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 paper investigates the linkages between commodity price bubbles and macroeconomic factors, with an application to agricultural commodity markets in China from 2006 to 2014. Price bubbles are identified using a newly-developed recursive righttailed unit root test. A Zero-inflated Poisson Model is used to analyze the factors contributing to bubbles. Results show that a) there were speculative bubbles in most of the Chinese agricultural commodities during the sample period, though their presences are rather infrequent; b) economic growth, money supply and inflation have positive effects on bubble occurrences, while interest rate has a negative effect; c) among all macroeconomic factors considered, economic growth and money supply have the greatest effects on bubble occurrences. Our findings shed new light on the nature and formation of bubble behavior in the Chinese agricultural commodity markets.
We conduct a comprehensive evaluation of the season-average price projections for U.S. corn as published by the U.S. Department of Agriculture's World Agricultural Supply and Demand Estimates (WASDE), an important issue given reduced resources and increased program scrutiny within the Federal Government. This study is the first in the literature to evaluate the WASDE corn projections relative to futures adjusted forecasts throughout the forecasting cycle using a lengthy evaluation period (1980/81-2012/13). We find that WASDE projections provide lower RMSEs relative to futures adjusted forecasts for 9 of the 16 forecast periods, 4 of which are statistically different. Encompassing tests show that WASDE projections often provide incremental information not present in the futures adjusted forecasts. Composite forecasts based on futures adjusted forecasts and WASDE projections reduced the RMSEs over all forecast periods by an average 12-16%. Favorable average trading profits may be generated for some forecast months using WASDE projections. Overall, our results suggest that WASDE projections of the U.S. corn season-average price provide useful information to the market and could enhance the efficiency of the agricultural sector.JEL classifications: Q11, Q13
Purpose
The purpose of this study is to investigate the causal linkages between tourism and economic growth in the USA and determine how they respond to shocks in the system.
Design/methodology/approach
The study uses a variety of time series procedures, including the bounds test, Granger causality test, impulse response functions and generalized variance decomposition to analyze the relationship between monthly tourist arrivals (TA) to the USA, real gross domestic product (GDP) and real effective exchange rates.
Findings
Results suggest that GDP Granger causes TA in the USA in the long run, indicating the economy-driven tourism growth hypothesis. Additionally, a shock to GDP generates a positive and significant effect on TA that persists in the long-run, while exchange rate shocks only have a significant effect in the first six months.
Research limitations/implications
Different tourism sectors may exert different degrees of influence on the economy. The use of aggregate data on TA in the analysis assumes homogeneity in the industry, thus, only represents the average relationship between tourism and GDP.
Practical implications
This study provides insight that shapes the investment, marketing, sustainability decisions of the public and private sectors aim at increasing tourist flows to drive economic development at the national, state and local levels.
Originality/value
Though several studies have examined the factors influencing the international tourist demand of the USA, this is the first to investigate the causal relationships between tourism, GDP and exchange rates for the USA. It is also the first in the US tourism literature to account for the nature of interactions between the three variables because of innovations in the system.
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