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Nsabimana, Aimable, Fidele Niyitanga, Dave D. Weatherspoon et Anwar Naseem. « Land Policy and Food Prices : Evidence from a Land Consolidation Program in Rwanda ». Journal of Agricultural & ; Food Industrial Organization 19, no 1 (2 mars 2021) : 63–73. http://dx.doi.org/10.1515/jafio-2021-0010.
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Abstract Rwanda’s “Crop Intensification Program (CIP)” is primarily a land consolidation program aimed at improving agricultural productivity and food security. The program, which began in 2007, focuses on monocropping and commercialization of six priority crops: maize, wheat, rice, white potato, beans, and cassava. CIP has facilitated easy access to improved seed stocks, fertilizer, extension services, and postharvest handling and storage services. Although studies have documented the impact of CIP on changes in farm yield, incomes, and productivity, less is known about its impact on food prices. In this study, we examine the crop-food price differences in intensive monocropped CIP and non-intensive monocropped CIP zones in Rwanda. Specifically, the study evaluates price variations of beans and maize along with complementary food crops in intensive and non-intensive monocropped zones before and after the introduction of the CIP policy. We find that the CIP policy is not associated with differences in CIP crop prices between the intensive and non-intensive monocropped zones. Over time, prices increased for CIP crops but generally, the crop prices in the two zones were cointegrated. Prices for non-CIP crops in the two different zones did show price differentials prior to the implementation of CIP, with the prices in intensive monocropped zones being greater than in the non-intensive monocropped zones. Moreover, the prices in intensive areas are cointegrated with prices in non-intensive areas for maize and beans and these prices are converging. This indicates that farmers who intensively produced one CIP crop were able to go to the market and purchase other food crops and that price differences between zones have decreased over time, potentially making the CIP intensive farmers better off.
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Ghutake, Ishita, Ritesh Verma, Rohit Chaudhari et Vidhate Amarsinh. « An intelligent Crop Price Prediction using suitable Machine Learning Algorithm ». ITM Web of Conferences 40 (2021) : 03040. http://dx.doi.org/10.1051/itmconf/20214003040.
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Planning of crops for the next season has been a tedious task for the farmers as it is a difficult prediction about metrics of prices that their crop will fetch in a particular season which will be typically based on dynamic weather conditions. This leads to inaccurate prediction of crops’ prices by farmers, and they happen to wrongly select the crops or in haste they happen to sell their crops early without storing and thus earning less than what the same crop would have fetched them in the future. This problem could be addressed by an ML model which will predict the prices of crops in advance showing the proper analysis of the crop and presenting their future scenario so that farmers can select the right crops to strategize crop production which involves crop selection, time of sowing deciding crop pattern and storage of harvested crops providing enough insights for predicting the appropriate price in the markets.
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Ramsey, A. Ford, Sujit K. Ghosh et Barry K. Goodwin. « Rating exotic price coverage in crop revenue insurance ». Agricultural Finance Review 80, no 5 (1 mai 2020) : 609–31. http://dx.doi.org/10.1108/afr-10-2019-0107.
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PurposeRevenue insurance is the most popular form of insurance available in the US federal crop insurance program. The majority of crop revenue policies are sold with a harvest price replacement feature that pays out on lost crop yields at the maximum of a realized or projected harvest price. The authors introduce a novel actuarial and statistical approach to rate revenue insurance policies with exotic price coverage: the payout depends on an order statistic or average of prices. The authors examine the price implications of different dependence models and demonstrate the feasibility of policies of this type.Design/methodology/approachHierarchical Archimedean copulas and vine copulas are used to model dependence between prices and yields and serial dependence of prices. The authors construct several synthetic exotic price coverage insurance policies and evaluate the impact of copula models on policies covering different types of risk.FindingsThe authors’ findings show that the price of exotic price coverage policies is sensitive to the choice of dependence model. Serial dependence varies across the growing season. It is possible to accurately price exotic coverage policies and we suggest these add-ons as a possible avenue for developing private crop insurance markets.Originality/valueThe authors apply hierarchical Archimedean copulas and vine copulas that allow for flexibility in the modeling of multivariate dependence. Unlike previous research, which has primarily considered dependence across space, the form of exotic price coverage requires modeling serial dependence in relative prices. Results are important for this segment of the agricultural insurance market: one of the main areas that insurers can develop private products around the federal program.
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Liang, Yan, J. Corey Miller, Ardian Harri et Keith H. Coble. « Crop Supply Response under Risk : Impacts of Emerging Issues on Southeastern U.S. Agriculture ». Journal of Agricultural and Applied Economics 43, no 2 (mai 2011) : 181–94. http://dx.doi.org/10.1017/s1074070800004156.
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In this paper we consider factors that affect both crop prices and yields in order to examine supply responses of major crops in the Southeast. Due to the variable nature of crop production in the Southeast, previous studies that ignore price and yield risk may fail to capture one of the salient features of the region's agriculture. Our results indicate supply elasticity values for corn, cotton, and soybeans of approximately 0.670, 0.506, and 0.195, respectively. Compared with the results of studies in other regions, corn and cotton acres respond more to price changes and soybean acres respond less to price changes.
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Ye, Minghua, Rongming Wang, Guozhu Tuo et Tongjiang Wang. « Crop price insurance in China : pricing and hedging using futures market ». China Agricultural Economic Review 9, no 4 (6 novembre 2017) : 567–87. http://dx.doi.org/10.1108/caer-12-2015-0178.
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Purpose The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market. Design/methodology/approach Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market. Findings The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks. Originality/value This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.
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BWALA, M. A., Y. ROSAINE et S. BAUER. « RISK PERCEPTION AMONG FARM HOUSEHOLDS IN NORTH CENTRAL REGION OF NIGERIA : A LOWER PARTIAL MOMENT APPROACH ». Journal of Agricultural Science and Environment 15, no 1 (2 mars 2016) : 48–59. http://dx.doi.org/10.51406/jagse.v15i1.1473.
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This study investigated the perception of production and price risk by farm households and the factors that influence their level of perception in North Central Nigeria. The study attempted to capture the opinion of farmers about the quantity of crops they expect to harvest at the end of the season, and the prices they also expect for each of the crop cultivated. It was confirmed that the households do have an opinion for the quantity of crops outputs cultivated and also for the price they expect at the end of every season. The study established that farm households do give negative allowances regarding the quantity expected of a crop for a particular land cultivated, this is also true for prices expected. In other words farm households were found to be aware of the possibility that the final output they get from their farming activity may not commensurate with the inputs invested and so therefore expect less than what should be the potential. Furthermore, it was discovered that household crop specific risk percep- tion varies within the region. Majority of the farm households perceived higher price risks for sorghum, rice, and yam crops.
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Shafer, Carl E. « Price and Value Effects of Pecan Crop Forecasts, 1971–1987 ». Journal of Agricultural and Applied Economics 21, no 1 (juillet 1989) : 97–103. http://dx.doi.org/10.1017/s0081305200000959.
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AbstractPrice equations incorporating USDA October crop forecasts and June pecan stocks provided reasonable formulations for pecan price explanation and forecasting. USDA crop forecasts exceeded final reported production in 12 of the 18 seasons from 1970 to 1987, probably resulting in slightly lower prices and crop values. Large crop forecast errors in both direction and level in 1986 and 1987 confounded the price determination process. Nevertheless, producer prices may have been lower absent the October crop forecasts, which somewhat reduce buyers' uncertainty regarding supply. Early crop estimates provided a better explanation of price behavior than postseason revised production data.
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V, Niharika. « Crop Gen Forecast ». International Journal for Research in Applied Science and Engineering Technology 10, no 8 (31 août 2022) : 472–77. http://dx.doi.org/10.22214/ijraset.2022.46222.
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Abstract: Primary source of Indian livelihood is Agriculture. It has become a strenuous task for the farmers to plan the crops for the next season as it is a critical prediction about the prices that their harvest might yield in that particular season that will be based on driving weather conditions. This in turn results in imprecise prediction of crop prices by farmers which leads in choosing the fallacious crops or in quickly sell their yield resulting in low revenue. The same crop would have gained more value in the future. This paper mainly aims at addressing these issues by using Machine learning algorithms where the input is given through the sensors as live data and the result is displayed on a webpage. The webpage consists of a recommendation engine and the price prediction data of each crop in that particular region.
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Guenthner, Joseph F. « Forecasting Annual Vegetable Plantings ». HortTechnology 2, no 1 (janvier 1992) : 89–91. http://dx.doi.org/10.21273/horttech.2.1.89.
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Vegetable producers and marketers make business decisions based on supply estimates. The U.S. Dept. of Agriculture provides estimates of planting intentions for field crops but not for most vegetable crops. This study developed models that can be used to forecast vegetable crop plantings. Multiple linear regression analysis was used to determine the factors that influence plantings of potatoes and onions. Field crop planting intentions, industry structure, lagged values of plantings, prices received, price volatility, and the price of sugar beets were found to be significant factors. The models and/or methods used in this study should be useful to those interested in forecasting vegetable plantings.
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N, Karunakaran. « Growth of Crop-output in Kerala–Is it Real or monetary ? » Artha - Journal of Social Sciences 14, no 4 (1 octobre 2015) : 89. http://dx.doi.org/10.12724/ajss.35.5.
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The main feature of the development of agriculture in Kerala in the last five decades is the change in cropping pattern and shift in cultivation, that is, shift in the cultivated area under food grain crops to non-food grain crops and shift in the cultivated area under one non-food grain crop to another non-food grain crop. The growth of agricultural crop output and productivity has been affected by many factors. The sources of output growth like area effect, yield effect and cropping pattern effect have relevance in deciding the programmes of agricultural development and priorities of investment in it. The growth of agricultural output in the state like that of other parts of India is influenced by the gross cropped area, productivity and level of prices. The increase in the agricultural crop output is decomposed into real and monetary components. The real component includes area effect, yield effect, cropping pattern effect and interaction effect. The monetary elements consist of the pure price effect, price yield effect, price cropping pattern effect and total interaction effect. From the analysis of thedecomposition of output growth into real and monetary components of Kerala agriculture in the last five decades, the general conclusions arrived at are: price factor is the major element in determining the relative contribution of different elements to the growth of crop output and the overall growth in the Kerala agriculture is monetary growth in nature rather than real growth.
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Tew, Bernard V., et Donald W. Reid. « Probability Distributions of Crop Prices, Yields, and Gross Revenue ». Northeastern Journal of Agricultural and Resource Economics 17, no 2 (octobre 1988) : 118–24. http://dx.doi.org/10.1017/s0899367x00001744.
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This study shows that the price-yield correlation is a major influence in determining the skewness of revenue. Therefore, normality for revenue may not be rejected even if the price and/or yield distributions are significantly skewed. Analysis of cotton revenue for Mississippi shows that this can be the case empirically when the correlation between price and yield is moderately negative and the relative variability of yield and price is not too high. Hence, for crops produced in their major production regions where negative correlations between prices and yields are the greatest, revenue distributions may have a greater tendency toward normal.
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Maniriho, Aristide, Edouard Musabanganji et Philippe Lebailly. « A Comparative Study between Major Crop (Potato) and Minor Crop (Onion) in Volcanic Highlands of Rwanda ». Journal of Agriculture and Crops, no 82 (4 mars 2022) : 68–74. http://dx.doi.org/10.32861/jac.82.68.74.
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This paper aims to assess the competition between the priority (major) crops and the non-priority (minor) crops. Competition between crops is defined as the significant major differences between two crops in terms of production costs and their performance. Data were collected using a questionnaire administered to a random sample of 226 small-scale crop producers including 94 onion producers and 132 potato producers. The T-test was conducted to state whether there is a significant difference of mean land sizes, mean crop yields, mean selling prices, and mean net farm incomes between the two groups of crop producers. Results showed non significant difference between the mean land size allocated to onion production and that allocated to potato farming. Results also indicate that onion yield is significantly greater than potato yield, onion selling price is significantly greater than that of potato, and the net income from onion production is far away greater than the income from potato production. It is remarkable that, in some circumstances, the authorities may prioritize and thus propose to farmers the crops that are less competitive considering their price, yield or income, if the current climatic conditions and economic settings are maintained in the medium or long term. Referring to these findings, policy efforts should encourages to the farmers to shift from potato farming to onion production, or simply inclusion of crop diversification via adopting onion may be the best option to maximize the potentials of the selected crops.
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Cariappa, A. G. Adeeth, Babita Kathayat, S. Karthiga et R. Sendhil. « Price analysis and forecasting for decision making : Insights from wheat markets in India ». Indian Journal of Agricultural Sciences 90, no 5 (4 septembre 2020) : 979–84. http://dx.doi.org/10.56093/ijas.v90i5.104376.
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Wheat occupies a prime position in supplementing the food security needs of India. Price forecast related to a food commodity is essential in executing policies which ensure market support. Keeping this in view, an attempt was made to forecast monthly wholesale wheat prices adopting ARIMA model in spatially separated markets of India using the historical data sourced from AGMARK price portal (July 2002-June 2018). Wheat prices exhibited a clearcut seasonality captured through monthly price indices. The prices were found to be highest during the crop season (November-March) as it is the production phase lacking market supply and lowest during post-harvest season (June- October) wherein supply surge is witnessed. The average seasonal price variation and intra-year price rise were found to be highest in Haryana, followed by Punjab. Forecasted prices estimated by fitting the ARIMA model were found to be higher for low or negligible wheat producing states such as Kerala and Karnataka, and lower for higher wheat producing states like Haryana, Punjab, Madhya Pradesh and Uttar Pradesh. Forecast performance the fitted models were further supported by using measures like RMSE, MAPE and MAE with 95% confidence interval. The study emphasized the need for effective dissemination of market information such as price forecast to farmers, agri-based industries and other concerned stakeholders which will help in decision making apart from tracking price volatility.
