Wheat is a staple agricultural grain commodity used within the United States and is grown in nearly every state. Modeling the price of Hard Winter Red wheat (the most common type of wheat) is of extreme economic and s...Wheat is a staple agricultural grain commodity used within the United States and is grown in nearly every state. Modeling the price of Hard Winter Red wheat (the most common type of wheat) is of extreme economic and social importance. The 2008 financial crisis had a drastic effect on the price of food in real terms, tightening household budgets and increasing the US percentage of citizen classed below the poverty line. Understanding the influential factors in the econometric modeling of the price of wheat allows for more effective governmental intervention and price stabilization. Results indicate that the price of wheat is influenced by a combination of 5 separate functions: “supply”, “demand”, “macroeconomic”, “climate” and “natural resource” related functions. These functions derive from a wide variety of different data sources. The functions were determined and then incorporated into an Ordinary Least Squares (OLS) regression model taking into account variable interaction, variable transformation and time. This regression exercise resulted in a good model, explaining just over 90% of the variation in the price of wheat. Yet, results indicate that the model though sensitive to sharp decreases in the price of wheat is insensitive to sharp increases in the price of wheat. Ideas are discussed of ways of improving the price model. These include the addition of other variables, such as financial speculation/increased use of climate related variables and the idea of using alternative statistical modeling techniques in place of robust OLS regression modeling, such as SVAR models and Spline GARCH models. This research implies that further research into the modeling of the price of wheat within the US has useful potential for a more productive outcome.展开更多
The digital social network of a user, who had undergone two radical locational changes, was analyzed to assess if digital social networks were influencing the ability of the user to create new physical social bonds in...The digital social network of a user, who had undergone two radical locational changes, was analyzed to assess if digital social networks were influencing the ability of the user to create new physical social bonds in regards to proximal distance of existing social interactions and if new physical social networks conformed to Dunbar’s theorem of the social network size limit. The social network data (users equating to nodes and physical friendships to links) was implemented into the network analysis software “Gephi”. Standard network measures were assessed on the three digital sub-networks with the user removed from the calculations. Two separation algorithms were assessed on the network data, the Force Atlas algorithm and the Fruchterman Reingold algorithm. The results contradicted with existing research indicating that existing digital social networks did not have an effect on the creation of new social bonds after a radical locational change. The creation of new physical social networks conformed in part to Dunbar’s network size limit theorem and existing social links did not affect the user’s ability to create new social partnerships.展开更多
文摘Wheat is a staple agricultural grain commodity used within the United States and is grown in nearly every state. Modeling the price of Hard Winter Red wheat (the most common type of wheat) is of extreme economic and social importance. The 2008 financial crisis had a drastic effect on the price of food in real terms, tightening household budgets and increasing the US percentage of citizen classed below the poverty line. Understanding the influential factors in the econometric modeling of the price of wheat allows for more effective governmental intervention and price stabilization. Results indicate that the price of wheat is influenced by a combination of 5 separate functions: “supply”, “demand”, “macroeconomic”, “climate” and “natural resource” related functions. These functions derive from a wide variety of different data sources. The functions were determined and then incorporated into an Ordinary Least Squares (OLS) regression model taking into account variable interaction, variable transformation and time. This regression exercise resulted in a good model, explaining just over 90% of the variation in the price of wheat. Yet, results indicate that the model though sensitive to sharp decreases in the price of wheat is insensitive to sharp increases in the price of wheat. Ideas are discussed of ways of improving the price model. These include the addition of other variables, such as financial speculation/increased use of climate related variables and the idea of using alternative statistical modeling techniques in place of robust OLS regression modeling, such as SVAR models and Spline GARCH models. This research implies that further research into the modeling of the price of wheat within the US has useful potential for a more productive outcome.
文摘The digital social network of a user, who had undergone two radical locational changes, was analyzed to assess if digital social networks were influencing the ability of the user to create new physical social bonds in regards to proximal distance of existing social interactions and if new physical social networks conformed to Dunbar’s theorem of the social network size limit. The social network data (users equating to nodes and physical friendships to links) was implemented into the network analysis software “Gephi”. Standard network measures were assessed on the three digital sub-networks with the user removed from the calculations. Two separation algorithms were assessed on the network data, the Force Atlas algorithm and the Fruchterman Reingold algorithm. The results contradicted with existing research indicating that existing digital social networks did not have an effect on the creation of new social bonds after a radical locational change. The creation of new physical social networks conformed in part to Dunbar’s network size limit theorem and existing social links did not affect the user’s ability to create new social partnerships.
