The Importance of Predicting Things in Advance

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The 2016 election really took a ton of people by surprise. That's an example I talk about a lot in the book because I want to understand sort of how people reacted to it. So on the one hand, we have the sort of single worst form of social science question there. We're trying to explain a single outcome that has 50 or more variables that are related to it. But nonetheless, we do still make progress because it's still a question that people want to know.

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What makes studying humans harder than studying other parts of the universe? Is social science currently improving its rigor, relevance, and self-reflection? Is it improving its predictive power over time? Why have sample sizes historically been so small in social science studies? Is social science actually able to accumulate knowledge? Have social scientists been able to move the "needle" on real-world problems like vaccine adoption? Is social science becoming more diverse? Specifically, does social science have a political bias? Are universities in crisis? Do the incentive structures in universities make them difficult or even impossible to reform?

Matt Grossmann is Director of the Institute for Public Policy and Social Research and Professor of Political Science at Michigan State University. He is also Senior Fellow at the Niskanen Center and a Contributor at FiveThirtyEight. He has published analysis in The New York Times, The Washington Post, and Politico, and hosts the Science of Politics podcast. He is the author or co-author of How Social Science Got Better, Asymmetric Politics, Red State Blues, The Not-So-Special Interests, Artists of the Possible, and Campaigns & Elections, as well as dozens of journal articles. You can find more about him on his website.

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