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Browsing by Author "Isengildina-Massa, Olga"

Now showing 1 - 10 of 10
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    Are USDA reports still news to changing crop markets?
    Karali, Berna; Isengildina-Massa, Olga; Irwin, Scott H.; Adjemian, Michael K.; Johansson, Robert C. (2019-04)
    This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market "surprise," is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.
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    Costs of Futures Hedging in Corn and Soybean Markets
    Shi, Ruoding; Isengildina-Massa, Olga (2021)
    This study develops a comprehensive framework to measure, explain and anticipate the costs of futures hedging. Using historical futures prices and margin requirements, we simulate hedging costs for corn and soybeans over 2004-2018. Empirical distributions derived from the simulation results provide unconditional estimates of the costs of hedging as well as the probability of hedging failure. Conditional estimates assess the impact of margin requirements, price volatility and price changes as well as seasonal patterns using quantile regressions. Our findings demonstrate that price volatility is a main driver of the costs of hedging and can be used to anticipate future hedging costs.
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    Essays on Environmental Economics with a Focus on Non-market Valuation
    Cao, Xiang (Virginia Tech, 2019-07-09)
    This dissertation consists of two research projects in the area of Environmental Economics: water-recycling technology adoption and its cost-effectiveness in the U.S. horticulture industry (in Chapter 2), and urban tree cover's impact on residential location decision making in Milwaukee, WI (in Chapter 3). Chapter 2 evaluates the economic effects of labeling plants grown with water-recycling technology (WRT) practices in selected nursery operations in the Mid-Atlantic region of Virginia, Maryland and Pennsylvania. Partial budgeting, whole enterprise-level budgeting, sensitivity and break-even analyses are conducted to determine whether consumer premiums for plants grown with recycled water are sufficient to make WRT economically feasible combined with plant eco-labeling, and how such a labeling program would affect greenhouse/nursery production costs, gross revenues and net revenues. It is concluded that consumer premiums for plants grown with recycled water could offer nursery growers a method to improve their net returns while reducing pollution runoff and improving irrigation water usage efficiency. Chapter 3 focuses on non-market valuation of environmental (dis)amenities. Specifically, this chapter investigates the impact of urban tree cover on residential property location decision in the housing market of Milwaukee, WI. Residential sorting model embedded with "horizontal preference structure" is established to estimate the heterogeneous preferences for tree cover and other land cover attributes that vary by household socio-economic characteristics and then to identify the housing property owners' demand for these land cover attributes. The first part of this chapter mainly recovers the demand for "community trees" at the census block group level combined with 10 years property transaction data and neighborhood characteristics where the median income is aggregated to represent the household annual income. It is found that "community trees" are positively valued by the housing property owners and have a positive impact on housing price due to its positive externalities. Furthermore, income is found to be a strong exogenous demand shifter, leading to heterogeneous preference for the tree cover. The second part of Chapter 3 further investigates the impacts of both nearby trees and distant trees on residential property location decision using different spatial scales of land covers measurements. Instead of aggregating block group level median income, this study matches and merges disaggregated individual household annual incomes from the Home Mortgage Disclosure Act (HMDA) dataset to mitigate the potential aggregation bias. It is found that different spatial scales of land cover measurement result in varying willingness to pay estimates, implying that housing property owners have heterogeneous demands for nearby trees and distant trees. In other words, preferences for urban tree cover not only vary by household annual income, but also differ across spatial scales of the tree cover measurement.
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    Futures-Based Forecasts of U.S. Crop Prices
    Zhu, Jiafeng (Virginia Tech, 2017-10-03)
    Over the last decade, U.S. crop prices have become significantly more volatile. Volatile markets pose increased risks for the agricultural market participants and create a need for reliable price forecasts. Research discussed in this paper aims to find different approaches to forecast crop cash prices based on the prices of related futures contracts. Corn, soybeans, soft red winter wheat, and cotton are the focus of this research. Since price data for these commodities is non-stationary, this paper used two approaches to solve this problem. The first approach is to forecast the difference in prices between current and future period and the second is to use the regimes. This paper considers the five-year moving average approach as the benchmark when comparing these approaches. This research evaluated model performance using R-squared, mean errors, root mean squared errors, the modified Diebold-Mariano test, and the encompassing test. The results show that both the difference model and the regime model render better performance than the benchmark in most cases, but without a significant difference between each other. Based on these findings, the regime model was used to make forecasts of the cash prices of corn and soybeans, the difference model was used to make predictions for cotton, and the benchmark was used to forecast the SRW cash price.
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    How Well Do Commodity Based ETFs Track Underlying Assets?
    Neff, Tyler Wesley (Virginia Tech, 2018-06-08)
    Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium.
