Crop Yield and Price Distributional Effects on Revenue Hedging

The use of crop yield futures contracts is examined. The expectation being modeled here reflects that of an Illinois corn and soybeans producer at planting, of revenue realized at harvest. The effects of using price and crop yield contracts are measured by comparing the results of the expected distribution to the expected distribution found under five general alternatives: 1) a revenue hedge using just price futures, 2) a revenue hedge using crop yield futures, 3) an unhedged scenario where revenue is determined by realized prices and yields, 4) an unhedged scenario where revenue is determined by realized prices and yields and by participation in government support programs with deficiency payments, and 5) a no hedge scenario where revenue is determined by realized prices and yields and by participation in a proposed revenue-assurance program. We draw four major conclusions from the results. First, hedging effectiveness using the new crop yield contract depends critically on yield basis risk which presumably can be reduced considerably by covering large geographical areas. Second, crop yield futures can be used in conjunction with price futures to derive risk management benefits significantly higher than using either of the two alone. Third, hedging using price and crop yield futures has a potential to offer benefits larger than those from the simulated revenue assurance program. However, the robustness of the findings depends largely on whether yield basis risk varies significantly across regions. Finally, the qualitative results described by the above three conclusions do not change depending on whether yields are distributed according to the beta or lognormal distribution.published or submitted for publicationnot peer reviewe

CROP YIELD AND PRICE DISTRIBUTIONAL EFFECTS ON REVENUE HEDGING

The use of crop yield futures contracts is examined. The expectation being modeled here reflects that of an Illinois corn and soybeans producer at planting, of revenue realized at harvest. The effects of using price and crop yield contracts are measured by comparing the results of the expected distribution to the expected distribution found under five general alternatives: 1) a revenue hedge using just price futures, 2) a revenue hedge using crop yield futures, 3) an unhedged scenario where revenue is determined by realized prices and yields, 4) an unhedged scenario where revenue is determined by realized prices and yields and by participation in government support programs with deficiency payments, and 5) a no hedge scenario where revenue is determined by realized prices and yields and by participation in a proposed revenue-assurance program. We draw four major conclusions from the results. First, hedging effectiveness using the new crop yield contract depends critically on yield basis risk which presumably can be reduced considerably by covering large geographical areas. Second, crop yield futures can be used in conjunction with price futures to derive risk management benefits significantly higher than using either of the two alone. Third, hedging using price and crop yield futures has a potential to offer benefits larger than those from the simulated revenue assurance program. However, the robustness of the findings depends largely on whether yield basis risk varies significantly across regions. Finally, the qualitative results described by the above three conclusions do not change depending on whether yields are distributed according to the beta or lognormal distribution.Marketing,

Criminal Justice Decision Making as a Stratification Process: The Role of Race and Stratification Resources in Pretrial Release

Our purpose is to bridge the criminal justice and stratification research literatures and to pursue the argument that homologous structural principles stratify allocation processes across central institutions of American society. The principle observed here in the making of bail decisions, as in earlier studies of the allocation of earnings, is that stratification resources operate to the greater advantage of whites than blacks. The operation of this principle is established through the estimation of covariance structure models of pretrial release decisions affecting 5660 defendants in 10 federal courts. Education and income are treated in this study as observed components of a composite construct, stratification resources, which works to the greater advantage of whites. Prior record is also found to operate to the greater advantage of whites. Two further variables, dangerousness and community ties, increase bail severity among blacks and whites. While the effect of community ties has been legally legitimized since the Bail Reform Act of 1966, the effect of dangerousness was not so legitimized until the Bail Reform Act of 1984. However, because our data precede the latter act, they confirm that this act simply reinstitutionalized earlier practice. Meanwhile, our race-specific findings may explain why although this and earlier studies find negligible main effects of race on criminal justice outcomes, black Americans nonetheless perceive more criminal injustice than do whites. In the criminal justice system, as in other spheres of American society, whites receive a better return on their resources, but our findings that the statutory severity of the offense and dangerousness work to the relative disadvantage of white defendants’ challenges conflict and labeling theory\u27s one-dimensional characterization of black defendant disadvantage

ABERRANT TESTA SHAPE encodes a KANADI family member, linking polarity determination to separation and growth of Arabidopsis ovule integuments

