This study proposes and evaluates a new procedure for use in analysis of both agricultural markets and prices. Causal models of both corn and wheat prices are presented as empirical examples. Results have implications for both grain market structure and the robustness of Granger‐type causality tests.
Grain, hog, and fed cattle producers were surveyed to identify factors affecting the use of selected marketing alternatives. Iowa data were collected on farm size, financial status, management practices, and farm policy preferences. Differences were found among farm operators marketing various commodities. In all regressions, use of one forward pricing alternative was related to use of other forward pricing alternatives. Gross sales appeared to be related to the use of forward pricing alternatives for all enterprises. Finally, the study identified various factors that may help agribusinesses to more effectively target education programs on the forward pricing alternatives.
One of the most common problems faced by analysts of agribusiness markets is that available data are aggregated to a degree that obscures the underlying decision process. This article reminds analysts of the implications of temporal data aggregation for market identification and its effects on the robustness of empirical results. Also, three major commodity market price series are analyzed to demonstrate how aggregation can affect empirical results. Finally, guidelines are suggested for selecting the appropriate level of aggregation for empirical problems.One of the most common problems faced by analysts of agribusiness markets is that available data are aggregated to a degree that obscures the underlying decision process. In particular, temporal data aggregation is a major source of specification error in economic time series analysis because it involves missing information. l,* The implications of time series aggregation for economic modeling has been occasionally analyzed since the 1950s. Yet, empirical studies of agricultural markets continue to use data sets containing daily, one day of the week, weekly average, monthly average, quarterly, and annual prices while largely ignoring the implications of such aggregation.Learner3 suggests the addition of two words to econometric discourse: "whimsy" and "fragile". According to Learner:In order to draw inferences from data as described by econometric texts, it is necessary to make whimsical assumptions. The professional audience consequently and properly withholds belief until an inference is shown to be adequately insensitive (not fragile) to the choice of assumptions.Hypothesis tests using regression often require a large number of distributional assumptions in order to estimate the models. The concept of "fragile" refers to This is Giannini Foundation Research Paper No. 906.
The authors are faculty members oft respectively,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.