HOW DIFFERENTLY DO THE AGRICULTURAL AND INDUSTRIAL SECTORS RESPOND TO EXCHANGE RATE FLUCTUATION?

This study divides the U.S. economy into the agricultural and industrial sectors and compares the degree of involvement of exchange rates in each sector without specifying the rigid assumption of either exogeneity or endogeneity of exchange rates. Both short- and long-run impacts of shocks in the exchange rate are found to be significant. However, the effect of an exchange rate shock on the agricultural sector is larger than that on the industrial sector. This study examines a fundamental question about the role of the exchange rate in the two sectors. The exchange rate is exogenous in the agricultural sector, while being endogenous in the industrial sector.role of exchange rates, endogeneity, exogeneity, over-identification, short- and long-run impulse response., International Relations/Trade,

NONPARAMETRIC KERNEL ESTIMATION OF MULTIPLE HEDGE RATIOS

It is possible for the traditional hedge ratio estimation to produce erroneous guidance to risk managers because of the restrictive assumptions. This study adopts nonparametric locally polynomial kernel estimation to exclude the assumptions. Results from the hog complex find that hedge ratios estimated by local polynomial kernel regression outperform naïve and GARCH models. Because of the potential assumption violations associated with the estimation and implementation of hedge ratios by GARCH models, LPK is a reasonable alternative for estimating hedge ratios to manage price risks.Marketing, Research Methods/ Statistical Methods, Risk and Uncertainty,

THE DISTRIBUTIONAL BEHAVIOR OF FUTURES PRICE SPREADS

The distributional behavior of futures price spreads is examined for four commodities: corn, live cattle, gold and T-bonds. Remarkably different results are found over commodities, time period, and sample size. Actual spread changes for the smaller sample size of gold and T-bonds and for corn produce more normal distributions for weekly than for daily differencing intervals, while all live cattle spreads for actual changes are normally distributed. However, the larger sample size of both gold and T-bonds and the relative spread changes for corn and live cattle do not become more normally distributed under temporal aggregation of the data.corn, futures price spreads, gold, goodness of fit, live cattle, normality tests, spread distributions, T-bonds, Marketing,

Causal Inference in Disease Spread across a Heterogeneous Social System

Diffusion processes are governed by external triggers and internal dynamics in complex systems. Timely and cost-effective control of infectious disease spread critically relies on uncovering the underlying diffusion mechanisms, which is challenging due to invisible causality between events and their time-evolving intensity. We infer causal relationships between infections and quantify the reflexivity of a meta-population, the level of feedback on event occurrences by its internal dynamics (likelihood of a regional outbreak triggered by previous cases). These are enabled by our new proposed model, the Latent Influence Point Process (LIPP) which models disease spread by incorporating macro-level internal dynamics of meta-populations based on human mobility. We analyse 15-year dengue cases in Queensland, Australia. From our causal inference, outbreaks are more likely driven by statewide global diffusion over time, leading to complex behavior of disease spread. In terms of reflexivity, precursory growth and symmetric decline in populous regions is attributed to slow but persistent feedback on preceding outbreaks via inter-group dynamics, while abrupt growth but sharp decline in peripheral areas is led by rapid but inconstant feedback via intra-group dynamics. Our proposed model reveals probabilistic causal relationships between discrete events based on intra- and inter-group dynamics and also covers direct and indirect diffusion processes (contact-based and vector-borne disease transmissions).Comment: arXiv admin note: substantial text overlap with arXiv:1711.0635

RELATIVE AGRICULTURAL PRICE CHANGES IN DIFFERENT TIME HORIZONS

Using a monthly data covering from 1974:1 to 2002:12, this paper explores the linkage between changes in macroeconomic variables (real exchange rate and inflation rate) and changes in relative agricultural prices in different time horizons (1, 12, 24, 36, 48, and 60 months). Controlling for factors likely to determine the long run trend of relative agricultural prices, the results show that long-term changes in real exchange rate has had a significant negative correlation with the long-term changes in relative agricultural prices. Conversely, changes of the general price have a role in explaining short-term changes in relative agricultural price at best.Demand and Price Analysis,

HOW DIFFERENTLY AGRICULTURAL AND INDUSTRIAL SECTORS RESPOND TO EXCHANGE RATE FLUCTUATION?

This study divides the U.S. economy into the agricultural and industrial sectors and compares the degree of the involvement of exchange rates in each sector without specifying the rigid assumption of either exogeneity or endogeneity of exchange rates. Both short- and long-run impacts of shocks in the exchange rate are found to be significant. However, the effect of an exchange rate shock on the agricultural sector is larger than the industrial sector. This study fulfills a fundamental question about the role of exchange rate between the two sectors. The exchange rate is exogenous in the agricultural sector, while being endogenous in the industrial sector.Agricultural Finance,

Macro Effects on Agricultural Prices in Different Time Horizons

Using monthly data covering 1974:1 to 2002:12, this paper explores the linkage between changes in macroeconomic variables (real exchange rate and inflation rate) and changes in relative agricultural prices in different time horizons (1, 12, 24, 36, 48, and 60 months). By controlling factors that determine the long-run trend of relative agricultural prices, the results show that long-term changes in real exchange rates have had a significant negative correlation with the long-term changes in relative agricultural prices. Conversely, changes in the general price significantly affect short-term changes in the relative agricultural price.Relative agricultural price, exchange rates, inflation rates, unit root test, canonical cointegration regression, money neutrality, Demand and Price Analysis,

DETERMINING BILATERAL TRADE PATTERNS USING A DYNAMIC GRAVITY EQUATION

Using a dynamic gravity equation, we show that the national product differentiation model explains food and agricultural trade more properly, while the product differentiation model is more appropriate to explain large-scale manufacturing trade. In this context, our result is not consistent with the one found by Head and Ries (2001) in the short-run. The intuitive explanation for this result is that inward foreign direct investment can occur through either merger or acquisition in the short-run. Second, the pattern of bilateral trade could quickly adjust to changes in relative income between countries. Furthermore, we illustrate the positive impacts of world income growth on bilateral trade, which is in sharp contrast with the conventional analysis. This reveals yet another way to test the pattern of bilateral trade.dynamic gravity equation, national product differentiation, product differentiation, world income growth, International Relations/Trade,