U.S./CANADA GRAIN HANDLING AND TRANSPORTATION SYSTEMS

The United States and Canada have developed very different grain handling and transportation systems (GHTSs) over the last several decades to compete for global and domestic markets in Canada and the United States under CUSTA. Because the grain industries in both countries face long distance hauls, GHTSs are critically important to their operations and to producer returns. There has been considerable pressure for change in Canada's grain handling and transportation sector. Some industry trends, such as the rationalization of elevators in the Prairies and investments in new high through-put facilities, are being driven by market and competitive forces. Changes in grain handling, reciprocal access to marketing functions, and elimination of rate caps may have a significant impact on cross-border grain flows. Canadian Transport announced reforms to improve the efficiency of its GHTS. Possible multi-level effects, created by the reform package, would affect the grain flow from Canada to the United States. The most significant reforms include 'port buying' by the Canadian Wheat Board, which would remove the Board's control over internal logistics and shipping, and replacement of the current maximum railway rate scale with a cap on annual railway revenues for grain shipments.Canadian Wheat Board (CWB), Grain Trade, Grain Transportation and Handling System (GHTS), Rail Rate, Railcar Allocation, Rationalization, Rate Cap, Reciprocal Access, Regulation, Reform Package., Crop Production/Industries,

Nonlinearity, Nonstationarity, and Thick Tails: How They Interact to Generate Persistency in Memory

We consider nonlinear transformations of random walks driven by thick-tailed innovations that may have infinite means or variances. These three nonstandard characteristics: nonlinearity, nonstationarity, and thick tails interact to generate a spectrum of asymptotic autocorrelation patterns consistent with long-memory processes. Such autocorrelations may decay very slowly as the number of lags increases or may not decay at all and remain constant at all lags. Depending upon the type of transformation considered and how the model error is speci- fied, the autocorrelation functions are given by random constants, deterministic functions that decay slowly at hyperbolic rates, or mixtures of the two. Such patterns, along with other sample characteristics of the transformed time series, such as jumps in the sample path, excessive volatility, and leptokurtosis, suggest the possibility that these three ingredients are involved in the data generating processes of many actual economic and financial time series data. In addition to time series characteristics, we explore nonlinear regression asymptotics when the regressor is observable and an alternative regression technique when it is unobservable. To illustrate, we examine two empirical applications: wholesale electricity price spikes driven by capacity shortfalls and exchange rates governed by a target zone.persistency in memory, nonlinear transformations, random walks, thick tails, stable distributions, wholesale electricity prices, target zone exchange rates

Extracting a Common Stochastic Trend: Theories with Some Applications

This paper investigates the statistical properties of the Kalman filter for state space models including integrated time series. In particular, we derive the full asymptotics of maximum likelihood estimation for some prototypical class of such models, i.e., the models with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that the conventional method of inference is valid for this class of models. The models considered explicitly in the paper comprise a special, yet useful, class of models that we may use to extract the common stochastic trend from multiple integrated time series. As we show in the paper, the models can be very useful to obtain indices that represent fluctuations of various markets or common latent factors that affect a set of economic and financial variables simultaneously. Moreover, our derivation of the asymptotics of this class makes it clear that the asymptotic Gaussianity and the validity of the conventional inference for the maximum likelihood procedure extends to a larger class of more general state space models involving integrated time series. Finally, we demonstrate the utility of the state space model by extracting a common stochastic trend in three empirical analyses: interest rates, return volatility and trading volume, and Dow Jones stock prices.

Extracting a Common Stochastic Trend:Theories with Some Applications

This paper investigates the statistical properties of the Kalman filter for state space models including integrated time series. In particular, we derive the full asymptotics of maximum likelihood estimation for some prototypical class of such models, i.e., the models with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that the conventional method of infer- ence is valid for this class of models. The models considered explicitly in the paper comprise a special, yet useful, class of models that we may use to extract the common stochastic trend from multiple integrated time series. As we show in the paper, the models can be very useful to obtain indices that represent fluctuations of various markets or common latent factors that affect a set of economic and financial variables simultaneously. Moreover, our derivation of the asymptotics of this class makes it clear that the asymptotic Gaussianity and the validity of the conventional inference for the maximum likelihood procedure extends to a larger class of more general state space models involving integrated time series. Finally, we demonstrate the utility of the state space model by ex- tracting a common stochastic trend in three empirical analyses: interest rates, return volatility and trading volume, and Dow Jones stock prices.state space model, Kalman filter, common stochastic trend, maximum likelihood estimation, stock price index, interest rates, return volatility and trading volume.

