Working Papers

The WNE Working Papers series has been published by the Faculty of Economic Sciences at the University of Warsaw since 2008.

The WNE Working Papers series provides a fast, open channel for disseminating research conducted at the Faculty of Economic Sciences, University of Warsaw. The papers hosted here are working versions (pre-prints) and may evolve as authors refine their analyses, incorporate feedback, or progress through formal peer-review. What you read is the current version released by the authors, timestamped and assigned DOI/ISSN identifiers to ensure precise citation and version tracking. Copyright remains with the authors, who may, at any time, upload a revised file or add a note directing readers to a later, peer-reviewed publication.

The Working Papers series accepts articles by research employees of the Faculty and publications from conferences organised at the Faculty of Economic Sciences at the University of Warsaw. Articles should be original research papers which have not been previously published, on the subject of economics.

Please send your paper by e-mail: ?Nuv6RUBXQs`JV/Z75r*qD0mI&M]#[3=hbzA9/6BYS=m%IwBh|z$ocRt6 

Please send 2 files:

(1) the main text without the title of the article and the authors (DOC/DOCX file) and

(2) the title page including: the title of the paper, the authors and their affiliation (DOC/DOCX file).

Please read the detailed editing requirements before submitting your text. 

Number of Results 1

WP(12/2021)360. Don’t Worry, Be Happy – But Only Seasonally

Authors: Kijewski Mateusz, Lis Szymon, Woźniak Michał, Wysocki Maciej
Current scientific knowledge allows us to assess the impact of socioeconomic variables on musical preferences. The research methods in these studies were psychological experiments and surveys conducted on small groups or analyzing the influence of on…

WP360. Don’t Worry, Be Happy – But Only Seasonally

Current scientific knowledge allows us to assess the impact of socioeconomic variables on musical preferences. The research methods in these studies were psychological experiments and surveys conducted on small groups or analyzing the influence of only one or two variables at the level of the whole society. Instead inspired by the article of The Economist about February being the gloomiest month in terms of music listened to, we have created a dataset with many different variables that will allow us to create more reliable models than the previous datasets. We used the Spotify API to create a monthly dataset with average valence for 26 countries for the period from January 1, 2018, to December 1, 2019. Our study almost fully confirmed the effects of summer, December, and number of Saturdays in a month and contradicted the February effect. In the context of the index of freedom and diversity, the models do not show much consistency. The influence of GDP per capita on the valence was confirmed, while the impact of the happiness index was disproved. All models partially confirmed the influence of the music genre on the valence. Among the weather variables, two models confirmed the significance of the temperature variable. All in all, effects analyzed by us can broaden artists' knowledge of when to release new songs or support recommendation engines for streaming services.


Kijewski Mateusz, Lis Szymon, Woźniak Michał, Wysocki Maciej
valence spotify happiness statistical panel analysis explainable machine learning
  • 1