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Jiang, Yangming, Tuo Wang, Huihui Zhao, Xiaodong Shao, Weihong Cui, Kun Huang et Lingping Li. « Big Data Analysis Applied in Agricultural Planting Layout Optimization ». Applied Engineering in Agriculture 35, no 2 (2019) : 147–62. http://dx.doi.org/10.13031/aea.12790.
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Abstract. Mile is a region in Yunnan Province, China. The planting-related industry is its pillar industry. Its agricultural population accounts for 59.3% of the total population. Temporal fluctuations of crop price and yield have a significant influence on farmers’ revenue. Farmers’ selection of crop species, crop planting strategy, and agricultural planting layout according to the market price is important in securing their revenue. In this study, we used a web crawler program to obtain a large amount of data on agricultural product prices from the Internet. Then, the price fluctuation trend of the main economic crops was analyzed by using the K-means clustering method. The net investment yield and the Sharpe ratio were used to compare the economic benefits and investment risks of 10 crops and five cultivation strategies in Mile. Furthermore, a comprehensive comparative advantage index, which integrates the net investment yield, Sharpe ratio, scale advantage index, productivity advantage index, and ecological suitability advantage index, was adopted to comprehensively measure the advantages of crop cultivation. Finally, we propose a spatial-temporal big data analysis model based on the cuckoo search algorithm to optimize the spatial layout of the main crops in Mile in 2017. Based on the comparative analysis of the remote sensing monitoring results and the spatial optimization layout results of the main crops in 2017, several suggestions were given. The results based on agricultural big data analysis, such as crop selection cluster analysis, economic benefit analysis, and crop planting layout optimization, can give suggests to farmers plant suitable crops on right lands, in right time. Thus, it can help farmers stabilize their revenue and minimize the risk by choosing the right crops and planting strategy in accordance with the local conditions. Keywords: Agriculture investment risk, Agricultural layout optimization, Cuckoo search algorithm, K-means clustering, Relative advantage analysis, Spatial-temporal big data analysis.
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Regmi, Hem Raj. « Rising Food Price and Its Consequences ». Journal of Agriculture and Environment 9 (2 août 2009) : 93–97. http://dx.doi.org/10.3126/aej.v9i0.2123.
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Agricultural prices have risen worldwide sharply in the last two years, which has been a dilemma especially to policy makers. Higher agricultural prices would improve farmer's income and their living standards as well as investment in agriculture provided a fair mechanism of income transfer to them be instituted. However, the price rise seriously affects urban poors' food affordability and thus their livelihood. Various types of natural disasters particularly floods, droughts and landsides have affected agricultural crop production in Nepal resulting in fluctuations in food supplies and prices. Besides, policy measures associated with crop production, food balance and trade, petroleum price stabilization and liquor production directly or indirectly affect food market and prices. National food production, demand-supply, consumption and price scenarios and associated reasons are analyzed based on reviews of pertinent literatures. Key words: Food production, food consumption, demand-supply, price-scenario, NepalThe Journal of Agriculture and Environment Vol:.9, Jun.2008 Page: 93-97
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Kademani, Sanju. « Kisan Assistant (Crop Price Prediction) ». Asian Journal of convergence in Technology 8, no 1 (27 avril 2022) : 1. http://dx.doi.org/10.33130/ajct.2022v08i01.001.
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Edison, Edison, Dharia Renate et Denny Denmar. « DYNAMIC SUPPLY RESPONSE : IMPLICATIONS FOR INDONESIA SOYBEAN CROP ». Dinasti International Journal of Economics, Finance & ; Accounting 1, no 4 (23 septembre 2020) : 568–80. http://dx.doi.org/10.38035/dijefa.v1i4.530.
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The purpose of the study is to explore the supply response model of the soybean crop in terms of alternative specifications also implications economics. To apply model, considerations through the availability of production lags concept also the existence of expected price and gross revenue because of producer’s response explanatory preference on movement economic situation. The results showed that the existing lags were due mostly to the problems also quick adjustment expenditure rather than correcting expected time. The quantitative result was the same as gross margins and prices alternative specification as the availability of economic decisions. Meanwhile, elasticities price found through the model response specification tended around a fourth of the model applying price specification. The model response specification produced more explanation in terms of production also elasticity of input expenditure.
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Nalini, T., A. Rama, M. Shanmuganathan, Dahila Sam et Dr Adlin Sheeba. « The Empirical Analysis For Effective Prediction of Crop Price Using Neuro Evolutionary Algorithm based on Machine Learning Approach ». Journal of Physics : Conference Series 2251, no 1 (1 avril 2022) : 012006. http://dx.doi.org/10.1088/1742-6596/2251/1/012006.
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Abstract : Based on a neuro evolutionary algorithm, this study proposes a neural network model for efficient crop price prediction. When viewed from the perspective of agricultural business, the market price of corn reflects its current demand. For agricultural management, to improve profits, it is important to track and predict the market price. In this manuscript, a neural network model based on the output prediction of a neuro evolutionary algorithm is used to predict the price of the crop and compared with the existing Naive Bayes algorithm. By recognizing patterns in our training dataset, which serves as one of the inputs to the algorithm, we are able to determine the price of the crop. The parameters (Yield, Rainfall, Minimum Support Price, and Maximum Trade ) are fed to the algorithm by the user. It is compared with existing algorithms to determine the performance of the proposed algorithm. The features considered for the analysis are Climate, historical costs, location, demand indicators, and crop health are the variables used for predicting future corn crop cost. According to the empirical analysis, the proposed model is significantly more accurate in predicting crop prices.
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Smith, E. G., J. M. Barbieri, J. R. Moyer et D. E. Cole. « The effect of companion crops and herbicides on economic returns of alfalfa-bromegrass establishment ». Canadian Journal of Plant Science 77, no 2 (1 avril 1997) : 231–35. http://dx.doi.org/10.4141/p96-064.
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In moist regions and under irrigation in western Canada, there may be an economic advantage to using companion crops in forage establishment. Economic returns of establishing a mixture of alfalfa (Medicago sativa L.) and bromegrass (Bromus spp.) were determined with and without a companion crop of barley grain and silage (Hordeum vulgare L.) and with and without post-emergence herbicides at Westlock, Alberta under dryland, and with and without a companion crop of soft white spring wheat (Triticum aestivum L.) and with and without post emergence herbicides at Lethbridge, Alberta under irrigation conditions. The yearly economic benefit of companion crops was greater on irrigation than on dryland ($15 to $27 ha−1), higher for companion crops harvested for silage than for grain ($55 to $75 ha−1), and was dependent on the price of forage and grain. On dryland with medium product price levels, economic returns were 100% higher for a barley silage companion crop, and were 14% lower for a barley grain companion crop than without a companion crop. At high hay prices, returns for the barley silage companion crop were 5% higher than without a companion crop. On irrigation, the yearly economic returns with a companion crop were higher ($23 to $139 ha−1) than without a companion crop. The use of post-emergence herbicides had no long-term economic benefit for forage establishment and reduced yearly net returns $13 ha−1 on dryland and $41 ha−1 on irrigation. Key words: Companion crop, forage establishment, economics, herbicide
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Rodrigues, Gonçalo C., Francisco G. da Silva et José C. Coelho. « Determining Farmers’ Willingness to Pay for Irrigation Water in the Alentejo Region (Southern Portugal) by the Residual Value Method ». Agronomy 11, no 1 (13 janvier 2021) : 142. http://dx.doi.org/10.3390/agronomy11010142.
