Published since January 1, 2010

Statistics, Politics and Policy

ISSN: 2151-7509

Editor-in-chief: Uwe Wagschal

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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

Your Benefits

CALL FOR PAPERS

Topic: Machine Learning
Submission Deadline: 31.07.2022
Please see the call details in the PDF at the bottom of this page

Topic: Polarization (call extended)
Submission Deadline: 31.03.2022
Please see the call details in the PDF at the bottom of this page

The current Call for Papers does not correspond with your research topic? Submit your paper to our regular issues if your field of research corresponds with the overall focus of Statistics, Politics and Policy (SPP). We are always looking forward to publish new and innovative contributions to the fields of political, social, economic and statistical sciences.

Your benefits

Prestigious editors
High quality peer review
International recognition of the journal
Innovative approach to Statistics, Politics and Policy
Practical use of scientific knowledge in policy implementation

From 2021 onwards, Statistics, Politics and Policy awards the Emil J. Gumbel Prize for outstanding contributions to the Journal.
All submitted full articles and research notes are eligible to win this award. The award comes with a modest financial reward of 500 $ and the full recognition regarding the merits of the published research contribution.
The award winner is chosen annually by members of our editorial board.　

History

From 2022 onwards, three issues/year, updated continuously
ISSN: 2151-7509

Abstracting and Indexing

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Baidu Scholar
CNKI Scholar (China National Knowledge Infrastructure)
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Current Index to Statistics
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ERIH PLUS (European Reference Index for the Humanities and Social Sciences)
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IBZ (International Bibliography of Periodical Literature in the Humanities and Social Sciences)
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WorldCat (OCLC)
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Supplementary Materials

Topics

External Links

Online Submission of Manuscripts

Volume 14 Issue 2

June 2023

Publicly Available September 14, 2023

Frontmatter

Page range: i-iii

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Articles

June 27, 2023

Investigating the Economic Consequence of Terrorism in Sub-Saharan Africa: Evidence from a Dynamic Panel Model

Christian Agu, Augustine Jideofor Mbah, Chukwuagoziem Samuel Agu

Page range: 125-149

Abstract

This study examines the economic consequence of terrorism in Sub-Saharan Africa (SSA) with a panel of 38 countries between 2010 and 2020. Specifically, the study examined the impact of terrorism on economic growth, international tourism demand, income inequality, unemployment rate, and inflation rate. The study employed the two-step system GMM and quantile regression for the estimation. The results show that terrorism has had a significant negative impact on economic growth in SSA. Similarly, the study results indicate that terrorism impacts negatively on international tourism demand, widens the income gap, and increases the rate of unemployment and inflation in SSA. Furthermore, the two governance institution indicators employed in the study (government effectiveness and control of corruption) shows a significant negative impact on economic growth in the zone, while credit to the private sector and human capital had performed abysmally in the zones’ growth trajectory. These findings were further supported by the quantile regression results. The study employed both system GMM model and quantile regression in the analysis. The use of these two different methods makes the results obtained to be robust and efficient for policy purpose, which no other author has done before now.

May 29, 2023

Model-Based Small Area Estimation of Regional-Level Maternal Mortality Prevalence in Ghana

Dioggban Jakperik, Queensley Chidimma Chukwudum, Michael Jackson Adjabui

Page range: 151-162

Abstract

The study involved 1240 women covering the ten administrative regions of Ghana. The aim was to study the prevalence of maternal mortality and its distribution across the ten regions based on given demographic factors. Three main analytical methods were used: Direct estimation method, Fay-Herriot method and Binary Logistic regression. The study revealed that prevalence of maternal mortality in Ghana was high among women engaged in manual works, rural dwellers, women living without partners and women living in pro-poor families. The Northern region had the highest number of maternal deaths followed by the Western region whilst the Ashanti and the Upper East regions had the lowest number of maternal deaths. There is therefore the need for Ghana Health Service to engage all stakeholders in checking maternal mortality in the country.

June 26, 2023

NATO’s Expansion and Russia’s Aggressiveness: An Empirical Study from the Perspective of the U.S. Public

Kerry Liu

Page range: 163-182

Abstract

Russia’s aggression on Ukraine has attracted worldwide attention. The relations between Russia’s aggression and NATO’s expansion are being debated with conflicting viewpoints. Based on weekly Google Trends data from 5 March 2017 to 13 February 2022, this study creatively creates a series of time series variables to measure the public agenda in the US. Based on time series modellings, this study finds that the U.S. public believes that there are bi-directional relations between NATO’s expansion and Russia’s aggressiveness. In particular, Russia’s aggressiveness is driven by both NATO’s expansion and Russia’s imperialism. NATO’s expansion is driven by Russia’s foreign policy, Russia’s aggressiveness, and Russia’s imperialism. These conclusions predicted the U.S. government’s policy towards this war. This study contributes to policymakers by providing solid empirical evidence on the U.S. public’s opinion on this important issue and to academia as well by presenting a (still) new quantitative method in international relations. By employing this method, we can leverage readily accessible high-frequency time series data to gain valuable insights into U.S. public opinion, potentially enabling people to predict U.S. foreign policies.

