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We use time series methods to explore the relationship between prices for two different niche versions of feed corn and soybeans, and their conventional counterparts. Whereas organic versions are linearly cointegrated, and their premia are high and stable, non‐GE products – which are nonlinearly cointegrated – exhibit narrower premia that are subject to collapse. Because organics are also non‐GE, these differences point to the value of a well‐recognised and enforced USDA organic label and/or the importance consumers place on the non‐GE attributes of organic products.

We use linear time series and wavelets approach to study the relationships between U.S. and international prices for corn, soybeans, and cotton. We then compare results obtained with each approach and verify that structural breaks discovered with wavelet analysis match those produced with subsequent partial-period cointegration analysis. We find little evidence that short-term fluctuations between domestic and international prices are stable, while long-term relationships for many price pairs experience distinct structural breaks. We further find that even though China is among the largest importers of U.S. agricultural products, its commodity prices share little or no relationship with those prevailing in U.S. markets.

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. Office of the Chief Economist of the U.S. Department of Agriculture [58-0111-15-014] Published version Funding support from the Office of the Chief Economist of the U.S. Department of Agriculture under Cooperative Agreement No. 58-0111-15-014 is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and not necessarily reflect the view of the U.S. Department of Agriculture. Public domain – authored by a U.S. government employee

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. Office of the Chief Economist of the U.S. Department of Agriculture [58-0111-15-014] Published version Funding support from the Office of the Chief Economist of the U.S. Department of Agriculture under Cooperative Agreement No. 58-0111-15-014 is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and not necessarily reflect the view of the U.S. Department of Agriculture. Public domain – authored by a U.S. government employee

We document the impact of the early stages of the COVID-19 pandemic on liquidity in U.S. agricultural markets. Notably, we show that soybean futures-market depth collapses weeks before the U.S. financial markets’ crash of March 2020. Soybean futures liquidity is affected the earliest, the most, and the longest. Soybean depth drops by half for outright futures and by over 90 percent for calendar spreads, and soybean bid-ask spreads increase significantly. This liquidity pullback starts on the night of February 12 to 13, 2020—a full two weeks before (i) liquidity evaporates in U.S. bond and equity markets and (ii) soybean prices start to fall sharply. The start of the soybean liquidity pullback coincides with overnight news of bleak COVID-19 developments in China (a dominant source of world demand for oilseeds). Following a series of emergency interventions by the U.S. Federal Reserve in March and April 2020, liquidity recovers in the soybean outright futures market—but depth remains abnormally low for calendar spreads. These patterns cannot be explained by other factors, such as seasonalities or changes in soybean futures trading volume and price volatility: the COVID-19 shock was novel, and it destroyed soybean-market liquidity in a way that foretold financial-market developments two weeks later. In contrast to soybeans, we find little evidence of a drop in corn or wheat futures liquidity until U.S. financial and crude oil markets sink in early March. Soybeans were truly the canary in the coal mine.

In 2012, the Chicago Board of Trade eliminated a morning trading halt that coincided with the normal publication time for important USDA commodity reports. Previously, market participants had hours of halted trading time to review the information in the reports and adjust their strategies in advance of market re-opening. We use 2009–2014 intraday grain futures market price and volume data to show that, without a trading halt, ensuing real-time trading on USDA crop announcements exhibits noticeable volatility spikes in agricultural futures markets, but that this heightened volatility dissipates within the space of a few trading minutes. In addition, continuously-traded markets appear to have a more difficult time distinguishing between the newsworthiness of government reports. Nevertheless, continuously traded crop markets take nearly the same time to fully absorb these shocks, following a very similar time path. Re-imposing a timeout would necessarily lengthen the price discovery process.