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This paper aims to determine farmers’ willingness to pay for irrigation water, using the residual value method, for the most representative crops at six Irrigation Communities from the Alentejo region, southern Portugal. The main objective of this assessment was to determine the value that farmers would be able to pay for the water to irrigate different crops at different locations, and to show that this approach can be used to provide information about farming economic sustainability and provide support on if crop prices need to be revised or if a national policy should be conceived to cover for farming costs. The results show that vegetables and fruit trees have the highest Residual Value of Water (RVW), while Wheat, Sunflower, Fodder crops, Semi-intensive Olive Orchards and Rice tend to have an RVW lower than the current variable irrigation water price. The results also show that, while, for Melon, Tomato, Onion, Super-high-density Olive Orchards, Peach and Almonds, both yields and price may decrease significantly, allowing one to save for faming inputs, Sunflower and Rice would require an increase in yields or prices to cover for the irrigation water price.
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Margarido, Mario A., Frederico A. Turolla et Carlos R. F. Bueno. « The world market for soybeans : price transmission into Brazil and effects from the timing of crop and trade ». Nova Economia 17, no 2 (août 2007) : 241–70. http://dx.doi.org/10.1590/s0103-63512007000200002.
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This paper investigates the price transmission in the world market for soybeans using time series econometrics models. The theoretical model developed by Mundlack and Larson (1992) is based on the Law of the One Price, which assumes price equalization across all local markets in the long run and allows for deviations in the short run. The international market was characterized by three relevant soybean prices: Rotterdam Port, Argentina and the United States. The paper estimates the elasticity of transmission of these prices into soybean prices in Brazil. There were carried causality and cointegration tests in order to identify whether there is significant long-term relationship among these variables. There was also calculated the impulse-response function and forecast error variance decomposition to analyze the transmission of variations in the international prices over Brazilian prices. An exogeneity test was also carried out so as to check whether the variables respond to short term deviations from equilibrium values. Results validated the Law of the One Price in the long run. In line with many studies, this paper showed that Brazil and Argentina can be seen as price takers as long as the speed of their adjustment to shocks is faster than in the United States, the latter being a price maker.
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AMASSAIB, Mahmoud Ali, Mohammed Salih Adam ABDALLA et Tarig GIBREEL. « Supply Response of Field Crops to Price and Environmental Factors in Traditional Rainfed Agriculture ». International Journal of Research and Innovation in Social Science 06, no 09 (2022) : 180–89. http://dx.doi.org/10.47772/ijriss.2022.6907.
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This study aimed to estimate supply response crops, i.e., sesame, groundnut, sorghum, and millet, in traditional rainfed agriculture, in North Kordofan State, Sudan, from 1990 to 2015. The response is estimated as the yield and area responses to prices, temperature, and rainfall. The study depended mainly on secondary data obtained from the records of the Ministry of agriculture and animal resources, Elobied Crops Market, and Elobied Airport Metrological Station. The co-integration and vector error correction approaches were applied to estimate the response. The results found that the estimated responses of crop yield in the long run to price were negative and inelastic for sesame, groundnut, and elastic for sorghum. It was positive and inelastic for yield millet yield. The estimated responses of crop area to price in the long run were negative and inelastic for sesame, sorghum, millet, and elastic for groundnut. The estimated responses of crop yield in the long run to temperature were negative and elastic for all crops and ranged from-24.01 to -197.83. The estimated responses of crop area in the long run to temperature were positive and elastic and ranged from 37.121 to 411.747.The estimated responses of crop yield to rainfall index, in the long run, were positive and elastic for groundnut (2.357), sorghum (4.667), and millet (1.142), but it is inelastic for sesame (0.509). The responses of crop area to rainfall index were negative and elastic and ranged from -13.745 to -1.086. The study concluded that rainfall index and temperature factors are the most dominating factors influencing yield and area behavior in the long-run, hence farmers’ decisions.
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DASTAGIRI, M. B., B. GANESH KUMAR, A. DHANDAPANI et NAGA SINDHUJA P V. « Economics of India’s agricultural domestic and international prices during WTO regime : signals and policies ». Indian Journal of Agricultural Sciences 92, no 5 (14 juin 2022) : 587–92. http://dx.doi.org/10.56093/ijas.v92i5.124668.
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Prices play a great role in living economics. Prices act as signals for shortages and surpluses which help government, firms, consumers to respond to changing market conditions. The study was conducted at NAARM, Hyderabad. The study period was from 1990–91 to 2018–19. Trends, growth rates, terms of trade, instability, elasticities, domestic and international agriculture price analysis were employed for achieving objectives. An increasing trend of MSP has been found in India’s major agricultural crops. Minimum Support Price (MSP) growth rate of pulses were more than cereals and oilseeds. WPI growth rate of pulse crops was greater than the cereal and oilseed crops except sorghum. The variation in WPI of major agricultural commodities in India was stable except sunflower. Consumer food price index has shown more or less linear trends. It indicates Government monitoring food prices stable. The variation inexport price of rice and sunflower and import price of sorghum was stable. The study found that India has comparative advantage for rice, gram, groundnut and soybean crops in international markets. The export price elasticities of rice, wheat, gram, groundnut, soybean and sunflower was observed to be marginally higher than their import price elasticities. The findings can be useful to government in designing price fixing mechanism and monetary policy, distortion of prices and control of inflation
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M Joshi, Aditi, et Sanjay G Patel. « Study of Agricultural Commodities Production and Price Movement in Gujarat Region : Demand and Sustainable Livelihoods ». Current Agriculture Research Journal 10, no 2 (10 septembre 2022) : 151–66. http://dx.doi.org/10.12944/carj.10.2.12.
