This final instalment on the state of replications in economics, 2020 version, continues the discussion of how to define “replication success” (see here and here for earlier instalments). It then delves further into interpreting the results of a replication. I conclude with an assessment of the potential for replications to contribute to our understanding of economic phenomena.
[This blog is based on the article “ Replication studies in economics—How many and which papers are chosen for replication, and why?” by Frank Mueller-Langer, Benedikt Fecher, Dietmar Harhoff, and Gert Wagner, published in the journal Research Policy] Academia is facing a quality challenge: The global scientific output doubles every nine years while the number of retractions and instances of misconduct is increasing.
[NOTE: This entry is based on the book “Corrupt Research: The Case for Reconceptualizing Empirical Management and Social Science” by Raymond Hubbard] Psychology’s “reproducibility crisis” (Open Science Collaboration, 2015) has drawn attention to the need for replication research. However, focusing on the reproducibility of findings, while clearly important, is a much too narrow interpretation of replication’s role in the scientific enterprise.