Detecting price links in the world cotton market

The authors examine the degree to which international cotton prices are linked and test whether such links have improved over the past decade. They conclude that the degree of linkage has improved over the past decade, in the short run largely as the result of short-run price transmission -- and to a lesser extent because of long-run comovement. Improvements in information technology have made it much easier for information about demand to be disseminated across markets, so changes in cotton prices attributable to a price shock in one place are soon transmitted to prices in other places. Moreover, many countries have liberalized their cotton subsectors, and in some countries the government's role has changed substantially. In East Africa, for example, cotton marketing and trade was handled entirely by government parastatals. Now Tanzania, Uganda, and Zimbabwe have liberalized their marketing and trade regimes, to varying degrees. In the former Soviet Union (FSU) cotton shipped from Central Asia to other parts of the FSU were considered part of domestic trade. Now cotton exports from Uzbekistan are the most important component of that country's foreign trade. With such changes, one should expect cotton prices to converge somewhat more in the long run. Price links between West Africa and Central Asia are much greater than between the United States and other markets -- in part because most West African and Central Asian cotton is exported, compared with only 40 percent of U.S. cotton (and 60 percent of Greek cotton). Prices in countries that export most of their cotton are more likely to converge than prices in countries where prices are subject to both domestic and international demand conditions. To improve price risk management, there should be future contracts other than those traded on the New York Cotton Exchange, which mostly serves domestic U.S. needs and is not used extensively by non-U.S. hedgers and speculators.Economic Theory&Research,Markets and Market Access,Environmental Economics&Policies,Payment Systems&Infrastructure,General Technology,Markets and Market Access,Environmental Economics&Policies,Economic Theory&Research,General Technology,Access to Markets

Parameter estimation of electric power transformers using Coyote Optimization Algorithm with experimental verification

In this work, the Coyote Optimization Algorithm (COA) is implemented for estimating the parameters of single and three-phase power transformers. The estimation process is employed on the basis of the manufacturer's operation reports. The COA is assessed with the aid of the deviation between the actual and the estimated parameters as the main objective function. Further, the COA is compared with well-known optimization algorithms i.e. particle swarm and Jaya optimization algorithms. Moreover, experimental verifications are carried out on 4 kVA, 380/380 V, three-phase transformer and 1 kVA, 230/230 V, single-phase transformer. The obtained results prove the effectiveness and capability of the proposed COA. According to the obtained results, COA has the ability and stability to identify the accurate optimal parameters in case of both single phase and three phase transformers; thus accurate performance of the transformers is achieved. The estimated parameters using COA lead to the highest closeness to the experimental measured parameters that realizes the best agreements between the estimated parameters and the actual parameters compared with other optimization algorithms