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Since ancient times, agriculture has been one of the chief factors in the advancement of many nations. Also, it has been a huge contributor to the GDP (Gross Domestic Product). But the farmers and the small-scale retailers are still unaware of the demand and supply of the commodities in mandis. Ultimately, they are compelled to use the repetitive pattern of crops. Through knowledge of the intra-mandi prices for seasonal crops is necessary to gain the desired profit. Price trends in several Gujarat markets were investigated for Ajwain and Isabgol (Psyllium Husk) in order to forecast price volatility and problems that produce mandi-level projections, enhancing its usefulness. Given that medicinal crops have various medical and culinary uses, boosting their productivity could increase farmers' profits in comparison to typical pattern crops. So, the aim of this study is to evaluate the optimum preferred crop conditions for important commodities like Isabgol, Ajwain, Fenugreek, Mint and Raw turmeric with respect to profit. A data from the past decade was screened to observe the variation in prices of the crops along with production analysis. Also, it was validated statistically by various statical measures like Standard Deviation, Mean and Coefficient of Variation. We examined intra-mandi prices and found that prices fluctuate over the whole peak season, with notable fluctuations in modal prices among several mandis. To demonstrate the variations in pricing reported for certain mandis on specific days, we've given a few instances. A low standard deviation implies that the commodities price is clustered around the mean, whereas a large standard deviation shows that the commodities price is more dispersed. Price volatility is the discrepancy between what is anticipated and what occurs.
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Wawale, Surindar Gopalrao, Malik Jawarneh, P. Naveen Kumar, Thomas Felix, Jyoti Bhola, Roop Raj, Sathyapriya Eswaran et Rajasekhar Boddu. « Minimizing the Error Gap in Smart Framing by Forecasting Production and Demand Using ARIMA Model ». Journal of Food Quality 2022 (24 mai 2022) : 1–9. http://dx.doi.org/10.1155/2022/1139440.
Texte intégralRésumé :
Agribusiness employs more than 66 percent of India’s rural population and is the country’s economic backbone. Beat crop growth is essential for practical farming since it increases soil diversity and actual design, and it may be grown in blended frameworks. Crop growth rates, applicability, and yields have not improved significantly over time in the United States. Crops are defined by their seasonality, derived nature of demand, and relatively inelastic pricing. The general purpose of this research is to demonstrate the usefulness of price forecasting for agricultural prices and validate it for rice, which is consumed more in Indian states, for the year 2022, using time series data from 2016 to 2021. Every year, data for 50 days is collected and multiplied. The range of ten and its multiple is used for predicting. The results were obtained through the use of univariate analysis. To develop grain price estimates, researchers used Autoregressive Integrated Moving Average (ARIMA) methods, and the precision of the forecasts was examined using conventional mean square error (MSE) and mean absolute percentage error (MAPE) standards. As proven by the outcomes of ARIMA price predictions, the ARIMA model’s efficacy as a tool for price forecasting was effectively demonstrated by realistic models of projected prices for 2020. Because the MSA and MAPE values were lower, the forecast was more accurate. In addition, the price forecasting in this model is dependent on government incentives.
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Qamar, Wardah, Muhammad Younas et Muhammad Waseem. « Price Fluctuations of Rice Crop in District Sheikhupura ». Journal of Agricultural Studies 7, no 2 (21 août 2019) : 227. http://dx.doi.org/10.5296/jas.v7i3.15163.
Texte intégralRésumé :
This research was done to explore the trends by using variables basmati prices, area in which rice were sown, coarse varieties area, coarse varieties’ area and coarse varieties prices respectively to estimate the yield and productivity of basmati rice. According to the results of three models it was estimated that the price of basmati prices had a positive and significant effect on yield. The probability value showed the positive and significant effect on yield. Similarly, the area in which basmati sown had both significant and insignificant effect; the probability value of area sown in second models suggested the insignificant effect on yield. Another variable coarse variety area had a positive and significant effect on yield on all the three models that means this variable positively and significantly affecting the yield of basmati over the selected time. The variable of coarse varieties prices also had significant and insignificant effect, according to the probability value of this variable in third model the effect is positive but insignificant but other remaining two models are positive and significant. The last variable used i.e. coarse varieties prices had also positive and significant effect in all the three models, so it was estimated that this variable is positively affecting the yield of basmati rice. The Durbin Watson results showed that in first two models there is no autocorrelation because the value is in between 1.7 to 2.3 but in third model the value of Durbin Watson is not in the limit so it had autocorrelation among variables.
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Ahmed, Ather Maqsood, et Rizwana Siddiqui. « Supply Response in Pakistan with "Endogenous" Technology ». Pakistan Development Review 33, no 4II (1 décembre 1994) : 871–88. http://dx.doi.org/10.30541/v33i4iipp.871-888.
Texte intégralRésumé :
Considering the significance of agriculture sector in Pakistan's economy, one of the major objectives of agricultural policy has been to raise the level of real income of the farmer by stabilising the agricultural output through a system of price support programme. In the recent past, a number of studies have confirmed that Pakistani farmers respond to changes in output prices.! The prime objective of these studies was to estimate price, acreage or yield elasticities based on the Nerlovian Adjustment Model under alternative expectation schemes. Naqvi and Burney (1992) estimated output supply and input demand functions based on the profit function approach.2 Surprisingly, the single-equation supply model has been used extensively for policy analysis without noticing the fact that such a model does not guarantee that the harvested share of each crop will always be non-negative and the sum of shares of all crops will be unity. Similarly, models which are based on applied duality theory do not take into account the actual decision-making at the farm level. The sequence of events is such that farmer first allocates area across crops and then chooses the input levels conditioned on the allocation of area across crops. Mundlak (1988) has shown that the optimisation model in this case will have to be modified to provide for sequential solution for area allocation and input use. This model clearly distinguishes the changes in optimal input and output combinations for each crop from changes in the quasi-fixed inputs across crops.
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SHIVELY, GERALD E. « Economic policies and the environment : the case of tree planting on low-income farms in the Philippines ». Environment and Development Economics 3, no 1 (février 1998) : 83–104. http://dx.doi.org/10.1017/s1355770x98000059.
Texte intégralRésumé :
This paper investigates the potential for economic policies to influence environmental outcomes in low-income agriculture. The analysis focuses on how changes in agricultural prices influence land-use decisions and environmental indicators. Tree-planting decisions of low-income farmers in the Philippines are examined using a stochastic dynamic household model. Empirical analysis and dynamic simulations demonstrate that changes in relative prices and relative price risks are important determinants of tree-planting decisions. Results show that small holders are sensitive to risks associated with tree crops, but that price risk is not an insurmountable barrier to tree crop adoption. The relationship between cropping patterns and two environmental indicators - erosion and species diversity - are discussed.
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Duncan, Hence, Jacob Eicher, Weston M. Bracey, Virginia R. Sykes, Christopher N. Boyer, Frank Yin, Gary E. Bates, David M. Butler et Alison R. Willette. « Is Harvesting Cover Crops for Hay Profitable When Planting Corn and Soybean in Tennessee ? » Agronomy 12, no 6 (1 juin 2022) : 1353. http://dx.doi.org/10.3390/agronomy12061353.
