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The Commodity Futures Trading Commission (CFTC) recently identified large intra‐day price changes or “flash events” in continuously traded commodity futures markets. These flash events fueled discussion on whether futures markets are becoming less effective as human intervention is diminishing in favor of automated trading. Using intra‐day data, we examine liquidity resilience during “flash events” in corn and lean hog futures markets from 2014 to 2019. Overall, we find little evidence that the liquidity provision in these two markets relative to normal days becomes fragile when large price movements occur. Our analysis suggests that flash events are heavily influenced by unanticipated changes in fundamentals that may lead to a new equilibrium price. Liquidity dynamics during these events supports the view that active market making helps absorb the increased volume and stabilize markets.

The article sheds light on price jump risk in corn futures prices in the era of electronic trading and after the shift to real‐time announcement of USDA reports. Using intraday prices from 2008 to 2015, we employ a nonparametric test to detect jumps and variance analysis to assess the relative importance of jump risk. Real‐time trading of major USDA reports has substantially increased the frequency and clustering of price jumps, and results in higher market liquidity costs. In contrast, although the presence of jumps on non‐announcement days has doubled recently, their magnitude has declined as have transactions costs during their occurrence. The largest jump risk or execution risk is experienced by high frequency traders due to heightened microstructure noise during price jumps. However, traders holding long‐term market positions are only minimally affected by increased jump risk.

Recently, U.S. live cattle futures prices have experienced high levels of intraday price variance, which have raised concerns about the possible impact of microstructure noise from high frequency trading on market instability. This article identifies both the magnitude and the duration of the bias caused by market microstructure noise in measuring efficient price variance in the live cattle futures market from 2011 to 2016, with emphasis on price variance behavior in recent years. Market microstructure noise increases observed price variance, but its effects are not large and do not last more than three to four minutes in response to changing information. Intraday price variance has increased in recent years, but the findings provide little evidence that high frequency traders were responsible for economically meaningful market noise. Informatively, steps taken by the CME and cattle producers to mitigate noise have not been fruitful to date, and signal that the magnitude of noise will likely vary with the magnitude of changes in demand and cyclical supply.

We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices. Individual density forecasts are generated using time series models and the implied distributions of USDA and Iowa State University outlook forecasts. Composite density forecasts are constructed using linear and logarithmic combinations of the individual forecasts and several weighting schemes. Density forecasts are evaluated on predictive accuracy (sharpness), goodness of fit (calibration), and their economic value in a hedging simulation. Logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and are modestly better than linear composites. Comparison of the outlook forecasts to the best composite demonstrates the usefulness of the composite procedure, and identifies the economic value that more accurate expected price probability distributions can provide to producers.

In a well-functioning futures market, the futures price at expiration equals the price of the underlying asset. This condition failed to hold in grain markets for most of 2005-2010, calling into question the ability of these markets to perform their price discovery and risk management functions. During this period, futures contracts expired up to 35% above the cash grain price. We develop a dynamic rational expectations model of commodity storage that explains how these recent convergence failures were generated by the institutional structure of the delivery system. When delivery occurs on a grain futures contract, the firm on the short side of the market provides a delivery instrument (a warehouse receipt or shipping certificate) to the firm on the long side of the market. The firm taking delivery may hold the delivery instrument indefinitely, providing it pays a daily storage rate. The futures exchange sets the maximum allowable storage rate at a fixed value. We show that non-convergence arises in equilibrium when the market price of physical grain storage exceeds the maximum storage rate on delivery instruments. We call the difference between the price of carrying physical grain and the maximum storage rate the wedge , and demonstrate theoretically and empirically that the magnitude of the non-convergence equals the expected present discounted value of a function of future wedges.

