Data Grant 2020 - Vorstellung der Forschungsprojekte [30.07.20]
Der wissenschaftliche Beirat des DALAHO kann erfreulicherweise mitteilen, dass alle vier eingegangenen Anträge für den Data Grant 2020 bewilligt werden.
Der Data Grant wurde in diesem Jahr zum ersten Mal vergeben und richtet sich an Forschende, die für ihr Forschungsvorhaben Zugang zu kommerziellen Datenbanken benötigen. Im Folgenden stellen die Forscher*innen ihre Projekte kurz vor:
Dr. Hamid Reza Oskorouchi und Prof. Dr. Alfonso Sousa-Poza, Fg. Haushalts- und Konsumökonomik (530A):
„A recent and growing body of literature has shown the potential of Nighttime Light (NTL) data in measuring and nowcasting national and regional GDP (Henderson et al. 2011). However, no application tests the GDP nowcasting performance of NTL-augmented AR models when a sudden and widespread economic crisis occurs. Considering the different phases of the COVID19 pandemic in EU as an economic shock, we construct several measures of luminosity growth using near-real time monthly NTL within a new pixel-by-pixel approach (first proposed by Galimberti, 2020) where only pixels which growth is statistically correlated with quarterly national GDP growth are retained for the final analysis. If this approach proves effective, it could be extremely useful both for its ability of timely providing reliable GDP estimates and its minimal data requirement.“
Prof. Dr. Robert Jung, Fg. Ökonometrie und Wirtschaftsstatistik (520K) und Prof. Dr. Sebastian Hess, Fg. Agrarmärkte (420B):
„We use data obtained from Agrarmarkt Informations-Gesellschaft (AMI) mbH to study hedging strategies for raw milk. Raw milk is the most important agricultural good produced by German farmers. AMI provides an unique dataset of standardized raw milk prices as well as spot prices based on important milk parameters (fat, protein, quality, e.g.) for German dairy processors over a time horizon of 10 years. Employing time series methods we study minimum-variance hedging strategies for raw milk based on futures prices on butter and skim milk. We seek to answer the question how an optimal hedging strategy can be obtained for raw milk and how it is related to standard (naive) hedging recommendations.“
Dr. Elisabeth Berger und Leif Brändle, Fg. Unternehmensgründungen und Unternehmertum (Entrepreneurship) (570C):
“We use BIOSCIDB database to assess how strategic alliance formation is affected by market dynamics. BIOSCIDB is one of the most comprehensive databases for alliance data in the biopharma industry. Based on a longitudinal analysis of the formation of R&D-driven network ties between biopharma ventures, we specifically aim to explain the role of technological discontinuity and firm failure on how this affects future alliance behavior.”
Prof. Dr. Hans-Peter Burghof, Fg. Betriebswirtschaftslehre, insbesondere Bankwirtschaft und Finanzdienstleistungen (510F):
"The dataset Moody's Analytics BankFocus includes a wide range of information about banks. We use bank balance sheet data to characterize banking systems within regions. In two of our projects we analyse the influence of local banking systems on regional economic measures as well as local firms. Within a third project bank balance sheet data from the dataset supports our research to investigate whether nations within the EU implement different regulatory capital requirements for their systemically important institutions and if so, which factors influence this decision."
