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Registros recuperados: 8
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A magyar gabonaágazat középtávú kilátásai AgEcon
Potori, Norbert; Varga, Edina.
Igaz, hogy a szélsőséges időjárás Magyarországon rendkívül nagy hozamingadozásokat okozhat, az agrárpolitika és a piaci szereplők pedig hajlamosak a túlzott reakciókra, mégis a gabonaágazat az, ahol a magyar mezőgazdaság a természeti adottságok, a termelés vonatkozásában még bizonyíthatóan komparatív előnyökkel rendelkezik az Európai Unióban. A szántóföldi növények nemzeti kiegészítő támogatása ugyan 2008-tól a termeléstől függetlenedik, de a gazdálkodók a rendelkezésre álló szántóterületet a jövőben is hasznosítják, mert a gabonafélék magas ára ösztönzi a termelést. A kidolgozott különböző modellváltozataink szerint a hazai búzatermelés 4,6-6,1 millió tonna, míg a kukoricatermelés 9-10,9 millió tonna között alakulhat 2013-ban. A hazai abrakfogyasztó...
Tipo: Journal Article Palavras-chave: Gabonatermelés; Piac; Kilátások; Cereal production; Market; Forecasts; Agribusiness; Crop Production/Industries.
Ano: 2008 URL: http://purl.umn.edu/57733
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Do Big Crops Get Bigger and Small Crops Get Smaller? Further Evidence on Smoothing in USDA Crop Production Forecasts AgEcon
Isengildina-Massa, Olga; Irwin, Scott H.; Good, Darrel L..
The purpose of this paper is to determine whether smoothing in USDA corn and soybean production forecasts is concentrated in years with relatively small and large crops. The sample consists of all USDA corn and soybean production forecasts released over the 1970 through 2006 crop years. Results show that USDA crop production forecasts in both corn and soybeans have a marked tendency to decrease in small crop years and increase in big crop years. The magnitude of smoothing is surprisingly large, with corn and soybean production forecasts cumulatively revised downward by about 6 to 7 percent in small crop years and upward by about 5 to 6 percent in large crop years. Crop condition ratings are useful in predicting whether the current year is likely to be a...
Tipo: Conference Paper or Presentation Palavras-chave: Corn; Crop production; Forecasts; Smoothing; Soybeans; USDA.
Ano: 2007 URL: http://purl.umn.edu/37563
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Hedge Effectiveness Forecasting AgEcon
Dahlgran, Roger A.; Ma, Xudong.
This study focuses on hedging effectiveness defined as the proportionate price risk reduction created by hedging. By mathematical and simulation analysis we determine the following: (a) the regression R2 in the hedge ratio regression will generally overstate the amount of price risk reduction that can be achieved by hedging, (b) the properly computed hedging effectiveness in the hedge ratio regression will also generally overstate the amount of risk reduction that can be achieved by hedging, (c) the overstatement in (b) declines as the sample size increases, (d) application of estimated hedge ratios to non sample data results in an unbiased estimate of hedging effectiveness, (e) application of hedge ratios computed from small samples presents a significant...
Tipo: Conference Paper or Presentation Palavras-chave: Out of sample; Post sample; Hedging; Effectiveness; Forecasts; Simulation; Agricultural Finance.
Ano: 2008 URL: http://purl.umn.edu/37604
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Intermediate Volatility Forecasts Using Implied Forward Volatility: The Performance of Selected Agricultural Commodity Options AgEcon
Egelkraut, Thorsten M.; Garcia, Philip.
Options with different maturities can be used to generate an implied forward volatility, a volatility forecast for non-overlapping future time intervals. Using five commodities with varying characteristics, we find that the implied forward volatility dominates forecasts based on historical volatility information, but that the predictive accuracy is affected by the commodity's characteristics. Unbiased and efficient corn and soybeans market forecasts are attributable to the well-established volatility during crucial growing periods. For soybean meal, wheat, and hogs, volatility is less predictable and investors appear to demand a risk premium for bearing volatility risk.
Tipo: Journal Article Palavras-chave: Agricultural commodity; Efficiency; Forecasts; Implied forward volatility; Options; Marketing.
