Over the past two decades, a surge of interest in the area of forecasting has produced a number of statistical models available for predicting the winners of U.S. presidential elections. While historically the domain of individuals outside the scholarly community - such as political strategists, pollsters, and journalists - presidential election forecasting has become increasingly mainstream, as a number of prominent political scientists entered the forecasting arena. With the goal of making accurate predictions well in advance of the November election, these forecasters examine several important election "fundamentals" previously shown to impact national election outcomes. In general, most models employ some measure of presidential popularity as well as a variety of indicators assessing the economic conditions prior to the election. Advancing beyond the traditional, non-scientific approaches employed by prognosticators, politicos, and pundits, today's scientific models rely on decades of voting behavior research and sophisticated statistical techniques in making accurate point estimates of the incumbent's or his party's percentage of the popular two-party vote. As the latest evolution in presidential forecasting, these models represent the most accurate and reliable method of predicting elections to date. This thesis provides an assessment of forecasting models' underlying epistemological assumptions, theoretical foundations, and methodological approaches. Additionally, this study addresses forecasting's implications for related bodies of literature, particularly its impact on studies of campaign effects. / Master of Arts

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Yes / This paper makes use of a leading UK supermarket’s loyalty card based data which records information on purchase decisions by consumers who shop at its stores in order to assess the effectiveness and impact of the UK reduced salt campaign. We present an empirical analysis of consumption data to assess the effectiveness of the UK Food Standard Agency’s (FSA) ‘reduced salt campaign’ on the basis of information on health related announcements undertaken by the FSA under its ‘low salt campaign’. We adopt a general approach to determining structural breaks in consumption data, including making use of minimum LM unit root tests whereby structural breaks are endogenously determined from the data. We find evidence supporting the effectiveness of the FSA’s reduced salt campaign.

Radverkehrsplanung wird aktuell sehr häufig als Angebotsplanung verstanden. Dieser Fakt steht zumindest teilweise im Widerspruch zu den oftmals knappen personellen und finanziellen Ressourcen. Eine nachfrageorientierte Planung kann an dieser Stelle deutliche Vorteile bei der Priorisierung von Maßnahmen und dem gezielten Mitteleinsatz bedeuten. Seit 2007 wird die Nutzung von GPS-Daten für die Radverkehrsplanung erforscht (Harvey und Krizek 2007) und als eine Möglichkeit betrachtet, um die Radverkehrsnachfrage im Zuge von Crowdsourcing Ansätzen zu erheben. Mit der zunehmenden Verfügbarkeit und Verbreitung von Smartphones in der Bevölkerung wurde dieser Ansatz in den vergangenen Jahren zunehmend relevanter. Für die Angebots- bzw. Datenqualität sind die genutzte Stichprobe sowie die Motivatoren zur Teilnahme an einer Kampagne jedoch von großer Wichtigkeit. Die genannten Punkte wurden bisher allerdings meist nicht oder nur unzureichend untersucht, sodass elementare Fragen zur Repräsentativität der Stichproben und zum Nutzen von Kampagnen unbeantwortet blieben. Die vorliegende Arbeit soll diese Forschungslücke für die bundesweite Radverkehrskampagne STADTRADELN schließen.