In 2018, China retaliated to U.S. trade actions by levying a 25% retaliatory tariff on U.S. soybean exports. That tariff shifted market preferences so that Chinese buyers—who make up a substantial share of total world consumption—favored Brazilian soybeans. We use the relative price of a substitute (RPS) method to estimate that the resulting trade disruption effectively drove a wedge into the world soybean market, lowering U.S. prices at Gulf export locations by $0.74/bu on average for about five months, and increasing Brazilian prices by about $0.97/bu, compared to what would have been observed without the tariff in place. By the end of that period, world markets adjusted and the soybean prices in both countries returned to the ex-ante state of near parity, even if U.S. export volume did not recover until the end of the following marketing year. Our price impact estimate is substantially lower than subsequent U.S. government “trade aid” payments to American soybean producers: although actual payments to producers varied based on county-level differences, USDA’s nominal calculation of the commodity-specific payment rate for soybeans under MFP summed to $3.70 for two bushels produced over the course of two years. We project that USDA’s near-$8.5 billion in trade aid to U.S. soybean producers exceeded the tariff damage by about $5.4 billion. These difference could be attributed to USDA’s broader definition of “economic injury”, beyond the short-run price impacts we estimate.

The United States may be losing its leadership role in the world wheat market. Rising trading volume in foreign futures markets and shifting shares of world trade are suggested as evidence of this shift, but neither necessitates that futures markets in the United States are any less important for wheat price discovery. This paper applies high frequency pricing data and market microstructure methods, including the Yan and Zivot (2010) information leadership share, to estimate the proportion of price discovery occurring in wheat futures markets associated with Chicago, Kansas City, Minneapolis, and Paris. We find United States futures markets remain dominant, although the share of price discovery for the Paris market increased noticeably in 2010, coinciding with major supply shocks in Russia and Ukraine. Prior to August 2010, 91% of information about the common fundamental value of wheat was first revealed in United States futures markets in an average month. After August 2010, this share dropped to 75%.

In January 2019, a government shutdown prevented the U.S. Department of Agriculture from publishing information about the situation and outlook for major U.S. agricultural commodities. We show that, as a result, Chicago Mercantile Exchange markets for corn and soybeans experienced heightened uncertainty, elevating the cost of managing risk using options. We use historical options data to estimate that, on the first day of trading following the normally scheduled USDA publication time, the additional commodity market uncertainty caused by the government shutdown increased the price of managing risk using ATM corn and soybean options by 2.95 % and 1.66%, respectively, using an approach that assumes a normal January report impact. Using a different counterfactual approach -- assuming that the observed, abnormally large implied volatility reduction following the February 2019 publication would have been experienced in January -- we find that the increase in risk management costs due to missing information was actually about 11.5% for corn and 4.4% for soybeans.

We use rich IRI household- and individual-level data sets to examine the relationships between heart disease and type 2 diabetes with alcohol consumption. We control for a wide variety of potential confounders, including diet quality and lifestyle choices. Beer has long been studied in related literature to ambiguous outcomes. We explore the role of beer consumption in detail by separating craft beer from macrobeer and imported beer. The results indicate that most alcohol types could have protective effects against heart disease and diabetes, with the strongest effects occurring for craft beer and wine. Treating beer as a single, homogenous category in health studies likely leads to measurement error. (JEL Classifications: D12, I12, R20, L66, P36)

Thinly traded agricultural commodity markets are a concern for farmers and policy markers due to the belief that prices in these settings will be highly volatile, subject to manipulation, and incapable of efficiently allocating resources. Analysis of thin agricultural markets has to date been impeded by lack of an appropriate analytical framework from which to study their behavior. In this paper we propose the modern agricultural markets (MAM) framework as an appropriate paradigm through which to view and evaluate thin markets. We argue that thinly traded markets that meet key conditions required for a MAM will generate maximum economic surplus and enable farmers to earn at least a competitive return on their investments. In the absence of these conditions, however, the concerns known as the “thin market problem” have validity. We set forth the MAM framework, interpret it in a thin‐market context, and conduct several brief case studies of thin markets to illustrate use of the approach and draw some key inferences about these markets' behavior. The analysis indicates that appropriate government policies directed to thin markets are those that facilitate their convergence to MAM status, but in reality key policies under recent consideration would have the opposite effect.