Ano: 2006 URL: http://purl.umn.edu/8637
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Price Determination for Corn and Wheat: The Role of Market Factors and Government Programs AgEcon
Westcott, Paul C.; Hoffman, Linwood A..
Annual models for U.S. farm prices for corn and wheat are developed based on market factors as well as government agricultural commodity programs. The pricing relationships utilize a stocks-to-use modeling framework to capture the effects of market supply and demand factors on price determination. This formulation is augmented by factors that represent the changing role of agricultural policies, particularly government price support and stockholding programs. For wheat, international market effects as well as wheat feed use and related crosscommodity pricing considerations also are included. Model properties and model performance measures are presented. Additionally, recent price-forecasting applications of the models are discussed. The relatively simple...
Tipo: Report Palavras-chave: Corn; Wheat; Farm price; Price determination; Stocks-to-use ratio; Price supports; Commodity programs; Forecasts; Crop Production/Industries; Demand and Price Analysis.
Ano: 1999 URL: http://purl.umn.edu/33581
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The Relative Performance of In-Sample and Out-of-Sample Hedging Effectiveness Indicators AgEcon
Dahlgran, Roger A..
Hedging effectiveness is the proportion of price risk removed through hedging. Empirical hedging studies typically estimate a set of risk minimizing hedge ratios, estimate the hedging effectiveness statistic, apply the estimated hedge ratios to a second group of data, and examine the robustness of the hedging strategy by comparing the hedging effectiveness for this "out-of-sample" period to the "in-sample" period. This study focuses on the statistical properties of the in-sample and out-of-sample hedging effectiveness estimators. Through mathematical and simulation analysis we determine the following: (a) the R2 for the hedge ratio regression will generally overstate the amount of price risk reduction that can be achieved by hedging, (b) the properly...
Tipo: Conference Paper or Presentation Palavras-chave: Out-of-sample; Post sample; Hedging; Effectiveness; Forecasts; Simulation; Agribusiness; Agricultural Finance; Demand and Price Analysis; Farm Management; Financial Economics; Marketing; Research Methods/ Statistical Methods; Risk and Uncertainty.
Ano: 2009 URL: http://purl.umn.edu/53042
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The Value of Accurate Crop Production Forecasts. AgEcon
Jayne, Thomas S.; Rashid, Shahidur.
Crop production forecasts are widely recognized as an important input into food balance sheets and for anticipating production shortfalls. However, the role of accurate crop production forecasting systems in mitigating food price instability and transitory food insecurity is often under-appreciated. This paper explains how crop production forecasting systems affect price instability and risks, and how they can be improved to stabilize the food system.
Tipo: Report Palavras-chave: Africa; Food security; Forecasts; Production; Agricultural and Food Policy; Community/Rural/Urban Development; Crop Production/Industries; Demand and Price Analysis; Food Consumption/Nutrition/Food Safety; Food Security and Poverty; International Development; Productivity Analysis; C10; Q11.
Ano: 2010 URL: http://purl.umn.edu/97032
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USING THE CRUDE OIL AND HEATING OIL MARKETS FOR DIESEL FUEL PURCHASING DECISIONS AgEcon
Dhuyvetter, Kevin C.; Dean, Erik; Parcell, Joseph L..
Agricultural producers and input suppliers must regularly make decisions based on forecasts; however, most publicly available forecasts are for outputs. Research has shown the importance of being a low-cost operator. Thus, focusing on inputs may be beneficial. The objective of this research was to estimate models based on futures markets to forecast diesel fuel prices. Results suggest diesel fuel prices forecasted using the crude oil or heating oil futures market are reasonably accurate, and that this approach is superior to using a historical average. Based on out-of-sample price predictions, producers could profitably use crude oil futures-based models to make diesel fuel purchasing decisions. While the gains from following a model-based decision rule...
Tipo: Journal Article Palavras-chave: Crude oil; Diesel fuel; Forecasts; Forward contracting; Heating oil; Resource /Energy Economics and Policy.
Ano: 2003 URL: http://purl.umn.edu/14664
Registros recuperados: 8
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