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    Impacts of the COVID-19 Pandemic on the U.S. and Virginia Farms and Businesses: May 2020
    Holt, Matthew T.; Bovay, John; Friedel, Jennifer S.; Isengildina-Massa, Olga; Kayser, Patrick; van Senten, Jonathan; Grant, Jason H.; Orden, David R.; Marchant, Mary A. (Virginia Tech. Agricultural and Applied Economics, 2020-05)
    This report addresses various aspects of the impact the COVID-19 pandemic has had on Virginia’s farm and agribusiness sector as of the beginning of May 2020. At the time of this writing (May 7, 2020) the Centers for Disease Control and Prevention reports approximately 1.2 million cases of coronavirus disease 2019 (COVID-19) in the United States, and over 70,000 deaths.1 Virginia’s Department of Public Health reports over 21,000 cases and over 700 deaths.2 33.5 million people have filed for unemployment claims in the United States since mid-March.3 The economic impacts of the disease have been felt much more broadly, as businesses have been forced to close or operate under different conditions, and as consumer spending power declines. As we look ahead, there is tremendous uncertainty about how the pandemic will end and how it will affect the global economy and our individual lives and livelihoods both in the short term and permanently. This report includes a general economic outlook, by Matthew Holt; overviews of the pandemic’s disruptions to the U.S. food supply chain and several major agricultural industries in Virginia, by John Bovay; an overview of agricultural policy under the pandemic, by Jennifer Friedel; a detailed analysis of effects of the pandemic on Virginia grain markets, by Olga Isengildina Massa and Patrick Kayser; an overview of results of a national survey of the impacts of the pandemic on aquaculture producers, with a focus on Virginia’s main aquaculture products, by Jonathan van Senten; and analysis of the current state of affairs for U.S.-China agricultural trade, by Jason Grant, David Orden, and Mary Marchant.
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    Student-Managed Commodity Fund—A New Frontier in Experiential Learning
    Isengildina-Massa, Olga; Ramsey, A. Ford (Cambridge University Press, 2019-10-03)
    This study provides a road map for creating and operating a student-managed investment fund (SMIF) as an experiential learning opportunity in commodity market analysis. We describe the reasons for implementing a SMIF and the benefits it offers relative to traditional simulation approaches. We outline the necessary steps for starting a SMIF and explain its organizational structure. We discuss a SMIF’s operation and main activities, which include recruitment, training, trading, and interaction with the client and alumni. The implications of participating in a SMIF are reviewed within a cost-benefit framework.
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    Understanding Organic Prices: An Analysis of Organic Price Risk and Premiums
    McKay, Sarah Michele (Virginia Tech, 2016-06-29)
    Organic food products are produced without synthetic chemicals, including herbicides, pesticides, and fertilizers. Food grown in organic systems that are certified organic by the United States Department of Agriculture command a price premium, whether it is direct to consumer via farmers markets or in conventional grocery stores. Organic food and food products are representing a relatively larger portion of overall food sales in recent years, and the demand for organic meat has also increased. However, there is a lack of available U.S.-grown organic grains and soybeans to feed the growing number of organic certified livestock to produce organic meat to meet this demand. This shortage results from many factors, yet is primarily due to organic production requirements for significantly more land and operating capital when compared to conventionally grown counterparts. There is a lack of information detailing the relative costs and returns of organic grain production, and, limited understanding of organic premiums. The overall goal of this study is to examine differences in price levels between organic and conventional corn, soybeans, wheat, oats, and barley between 2007 and 2015, as well as factors that may affect the organic premium. For organic grain and soybean producers, study findings reveal that the least risky organic commodities to grow include corn and soybeans, especially if sold in the cash market. However, the author suggests that growers may consider growing wheat, barley, and oats if they have a buyer willing to contract in advance to ensure a premium and reduce price risk. For purchasers of organic grains and soybeans, including major food companies as well as livestock producers, it is recommended they continue to study developments in organic grain supplies as producers continue to consider adoption of organic production methods.
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    US grass-fed beef premiums
    Wang, Yangchuan; Isengildina-Massa, Olga; Stewart, Shamar (Wiley, 2022-12)
    This study examined monthly retail-level price premiums for grass-fed beef (relative to conventional grain-fed beef) in the United States from 2014 through 2021. We found that premiums were heterogeneous, with premium cuts, such as sirloin steak, tenderloin, ribeye and filet mignon enjoying the highest premiums. Premiums were not consistent with price levels, as the lowest premiums were observed for short ribs, skirt steak and flank steak. Our findings suggest that grass-fed beef price premiums were negatively affected by the consumption of food away from home. Changes in income, increased information about taste, protein and minerals, fat, revocation of the USDA grass-fed certification program in 2016 and COVID-19 pandemic, also affected premiums for several individual cuts. Premiums were not sensitive to changes in information about climate change.
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    When does USDA information have the most impact on crop and livestock markets?
    Isengildina-Massa, Olga; Cao, Xiang; Karali, Berna; Irwin, Scott H.; Adjemian, Michael K.; Johansson, Robert C. (2021-06)
    This study compares the impact of Prospective Plantings, Acreage, Crop Production, Crop Production Annual Summary, Grain Stocks, WASDE, Cattle on Feed, and Hogs and Pigs reports on corn, soybean, wheat, cotton, live cattle, and lean hogs markets over 1985-2018. Simultaneous releases of several reports are handled by evaluating the impact of report clusters. Our approach allows us to demonstrate the relative impact of various information releases and shows when the markets tend to be affected the most. The findings of this study provide evidence and guidance for future policy decision regarding the role of USDA information in modern agricultural markets.