Open Access April 3, 2023

Analysis of the Number of Tests, the Positivity Rate and Their Dependency Structure During COVID-19 Pandemic

Babak Jamshidi, Hakim Bekrizadeh, Shahriar Jamshidi Zargaran, Mansour Rezaei

Page range: 183-204

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Abstract

Recent advances in medical instruments, information technology, and unprecedented data sharing allowed scientists to investigate, trace, and monitor the COVID-19 pandemic faster than any previous outbreak. This extraordinary speed makes COVID-19 a medical revolution that causes some unprecedented analyses, discussions, and models. Modeling the dependence between the number of tests and the positivity rate is one of these new issues. Using four classes of copulas (Clayton, Frank, Gumbel, and FGM), this study is the first attempt tom model the dependency. The estimation of the parameters of the copulas is obtained using the maximum likelihood method. To evaluate the goodness of fit of the copulas, we calculate AIC. The computations are conducted on Matlab R2015b, R 4.0.3, Maple 2018a, and EasyFit 5.6. Findings indicate that at the beginning of a typical epidemic, the number of tests is relatively low and the proportion of positivity is high. As time passes, the number of tests increases, and the positivity rate decreases. The epidemic peaks are occasions that violate the stated general rule –due to the early growth of the number of tests. Also, during both peak and non-peak times, the rising number of tests is accompanied by decreasing the positivity rate. We find that the proportion of positivity is more proportional than the number of tests to the number of infected cases. Therefore, the changes in the positivity rate can be considered a representative of the level of the spreading. Approaching zero positivity rate is a good criterion to scale the success of a healthcare system in fighting against an epidemic. Accordingly, the number and accuracy of tests can play a vital role in the quality level of epidemic data.

Open Access July 31, 2023

Evaluating Different Covariate Balancing Methods: A Monte Carlo Simulation

Hideki Fukui

Page range: 205-326

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Abstract

We investigate the effectiveness of five weighting and matching techniques, including propensity score matching (PSM), in improving covariate balance and reducing bias when estimating treatment effects in finite-sample situations through Monte Carlo simulations. King and Nielsen (2019. “Why Propensity Scores Should Not Be Used for Matching.” Political Analysis 27 (4): 435–54) argue that pruning observations based on PSM with 1-to-1 greedy matching can worsen rather than improve covariate balance and can increase the bias in the estimates of treatment effects. In our simulations, we observed this phenomenon not only in PSM with 1-to-1 greedy matching but also in other covariate balancing techniques that King and Nielsen (2019. “Why Propensity Scores Should Not Be Used for Matching.” Political Analysis 27 (4): 435–54) recommend as better matching methods, i.e. Mahalanobis distance matching (MDM) and coarsened exact matching (CEM). Regardless of the weighting/matching techniques and the data generation processes in this study, our findings indicate that matching and weighting under extreme caliper or cut-point settings does not improve covariate balance. In addition, once a substantially improved covariate balance is achieved in a given sample, the estimated bias tends to worsen slightly as the covariate balance continues to improve. Moreover, our simulation results suggest that OLS with proper covariates reduces selection bias as well as other weighting and matching methods. The results suggest that when analyzing observational data, it is important to avoid looking for a one-size-fits-all estimator and to identify the appropriate nonexperimental estimator carefully for the sample by thoroughly investigating the available data’s characteristics.

Ahead of Print / Just Accepted

Ahead of Print / Just Accepted

Volume 14 (2023)

Volume 13 (2022)

Volume 12 (2021)

Volume 11 (2020)

Volume 10 (2019)

Volume 9 (2018)

Volume 8 (2017)

Volume 3 (2012)

Volume 2 (2011)

Issue 1

Volume 1 (2010)

Issue 1

CiteScore	0.8	2022, Scopus (Elsevier B.V., 2023)

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In this journal, authors have the option to publish their article under an open access license. Open Access allows you as an author to retain copyright and share your findings with colleagues and interested parties worldwide without any restraints.
Please note that authors from institutions with which we have a transformative agreement can publish open access without paying an article processing charge (APC). More information on the eligible institutions and articles can be found under the "Funding and Support" tab here.

Editorial

Editor
Uwe Wagschal, University of Freiburg, Germany

Assistant Managing Editor
Felix Ettensperger, University of Freiburg, Germany

Associate Editors
David W. Nickerson, Temple University, Philadelphia, USA
Georg Wenzelburger, University of Kaiserlautern, Germany

Editorial Board
Hanna Bäck, Lund University, Sweden
Keith Dowding, The Australian National University, Canberra, Australia
Carsten Jensen, Aarhus University, Denmark
Gary King, Harvard University, Cambridge, MA, USA
Bernhard Kittel, University of Vienna, Austria
Maria Kolosnitsyna, Higher School of Economics, Moscow, Russia
Jonathan Slapin, University of Essex, Colchester, UK
Adrian Vatter, University of Bern, Switzerland
Barbara Vis, Utrecht University, Netherlands

(Deutsch)

Online ISSN: 2151-7509
Print ISSN: 2194-6299
Type: Journal
Language: English
Publisher: De Gruyter
First published: January 1, 2010
Publication Frequency: 3 Issues per Year
Audience: Professional statisticians, statistically trained professionals from fields including epidemiology, education, economics, law, and policy analysis; policy analysts, and anyone interested in the implicit yet powerful ways that statistical thinking influences decisions that affect many aspects of public life.