Texte intégralRésumé :
Winter cover crops can improve the soil’s moisture-holding capacity, reduce soil water evaporation, and mitigate water-induced soil erosion; however, economic studies show mixed results on cover crop impacts on profits. One way to potentially increase the profits from planting cover crops is to harvest the cover crop for hay. The objective of this study was to determine the profitability of planting and harvesting cover crops when planting corn (Zea mays) or soybean (Glycine max (L.) Merr.) as a cash crop. We determined the difference in net returns among 15 cover crop species when planted before corn and soybeans. We then calculated the breakeven hay price if the cover crop was harvested. Data were collected from an experiment in Tennessee, from 2017 to 2019, at two locations. There was no difference in net returns across cover crop treatments for both corn and soybeans, thus indicating that planting a cover crop does not reduce profits. The breakeven prices for harvesting cover crops suggest that this system would not likely be profitable for corn but might be profitable if planting soybeans, depending on labor availability and local demand for hay.
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Saad, Ammar, Zhang Rui Tao et Xia Ying. « Comparative Advantage and Market Distortions : A Policy Analysis Matrix for Iraqi Wheat Crop Production ». Journal of Agricultural Science 11, no 2 (15 janvier 2019) : 82. http://dx.doi.org/10.5539/jas.v11n2p82.
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Wheat is the most crop have been subsidized by the government in Iraq, through subsidizing the input of the production (seed, pesticide, and machines), as well as, subsidize the output of the production through purchasing it from the producers at a high price compared to the world market price. The study aims to assess the competitive advantage of wheat production in Iraq through some of the measures derived from the policy analysis matrix. This study according to secondary data has published by Iraqi Ministry of Planning/Central Organization of Statistics and Information Technology 2018, for wheat production costs of cultivation season in Iraqi provinces 2017. The results of the study indicated that the coefficients measures show, there is a government subsidy for wheat output and that means, producers receive prices higher than international prices with the existence of this policy. While the comparative advantage indicators showed, the wheat crop in Iraq was achieved private profits due to government intervention in the inputs and outputs of production, nor competitive advantage in social prices. Where the policy reflection indexes/market distortions analysis shows, that the government policy for wheat production 2017 subsidized the producers on the consumer cost, where the local market price for wheat is higher than the price of wheat in the world market.
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Bavrka, Ivan, Branka Šakić Bobić, Lari Hadelan, Željko Jukić et Ana Matković. « Generating cost price for crop residues ». Journal of Central European Agriculture 20, no 1 (2019) : 542–55. http://dx.doi.org/10.5513/jcea01/20.1.2209.
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Mohammad, Nasaif jasim. « Estimation of the supply function of corn crop in Iraq for the period (1990-2019) ». Tikrit journal for agricultural sciences 21, no 4 (31 décembre 2021) : 91–101. http://dx.doi.org/10.25130/tjas.21.4.10.
Texte intégralRésumé :
The corn crop is one of the main crops in Iraq and is of great importance in terms of food and industry, as it is used in the manufacture of corn flakes, starch, oil, etc., and is used as animal feed. The research aimed to estimate the supply function of the maize crop in Iraq for the period (1990 - 2019) and to determine the factors affecting the production of the crop, represented by the price and non-price factors. The Nerlov partial adjustment model was used for a set of explanatory variables, namely, corn production as a dependent factor, the price of the crop for the current and previous years, rains, corn production in the previous year, price risk, technology variable, and the qualitative variable represented by the economic blockade as independent factors. The method of least squares was used in the analysis of several functions including linear, double logarithmic, half logarithmic and inverse logarithmic. The results indicated that the double logarithmic function is the best in terms of its conformity with the logic of economic theory and statistical criteria. The value of the coefficient of determination R2 was (0.89), and this indicates that the independent factors affect by (89%) the dependent variable, and that (11%) are due to other factors outside the model whose impact is absorbed by the random variable. The results of all parameters appeared significant according to the t-test at a level of significance (1%) to express the relationship between the dependent variable and the independent variables, and that the calculated F value is greater than the tabular F value, which amounted to (76.69), which indicates the significance of the model as a whole. The results indicated that corn supply is elastic in the short-run and inelastic in the long-run, which indicates that corn growers are less sensitive to price changes. And it was found that the supply of corn increases by (0.14, 0.19, 0.27) when the cultivated areas and prices of the current and previous year increase by one unit in order, and the research concluded that the supply of corn depends on several factors, the most important of which are prices in the current and previous year and the areas planted with the crop and to a lesser extent on the amount of rain And the production of corn in the previous year and the technological factor and other factors despite their positive impact on the production of the crop. The study recommends adopting policies that focus on non-price factors as a means to stabilize and increase corn production.
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Choi, Jung-Sup, et Peter G. Helmberger. « How Sensitive are Crop Yields to Price Changes and Farm Programs ? » Journal of Agricultural and Applied Economics 25, no 1 (juillet 1993) : 237–44. http://dx.doi.org/10.1017/s1074070800018794.
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AbstractA two-stage approach is used to estimate sensitivity of corn, wheat, and soybean yields to changes in prices and land idled. Estimated elasticity of demand for fertilizer per acre with respect to expected output price equals 0.47, 0.10, and 0.82 for corn, wheat, and soybeans. Upper estimates of the elasticity of yield with respect to fertilizer equals +0.58, +0.29, and +0.16 for corn, wheat, and soybeans. Yields are found to be quite insensitive to price changes. Fertilizer demands and yields are insensitive to land idled under farm programs.
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Lamberts, Mary, Sylvia Gordon et George Fitzpatrick. « Validating a Crop Production Budget for Containerized Specialty Vegetables ». HortScience 32, no 3 (juin 1997) : 456D—456. http://dx.doi.org/10.21273/hortsci.32.3.456d.
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Growers producing new crops often do not understand how to price individual items. The prices of common container nursery stock items may be listed in monthly trade publications. Prices for fruits and vegetables fluctuate on a daily basis. A production budget for containerized specialty vegetables was adapted from one developed for ornamental nurseries, using some specific costs for field-grown vegetables. This gave a realistic way to calculate prices for individual products. Once the crops had been sold, the authors were able to validate the model by comparing actual costs with projected costs.
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Dipali, Dakhole. « Krishi-Stats : A Web-based System for Crop Price Prediction using Machine Learning Approach ». September 2022 4, no 3 (16 septembre 2022) : 212–23. http://dx.doi.org/10.36548/jitdw.2022.3.006.
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Agriculture is the main livelihood in India. Most of the people earn bread and butter through farming, but the farmers are not getting enough profit and the field is facing growth downward due to irregular rainfall, high volatility in agriculture commodity prices and uncertainties in production. The objective of this study is to design and implement an automated crop price prediction system with best suitable machine learning technique, as well as displaying prediction results on website Krishi-Stats designed for easy understanding for Farmers. In this study, three machine-learning (ML) algorithms, ARIMA, VAR and XGBoost are applied on large historical data collected from government website. The ML algorithms compared with their root mean square error values (RMSE). As XGBoost has given optimum RMSE value of 0.94, has been selected as the prediction system engine of our website Krishi-Stats. On website, the crop prediction prices are plotted for all twelve selected crops and visualized using prediction graphs.
