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Speaking Stata: Graphs for all seasons AgEcon
Cox, Nicholas J..
Time series showing seasonality—marked variation with time of year—are of interest to many scientists, including climatologists, other environmental scientists, epidemiologists, and economists. The usual graphs plotting response variables against time, or even time of year, are not always the most effective at showing the fine structure of seasonality. I survey various modifications of the usual graphs and other kinds of graphs with a range of examples. Although I introduce here two new Stata commands, cycleplot and sliceplot, I emphasize exploiting standard functions, data management commands, and graph options to get the graphs desired.
Tipo: Journal Article Palavras-chave: Cycleplot; Sliceplot; Seasonality; Time series; Graphics; Cycle plot; Rotation; State space; Incidence plots; Folding; Repeating; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/117590
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Dynamic and Stochastic Structures of U.S. Cotton Exports and Mill Demand AgEcon
Fadiga, Mohamadou L..
This study employs a structural time-series method to model and estimate U.S. cotton exports and mill use. The results show that the stochastic process governing cotton export fluctuations is transitory, while the process pertaining to mill use has transitory, seasonal, and secular origins. The estimated structural relationships after accounting for the unobserved components indicate U.S. cotton exports respond directly to higher international price relative to domestic price of cotton, while mill use responds directly to U.S. textile output price and cotton-to-polyester price ratio. Exchange rate volatility and the U.S. Export Enhancement Program have no significant effect on cotton exports.
Tipo: Journal Article Palavras-chave: Cotton exports; Cotton mill use; Kalman filter; State space; Unobserved components; Crop Production/Industries; International Relations/Trade; Production Economics; Productivity Analysis.
Ano: 2006 URL: http://purl.umn.edu/57698
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