An Econometric Analysis of Ocean Freight Rates for Grain Shipments from the United States to Major Importing Countries

This article uses a cross-sectional econometric model to evaluate structural changes and price differentials in ocean freight rates for grain shipments from U.S. ports to various major importing countries. Cost factors included are distance and the ship size, and competitive factors are shipping seasons, shipping frequencies, multiple destinations, commodity types, and characteristics of origins and destinations. Results suggest cost factors play a significant role in determining ocean freight rates, and the ocean shipping industry charges different rates by season and commodity. This study also indicates that ocean freight rate structures have changed during the 1987-1998 period

OPERATIONAL EFFICIENCY OF A U.S./CANADIAN WHEAT POOL: A GAME THEORY ANALYSIS

The problem of declining wheat prices and excess supply has been the subject of recent economic studies partly because it coincides with the Federal Agriculture Improvement and Reform (FAIR) Act of 1996, and partly because efforts to decrease supply domestically have led to increased imports from Canada. This paper develops a game theory optimization model of market efficiency and derives conditions under which voluntary pooling is sustained for U.S./Canadian durum and hard red spring wheat producers. Analysis reveals that U.S. and Canadian farmers can increase farm returns with efficiency gains from pooling and by internalizing benefits from grain blending and logistics. The model is used to analyze diverse factors affecting the sustainability of such a pool.Voluntary pooling, game theory, efficiency gains, durum and HRS wheat marketing, Crop Production/Industries, Marketing,

Extracting a Common Stochastic Trend: Theory with Some Applications

This paper investigates the statistical properties of estimators of the parameters and unobserved series for state space models with integrated time series. In particular, we derive the full asymptotic results for maximum likelihood estimation using the Kalman filter for a prototypical class of such models -- those with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that the conventional method of inference is valid for this class of models. The models we explicitly consider comprise a special -- yet useful -- class of models that may be employed to extract the common stochastic trend from multiple integrated time series. Such models can be very useful to obtain indices that represent fluctuations of various markets or common latent factors that affect a set of economic and financial variables simultaneously. Moreover, our derivation of the asymptotics of this class makes it clear that the asymptotic Gaussianity and the validity of the conventional inference for the maximum likelihood procedure extends to a larger class of more general state space models involving integrated time series. Finally, we demonstrate the utility of this class of models extracting a common stochastic trend from three sets of time series involving short- and long-term interest rates, stock return volatility and trading volume, and Dow Jones stock prices

Bucillamine prevents cisplatin-induced ototoxicity through induction of glutathione and antioxidant genes.

Bucillamine is used for the treatment of rheumatoid arthritis. This study investigated the protective effects of bucillamine against cisplatin-induced damage in auditory cells, the organ of Corti from postnatal rats (P2) and adult Balb/C mice. Cisplatin increases the catalytic activity of caspase-3 and caspase-8 proteases and the production of free radicals, which were significantly suppressed by pretreatment with bucillamine. Bucillamine induces the intranuclear translocation of Nrf2 and thereby increases the expression of γ-glutamylcysteine synthetase (γ-GCS) and glutathione synthetase (GSS), which further induces intracellular antioxidant glutathione (GSH), heme oxygenase 1 (HO-1) and superoxide dismutase 2 (SOD2). However, knockdown studies of HO-1 and SOD2 suggest that the protective effect of bucillamine against cisplatin is independent of the enzymatic activity of HO-1 and SOD. Furthermore, pretreatment with bucillamine protects sensory hair cells on organ of Corti explants from cisplatin-induced cytotoxicity concomitantly with inhibition of caspase-3 activation. The auditory-brainstem-evoked response of cisplatin-injected mice shows marked increases in hearing threshold shifts, which was markedly suppressed by pretreatment with bucillamine in vivo. Taken together, bucillamine protects sensory hair cells from cisplatin through a scavenging effect on itself, as well as the induction of intracellular GSH