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Cooper, Joseph. « Payments under the Average Crop Revenue Program : Implications for Government Costs and Producer Preferences ». Agricultural and Resource Economics Review 38, no 1 (avril 2009) : 49–64. http://dx.doi.org/10.1017/s1068280500000186.
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This paper develops a stochastic model for comparing payments to U.S. corn producers under the U.S. Senate's Average Crop Revenue Program (ACR) versus payments under the price-based marketing loan benefit and countercyclical payment programs. Using this model, the paper examines the sensitivity of the density function for payments to changes in expected price levels. We also assess the impact of the choice of yield aggregation used in the ACR payment rate on the mean and variance of farm returns. We find that ACR payments lower the producer's coefficient of variation of total revenue more than does the price-based support, although ACR may not raise mean revenue as much. While corn farmers in the heartland states might still prefer to receive the traditional forms of support when prices are low relative to statutory loan rates and target prices, this outcome is not necessarily the case for farmers in peripheral production regions.
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Tripepi, Robert R., et Edward J. Kuchar. « Plant Cost Accounting : A Microcomputer Program to Calculate Crop Production Costs ». HortScience 23, no 5 (octobre 1988) : 905–6. http://dx.doi.org/10.21273/hortsci.23.5.905.
Texte intégralRésumé :
Abstract Growers must know their production costs to be competitive and profitable. A microcomputer program has been developed to calculate these costs based on various production inputs involved in growing crops. The user enters costs for land, buildings, equipment, general overhead expenses, and cultural practices. The program produces cost summaries for capital requirements, annual fixed costs, variable cost per hour of equipment, estimated costs of production, and final price per plant. With this information, growers can compare their prices against those of competitors to determine if the crop will be profitable.
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Meeradevi, Monica R. Mundada et Hrishikesh Salpekar. « Decision Support System for Enhancing Crop Productivity ». Journal of Computational and Theoretical Nanoscience 17, no 9 (1 juillet 2020) : 4438–41. http://dx.doi.org/10.1166/jctn.2020.9092.
Texte intégralRésumé :
Agriculture is the important aspect for the people of India. The life of large percentage of people in India is dependent on agriculture. The farmers are facing difficulty in selling their product to the markets due to lack of knowledge on crop prices. The market prices changes drastically in time. Using neural networks market price can be predicted and made available to the farmers to decide the time to sell their product. The ARIMA model is used to forecast the prices which can help the farmers to improve their economy and also the crop yield is predicted using neural network in the proposed system. So, that the user can check the yield of the crop in the particular piece of land before sowing. The prediction using the neural network model results in deciding the time to sell the prices and what will be the production of the crop over the year.
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Amrouk, El Mamoun, Thomas Heckelei et Stephanie-Carolin Grosche. « International Interdependence between Cash Crop and Staple Food Futures Price Indices : A Dynamic Assessment ». Journal of Agricultural and Applied Economics 51, no 3 (10 juin 2019) : 450–71. http://dx.doi.org/10.1017/aae.2019.12.
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Abstract:This study examines the price level and volatility interaction between international staple food and cash crop futures price indices. Understanding the relationship between these commodities bears significant implications for low-income food deficit countries that depend on cash crops to finance food import bills. We use a wavelet analysis to decompose the price indices and then apply a BEKK-MGARCH (Baba, Engle, Kraft and Kroner–multivariate generalized autoregressive conditional heteroskedasticity) approach to analyze the relationship across timescales. Results indicate the level of correlation and volatility linkages are strongest at lower frequencies (longer run) than at higher timescales (short run), with information running from staple food to cash crop markets.
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Hyde, Charles E. « CROP INSURANCE : THE RELATIONSHIP BETWEEN INDEMNITY PRICE AND EXPECTED OUTPUT PRICE ». Journal of Agricultural Economics 47, no 1-4 (janvier 1996) : 236–46. http://dx.doi.org/10.1111/j.1477-9552.1996.tb00687.x.
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Ali, Mubarik. « The Price Response of Major Crops in Pakistan : An Application of the Simultaneous Equation Model ». Pakistan Development Review 29, no 3-4 (1 septembre 1990) : 305–25. http://dx.doi.org/10.30541/v29i3-4pp.305-325.
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This paper specifies a model to simultaneously estimate the price response, assuming an interdependence among crops. The model is applied to estimate ownand cross-price elasticities of five major crops in Pakistan, viz., wheat, cotton, rice, sugan:ane, and maize based on the production and expected wholesal~price data for the period 1957-86. The study found little potential to· enhance overall agricultural productivity by ir.:reasing the single crop price, sillCe either the ownprice elasticities were low or, otherwise, the nagative cross-price effec ts on the production of other crops were high. However, a 100percent system at;; improv~ ment in terms of trade for agriculture will illCrease overall agricultural productivity by about 6 percent in the long run.
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Steen, Marie, Olvar Bergland et Ole Gjølberg. « Climate Change and Grain Price Volatility : Empirical Evidence for Corn and Wheat 1971–2019 ». Commodities 2, no 1 (6 janvier 2023) : 1–12. http://dx.doi.org/10.3390/commodities2010001.
Texte intégralRésumé :
It is widely recognized that climate change makes the weather more erratic. As the combination of temperature and precipitation is a major driver of grain crop productivity, more frequent extreme rainfalls and heat waves, flooding and drought tend to make grain production and hence grain prices more volatile. We analyze daily prices during the growing season for corn and wheat over the period 1971–2019 using an EGARCH model. There have been occasional spikes in price volatility throughout this period. We do not, however, find that grain prices have become more volatile since the 1970s, with an exception for a small but statistically significant upward trend in wheat price volatility. To the extent that climate change has caused more frequent weather extremes affecting crop yields, it appears that the price effects have been softened, most likely through farmers’ adaption to climate changes, introduction of more stress-tolerant hybrids, storage, regional and international trade and risk management instruments.
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Mardiyanto, Ilyas Cahaya, et Panji Kusuma Prasetyanto. « PENGARUH HARGA TANAMAN PANGAN TERHADAP INFLASI DI KABUPATEN KENDAL ». TRANSEKONOMIKA : AKUNTANSI, BISNIS DAN KEUANGAN 3, no 1 (3 janvier 2023) : 98–109. http://dx.doi.org/10.55047/transekonomika.v3i1.346.
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This study aims to analyze the effect of food crop prices on inflation in Kendal Regency. The increasing demand for agricultural commodities has resulted in the price of agricultural commodities increasing due to the high demand. The impact arising from the increase in the price of agricultural commodities is an increase in inflation, which causes a decrease in people's purchasing power because prices are increasingly unaffordable. The data used in this study is time series data for the period 2016 to 2022, the data used is secondary data on monthly developments in food crop prices and inflation in Kendal Regency. The tool used in this research is the analysis of the VAR/VECM (Vector Autoregression (VAR) or Vector Error Correction Model (VECM)) model with the help of the Eviews 10 application. The findings show that a number of variables, including the price of garlic, large red chilies, and Red cayenne pepper has a significant effect on inflation in Kendal Regency in the long run. In the short term, several variables such as the price of shallots and red cayenne pepper also have a significant effect on inflation in Kendal Regency.
