Combining Data Sources: A Path to Improved Understanding and Prediction

Abstract

Over the last few years, data has often been described as the oil of the 21st century, e.g., by Bhageshpur (2019). Just as access to oil dominated power and development in the last century, this claim implies that personal data is not only assumed to be similarly valuable, but also equally as influential in politics and society as oil once was. However, oil sources mainly diverge in their accessibility, quality, quantity, and cost of exploitation but, once extracted and refined theses sources may lead to roughly similar products. Data also differs in these four categories but, additionally, data sources typically lead to very specific insights. One single data source is often neither sufficient to answer important and complex scientific (or economic) questions nor to make any predictions with fine granularity and high precision. In such cases, combining data from different sources that provide additional aspects to the problem at hand is one promising approach to achieve these aims. In this dissertation, combining data sources is conducted for two purposes. Part I of this work focuses on combining data to achieve additional understanding. In the paper presented in Part I, the authors analyze reasons why students drop out of undergraduate courses in economics and business administration. From a university perspective, administrative data is readily available, e.g., which modules are completed in which semester, how many educational credit points are achieved by each student in each semester. Socioeconomic data at individual level, however, is usually unavailable to university administrations. In order to overcome this hurdle, the authors proposed and executed a novel prospective study design. A survey was conducted on students starting the second semester and the data was combined with administrative longitudinal data. Hence, the authors were able to analyze individual studying behavior conditioned on a large pool of socio-demographic variables. Among other results, the authors were able to show that college ...