Many USDA reports are anticipated by commodity traders because they contain news about market fundamentals. USDA has made several recent changes to the publication of these reports, including shifting their publication time, releasing them so that traders can respond in real-time, and--just last July--removing media from the lockup environment where reports are prepared. Previously, traders had hours to digest USDA news, or at least access media summaries of that news, before or just as active trading resumed; now traders must digest news while markets are open. We show that continuous trading of government news coincided with wider daily session price ranges in the CBOT corn market. At the intraday level, we confirm recent findings about elevated trading volatility at report publication time under the real-time format: that these volatility spikes moderate fairly quickly, and that the CBOT corn market has a more difficult time distinguishing important news events. Although the sample of news events since the lockup policy change is small, we do not find evidence that removing media members from lockup has increased announcement time price volatility using either daily or intraday data.

From 1977 through April 2019, USDA published monthly season-average price (SAP) forecasts for key agricultural commodities in the form of intervals meant to indicate forecasters’ uncertainty — but without attaching a confidence level. In May 2019, USDA eliminated the intervals and began publishing a single point estimate. The intervals were not very informative, with realized SAPs regularly falling outside of the USDA-forecasted intervals — particularly those made either prior to harvest or late in the marketing year — calling into question the accuracy of the USDA methodology. We demonstrate how a density forecasting format can improve the usefulness of USDA price forecasts, and we explain how such a methodology can be implemented. We simulate 21 years of out-of-sample density-based SAP forecasts using historical data, using forward-looking, backward-looking, and composite methods, and we evaluate them based on commonly-accepted criteria. Each of these approaches would offer USDA the ability to portray richer price forecasts than both its old intervals and its current single point estimates. In particular, since the option-implied volatilities (IVs) used to generate our forward-looking and composite models anticipate future market conditions, their densities reflect and adjust dynamically to market sentiment — a feature that is impossible using backward-looking data alone. At the same time, even with efficient grain and oilseed futures markets, our composite method provides useful information regarding farm-level prices beyond that contained in IVs.

We estimate the general equilibrium price flexibility of demand for corn and soybeans using monthly changes in expected supply published by the USDA. Our estimates reflect the demand response to a one-year supply shock and thus correspond to the inverse demand elasticity. We derive the conditions under which our estimates are consistent, and we show how demand flexibility varies by season, inventory, time horizon, and demand composition. At average inventory and without accounting for corn-ethanol use, we obtain price flexibility estimates of - 1.35 and - 1.03 for corn and soybeans, respectively. Current corn-ethanol production levels are associated with much larger absolute flexibilities for both commodities. Copyright 2012, Oxford University Press.

In this article, we show that vehicle type ownership is spatially dependent at both the regional and household-level even after controlling for income and population density. We discuss reasons for the existence of spatial effects in vehicle ownership, and note potential implications for policymakers. Our results point to the importance of spatial relationships in transportation research and highlight the hazards of ignoring their role in affecting transportation outcomes. For example, if vehicle type choice is affected by neighborhood spillovers, agencies that regulate traffic flow and road safety could tailor their choice projections and policy tools to account for such interdependence.

State-specific case numbers and costs are critical for quantifying the burden of pulmonary nontuberculous mycobacterial disease in the United States.To estimate and project national and state annual cases of nontuberculous mycobacterial disease and associated direct medical costs.Available direct cost estimates of nontuberculous mycobacterial disease medical encounters were applied to nontuberculous mycobacterial disease prevalence estimates derived from Medicare beneficiary data (2003-2007). Prevalence was adjusted for International Classification of Diseases, 9th Revision, undercoding and the inclusion of persons younger than 65 years of age. U.S. Census Bureau data identified 2010 and 2014 population counts and 2012 primary insurance-type distribution. Medical costs were reported in constant 2014 dollars. Projected 2014 estimates were adjusted for population growth and assumed a previously published 8% annual growth rate of nontuberculous mycobacterial disease prevalence.In 2010, we estimated 86,244 national cases, totaling to $815 million, of which 87% were inpatient related ($709 million) and 13% were outpatient related ($106 million). Annual state estimates varied from 48 to 12,544 cases ($503,000-$111 million), with a median of 1,208 cases ($11.5 million). Oceanic coastline states and Gulf States comprised 70% of nontuberculous mycobacterial disease cases but 60% of the U.S. population. Medical encounters among individuals aged 65 years and older ($562 million) were twofold higher than those younger than 65 years of age ($253 million). Of all costs incurred, medications comprised 76% of nontuberculous mycobacterial disease expenditures. Projected 2014 estimates resulted in 181,037 national annual cases ($1.7 billion).For a relatively rare disease, the financial cost of nontuberculous mycobacterial disease is substantial, particularly among older adults. Better data on disease dynamics and more recent prevalence estimates will generate more robust estimates.