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Yoon, Byung-Sam, et B. Wade Brorsen. « Market Inversion in Commodity Futures Prices ». Journal of Agricultural and Applied Economics 34, no 3 (décembre 2002) : 459–76. http://dx.doi.org/10.1017/s107407080000924x.
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In an inverted market, current prices are higher than future prices and thus the price of storage is negative. Market inversions as measured with futures spreads rarely occur during early months of the crop year. However, market inversions frequently occur across crop years and near the end of the crop year. In the last half of the crop year, market inversions clearly reflect a signal to sell stocks. Too few inversions occur early in the crop year to reach a definitive conclusion for that period. Behavioral finance offers possible explanations of why producers would hold stocks in an inverted market.
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Smith, T. A., C. L. Huang et B. H. Lin. « Estimating organic premiums in the US fluid milk market ». Renewable Agriculture and Food Systems 24, no 3 (30 juillet 2009) : 197–204. http://dx.doi.org/10.1017/s1742170509002579.
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AbstractUsing actual retail purchases from the 2006 Nielsen Homescan panel data, we estimate a hedonic model on price premiums and discounts associated with household characteristics, market factors, and product attributes focusing on the organic attribute for fluid milk. The organic attribute carries a significant price premium, which is largest of all product attributes considered in this study. Further, additional price variations among organic milk are observed for differences in fat content, container size and branding. Specifically, the results suggest that organic price premiums for half-gallon milk range from $1.23 for whole private label organic milk (60–68% above conventional counterpart) to $1.86 for nonfat/skim-branded organic milk (89–109% above conventional counterpart). The study also found that milk sold in a discount store (i.e., supercenter or club warehouse) was price 13 cents per half gallon, or 7.4%, below milk sold through other venues, and that milk on sale was priced 26 cents per half gallon, or 14.3%, less than the regular average price. Although household characteristics exert little influence on price relative to product attributes and market factors, the study does find that unmarried households and those with children under six pay slightly higher prices for milk, possibly due to time constraints.
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Shao, Yuehjen E., et Jun-Ting Dai. « Integrated Feature Selection of ARIMA with Computational Intelligence Approaches for Food Crop Price Prediction ». Complexity 2018 (10 juillet 2018) : 1–17. http://dx.doi.org/10.1155/2018/1910520.
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Because of global climate change, lack of arable land, and rapid population growth, the supplies of three major food crops (i.e., rice, wheat, and corn) have been gradually decreasing worldwide. The rapid increase in demand for food has contributed to a continuous rise in food prices, which directly threatens the lives of over 800 million people around the world who are reported to be chronically undernourished. Consequently, food crop price prediction has attracted considerable attention in recent years. Recent integrated forecasting models have developed various feature selection methods (FSMs) to capture fewer, but more important, explanatory variables. However, one major problem is that the future values of these important explanatory variables are not available. Thus, predictions based on these variables are not actually possible. Because an autoregressive integrated moving average (ARIMA) can extract important self-predictor variables with future values that can be calculated, this study incorporates an ARIMA as the FSM for computational intelligence (CI) models to predict three major food crop (i.e., rice, wheat, and corn) prices. Other than the ARIMA, the components of the proposed integrated forecasting models include artificial neural networks (ANNs), support vector regression (SVR), and multivariate adaptive regression splines (MARS). The predictive accuracies of ARIMA, ANN, SVR, MARS, and the proposed integrated model are compared and discussed. Experimental results reveal that the proposed integrated model achieves superior forecasting performance for predicting food crop prices.
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Valdes Salazar, Rodrigo Andres. « The role of fuel prices in spatial price transmission between horticultural markets : empirical analysis from a developing country ». Revista de la Facultad de Ciencias Agrarias UNCuyo 53, no 2 (1 décembre 2021) : 193–203. http://dx.doi.org/10.48162/rev.39.052.
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This article aims to analyze how fuel prices impact spatial price transmission between two Chilean horticultural wholesale markets. We implement a regime-dependent VECM where price transmission parameters depend on dynamics imposed by a stationary exogenous variable (fuel price). We identified two price transmission regimes characterized by different equilibrium relationships and short-run adjustment processes. This implies that fuel prices affect price transmission elasticities and intermarket adjustment speeds. Our results show increasing marketing costs as farm to market distance grows. This impact depends on each product’s attributes. Highlights This article analyzes the effect of fuel prices on the price transmission mechanism between the most relevant Chilean horticultural wholesale markets. A regime-dependent Vector Error Correction Model where price transmission parameters depend on fuel price was implemented. Clear evidence of the role played by fuel prices for in horizontal price transmission between the wholesale markets considered in this study was found. This situation supports the idea that regardless of quantities traded in regional markets, the major effect of price adjustment is a result of the high demand, distances and market concentration of a central market. This impact depends on each product’s attributes.
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LEISTER, AMANDA M., PHILIP L. PAARLBERG et JOHN G. LEE. « DYNAMIC EFFECTS OF DROUGHT ON U.S. CROP AND LIVESTOCK SECTORS ». Journal of Agricultural and Applied Economics 47, no 2 (mai 2015) : 261–84. http://dx.doi.org/10.1017/aae.2015.8.
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AbstractThis study investigates the long-term adjustments to drought by crop and livestock sectors using a dynamic partial equilibrium quarterly model of the U.S. agricultural economy. Results show that short-term drought effects including increases in crop and forage prices are in tandem with decreased live cattle prices resulting from drought-induced beef cattle herd liquidation. Crop price increases in the long run cause livestock inventory reductions, leading to fewer animals moving through the U.S. meat supply chain and increased livestock prices. Longer-term market adjustments cause a significant decrease in consumer surplus, and prolonged drought amplifies and extends the model-predicted results.
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Zimmer, David M. « Crop price comovements during extreme market downturns ». Australian Journal of Agricultural and Resource Economics 60, no 2 (25 juin 2015) : 265–83. http://dx.doi.org/10.1111/1467-8489.12119.
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Hinson, Roger, Mooyul Huh et John G. Lee. « Evaluation of Selected Fresh Vegetable Terminal Markets : A Stochastic Dominance Approach ». Journal of Agricultural and Applied Economics 22, no 2 (décembre 1990) : 39–48. http://dx.doi.org/10.1017/s1074070800001784.
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Abstract Vegetable production can offer a high-valued cash crop alternative. While returns may be high, vegetables are perceived to have more risk than conventional row crops. This study used stochastic dominance analysis to evaluate terminal market price risk for four vegetable crops across five market locations. Results from the analysis identify differences in efficient market selection depending on the form which price risk follows. While vegetables as a whole are considered risky, substantial differences in the type of terminal market price variability existed between the commodities.