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Registros recuperados: 61
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A Limited Information Bayesian Forecasting Model of the Cattle SubSector AgEcon
Abidoye, Babatunde O.; Lawrence, John D..
The first step towards forecasting the price and output of the cattle industry is understanding the dynamics of the livestock production process. This study follows up on the Weimar and Stillman (1990) paper by using data from 1970 to 2005 to estimate the parameters that characterizes the cattle output supply. The model is then used to estimate forecast values for the periods 2006 and 2007. Bayesian limited information likelihood method is used to estimate the parameters when endogeneity exists between these variables. The forecasting ability of the model for a two-step ahead forecast for majority of the variables are relatively good and test statistic of the forecast are reported.
Tipo: Conference Paper or Presentation Palavras-chave: Cattle; Bayesian; Forecasting; Inventory; Slaughter; Agribusiness; Agricultural Finance; Financial Economics; Livestock Production/Industries; Marketing; Production Economics; Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/53051
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A weather-based simulation model for wheat blast incidence. Repositório Alice
BAVARESCO, J. L.; LAZZARETTI, A. T.; TSUKAHARA, R. Y.; PAVAN, W.; FERNANDES, J. M. C..
2016
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Wheat; Disease; Wheat blast; Forecasting; Trigo; Doença; Brusone; Previsão.
Ano: 2016 URL: http://www.alice.cnptia.embrapa.br/handle/doc/1049434
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Alternative Model Selection Using Forecast Error Variance Decompositions in Wholesale Chicken Markets AgEcon
McKenzie, Andrew M.; Goodwin, Harold L., Jr.; Carreira, Rita I..
Although Vector Autoregressive models are commonly used to forecast prices, specification of these models remains an issue. Questions that arise include choice of variables and lag length. This article examines the use of Forecast Error Variance Decompositions to guide the econometrician’s model specification. Forecasting performance of Variance Autoregressive models, generated from Forecast Error Variance Decompositions, is analyzed within wholesale chicken markets. Results show that the Forecast Error Variance Decomposition approach has the potential to provide superior model selections to traditional Granger Causality tests.
Tipo: Journal Article Palavras-chave: Broiler markets; DAGs; Forecasting; Market structure; VAR; Agribusiness; Demand and Price Analysis; Livestock Production/Industries; Risk and Uncertainty; C53; D4; L1; Q00.
Ano: 2009 URL: http://purl.umn.edu/48750
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An easy way to assess photoperiod sensitivity in sorghum: relationships of the vegetative-phase duration and photoperiod sensitivity Open Agri
Clerget, B..
Palavras-chave: Photoperiodicity; Sowing date; Sorghum; Genotypes; Fruits; Forecasting; Latitude; Tropical zones; Replication; Exhibitions.
Ano: 2007 URL: http://agropedia.iitk.ac.in/openaccess/?q=node/3308
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Can Calibration Reconcile Stated and Observed Preferences? AgEcon
Norwood, F. Bailey.
Hypothetical bias is a pervasive problem in stated-preference experiments. Recent research has developed two empirically successful calibrations to remove hypothetical bias, though the calibrations have not been tested using the same data or in a conjoint analysis. This study compares the two calibrations in a conjoint analysis involving donations to a public good. Results find the calibrations are biased predictors of true donations but that calibrated and uncalibrated models together provide upper and lower bounds to true donations.
Tipo: Journal Article Palavras-chave: Calibration; Experimental economics; Forecasting; Hypothetical bias; Public goods; Stated preference; Voluntary contributions; Research Methods/ Statistical Methods; Q51; H41.
Ano: 2005 URL: http://purl.umn.edu/43735
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Can the Federal Reserve Bank’s Survey of Agricultural Credit Conditions Forecast Land Values? AgEcon
Zakrzewicz, Christopher J.; Brorsen, B. Wade; Briggeman, Brian C..
The value of land dominates the financial structure of most American agricultural production firms, and land values are an important factor in long-term agricultural planning and risk management. As the primary source of collateral for farm loans, farmland values have significant implications for both producers as well as bankers financing agricultural loans. The Federal Reserve Bank of Kansas City’s Survey of Agricultural Credit Conditions is an expert opinion survey in which agricultural bankers provide land value forecasts. As the survey has drawn increased attention, the survey has drawn criticism regarding its use qualitative data to forecast land values. Our research examines the value of the survey data with respect to its ability to forecast...