A recently developed testing procedure is used to detect and date-stamp explosive episodes ("bubbles" in corn, soybean, and wheat futures markets during 2004-2013. We find that the markets experienced price explosiveness only approximately two percent of the time and, when bubbles do occur, they are generally short-lived and small in magnitude. The correspondence between observed price spikes and bubbles is rather low, with a large portion of the price explosiveness occurring during downward price movements. Commodity index trader positions do not significantly affect the probability of a positive bubble occurring in grain futures markets, which directly contradicts the argument (the "Masters Hypothesis" that waves of index investment distorted underlying supply-and-demand relationships and led to a series of massive bubbles in agricultural futures markets. In addition, commodity index trader positions tend to reduce negative bubble occurrence, while general speculative activity as measured by Working's T reduces the probability of a positive bubble. There is some evidence that the positions of noncommercial traders have a direct effect on positive bubble occurrence, but the effect declines when accounting for the composition of other traders in the market. Overall, speculation has little effect or negative effects on price explosiveness. Finally, positive bubbles are more likely to occur in the presence of low inventories, strong exports, a weak U.S. dollar, and booming economic growth, whereas negative bubbles are more likely to occur with large inventories, weak exports, and stagnant economic growth.

This is the first paper to analyze liquidity costs in agricultural futures markets based on the observed bid‐ask spread (BAS) faced by market participants. The results reveal a highly liquid corn market that mostly offers order execution at minimum cost. The BAS responds negatively to volume and positively to price volatility, but also affects volume traded and price volatility. While statistically significant, these responses on a cents/bushel or a percentage basis are generally small. Liquidity costs are also virtually impervious to short‐term changes in demand for spreading and trend‐following trader activity, as well as differences from day‐of‐the‐week changes in market activity. Much larger cents/bushel and percentage changes in BAS occur during commodity index trader roll periods and on USDA report release days. The roll period findings indicate a sunshine trading effect, while announcement effects identify the importance of unexpected information and adverse selection on order execution costs. Overall, our research demonstrates that the transition to electronic trading in the corn futures market has led to low and stable liquidity costs, despite the market turbulence in 2008–2009.

Understanding the determinants of liquidity costs in agricultural futures markets is hampered by a need to use proxies for the bid-ask spread which are often biased, and by a failure to account for a jointly determined micro-market structure. We estimate liquidity costs and its determinants for the live cattle and hog futures markets using alternative liquidity cost estimators, intraday prices and micro-market information. Volume and volatility are simultaneously determined and significantly related to the bid-ask spread. Daily volume is negatively related to the spread while volatility and volume per transaction display positive relationships. Electronic trading has a significant competitive effect on liquidity costs, particularly in the live cattle market. Results are sensitive to the bid-ask spread measure, with a modified Bayesian method providing estimates most consistent with expectations and the competitive structure found in these markets.

Options with different maturities can be used to generate volatility estimates for non-overlapping future time intervals. This paper develops the term structure of volatility implied by corn futures options, and evaluates the informational content of the implied forward volatility as a predictor of subsequent realized volatility. Using data from 1987-2001 and employing a flexible method to obtain the implied forward volatilities, two types of information are examined: 1) the market's estimate of future realized volatility for the nearby interval of the term structure and, 2) the market's expectation of the direction and magnitude of change of future realized volatility over time. In contrast to previous research, the results indicate that the implied forward volatilities anticipate the realized volatilities provide unbiased forecasts and capture a larger portion of the systematic variability in the realized volatilities than forecasts based on historical volatilities. Using information on the direction and magnitude of change in volatility over time, we find that the early-year options forecast volatility about as well as the three-year moving average and better than the naive forecast, while later-year options and alternative forecasts are less able to predict the direction and magnitude of changing volatility. During this later-year period, the implied forward volatilities tend to over-predict the magnitude of actual volatility. Overall, we find that the term structure of volatility implied by corn futures options contains information on future realized volatility.

