|
on Sociology of Economics |
By: | Wojciech Charemza; Michał Lewandowski; Łukasz Woźny |
Abstract: | Over the last few years, ranking lists of academic journals have become one of the key indicators for evaluating individual researchers, departments and universities. How to optimally design such rankings? What can we learn from commonly used journal ranking lists? To answer these questions, we propose a simple model of optimal rewards for publication in academic journals. Based on a principal-agent model with researchers' hidden abilities, we characterize the second-best journal reward system, where all available journals are assigned to one of several categories or ranks. We provide a tractable example that has a closed-form solution and allows numerical applications. Finally, we show how to calibrate the distribution of researchers' ability levels from the observed journal ranking schemes. |
Keywords: | journal rankings, publication reward mechanisms, optimal categorization, journal quality |
JEL: | I23 D61 O31 |
Date: | 2023–09 |
URL: | http://d.repec.org/n?u=RePEc:sgh:kaewps:2023092&r=sog |
By: | Donna K. Ginther; Carlos Zambrana; Patricia Oslund; Wan-Ying Chang |
Abstract: | This paper examines whether publication data matched to the Survey of Doctorate Recipients can be used for research purposes. We use Gold Standard data created to validate the publication match quality and compare these measures to publications assigned by a machine-learning algorithm developed by Thomson Reuters (now Clarivate). Our econometric model demonstrates that publications likely suffer from non-classical measurement error. Using horse race and instrumental variable models, we confirm that the Gold Standard data are relatively free from measurement error but show that the Clarivate data suffer from non-classical measurement error. We employ a variety of methods to adjust the Clarivate data for false negatives and false positives and demonstrate that with these adjustments the data produce estimates very similar to the Gold Standard. However, these adjustments are not as useful when publications are used as a dependent variable. We recommend using subsamples of the data that have better match quality when using the Clarivate data as a dependent variable. |
JEL: | C26 J40 O30 |
Date: | 2023–11 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31844&r=sog |
By: | Henao, Leandro; Berens, Johannes; Schneider, Kerstin |
JEL: | H52 I23 I28 H75 |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc23:277578&r=sog |