Tipo: Conference Paper or Presentation Palavras-chave: Farmland; Forecasting; Land values; Federal Reserve Bank; Agribusiness; Financial Economics.
Ano: 2010 URL: http://purl.umn.edu/61758
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Comparison of NNARX, ANN and ARIMA Techniques to Poultry Retail Price Forecasting AgEcon
Karbasi, Ali Reza; Laskukalayeh, Somayeh Shirzadi; Fahimifard, Seiad Mohammad.
The lack of study among the economic forecasting literature that can empirically proves the hypothesis of being more powerfulness of dynamic neural networks in comparison with the static neural networks models for forecasting, is the most important motivation of this study. In this paper, the utilization of NNARX as a nonlinear dynamic neural network model, ANN as a nonlinear static neural network model and ARIMA as a linear model were compared to forecast poultry retail price. As a case study on Iranian poultry retail price, we compare forecast performance of these models for three forecasts (1, 2 and 4 week ahead). Results show that NNARX and ANN models outperform ARIMA model, and also NNARX model outperforms ANN model for all three forecasts.
Tipo: Conference Paper or Presentation Palavras-chave: NNARX; Poultry Retail Price; Forecasting; Demand and Price Analysis; Marketing.
Ano: 2009 URL: http://purl.umn.edu/50321
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Correction of seabed layer thickness in processing subbottom profile data. OceanDocs
Wang, Fangqi; Qi, Faqing; Hu, Guanghai; Dong, Lifeng; Tao, Changfei.
The subbottom profiling is an important means of marine engineering survey, hazardous geology study and continental shelf scientific research. The accuracy of subbottom profile data interpretation has a direct impact on the research and investigation results. Because some of profilers’ transducer and hydrophone are separately installed, when the survey area is very shallow, distortion of shallow layers will be caused if it is seen as a self-excited and self-collected single-channel seismic system. According to the principle of subbottom profiler, the distortion correction formula is deduced and analyzed, providing actual value to using C-View software to interpret such subbottom profile data more accurately. In addition, the seabed sediments sound velocity...
Tipo: Journal Contribution Palavras-chave: Crustal thickness; Sound velocity; Porosity; Forecasting.
Ano: 2012 URL: http://hdl.handle.net/1834/5852
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Do Economic Restrictions Improve Forecasts? AgEcon
Murphy, Elizabeth A.; Norwood, F. Bailey; Wohlgenant, Michael K..
A previous study showed that imposing economic restrictions improves the forecasting ability of food demand systems, thus warranting their use even when they are rejected in-sample. This article evaluates whether this result is due to economic restrictions enhancing degrees of freedom or containing nonsample information. Results indicate that restrictions improve forecasting ability even when they are not derived from economic theory, but theoretical restrictions forecast best.
Tipo: Journal Article Palavras-chave: Demand systems; Economic restrictions; Forecasting; Representative consumer; B4; C1; C3; C5.
Ano: 2004 URL: http://purl.umn.edu/43447
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Evaluation of different predicting methods in forecasting Hungarian, Italian and Greek lamb prices AgEcon
Fenyves, Veronika; Orban, Ildiko; Dajnoki, Krisztina; Nabradi, Andras.
The Hungarian sheep sector has become a one-market sector, almost the whole amount of slaughter lamb went to Italy. It would worth to exploit possibilities in other European markets. Such markets can be the Spanish and Greek for ”light” and the French, German and English markets for ”heavy” lambs. The European lamb prices are characterized by large seasonal fluctuation and the degree and timing of changes are different. Due to these seasonal changes, the producers often suffer great losses. Study of the literature on lamb sales called for an analysis of price forecasting. In my study, I performed a forecasting of lamb prices in Hungary, Italy and Greek for the period between 1996 and 2007 based on the data of the European Committee. Among the forecasting...
Tipo: Conference Paper or Presentation Palavras-chave: Forecasting; Lamb prices; Comparison; Agricultural and Food Policy.
Ano: 2009 URL: http://purl.umn.edu/58012
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Food-fodder traits in groundnut Open Agri
Blümmel, M..
Palavras-chave: Genotypes; Nutritive value; Groundnuts; Forecasting; Nitrogen; Yields; Organic matter; Sampling; Quality; Breeds (animals).
