Published by De Gruyter

Volume 7 Issue 1-2

Issue of Statistics, Politics and Policy

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Contents
Journal Overview

Publicly Available June 20, 2017

Editor’s Note

June 20, 2017

Articles

April 27, 2017

Self-Interest or Solidarity?

Sean Mueller, Adrian Vatter, Charlie Schmid

Page range: 3-28

Abstract

This article puts the self-interest hypothesis to an empirical test by analysing the 2004 referendum on fiscal equalisation in Switzerland. That vote put forth a series of reforms which created regional winners and loser in terms of having to pay or receiving unconditional funding. Although Switzerland is usually portrayed as a paradigmatic case in terms of inter-regional solidarity and national integration, we show that rational and selfish cost-benefit calculations strongly mattered for the end-result. We rely on a multi-level model with referendum and other data on more than 2700 municipalities and all 26 cantons. More broadly, our findings confirm that rational choice theory works well for voting on straightforward monetary issues with a clearly defined group of winners and losers. However, symbolic interests such as party strength and cultural predispositions against state intervention and in favour of subsidiarity also matter and need to be taken into account alongside.

May 11, 2017

Measurement Error and Attenuation Bias in Exponential Random Graph Models

Yeaji Kim, Leonardo Antenangeli, Justin Kirkland

Page range: 29-54

Abstract

Exponential Random Graph Models (ERGMs) are becoming increasingly popular tools for estimating the properties of social networks across the social sciences. While the asymptotic properties of ERGMs are well understood, much less is known about how ERGMs perform in the face of violations of the assumptions that drive those asymptotic properties. Given that empirical social networks rarely meet the strenuous assumptions of the ERGM perfectly, practical researchers are often in the position of knowing their coefficients are imperfect, but not knowing precisely how wrong those coefficients may be. In this research, we examine one violation of the asymptotic assumptions of ERGMs – perfectly measured social networks. Using several Monte Carlo simulations, we demonstrate that even randomly distributed measurement errors in networks under study can cause considerable attenuation in coefficients from ERGMs, and do real harm to subsequent hypothesis tests.

June 2, 2017

A Demographic Peace? Youth Bulges and Other Population-Related Causes of Domestic Conflict

Uwe Wagschal, Thomas Metz

Page range: 55-97

Abstract

The following article analyzes violent political conflicts. Starting from theoretical debates on the determinants of violent conflicts, it focuses on intrastate conflicts. The main explanatory factors which are analyzed from different perspectives are demographic factors. Not only the size of the population or the population density is relevant, but also the so-called youth bulge. Youth bulges, i.e. large cohorts of young people, are the main driving forces of war. Especially variants like male youth bulges are highly significant in the empirical analysis. The article uses different data sets for the analysis, like the Global Peace Index and the CONIS data. Various statistical methods are used in the analysis. The article also draws attention to intervening factors, which might intensify or lessen the impact of the youth bulge.

May 11, 2017

Statistical Literacy in the Classroom: Should Introductory Statistics Courses Rethink their Goals?

Cynthia McLauchlan, Matthias Schonlau

Page range: 99-115

Abstract

Many undergraduate degrees require the completion of an introductory statistics course, but it is unclear to what extent taking a statistics course improves statistical literacy. We conducted an online survey with a simple random sample of undergraduate students at the University of Waterloo, Canada. We then compared students who have completed at least one statistics course to those who have completed none and found that taking a statistics course did not improve statistical literacy on the questions asked (causation versus correlation, margin of error, and others). Introductory statistics courses may want to address statistical literacy as a learning outcome more explicitly for a better understanding of public policies.

About this journal

Objective
Statistics, Politics, and Policy studies the ways that statistical analysis drives public policy decisions, and publishes significant research on the application of statistical ideas to problems that relate to policy implementation.

The increasing amount and complexity of available data is constantly creating new challenges for statistical thinking in policy problems. While many academic statisticians tend to share among themselves their latest methods and models, less attention has been paid to the usefulness of those statistical methods and models to inform public policy decisions, and what statistical approaches might be most effective in designing how policies are implemented. In the policy sphere, statistical methods are sometimes taken as a given, with less attention to all the variations, assumptions, and effects of different methods in differing contexts. But it is in the policy sphere that statistical debates can have the great value and impact, and the intersection of statistics and public policy is a fertile ground for statistical research and analysis to address important policy issues that may have widespread ramifications.

As an electronic journal, Statistics, Politics, and Policy will use a mix of voices and approaches to reach a broad audience. The journal aims to open avenues of communication between statisticians and policy makers on questions that pique the interest of the public. The primary objective of the journal will be to highlight the use of innovative statistical methodology in order to elucidate and resolve important public policy issues.

Statistics, Politics, and Policy will publish applied research articles that explore the implications of statistical thinking and methods applied to public policy issues. The journal will also publish engaging commentary pieces and innovative policy ideas on the public issues of the day where statistics plays, or ought to play, a role.

Papers for the commentary and ideas section are short, ideally 600-2000 words, and are intended to be of general interest and readability. That is, they should contain deeper analysis than is found on the Op-Ed page of The Wall Street Journal or The New York Times, but to be of comparable interest the Statistics, Politics, and Policy readership.

Topics

Applied statistical research
Policy issues
Educational testing and policy
Energy and environmental policy
Demography
Climate change
Public finance
History and review of statistical ideas applied to public policy controversies
Taxation and business policy
Justice, crime and forensic analyses
Health policy including health care finance
Drug development
Approval and monitoring
Politics
Sociological policy analyses
Statistical methodology including study design and causal inference, and survey methods

Article formats
Research articles, commentaries

Volume 7 Issue 1-2

Issue of Statistics, Politics and Policy

Frontmatter

Editor’s Note

Self-Interest or Solidarity?

Abstract

Measurement Error and Attenuation Bias in Exponential Random Graph Models

Abstract

A Demographic Peace? Youth Bulges and Other Population-Related Causes of Domestic Conflict

Abstract

Statistical Literacy in the Classroom: Should Introductory Statistics Courses Rethink their Goals?

Abstract