The Arabidopsis aberrant testa shape (ats) mutant produces a single integument instead of the two integuments seen in wild-type ovules. Cellular anatomy and patterns of marker gene expression indicate that the single integument results from congenital fusion of the two integuments of the wild type. Isolation of the ATS locus showed it to encode a member of the KANADI (KAN) family of putative transcription factors, previously referred to as KAN4. ATS was expressed at the border between the two integuments at the time of their initiation, with expression later confined to the abaxial layer of the inner integument. In an inner no outer (ino) mutant background, where an outer integument does not form, the ats mutation led to amorphous inner integument growth. The kan1 kan2 double mutant exhibits a similar amorphous growth of the outer integument without affecting inner integument growth. We hypothesize that ATS and KAN1/KAN2 play similar roles in the specification of polarity in the inner and outer integuments, respectively, that parallel the known roles of KAN proteins in promoting abaxial identity during leaf development. INO and other members of the YABBY gene family have been hypothesized to have similar parallel roles in outer integument and leaf development. Together, these two hypotheses lead us to propose a model for normal integument growth that also explains the described mutant phenotypes

Placental biomarkers of phthalate effects on mRNA transcription: application in epidemiologic research

<p>Abstract</p> <p>Background</p> <p>CYP19 and PPARγ are two genes expressed in the placental trophoblast that are important to placental function and are disrupted by phthalate exposure in other cell types. Measurement of the mRNA of these two genes in human placental tissue by quantitative real-time polymerase chain reaction (qPCR) offers a source of potential biomarkers for use in epidemiologic research. We report on methodologic challenges to be considered in study design.</p> <p>Methods</p> <p>We anonymously collected 10 full-term placentas and, for each, sampled placental villi at 12 sites in the chorionic plate representing the inner (closer to the cord insertion site) and outer regions. Each sample was analyzed for the expression of two candidate genes, aromatase (CYP19) and peroxisome proliferator activated receptor protein gamma (PPARγ) and three potential internal controls: cyclophilin (CYC), 18S rRNA (18S), and total RNA. Between and within placenta variability was estimated using variance component analysis. Associations of expression levels with sampling characteristics were estimated using mixed effects models.</p> <p>Results</p> <p>We identified large within-placenta variability in both transcripts (>90% of total variance) that was minimized to <20% of total variance by using 18S as an internal control and by modelling the means by inner and outer regions. 18S rRNA was the most appropriate internal control based on within and between placenta variability estimates and low correlations of 18S mRNA with target gene mRNA. Gene expression did not differ significantly by delivery method. We observed decreases in the expression of both transcripts over the 25 minute period after delivery (CYP19 p-value for trend = 0.009 and PPARγ (p-value for trend = 0.002). Using histologic methods, we confirmed that our samples were comprised predominantly of villous tissue of the fetal placenta with minimal contamination of maternally derived cell types.</p> <p>Conclusion</p> <p>qPCR-derived biomarkers of placental CYP19 and PPARγ gene expression show high within-placental variability. Sampling scheme, selection of an appropriate internal control and the timing of sample collection relative to delivery can be optimized to minimize within-placenta and other sources of underlying, non-etiologic variability.</p

Communication: Dopant-induced solvation of alkalis in liquid helium nanodroplets

Alkali metal atoms and small alkali clusters are classic heliophobes and when in contact with liquid helium they reside in a dimple on the surface. Here we show that alkalis can be induced to submerge into liquid helium when a highly polarizable co-solute, C60, is added to a helium nanodroplet. Evidence is presented that shows that all sodium clusters, and probably single Na atoms, enter the helium droplet in the presence of C60. Even clusters of cesium, an extreme heliophobe, dissolve in liquid helium when C60 is added. The sole exception is atomic Cs, which remains at the surface

An Introduction to the General Monotone Model with Application to Two Problematic Data Sets

We argue that the mismatch between data and analytical methods, along with common practices for dealing with “messy” data, can lead to inaccurate conclusions. Specifically, using previously published data on racial bias and culture of honor, we show that manifest effects, and therefore theoretical conclusions, are highly dependent on how researchers decide to handle extreme scores and nonlinearities when data are analyzed with traditional approaches. Within LS approaches, statistical effects appeared or disappeared on the basis of the inclusion or exclusion of as little as 1.5% (3 of 198) of the data, and highly predictive variables were masked by nonlinearities. We then demonstrate a new statistical modeling technique called the general monotone model (GeMM) and show that it has a number of desirable properties that may make it more appropriate for modeling messy data: It is more robust to extreme scores, less affected by outlier analyses, and more robust to violations of linearity on both the response and predictor variables compared with a variety of well-established statistical algorithms and frequently possesses greater statistical power. We argue that using procedures that make fewer assumptions about the data, such as GeMM, can lessen the need for researchers to use data-editing strategies (e.g., to apply transformations or to engage outlier analyses) on their data to satisfy often unrealistic statistical assumptions, leading to more consistent and accurate conclusions about data than traditional approaches of data analysis.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline