This is definitely a tour de force on how political science ought to be done. That being said, unless you are a political scientist or a student of political science, it might get a bit too detailed and mathy for your taste. But if you are in one of those two groups, I consider this book a must read! And I think their findings are also crucial to know if you are involved in electoral systems design, and probably highly interesting if you are an electoral reform advocate (like myself).
If you are not very versed in social science quantitative methods, you may find yourself getting bogged down after Part 2 or 3. If so, you may want to consider skipping to Chapter 16 and finishing from there, as they summarize their findings quite well there. If anything catches your interest at this point, they make it very clear where to go for more details. As for me, my background is economics and I’ve only taken a few political science classes and read a few dozen papers. However, I do consider myself a self-study student of political science, so I did struggle through the whole thing from start to finish, and I am very glad that I did, as I’m sure I’ll be reviewing my highlights and notes for years to come!
After a survey of various electoral systems from around the world and a detailed explanation of each one in Part 1, it then builds upon and extends the well-known Duverger’s Law, which predicts that single-seat plurality elections tend towards two-party systems while multi-seat proportional representation elections tend towards multi-party system. A recurring theme of the book is that social science models ought to provide more quantitative predictions than this to both be more scientific and useful, and so the book presents the Seat Product Model (SPM) which goes beyond Duverger and actually predicts the number of effective parties in a country based on the district magnitude (number of seats in the election, or M) and the assembly size (S) with startling accuracy, given the model’s simplicity.
Furthermore, it is a logical model (instead of just a regression that commonly appears in much social science research), and it is based upon the social science model-making methods presented by Taagepera in Logical Models and Basic Numeracy in Social Sciences (which they briefly summarize at the very end of the book). Only after they spend time thinking and theorizing how they think the whole system works and build the logical model do they then test it against empirical data and present the results (whereas they say many social scientists rush too quickly to create regressions). And I found their arguments for both the SPM and this scientific approach to be extremely compelling and convincing.
After that, they get more rigorous and defend the SPM against possible criticisms and extend the model to apply it to presidential systems, more complex electoral systems, and intraparty competition, and this is where I think a layperson’s eyes would probably glaze over as it is filled with math and regression results (in which case, I would recommend skimming over that stuff or, as I mentioned, skipping to chapter 16).
If you are an electoral reform advocate seeking to fight the duopoly, the takeaway lesson here is that you’ll probably need multi-seat proportional representation to do so. It is true that the SPM mostly focuses on simple systems like plurality due to the relative lack of empirical data for other single-seat methods, but from the later chapters, they show it hold up surprisingly well in the more complex cases involving the Alternative Vote (aka Ranked Choice Voting) and Mixed Member Proportional systems. They also summarize Gary Cox’s “M + 1” model from Making Votes Count that argues similarly on the basis that economies of scale mean that it just doesn’t pay off for parties/candidates beyond the first runner-up to keep running (or for elites to support them), and they also extend upon this model based on their findings.
As for as how the writing goes, it is quite clear and presents a watertight case (both for the SPM and for how social sciences ought to approach modeling), but it does proceed in a rather systematic and by-the-numbers fashion that, while rigorous, makes for rather less-than-lively reading. Furthermore, while the math isn’t complex at all, there is a fair amount of it. So, this is not a book for light beach reading. This is a solidly academic book, so if you’re reading it, you’re reading it with the intent to learn, and the wealth of content is exemplary. Both Shugart and Taagepera are simply top caliber scholars in comparative politics and this book demonstrates why. They’ve contributed an immense amount of knowledge to the field in many other papers and works and also Shugart’s excellent blog (which showcases numerous applications of SPM and extends upon it a bit as well), but I consider this book to be their crowning achievement. I am firmly convinced that the world would be a much, much better place if all social scientists pursued research and modeling the way these two scholars do.