Jeffrey J. Harden

Does open governance strengthen democracy? The Illusion of Accountability contends that it does not. Leveraging a wealth of data from decades of legislative politics in the American states, the book assesses the causes and consequences of 'open meetings laws,' which require public access to proceedings in state legislatures. The work traces the roots of these laws back to the founding constitutions of some states and analyzes the waves of adoptions and exemptions to open meetings that occurred in the twentieth century. The book then examines the effects of these transparency laws on a host of politically consequential outcomes both inside and outside the legislature. This analysis consistently finds that open meetings do not influence legislators' behavior or citizens' capacity to alter that behavior. Instead, a link between transparent legislatures and an expanded system of organized interests is established. This illuminating work concludes that transparency reform only creates the illusion of accountability in state government.

Does open governance strengthen democracy? The Illusion of Accountability contends that it does not. Leveraging a wealth of data from decades of legislative politics in the American states, the book assesses the causes and consequences of 'open meetings laws,' which require public access to proceedings in state legislatures. The work traces the roots of these laws back to the founding constitutions of some states and analyzes the waves of adoptions and exemptions to open meetings that occurred in the twentieth century. The book then examines the effects of these transparency laws on a host of politically consequential outcomes both inside and outside the legislature. This analysis consistently finds that open meetings do not influence legislators' behavior or citizens' capacity to alter that behavior. Instead, a link between transparent legislatures and an expanded system of organized interests is established. This illuminating work concludes that transparency reform only creates the illusion of accountability in state government.

Multidimensional Democracy examines political representation from the supply (legislator) and demand (constituent) perspectives. Focusing on four dimensions - policy, service, allocation, and descriptive representation - it documents systematic variation in what people want from legislators and what legislators choose to emphasize while in office. It has important implications for the study of representation, as well as normative questions about political inequality in America. The demand-side results show that constituents who are economically advantaged tend to prefer policy-based representation while the disadvantaged place relatively more importance in constituent service and/or allocation. Suggestive results from the legislator data complement this finding; legislators in wealthy, white districts tend to focus more on policy while those representing economically disadvantaged and racially diverse districts may place more emphasis on service and/or allocation. A likely consequence is that the policy choices made by representatives reflect the policy preferences of the economically advantaged because policy representation is what those citizens want.

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.