Necessary Condition Analysis (NCA) is an emerging approach and data analysis technique for identifying necessary (but not sufficient) conditions in data sets. It can complement traditional regression based data analysis as well as methods like QCA. NCA provides very relevant insights for practice. Recent methodological and substantive publications show that NCA can combine rigor and relevance.
Do you use Necessary Condition Analysis and would you like to receive feedback on a working paper? Consider applying for the NCA Paper Development Workshop 2021! Proposal can be submitted until the 27th August.
#nca #necessaryconditionanalysis
At the end of June (21 - 25th), we held our annual NCA Summer Course. The participants from all over the world appreciated greatly this 5-day hands-on online course. For example, one participant thought highly of the "meaningful lectures leading to practical applications of NCA and possible publication".
To complete this course, participants have to write an extended abstract as their final assignment. This assignment was well-received as it "allows to working with NCA in research projects".
If you are interested in more NCA events, take a look at our Events page: https://www.erim.eur.nl/necessary-condition-analysis/events-and-training/
NCA can also be applied to longitudinal and time-series data. We made an animation to show that the necessity can change over time. Using Worldbank data we show that a country's economic prosperity (GDP per capita) is necessary for a country's Life expectancy (years) and that the necessity changes between 1960 and 2018. See the animation.
ERIM
is the joint research institute of Rotterdam School of Management, Erasmus University and the Erasmus School of Economics, Erasmus University Rotterdam.
