Thesis (Ph. D.)--University of Chicago, 2003. / Includes bibliographical references (leaves 61-64). Also available on the Internet.

Bachelor-Arbeit Univ. St. Gallen, 2006.

Bachelor-Arbeit Univ. St. Gallen, 2007.

Bachelor-Arbeit Univ. St. Gallen, 2007.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1980. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 259-266).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1988. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographies.

Thesis (Ph. D.)--University of Missouri-Columbia, 2005. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 18, 2006) Vita. Includes bibliographical references.

Thesis (Ph.D.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (leaves 78-81)

Master of Science / Department of Agricultural Economics / Glynn T. Tonsor / Over the past decade, social media has risen from an emerging novelty to the normative form of expression for many Americans. As these platforms have risen in popularity, researchers have recognized the potential for capturing information users are self-reporting about their beliefs and preferences. Simultaneously, social media corporations have become privy to the value of this information being freely shared by consumers and have safeguarded much of their historical data to monetize the data. Faced with both an enticing new source of data, but a steep price to obtain it, researchers must evaluate the potential gains that can be extracted from the often difficult to analyze data. This study explored the acquisition of social media, namely Twitter, data and the potential uses in the field of agriculture economics. A contract was secured with Sysomos, a social media analytics firm, in July of 2017 to collect raw Twitter data over the proceeding thirteen months. Changes in frequency of tweets and sentiment scoring of tweets were used to attempt to explain election results from November 2017 proposed legislations pertaining to marijuana and minimum wage as well as to explain and predict changes in the stock prices of selected publicly traded firms in the food producing sector. Twitter frequency changes were then compared to changes in traditional print media articles in an effort to determine the exchangeability of the two media sources when used to track events pertaining to animal health. Results of this study suggested that Twitter data possess little power to explain the studied election results, but creation of a strong model was difficult due to the limited number of months of data available. Changes in the frequency of tweets were not found to be a strong indicator of changes in the stock market on the average day, but were shown to explain potentially highly valued information to investors on days with large changes in price. Twitter and traditional print media were shown to be unique sources of data when exploring the topic of animal health events.

This thesis examines the size-growth relationship for banking and manufacturing firms. In particular it tests the Law of Proportionate Effect (LPE) which suggests that there is no relationship between firm size and growth. Tests of the LPE are carried out for eight European banking markets (Belgium, Denmark, France, Germany, Italy, Netherlands, Spain and the United Kingdom) and for three bank types (commercial, co-operative and savings) over the period 1990 to 1994. Employing three measures of size (total assets, equity and off balance sheet business) models are estimated that test for size effects on growth, and the influences of previous growth, bank type and country membership. In the majority of cases, bank growth is independent of bank size, so the LPE holds. However, small banks grew faster than their larger counterparts (in terms of assets and equity) in France, Italy and Spain. The LPE is also investigated for a sample of European manufacturing firms drawn from five countries and eleven industry groups. In contrast to the banking industry there is less evidence that the LPE holds. In most cases small firms grew proportionately faster than their larger counterparts. Using stochastic simulation techniques, the effects of firm growth, entry, exit and merger activity on the evolution of bank sizes and market concentration is examined. Using a simulated industry in which the LPE holds as the benchmark, the implications of various alternative assumptions regarding bank growth were examined. Superimposition of entry leads to a lower mean bank size and lower levels of concentration. Exit leads to higher mean bank size and increased concentration. Mergers lead to increases in mean bank size and concentration in all simulated industries. Using the simulations methodology, hypothetical projections as to the future structure of the banking markets in France, Germany, Italy, Spain and the UK are carried out. Overall, the simulations suggest that bank numbers are likely to decrease in all countries. The market shares of the largest banks are also projected to decline in all countries with the exception of the UK.