 Should we care (more) about data aggregation?Klaus Gründler () and Tommy Krieger European Economic Review, 2022, vol. 142, issue C Abstract: Aggregation tools transform multidimensional data into indices. To investigate how the design of an aggregation process affects regression results, we build democracy indices that differ regarding their scale and aggregation function. Using the democracy–growth nexus as a testing ground, we illustrate that the choice of the aggregation procedure significantly affects OLS and 2SLS estimates since different methods produce systematically different index values for observations at the lower and upper end of the autocracy–democracy spectrum. We also illustrate that dichotomous measures produce significantly smaller OLS estimates than continuous measures due to lower discriminating power. Whether continuous and dichotomous indicators create different 2SLS estimates depends on their design. Because of the methodological similarities of democracy indicators and other social science indicators, we expect similar consequences for other empirical analyses. Keywords: Aggregation; Data transformation; Democracy; Economic development; Indices; Machine learning; Measurement of democracy; Political transitions; Scaling (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:eecrev:v:142:y:2022:i:c:s0014292121002804 DOI: 10.1016/j.euroecorev.2021.104010 Access Statistics for this article European Economic Review is currently edited by T.S. Eicher, A. Imrohoroglu, E. Leeper, J. Oechssler and M. Pesendorfer More articles in European Economic Review from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.