Time Counts

Gregory J. Wawro is professor of political science at Columbia University. His books include Filibuster: Obstruction and Lawmaking in the U.S. Senate. Ira Katznelson is the Ruggles Professor of Political Science and History at Columbia University. His books include Fear Itself: The New Deal and the Origins of Our Time.

• List of FiguresList of TablesPreface and AcknowledgmentsList of Abbreviations1 Designing Historical Inquiry1.1 Conundrums1.2 History and Political Science: A Century of Divergence1.3 Post-War Divisions between History, Economics, Political Science, and Sociology1.4 Possibilities1.5 Ways Ahead2 Quantitative Pathways for Qualitative Purposes2.1 Orientations2.2 Analytical History: Two Modes2.3 Identifying a Middle Range3 Methods3.1 Methodological Issues3.2 Semiparametric Methods3.3 Change Point Models3.4 Important Concerns3.4.1 Adjudicating between simple and more complex models3.4.2 Imposing less structure is not atheoretical3.5 Conclusion4 Congressional Demonstrations4.1 Coalition Sizes, Agenda Change, and Supermajority Rules in the U.S. Senate4.2 Party Power in the U.S. House of Representatives4.3 Realignment, the 17th Amendment, and Split Party Delegations in the Senate4.4 The 17th Amendment and Representation4.5 Sectionalism and Labor Policy in the New Deal and Fair Deal Periods4.6 Conclusion5 Path Dependence5.1 Path Dependence in Economics5.2 Contingency and Deterministic Patterns5.3 Positive Feedbacks5.4 Stability through Change5.5 Sequence, Externalities, and Path Dependence5.6 Empirical Modeling of Path Dependence5.7 Alternative Approaches to Modeling Path Dependence5.8 Critical Junctures and Initial Conditions5.9 Markov Switching Models with Time-Varying Transition Probabilities5.9.1 A representative MSM-TVTP model5.9.2 Stylized examples of MSM-TVTP indicating path dependence5.10 Replication of Path Dependence and Macropartisanship5.11 Path Dependence and Partisan Polarization5.12 Conclusion6 Natural Experiments, Causality, and Historical Analysis6.1 Randomness, Counterfactuals, and Comparisons for Causal Inference6.2 Opportunities and Challenges6.3 Historical Events and Causal Leverage6.3.1 Extreme weather events and economic development6.4 Discontinuities6.5 Instrumental Variables6.6 Persistence6.6.1 Potential problems with standard errors6.6.2 Multilevel concerns6.6.3 Path dependence and causal analysis6.6.4 A closer look at two studies featuring historical IV estimation6.7 Discussion7 ConclusionNotesBibliographyIndex

"[A] major new book…all political scientists stand to learn from this balanced and nonpolemical effort to reorient quantitative analysis for historical social science."---James Mahoney, Perspectives on Politics