In applied agricultural economic research various risk-attitude elicitation techniques are used. Here, we investigate whether risk-attitude measures rooted in the expected utility framework are related to measures rooted in the multi-item scale framework. Using a second-order factor analytical model, and data obtained from personal computer-guided interviews with 373 farmers, we investigate whether the common variance among the (latent) risk-attitude measures can be accounted for by a global risk-attitude construct. We find that the different risk-attitude measures are related, and that the global risk-attitude construct is significantly related to farmers’ intention to use futures contracts. Our research suggests that farmers’ risk attitude is a higher-order characteristic that cannot be effectively extracted by a single measure. In empiricalstudies deal ing with risk, risk attitudes and producers’ market behavior various risk-attitude measures are used. Two major approaches to quantify directly farmers’ risk attitudes can be distinguished: measures derived from the expected utility framework, and measures derived from responses to multi-item scales (e.g., Antle; Chavas and Holt; Goodwin and Schroeder; Saha, Shumway, and Talpaz; Smidts). The purpose of this research is to test whether risk-attitude measures rooted in the expected utility framework are related to the risk-attitude scales rooted in the multiitem scale approach and, if so, whether these risk-attitude measures share a common

We discuss and model the structure of the political economy of Japanese beef markets, and we apply Bullock's statistical test of the efficient redistribution hypothesis to our model to study the Pareto efficiency of Japanese beef policy in 1990 and 1991. We found that, under the hypothesis that our modeled political economy adequately reflects the true Japanese beef political economy, we could not reject at the 5% significance level that Japanese beef policy was inefficient in 1990 and in 1991; however, we could reject inefficiency in 1991 at a 7% level of significance. Copyright 1999, Oxford University Press.

Market power in regional fed cattle markets is measured with an econometric model which links behavior of the margin between boxed beef and fed cattle prices to an economic model of conduct. A noncooperative game theoretic model suggests that for tacitly collusive pricing behavior to persist in equilibrium, oligopsonists must follow a discontinuous pricing strategy. Meatpackers pay low prices for cattle during cooperative phases and purchase cattle aggressively during noncooperative phases. Tests for cooperative/noncooperative conduct and measures of market power are presented. Fed cattle prices in four direct trade regions in the central United States are examined. Evidence of cooperative/noncooperative conduct is present in all markets but has declined over time. Varying conduct across markets and over time suggests it is important to continue monitoring fed cattle markets to assure a competitive environment.

The financial statements considered here are the farm's balance sheet and pro forma cash flow statements. Analysis of factors influencing a farmer's decision to complete one or both of these statements involves an estimation technique appropriate for binary dependent variables. In addition, the two decisions considered here, whether to complete a balance sheet and/or a pro forma cash flow statement, are viewed as jointly determined. Hence the multivariate logistic model is used (Nerlove and Press). This paper is organized as follows: first, a conceptual framework for the acquisition of information is briefly detailed: second, the sample data used in this analysis is reviewed and a brief description of the multivariate logit model presented; finally, results for the sample are presented and discussed.

A comparison of primal and dual methods for measuring the impact of ozone on the profits and outputs of Illinois cash grain farms uses the sample data in Mjelde et al. after adding an additional year of data and making refinements. On the basis of the evidence presented, it is not possible to say definitively whether the production or profit function specification is superior. Both models seem to fit the data well and give plausible results in terms of indicating if an effect is present. While ozone has been shown to be deleterious to an individual farmer, however, this does not imply that reductions in ozone levels throughout the nation would lead to increased farmer profits. It could lead to an increase in supply, which would likely cause a decrease in price. Other factors highly correlated with ozone could also be responsible for the observed effect. 7 references, 1 table.

