Read on Twitter
Please, if you are teaching an overview of electoral system effects, consider using this. It is much more lawlike in its scientific derivation and empirically accurate than the (in)famous "law" that too often gets taken as if it were literal binding law. https://twitter.com/laderafrutal/status/1300857872595718144
Let me add: the heavy intellectual lifting in developing the seat product model was borne by Taagepera. He won the Skytte Prize, basically our Nobel, in 2008 for "his profound analysis of the function of electoral systems in representative democracy."
https://www.skytteprize.com/#prize-winners
https://www.skytteprize.com/#prize-winners
For the longer-form version of the seat product model, refer to our 2017 book. For a medium-form version, we have a chapter in the Oxford Handbook: https://twitter.com/laderafrutal/status/984608176099147776
First hint of what became Seat Product Model was in our joint APSR paper, 1993. But we referred to it as "SM"; for various reasons, I much prefer calling it "MS"!
(First place it was fully presented would be Taagepera's 2007 book, Predicting Party Sizes.)
https://www.jstor.org/stable/2939053?seq=1#metadata_info_tab_contents
(First place it was fully presented would be Taagepera's 2007 book, Predicting Party Sizes.)
https://www.jstor.org/stable/2939053?seq=1#metadata_info_tab_contents
This thread would not be complete without also listing:
(1) My paper with @DrHueyLi in which we introduced the first large-N regression analysis of the Seat Product Model. https://www.sciencedirect.com/science/article/abs/pii/S0261379415001845
(1) My paper with @DrHueyLi in which we introduced the first large-N regression analysis of the Seat Product Model. https://www.sciencedirect.com/science/article/abs/pii/S0261379415001845
and (2) the dataset article, with @corystruthers and @DrHueyLi https://journals.sagepub.com/doi/full/10.1177/2053168018813508
And to go direct to the datasets (one nationwide, the other district-level):
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ME2W6U
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ME2W6U