Ano: 2005 URL: http://agropedia.iitk.ac.in/openaccess/?q=node/3246
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Forecasting Corn Futures Volatility in the Presence of Long Memory, Seasonality and Structural Change AgEcon
Wang, Xiaoyang; Garcia, Philip.
Price volatility in the corn market has changed considerably globalization and stronger linkages to the energy complex. Using data from January 1989 through December 2009, we estimate and forecast the volatility in the corn market using futures daily prices. Estimates in a Fractional Integrated GARCH framework identify the importance of long memory, seasonality, and structural change. Recursively generated forecasts for up to 40-day horizons starting in January 2005 highlight the importance of seasonality, and long memory specifications which perform well at more distant horizons particularly with rising volatility. The forecast benefits of allowing for structural change in an adaptive framework are more difficult to identify except at more distant...
Tipo: Conference Paper or Presentation Palavras-chave: Corn price volatility; Long memory; Seasonality; Structural change; Forecasting; Agricultural Finance; Risk and Uncertainty.
Ano: 2011 URL: http://purl.umn.edu/103749
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Forecasting Demand for Rural Electric Cooperative Call Center AgEcon
Kim, Taeyoon; Kenkel, Philip L.; Brorsen, B. Wade.
This research forecasts peak call volume to allow a centralized call center to minimize staffing costs. A Gaussian copula is used to capture the dependence among nonnormal distributions. Peak call volume can be easily and more accurately predicted using the marginal probability distribution with the copula function than without using a copula. The modeling approach allows simulating adding another cooperative. Ignoring the dependence that the copula includes, causes peak values to be underestimated.
Tipo: Conference Paper or Presentation Palavras-chave: Call center data; Empirical distribution; Extreme value theory; Forecasting; Gamma distribution; Gaussian copula; Simulation; Agribusiness; Demand and Price Analysis; Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/46809
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Forecasting Hog Prices with a Neural Network AgEcon
Hamm, Lonnie; Brorsen, B. Wade.
Neural network models were compared to traditional forecasting methods in forecasting the quarterly and monthly farm price of hogs. A quarterly neural network model forecasted poorly in comparison to a quarterly econometric model. A monthly neural network model outperformed a monthly ARIMA model with respect to the mean square error criterion and performed similarly to the ARIMA model with respect to turning point accuracy. The more positive results of the monthly neural network model in comparison to the quarterly neural network model may be due to nonlinearities in the monthly data which are not in the quarterly data.
Tipo: Journal Article Palavras-chave: Forecasting; Hog prices; Neural networks; ARIMA; Econometric; Agribusiness; Livestock Production/Industries.
Ano: 1997 URL: http://purl.umn.edu/90646
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Forecasting Housing Prices under Different Submarket Assumptions AgEcon
Chen, Zhuo; Cho, Seong-Hoon; Poudyal, Neelam C.; Roberts, Roland K..
This research evaluated forecasting accuracy of hedonic price models based on a number of different submarket assumptions. Using home sale data for the City of Knoxville and vicinities merged with geographic information, we found that forecasting housing prices with submarkets defined using expert knowledge and by school district and combining information conveyed in different modeling strategies are more accurate and efficient than models that are spatially aggregated, or with submarkets defined by statistical clustering techniques. This finding provided useful implications for housing price prediction in an urban setting and surrounding areas in that forecasting models based on expert knowledge of market structure or public school quality and simple...
Tipo: Conference Paper or Presentation Palavras-chave: Clustering; Forecasting; Hedonic price; Housing Submarket; Demand and Price Analysis; C53; R21.
Ano: 2007 URL: http://purl.umn.edu/9689
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FORECASTING MARKET SHARE USING A FLEXIBLE LOGISTIC MODEL AgEcon
Quagrainie, Kwamena K..
There is a strong competition from low-priced imported catfish fillets resulting in a declining market share for domestic farm-raised catfish fillets. To match the competition, catfish processors are embarking on pricing policy measures that are volume-oriented instead of profit- or image-oriented. This could be an effective short-run pricing policy measure for optimal long-run sustainability and profitability of the industry. Volume pricing strategies are aimed at meeting target sales volumes or market shares. This paper explores and compares the performance of the standard logit, the inverse power transformation (IPT) logit and the logarithmic version of the inverse power transformation logit models in terms of generating forecasts for market share...
