Skip to main content
Advanced Search

Filters: Tags: principal component analysis (X)

4 results (54ms)   

View Results as: JSON ATOM CSV
The objective of this paper is to investigate the co-movement of food prices and the macroeconomic index, especially the oil price, by principal component analysis to further understand the influence of the macroeconomic index on food prices. We examined the food prices of seven major products: eggs, meat, milk, oilseeds, rice, sugar and wheat. The macroeconomic variables studied were crude oil prices, consumer price indexes, food production indexes and GDP around the world between 1961 and 2005. We use the Scree test and the proportion of variance method for determining the optimal number of common factors. The correlation coefficient between the extracted principal component and the macroeconomic index varies...
The objective of this paper is to investigate the co-movement of food prices and the macroeconomic index, especially the oil price, by principal component analysis to further understand the influence of the macroeconomic index on food prices. We examined the food prices of seven major products: eggs, meat, milk, oilseeds, rice, sugar and wheat. The macroeconomic variables studied were crude oil prices, consumer price indexes, food production indexes and GDP around the world between 1961 and 2005. We use the Scree test and the proportion of variance method for determining the optimal number of common factors. The correlation coefficient between the extracted principal component and the macroeconomic index varies...
The objective of this paper is to investigate the co-movement of food prices and the macroeconomic index, especially the oil price, by principal component analysis to further understand the influence of the macroeconomic index on food prices. We examined the food prices of seven major products: eggs, meat, milk, oilseeds, rice, sugar and wheat. The macroeconomic variables studied were crude oil prices, consumer price indexes, food production indexes and GDP around the world between 1961 and 2005. We use the Scree test and the proportion of variance method for determining the optimal number of common factors. The correlation coefficient between the extracted principal component and the macroeconomic index varies...
Land and water resource development can independently eliminate riparian plant communities, including Fremont cottonwood forest (CF), a major contributor to ecosystem structure and functioning in semiarid portions of the American Southwest. We tested whether floodplain development was linked to river regulation in the Upper Colorado River Basin (UCRB) by relating the extent of five developed land-cover categories as well as CF and other natural vegetation to catchment reservoir capacity, changes in total annual and annual peak discharge, and overall level of mainstem hydrologic alteration (small, moderate, or large) in 26 fourth-order subbasins. We also asked whether CF appeared to be in jeopardy at a regional level....