Apparently Teague has not reviewed all of the literature for examining relative efficiency. In the early work of Lau and Yotopoulos (LY), differences in economic efficiency are tested by incorporating only a dummy variable in the profit function to quantify differences associated with particular groups. (Teague implicitly argues that only this should have been done as evidenced by the assertion that equations (2) and (3) are redundant.) In an extension of this early work, Yotopoulos and Lau (YL) expand their conceptual framework to permit the assessment of relative technical and pricing efficiency as well as overall economic efficiency. This latter framework is utilized by Garcia, Sonka, and Yoo. Under this formulation, the profit functions of the two firms or groups under analysis differ by a constant factor which is a function of technical and pricing efficiency. In addition, the demand equations may differ across groups by constant factors which are a function of pricing efficiency. Similar formulations also are presented in Trosper, O'Connor and Hammonds, and Khan and Maki. Perhaps Teague's difficulty arises from either a misunderstanding of the methodology or an unfamiliarity with the approach and its standard notation. In the former case, the methodology permits tests for the relative efficiency (pricing and economic) without imposing it. That is, actual UOP and demand functions can be derived based on behavioral relationships. Differences in actual functions permit an assessment of relative efficiency. In the latter, producers respond to "effective prices." Profits and demand equations are derived based on these effective prices, not actual prices. The p's in Garcia, Sonka, and Yoo can be shown to represent an underlying structure that permits differences in efficiency between the groups based on effective prices. To understand the logic behind this formulation, consider the concept of relative efficiency developed by YL. This approach begins with the notion that given comparable endowments, identical technology, and normalized input prices, the actual profits of two firms should be identical if they both maximize profits. To the extent that one is more price efficient, or technically more efficient, than the other, the normalized profits will differ even for the same normalized input prices and endowments of fixed inputs. The actual normalized profit functions will then be different. Consider the case of the production functions of two firms: (4) Y = AIF(X', ZI); and r2 = A2F(X2, Z2), where the X's and Z's are variable and fixed inputs, respectively, A1 and A2 are scalar technical efficiency parameters, and the superscripts represent the two firms. The marginal conditions can be represented by

This study examines the effects of exchange rate uncertainty on bilateral soybean trade flows and finds that imports for Japan, France, and Spain are sensitive to short-term variations in nominal bilateral exchange rates. This research extends previous work by focusing on bilateral trade for a single commodity, using a longer sample period, and testing over a variety of model specifications. The results suggest that the effects vary across countries depending on access to forward markets, the availability of alternative soybean suppliers, the degree of market concentration in the domestic soybean processing sector, and the degree of currency risk importers are willing to assume. The decline in U.S. agricultural exports during the 1980s has been explained by numerous factors including stagnant world income, increased foreign competition, the existence of trade barriers, and the level of the exchange rate. An additional factor, exchange rate volatility, has received less attention in agricultural trade models. Since the adoption of the flexible exchange rate system in the early 1970s, variability in exchange rates has had a potentially destabilizing impact on trade. Disruptions in trade can occur because exchange rate variations change the actual price paid or received for traded goods, causing adjustments in quantities traded, domestic prices, or in the timing of sales in order to avoid the effects of variability on profits.' Other, longer-term effects may occur if exchange rate uncertainty persists. To the extent that goods are substitutable, such adjustments can be manifested as a sustained preference for domestic suppliers over foreign suppliers or alternative sources of foreign supply may be explored. The magnitude of the effect of exchange rate uncertainty on quantity imported is dependent upon, inter alia, the respective exchange rate elasticities and the importer's response to variability; for some goods this magnitude can be substantial. The objective of this study is to determine

Unanticipated basis changes can reduce the ability of futures markets to transfer risk and can affect income levels of producers and market participants. This study examines short-term basis risk, defined as the variance of the random component of the basis over time, for several Midwest livestock markets. Basis risk is related to several factors influencing the long-term pattern in the time series and unexpected changes in price. Little evidence is found that basis risk changed as maturity approached or that risk varied across markets except for the Interior Iowa hog market.

Empirical evidence about new corn production technology in Illinois supports the hypothesis that yield- and output-enhancing effects vary depending on whether technology is input (here, land) quality-dependent or independent. In turn, these differences affect the distribution of economic surplus from technology adoption across geographic regions with varying land quality. A competitive, market-clearing model for a traded commodity is used to estimate the gains in economic surplus from technological advance.

The pricing efficiency of the live cattle futures market is evaluated using out-of-sample forecasts from an econometric model, an ARIMA model, and composite forecasting procedures. In terms of the mean-squared error criterion, a necessary condition for market efficiency, at least one of the models, and frequently more, forecasted more accurately than did the futures market. However, market simulation results based on the most accurate forecasts generated large risk-return ratios. These results do not show strong evidence of inefficiency and call into question the use of only mean-squared errors to examine a market's pricing efficiency.