Although excessive alcohol consumption is a recognized cause of morbidity and mortality, many studies have linked moderate alcohol consumption to improved cardiovascular health and a lower risk of Type 2 Diabetes (T2D). Self-reported alcohol and diet data used to generate these results suffer from measurement error due to recall bias. We estimate the effects of diet, alcohol, and lifestyle choices on the prevalence and incidence of cardiovascular disease and T2D among U.S. adults using a nationally representative cohort of households with scanner data representing their food-at-home, alcohol, and tobacco purchases from 2007-2010, and self-reported health surveys for the same study participants from 2010-2012. Multivariate regression models were used to identify significant associations among purchase data and lifestyle/demographic factors with disease prevalence in 2010, and with incidence of new disease from 2011-2012. After controlling for important confounders, respondents who purchased moderate levels of wine were 25% less likely than non-drinkers to report heart disease in 2010. However, no alcohol-related expenditure variables significantly affected the likelihood of reporting incident heart disease from 2011-2012. In contrast, many types of alcohol-related purchases were associated with a lower prevalence of T2D, and respondents who purchased the greatest volumes of wine or beer--but not liquor--were less likely to report being diagnosed with T2D in 2011-2012 than non-drinkers.

This study aimed to describe the occurrence of Yersinia pestis, Rickettsia rickettsii, Anaplasma phagocytophilum, and ectoparasites in a wild rodent community in the eastern Sierra Nevada. From May to September 2006, rodents were live-trapped, examined for ectoparasites, and blood was collected. All rodents were serologically tested for antibodies to Y. pestis, R. rickettsii, and A. phagocytophilum; in addition, blood samples and ectoparasites were tested by PCR to detect the presence of these zoonotic agents. Overall, 89 rodents, 46 fleas, and four ticks were collected. Antibody prevalence rates observed for rodents were 14% for R. rickettsii or antigenically related spotted-fever group rickettsiae, and 8% for A. phagocytophilum. No samples were positive for antibodies to Y. pestis. Positive PCR results included one yellow-pine chipmunk for Y. pestis (CT=32.8), one golden-mantled ground squirrel for R. rickettsii (CT=33), and one flea found to be co-infected with both R. rickettsii (CT=17) and A. phagocytophilum (CT=36). The results of this study provide evidence of multiple zoonoses overlapping within a single, located rodent community.

Traditionally, researchers studying transportation choice have used data either acquired from household surveys or broad, region-wide aggregates. At the disaggregate level, researchers usually do not have access to important variables or observations. This study investigates the potential usefulness of a proxy approach to modeling discrete choice vehicle ownership: substituting narrow area-based aggregate proxies for missing micro-level explanatory variables by accessing large, publicly maintained datasets. We use data from the 2000 Bay Area Travel Survey (BATS) and the contemporaneous U.S. Census file to compare three models of vehicle ownership, drawing area-wide proxies from increasing levels of aggregation. The models with proxies are compared with a parallel model that uses only survey data. The results indicate that the proxy models are preferred in terms of model selection criteria, and predict vehicle ownership as well or better than the survey model. Parameter values produced by the proxy method effectively approximate those returned by household survey models in terms of coefficient sign and significance, particularly when the aggregate variables are representative of their household-level counterparts. The proxy model with the narrowest level of aggregation achieved the best fit, coefficient precision, and percentage of correct prediction.