A discounting app
I am a Research Associate (Postdoc) at the Department of Socioeconomics, Chair of Environmental Economics, at the University of Hamburg. My research focuses on various aspects of behavioral instruments to foster climate-protection behavior. I also investigate the various reasons and factors underlying skepticism towards climate change. I primarily use experimental and empirical methods, using R and Stata to apply statistical procedures, e.g. (non-) parametric tests, (non-) linear regression, or bayesian statistics. I am also interested in the utilization of big data for scientific purposes, quantitative text-analysis (including sentiment analysis), machine learning (supervised and unsupervised), as well as the reproducibility of experiments in psychology and economics.
Dr. of Economics (Dr. rer. pol.), 2018
International Max-Planck Research School on Earth System Modelling; Chair of Ecological Economics, Department of Socioeconomics, University of Hamburg, Germany
MA in Sustainability Economics and Management, 2015
University of Kassel, Germany
BA in Geography and Economics, 2011
University of Osnabrueck, Germany
In this project I use text-mining procedures to understand how we discuss climate change online. I quantitatively analyse online articles on climate change, both from skeptical and affirmative standpoints.
This project aims at mapping the potential interactions between various forms of scarcity on the performance of pro-social/ green nudges. Specifically, we use laboratory and field experiments to test whether economic, cognitive, and social scarcity change decision-makers proneness to nudges that aim to reduce negative externalities.
This project evaluates the relative performance of nudges and conventional instruments to foster pro-environmental behavior.
This project investigates causes underlying public skepticism towards the occurence of man-made climate change, as well as differences and similarities between arguments underlying both positions.
Science is there to answer questions, and it is a powerful tool at that. In this post I outline how I approach the task of coming up with research questions, how to answer them and how to create a publishable manuscript describing this procedure. It is very idiosyncratic, but I hope that it might be useful for some readers, especially students.
For one of my projects I needed to download text from multiple websites. I did this with
dplyr. While this can be relatively easy if the sources come from the same websites, it can be pretty tedious when the website hosts are various. The reason is how the content is kept in the HTML of the website. Assume that you want to extract the title, author information, publish date, and of course the main article text. You can access that information via CSS or XPath. The following text will walk you through an example and provide the relevant code.
We are a network of young data analysts that wants to change the world with a more inclusive, integrated and innovative approach to data analysis. CorrelAid builds on three pillars: We take a pioneer role in analytics consulting for Non-Profit-Organisations. We connect young, driven data scientists and offer them the possability to apply and develop their skills on real-world problems. Last but not least, we start a dialogue on the potential of data and analytics for the civic society.
Projekt Seehilfe e.V. aims on a long-term basis to strengthen integrative and educational structures for refugees arriving in Europe by providing workshops and general recreational offerings, as well as administrational and bureaucratic support, especially in Sicily.