Four hypotheses about the price-forecasting performance of live cattle and hog futures are tested using disaggregated data. Live cattle futures are found to have inadequate forecasting performance for each hypothesis and do not provide better forecasts than lagged cash prices. Live hog futures perform well for three hypotheses, but not when economic conditions are unstable. Hog futures provide better forecasts than lagged cash prices. The analysis does not support the contention that these futures markets are agencies for rational price formation.

Falling agricultural incomes, declining exports, and emerging biotechnologies have rekindled concern over farm structure and the viability of the medium-sized (often identified as the "family") farm. (See Stanton 1984 for a comprehensive discussion of farm structure issues.) Recent studies by Edwards, Smith, and Patterson; Zulauf; and the Office of Technology Assessment (OTA) examine the changing nature of the size distribution of U.S. farms. Gardner and Pope and also Leiby and Sumner investigate forces affecting farm growth. These studies are difficult to compare because of differences in models, time periods, and size measures used in empirical analyses. For example, a comparison of the OTA and the Edwards, Smith, and Patterson studies leads to very different views of farm sector structure in 2000. The OTA results, based on analysis of deflated gross value of farm income from 1969 to 1982, suggest a movement towards a bimodal distribution of very small and very large farms. In contrast, the USDA study, using acreage to measure farm size over a shorter period, 1974 to 1978, predicts a more stable distribution similar to today's. Interpretation of these results is complicated by the difficulty of defining farm size for a heterogenous set of multiple enterprise farms, the limited range of categories used to describe farm growth, and the lack of microlevel evidence to corroborate findings based on aggregate agricultural census data. The purpose of this analysis is to assess evidence of change in the size distribution of a sample of 161 Illinois cash grain farms over the past decade. Three issues are addressed in the empirical investigation. Markov transition probability matrices are estimated first, to investigate changes in distribution of the sample over the period 1976 to 1985. Second, we consider whether the results of this analysis and our predictions of future farm structure are invariant with respect to the measure of size used. Third, discriminant analysis is applied to identify factors associated with change in farm size.

International phenomena are having increased influence on U.S. agriculture (Schuh). One dimension of this increased interdependence is the rapid increase in the value of U.S. agricultural exports and imports, 349% and 209%, respectively, since 1970 (Kellogg). The value of U.S. agricultural exports has increased at a rate over twice as fast as total farm gross cash income since 1970-349% versus 155% (USDA, Economic Indicators). Not only have exports increased in importance, but their destination has changed. The percentage of U.S. agricultural exports going to developing countries has increased from 34.6 in 1974-76 to 41.3 in 1983-85 (table 1). Another dimension of this interdependence is agricultural development assistance which has received varying emphases during the past three decades in the U.S. development assistance program. In 1975, Congress passed Title XII of the Foreign Assistance Act, which provided a congressional mandate for the involvement of U.S. land grant and other similar universities in U.S. foreign aid programs (York). One area of emphasis in Title XII is agricultural development, and most land-grant universities have been involved in projects designed to increase agricultural production in developing countries. Recently, the U.S. farm sector has faced a number of conditions that have adversely affected farmers' net income and net worth positions. The 29% decline in value of agricultural exports since 1981 has contributed to the severity of these problems (table 1). Some believe that increased agricultural production in developing countries has been substantially responsible for the decline in U.S. agricultural exports (Avery). In this situation of increased international interdependence, declining export sales and other farm problems, and increased visibility of land grant university involvement in agricultural assistance to developing countries, U.S. agricultural leaders have become concerned about the relationship between increasing agricultural production in developing countries and those countries' agricultural imports. The purpose of this inquiry is to provide a preliminary examination of the relationship between imports of agricultural products into developing countries and changes in domestic agricultural production in these countries. The specific question is: What have been the effects of increased per capita production in developing countries on agricultural imports into these countries?