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Econometric Commodity Models Review and Comparison
Published in Margaret E. Slade, An Econometric Model of the U.S. Copper and Aluminum Industries, 1984
A somewhat later econometric commodity model is the Fisher-Cootner-Baily (FCB) (1972) model of the world copper industry. The focus of the FCB model is on geographic differences in the industry and on the two-price system generally prevailing (where most copper in the United States moves at the U.S. producer price while copper in the rest of the world moves at the London Metal Exchange (LME) price, which can be considerably different). FCB, unlike Desai, found both supply and demand to be sensitive to the price of copper; demand was found to be related to the price of a substitute (aluminum) as well. The FCB U.S. producer-price equation includes the difference between the U.S. and the LME copper prices as an explanatory variable; the U.S. price tends to move in the direction of the LME price if the two are very different. Like Desai’s model, the FCB model is basically competitive; price responds to changes in inventories divided by changes in consumption. A difference between the Desai and FCB models is that distributed lags have been added to all equations in the FCB model.1 The introduction of distributed lags captures the long-range effects of changes in the independent variables on the dependent variable.
Heat exposure and chronic kidney disease: a temporal link in a Taiwanese agricultural county
Published in International Journal of Environmental Health Research, 2023
Che-Jui Chang, Chun-Yi Chi, Hsiao-Yu Yang
For exploring time-lagged effects, we iterated the regression model over various choices of single and cumulative lags for exposure. This method has been recognized as appropriate for evaluating different exposures and outcome associations (Samoli et al. 2013; Lee et al. 2017). Researchers have also proposed more sophisticated methodologies, such as distributed lag non-linear models and treed distributed lag models (Gasparrini 2014; Mork and Wilson 2020). However, applying these methods did not yield a better fit of the model in our data than the original logistic regression.
Ambient temperature and pesticide poisoning: a time-series analysis
Published in International Journal of Environmental Health Research, 2019
Junhui Wang, Honglin Wang, Guijie Luan, Dongfeng Zhang
All statistical analyses were conducted using R software (version 3.3.1), with the ‘dlnm’ package to fit the distributed lag nonlinear model. All statistical tests were two-sided in this study. p-Values of less than 0.05 were considered as statistically significant.