Tipo: Conference Paper or Presentation Palavras-chave: Market share; Forecasting; Flexible logit; Marketing; Q130; C250; C530.
Ano: 2004 URL: http://purl.umn.edu/34724
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Forecasting the Path of China's CO2 Emissions: Offsetting Kyoto - and Then Some AgEcon
Auffhammer, Maximilian; Carson, Richard T..
Our results suggest that the anticipated path of China's Carbon Dioxide (CO2) emissions has dramatically increased over the last five years. The magnitude of the projected increase in Chinese emissions out to 2015 is several times larger than reductions embodied in the Kyoto Protocol. Our estimates are based on a unique provincial level panel data set from the Chinese Environmental Protection Agency. This dataset contains considerably more information relevant to the path of likely Chinese greenhouse gas emissions than national level time series models currently in use. Model selection criteria clearly reject the popular static environmental Kuznets curve specification in favor of a class of dynamic models with spatial dependence.
Tipo: Working or Discussion Paper Palavras-chave: Forecasting; Climate Change; China; Model Selection; Environmental Economics and Policy; Q43; C53.
Ano: 2006 URL: http://purl.umn.edu/7197
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Forecasting Wheat Output and Profits from Cropping Systems Using Simulation Models in Uasin Gishu, Kenya AgEcon
Nyangweso, P.M.; Odmori, Paul Okelo; Mapelu, M.Z.; Odhiambo, Mark O..
Simulation models have been used successfully to forecast productivity of cropping systems under various weather, management and policy scenarios. These models have helped farmers make efficient resource allocation decisions. However, in Kenya simulation models have not been used extensively and more specifically in modeling large scale cropping systems. The study aimed at forecasting productivity and profitability of wheat cropping systems in Uasin Gishu district, Kenya. Both primary and secondary data were used. Both time series and cross-sectional data for variables of interest were collected and complemented by a survey of 20 wheat farmers who were systematically selected to verify information obtained from secondary sources. Cropping Systems...
Tipo: Journal Article Palavras-chave: Wheat; Cropping system; Simulation; Forecasting; Productivity; Profits; Crop Production/Industries.
Ano: 2010 URL: http://purl.umn.edu/95960
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FORECASTING YIELD AND PROFITABILITY OF MAIZE CROPPING SYSTEM USING SIMULATION MODELS IN UASIN GISHU, KENYA AgEcon
Odwori, P.O.; Mapelu, M.Z.; Odhiambo, Mark O.; Nyangweso, P.M..
Simulation models have been used successfully to forecast productivity of cropping systems under various weather, management and policy scenarios. These models have helped farmers make efficient resource allocation decisions. However, in Kenya simulation models have not been used extensively and more specifically in modeling maize cropping system. The study aimed at forecasting productivity and profitability of maize cropping system in Uasin Gishu district, Kenya. Both primary and secondary data were used. Both time series and cross-sectional data for variables of interest were collected and complemented by a survey of 20 maize farmers who were systematically selected to verify information obtained from secondary sources. Cropping Systems simulation model...
Tipo: Conference Paper or Presentation Palavras-chave: Forecasting; Yields; Profits; Maize cropping system; Simulation models; Crop Production/Industries.
Ano: 2010 URL: http://purl.umn.edu/97080
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Fruit production forecasting by neuro-fuzzy techniques AgEcon
Atsalakis, George S.; Atsalakis, Ioanna G..
Neuro-fuzzy techniques are finding a practical application in many fields such as in model identification and forecasting of linear and non-linear systems. This paper presents a neuro-fuzzy model for forecasting the fruit production of some agriculture products (olives, lemons, oranges, cherries and pistachios). The model utilizes a time series of yearly data. The fruit forecasting is based on Adaptive Neural Fuzzy Inference System (ANFIS). ANFIS uses a combination of the least-squares method and the backprobagation gradient descent method to estimate the optimal food forecast parameters for each year. The results are compared to those of an Autoregressive (AR) model and an Autoregressive Moving Average model (ARMA).
Tipo: Conference Paper or Presentation Palavras-chave: Fruit forecasting; Neuro-fuzzy; ANFIS; AR; ARMA; Forecasting; Fruit production; Agricultural Finance; Crop Production/Industries.
Ano: 2010 URL: http://purl.umn.edu/57680
Registros recuperados: 61
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