Effects of exchange rate changes on investment : a study with U.S. firm level panel data

Title from PDF of title page (University of Missouri--Columbia, viewed on November 9, 2010).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Ronald Ratti.Vita.Ph. D. University of Missouri--Columbia 2008.In this paper I investigate the effects of exchange rate changes on firm investment through the export channel and imported input channel using U.S. manufacturing firm level data for 1998-2007. For this study, I create a 'small' sample, where the export ratio is 'export to sales ratio' obtained from financial statements, and a 'large' sample using industry level 'export to shipment ratio' as a proxy for the 'export to sales ratio'. Considering the possible dynamic panel bias problem in the empirical model, I use the 'difference' GMM and the 'system' GMM for the econometric methods. The findings of my study are as follows: appreciation (depreciation) of domestic currency reduces (increases) firm investment through the exports channel. Also appreciation (depreciation) of the domestic currency increases (reduces) firm investment through the imported input channel. Firms with low markup rates are more sensitive in their investment responses to the movement in exchange rate changes both in terms of the exports channel and imported input channel. Low cash flow firms are more sensitive in terms of investment responses to the exchange rate changes than high cash flow firms. Also smaller firms are more responsive in their investments to exchange rate changes than larger firms. The findings on the role of cash flow and firm size indicate that U.S. firms are exposed to widespread financial constraints. With regard to the role of leverage, overall estimation results imply that leverage does not affect the relationship between the exchange rate changes and firm investment. In most of the results in this paper, the coefficients associated with the export channel are more significant than those of the imported input channel. This suggests that firms' responses to the movement of exchange rates are more sensitive through the export channel than through the imported input channel.Includes bibliographical reference

Excavation Behaviour of Soft Marine Clay Deposit in South Korea

In this paper, it is demonstrated that the shear strength of soil around jet grouting pile may be increased with the elapsed curing time of grouting cement. Because soil around pile initially experiences the disturbance due to the jet grouting work process, the soil gains the strength as grouting cement is cured and the soil is stabilized. In addition, excavation behaviour of marine clay at sheet pile wall and strut excavation site is analyzed using measured data from inclinometers, load cells, and strain gauges. The time to install supporting system and not only depth to but also area of excavation are very important factors for analyzing excavation behavior of soft marine clay

A Uncertainty Perspective on Qualitative Preference

Collaborative filtering has been successfully applied for predicting a person\u27s preference on an item, by aggregating community preference on the item. Typically, collaborative filtering systems are based on based on quantitative preference modeling, which requires users to express their preferences in absolute numerical ratings. However, quantitative user ratings are known to be biased and inconsistent and also significantly more burdensome to the user than the alternative qualitative preference modeling, requiring only to specify relative preferences between the item pair. More specifically, we identify three main components of collaborative filtering-- preference representation, aggregation, and similarity computation, and view each component from a qualitative perspective. From this perspective, we build a framework, which collects only qualitative feedbacks from users. Our rating-oblivious framework was empirically validated to have comparable prediction accuracies to an (impractical) upper bound accuracy obtained by collaborative filtering system using ratings