Most previous studies reject the basic tenet of the Masters Hypothesis that the influx of financial index investments has pressured agricultural futures prices upwards substantially. However, the impact of index investment activities may be more complicated and nuanced than can be detected by the relatively simple linear Granger causality tests used in many previous studies. Our study applies a new cross-quantilogram (CQ) test to weekly index trader positions and returns in four agricultural futures markets. Overall, we find limited support for a significant relationship between extreme index trader position changes and returns, and even less support that increased index trading activities have pushed commodity prices higher.

In this paper we seek to characterize the robustness of the ENSO/soybean price relationship and to determine whether it has practical economic content. If such a meaningful relationship exists, the implications could be profound for commodity traders and for public sector investments in climate forecasting capabilities. Also, the validity of economic evaluations of climate impacts and climate forecasts based on ENSO-price independence would come into question. Our findings suggest a relationship between interannual climate and soybean prices, although we are not able to attribute the relationship to ENSO or to say that ENSO is economically important.

We examine the causal relationships between ethanol production and the agricultural economy and rural incomes in the United States for 1981 through 2010. We use bivariate cointegration and Granger causality procedures and account for two structural breaks in ethanol production in the analysis, which shows that ethanol production Granger-caused agricultural net value added, agriculture's share of U.S. employment, net returns to operators, and rural income per capita in the short run. These causal relationships generally persisted in the long run. However, the causality between ethanol and rural incomes diminished in the long run.

This study presents a testing methodology to analyze potential price asymmetries among the farm, wholesale, and retail levels of the U.S. broiler industry. Lag length, direction of causality, and asymmetric relationships are empirically determined. Results suggest that concentration and power of the integrators in the industry have allowed the wholesale price to become the center, causal price in the market. Asymmetric price transmissions, however, are limited. While downward movements in the wholesale price are passed on more fully to growers than increases in the wholesale price, only consumers in the North Central region of the U.S. share a larger portion of wholesalers’ price increases than price decreases.

Efforts to stabilize employment and output in the agricultural sector of Yugoslavia through monetization contributed to inflationary pressures. Granger causality tests suggest that increases in the rate of growth in the supply of money to subsidize state-owned agribusinesses were insufficient to maintain purchases of wheat and corn, but did cause purchases of cattle and swine. This result may be explained by producers having more flexibility in grain marketing (i.e., storage options and private buyers) and the perishability issues related to livestock marketing. The policy to maintain employment through monetization is shown to have been ineffective.

Agricultural economists have recently been attracted to procedures suggested by Granger and others which allow observed data to reveal causal relationships. Results of this study indicate that “causality” tests can be ambiguous in identifying behavioral relationships between agricultural price variables. Caution is suggested when using such procedures for model choice.

Although blind people heavily depend on working memory to manage daily life without visual information, it is not clear yet whether their working memory processing involves functional reorganization of the memory-related cortical network. To explore functional reorganization of the cortical network that supports various types of working memory processes in the early blind, we investigated activation differences between 2-back tasks and 0-back tasks using fMRI in 10 congenitally blind subjects and 10 sighted subjects. We used three types of stimulus sequences: words for a verbal task, pitches for a non-verbal task, and sound locations for a spatial task. When compared to the sighted, the blind showed additional activations in the occipital lobe for all types of stimulus sequences for working memory and more significant deactivation in the posterior cingulate cortex of the default mode network. The blind had increased effective connectivity from the default mode network to the left parieto-frontal network and from the occipital cortex to the right parieto-frontal network during the 2-back tasks than the 0-back tasks. These findings suggest not only cortical plasticity of the occipital cortex but also reorganization of the cortical network for the executive control of working memory. (JINS, 2011, 17, 407–422)

Clive W.J. Granger has summarized his personal viewpoint on testing for causality in numerous articles over the past 30 years and has outlined what he considers to be a useful operational version of his original definition of Granger causality, which he notes is partially alluded to in the Ph.D. dissertation of Norbert Wiener. This operational version of Granger causality is based on a comparison of the one-step-ahead predictive ability of competing models. However, Granger concludes his discussion by noting that it is common practice to test for Granger causality using in-sample F-tests. The practice of using in-sample type Granger causality tests continues to be prevalent. In this paper we develop simple (nonlinear) out-of-sample predictive ability tests of the Granger non-causality null hypothesis. In addition, Monte Carlo experiments are used to investigate the finite sample properites of the test. An empirical illustration shows that the choice of in-sample versus out-of-sample Granger causality tests can crucially affect the conclusions about the predictive content of money for output.