIES ANALYSIS IN RESPECT OF WHEAT ARRIVALS AND PRICES." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16998.
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Timely disseminating marketing related information of agricultural commodities throughout the country is essential in today’s scenario. AGMARKNET portal is one such initiative to collect, compile and disseminate prices and arrival data of agricultural commodities. The information that this portal provides is critical to all the stakeholders associated with agriculture. AGMARKNET aims to deliver correct and complete information to the farmers in order to strengthen their economic position. Farmers can know before going to the markets the price at which the crop can be sold which brings them in a better bargaining position. Consumers can benefit too as this will bring transparency in arrivals, curbing hoarding.
This study aims to develop a diagnostic for major markets where wheat arrivals are high. This diagnostic tool will help the data entry operators to have various checks on the entire process of data entry. Thereby, improving the data quality by monitoring the data reporting process continuously. Statistical Process Control (SPC) can help the correct reporting of data. Microsoft Excel 2016 was used for diagnostic tool development.
The second objective of the study is to forecast the modal prices of wheat for a particular variety using time series modeling. Data filtering, sorting and cleaning are the essential tasks conducted as part of this process. The time series modeling has been attempted to forecast wheat prices in 2017. Microsoft Excel 2016 and Eviews 9 have been used for time series analysis.