Matthew P Hitt – författare

The United States Supreme Court exists to resolve constitutional disputes among lower courts and the other branches of government, allowing elected officials, citizens, and businesses to act without legal uncertainty. American law and society function more effectively when the Court resolves these ambiguous questions of Constitutional law. Since lower courts must defer to its reasoning, the Court should also promulgate clear and consistent legal doctrine, giving a reason for its judgment that a majority of justices support. Yet a Court that prioritizes resolving many disputes will at times produce contradictory sets of opinions or fail to provide a rationale and legal precedent for its decision at all. In either case, it produces an unreasoned judgment. Conversely, a Court that prioritizes logically consistent doctrine will fail to resolve many underlying disputes in law and society. Inconsistency and Indecision in the United States Supreme Court demonstrates that over time, institutional changes, lobbied for by the justices, substantially reduced unreasoned judgments in the Court’s output, coinciding with a reduction in the Court’s caseload. Hence, the Supreme Court historically emphasized the first goal of dispute resolution, but evolved into a Court that prioritizes the second goal of logically consistent doctrine. As a result, the Court today fails to resolve more underlying questions in law and society in order to minimize criticism of its output from other elites. In so doing, the modern Court often fails to live up to its Constitutional obligation.

The United States Supreme Court exists to resolve constitutional disputes among lower courts and the other branches of government, allowing elected officials, citizens, and businesses to act without legal uncertainty. American law and society function more effectively when the Court resolves these ambiguous questions of Constitutional law. Since lower courts must defer to its reasoning, the Court should also promulgate clear and consistent legal doctrine, giving a reason for its judgment that a majority of justices support.Yet a Court that prioritizes resolving many disputes will at times produce contradictory sets of opinions or fail to provide a rationale and legal precedent for its decision at all. In either case, it produces an unreasoned judgment. Conversely, a Court that prioritizes logically consistent doctrine will fail to resolve many underlying disputes in law and society. Inconsistency and Indecision in the United States Supreme Court demonstrates that over time, institutional changes, lobbied for by the justices, substantially reduced unreasoned judgments in the Court’s output, coinciding with a reduction in the Court’s caseload. Hence, the Supreme Court historically emphasized the first goal of dispute resolution, but evolved into a Court that prioritizes the second goal of logically consistent doctrine. As a result, the Court today fails to resolve more underlying questions in law and society in order to minimize criticism of its output from other elites. In so doing, the modern Court often fails to live up to its Constitutional obligation.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

Although the Supreme Court has historically resisted a partisan sorting out of its public legitimacy, today, Republicans and Democrats look at the Court in very different ways. This Element assembles original survey and experimental data to unpack these changes in three ways. First, the authors illustrate the powerful role that partisanship plays in shaping judicial public opinion. Second, they validate a new three-item measure of specific support and show that it reliably predicts perceptions of Supreme Court legitimacy. Finally, they introduce a new, applied measure of support for the rule of law and connect it to specific and diffuse support. Taken as a whole, their work demonstrates that large chunks of the mass public view the Supreme Court critically. Looking ahead, it is unclear whether legitimacy will rebound when citizens perceive that the balance of judicial power within the nation's High Court has fractured along party lines.

Although the Supreme Court has historically resisted a partisan sorting out of its public legitimacy, today, Republicans and Democrats look at the Court in very different ways. This Element assembles original survey and experimental data to unpack these changes in three ways. First, the authors illustrate the powerful role that partisanship plays in shaping judicial public opinion. Second, they validate a new three-item measure of specific support and show that it reliably predicts perceptions of Supreme Court legitimacy. Finally, they introduce a new, applied measure of support for the rule of law and connect it to specific and diffuse support. Taken as a whole, their work demonstrates that large chunks of the mass public view the Supreme Court critically. Looking ahead, it is unclear whether legitimacy will rebound when citizens perceive that the balance of judicial power within the nation's High Court has fractured along party lines.

Local newspapers can hold back the rising tide of political division in America by turning away from the partisan battles in Washington and focusing their opinion page on local issues. When a local newspaper in California dropped national politics from its opinion page, the resulting space filled with local writers and issues. We use a pre-registered analysis plan to show that after this quasi-experiment, politically engaged people did not feel as far apart from members of the opposing party, compared to those in a similar community whose newspaper did not change. While it may not cure all of the imbalances and inequities in opinion journalism, an opinion page that ignores national politics could help local newspapers push back against political polarization.

Local newspapers can hold back the rising tide of political division in America by turning away from the partisan battles in Washington and focusing their opinion page on local issues. When a local newspaper in California dropped national politics from its opinion page, the resulting space filled with local writers and issues. We use a pre-registered analysis plan to show that after this quasi-experiment, politically engaged people did not feel as far apart from members of the opposing party, compared to those in a similar community whose newspaper did not change. While it may not cure all of the imbalances and inequities in opinion journalism, an opinion page that ignores national politics could help local newspapers push back against political polarization.

Local newspapers can hold back the rising tide of political division in America by turning away from the partisan battles in Washington and focusing their opinion page on local issues. When a local newspaper in California dropped national politics from its opinion page, the resulting space filled with local writers and issues. We use a pre-registered analysis plan to show that after this quasi-experiment, politically engaged people did not feel as far apart from members of the opposing party, compared to those in a similar community whose newspaper did not change. While it may not cure all of the imbalances and inequities in opinion journalism, an opinion page that ignores national politics could help local newspapers push back against political polarization.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

The politics of white identity pervade American national discourse, and many commentators and scholars rightfully express concern about rising tides of white nationalism in America politics. Yet white Americans today exhibit broad diversity in their ethnic origins, the relative importance of those origins, and their views on race in politics and society. In White Identities in American Politics, Dominik Stecuła and Matthew P. Hitt draw on two large original surveys to codify the various forms of white identities that exist in America today. White Americans are no more monolithic politically and psychologically than any other ethnic group. The various typologies of whiteness exhibit durable and meaningful relationships with other important political attitudes, including nativism, immigration attitudes, and racial resentment. In an era where all politics can be related to identity politics, oversimplifying and overgeneralizing the attitudes and behaviors of America’s largest racial and ethnic group risks accidentally reinforcing and affirming a hegemonic form of white identity divorced from nuance and ethnic origins, one responsible for centuries of violence and bigotry in the United States.