Causality in Quantiles and Dynamic Stock Return-Volume Relations

This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in distribution, as opposed to the existing tests that check only noncausality in certain moment. This test is readily extended to test non-causality in different quantile ranges, and the testing results enable us to identify the quantile range for which causality is relevant. In the empirical studies of 3 major stock market indices, we find that, while the conventional test suggests no causality in mean, there are strong evidences that lagged volume Granger causes return in all but some middle quantiles. In particular, the causal effects have opposite signs at lower and upper quantiles and are stronger at more extreme quantiles. These relations form (symmetric) V shapes across quantiles. They also show that the dispersion of the return distribution increases with volume so that volume has a positive effect on return volatility. It is also shown that the quantile causal effects of lagged return on volume are mainly negative.Granger non-causality in quantiles, quantile causal effect, quantile regression, return-volume relation, sup-Wald test

Estimating the Impacts of Climate Change on Mortality in OECD Countries

The major contribution of this study is to combines both climatic and macroeconomic factors simultaneously in the estimation of mortality using the capital city of 22 OECD countries from the period 1990 to 2008. The empirical results provide strong evidences that higher income and a lower unemployment rate could reduce mortality rates, while the increases in precipitation and temperature variation have significantly positive impacts on the mortality rates. The effects of changing average temperature on mortality rates in summer and winter are asymmetrical and also depend on the location. Combining the future climate change scenarios with the estimation outcomes show that mortality rates in OECD countries in 2100 will be increased by 3.77% to 5.89%.Climate change; mortality; panel data model

Chemotaxonomic Analysis of the Venom Composition within the Ant Genus Strumigenys (Hymenoptera, Formicidae) in Taiwan

In Taiwan, the ant genus Strumigenys is represented by 13 species, nine of which being endemic to this island. Classic morphological taxonomy can be complex and may lead to equivoque identification within this group. To clarify subtle species assignments, we investigated the venom composition of five Strumigenys species, using SPME extraction and GC/MS analyses, and searched for a suitable chemical marker. Our results indicate that three out of the five species tested showed enough specificity in their chemical profiles to allow clear differentiation. However, the two remaining species could not be distinguished from each other on the basis of their venom composition. We further assessed the phylogenetic relationships between the five species, analyzing both morphological and chemical characters. Our clusters revealed congruency between some species associations and suggested that the analysis of venom composition may apply, at least partially, to Strumigenys chemosystematics. However, important discrepancies also appeared, signifying that selective pressures for chemical diversification have operated differentially during the speciation and dispersal processes within this genus inTaiwan

Modeling the Effect of Oil Price on Global Fertilizer Prices

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model, are used to investigate the relationship between crude oil price and six global fertilizer prices. Weekly data for 2003-2008 for the seven price series are analyzed. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price, which explains why global fertilizer prices reached a peak in 2008. We also find that that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices. As volatility invokes financial risk, the relationship between oil price and global fertilizer prices and their associated volatility is important for public policy relating to the development of optimal energy use, global agricultural production, and financial integration.Volatility; Global fertilizer price; Crude oil price; Non-renewable fertilizers; Structural breakpoint unit root test