Band 15, Heft 3

Voting Advice Applications (VAAs), such as the German Wahl-O-Mat (WOM), have been examined extensively by researchers in various ways. Here, a subset of research uses data from the Wahl-O-Mat to investigate party relations. While these investigations focus on a limited number of WOM editions, I explicitly investigate the persistence of party relations in the WOM in a broad statistical analysis over 63 editions of the WOM in this exploratory research paper. At first glance, I find that intuitive differences in the overall proximities are observable. However, while many arguments exist that corroborate the suitability of the WOM data for the investigation of party relations, I identify statistically significant lower proximities for the six largest German parties in WOM editions from 2009 onward. Based on a review of changes in the design framework of the WOM and comparative data analyses based on the Chapel Hill Expert Survey and the Manifesto data set, these lower proximities are apparently linked to changes in the design of the WOM. As a result, I discuss the general ability of data from the WOM to give reliable insights into party relations. I argue that the WOM might roughly represent overall party relations but, due to a non-proportionality in the shift of the distances, potential design changes have distorting impacts on the relations between parties that make comparisons between different editions of the WOM problematic. This should be a starting point to investigate other VAAs for similar patterns to reevaluate the validity of data from VAAs for the examination of party relations in general.

In an analysis of 1,825 state or provincial election outcomes in five federal democracies the rate of decay of incumbency ( K ) serves to partition the distribution of the vote for the incumbent party, the party of the head of government, between those who win a subsequent term and those who do not. In conjunction with the mean and standard deviation of the distribution, the weighted mean of the vote in re-election and defeat is identified. The model’s predictions are generally within 2–3 percentage points of the actual outcome.

Accurate forecasting of municipal solid waste (MSW) generation is critical for effective waste management, given the rising volumes of waste posing environmental and public health challenges. This study investigates the efficacy of hybrid forecasting models in predicting MSW generation trends across Organization for Economic Cooperation and Development (OECD) countries. The empirical analysis utilizes five distinct approaches – ARIMA, Theta model, neural networks, exponential smoothing state space (ETS), and TBATS models. MSW data spanning 1995–2021 for 29 OECD nations are analyzed using the hybrid models and benchmarked against individual ARIMA models. The results demonstrate superior predictive accuracy for the hybrid models across multiple error metrics, capturing complex data patterns and relationships missed by individual models. The forecasts project continued MSW generation growth in most countries but reveal nuanced country-level differences as well. The implications for waste management policies include implementing waste reduction and recycling programs, investing in infrastructure and technology, enhancing public education, implementing pricing incentives, rigorous monitoring and evaluation of practices, and multi-stakeholder collaboration. However, uncertainties related to model selection and data limitations warrant acknowledgment. Overall, this study affirms the value of hybrid forecasting models in providing robust insights to inform evidence-based waste management strategies and transition toward sustainability in the OECD region.

The current United States National Defense Strategy prioritizes strategic competition with Russia and China, whereas for the previous two decades, the priority was counter-terrorism. This research aims to measure the extent to which competition among great powers is intensifying and identify where such intensification is taking place. To achieve this, we utilize a large, open-source dataset called GDELT 2.0, which provides an archive of global news articles. We calculate the entropy for local press coverage of great powers (e.g., the United States, China, Russia, France, and India) across 96 African and Asian nations to measure static competition levels. Additionally, we identify African and Asian nations where competition levels have changed significantly between 2015 and 2020. Our findings show that seven countries are experiencing increased competition among great powers, whereas seven other countries experience increased domination by one great power. When we aggregate the data geographically, we find that Southeast Asia is the only subregion where there is a significant decrease in competition. Our results align with the primary concern of the National Defense Strategy: that American influence is decreasing. Specifically, we have identified increased competition across Africa and increased domination across Asia. These trends are due to a relatively higher reporting of Chinese in-country public and private entities between 2015 and 2020.

This study analyzed the impact of macroeconomic variables (manufacturing, real exchange rate, government expenditure, and gross fixed capital formation) on GDP growth in Ghana. Utilizing secondary data from the World Development Indicators of the World Bank (1991–2021), we employed a hierarchical Bayesian linear model with interaction effects to assess these relationships. The results indicate that the real exchange rate, manufacturing, and government expenditure have a positive influence on GDP growth, while gross fixed capital formation exhibits a moderately negative effect. To enhance economic growth, it is crucial to optimize capital investments, bolster export competitiveness through targeted policies, and invest in manufacturing innovation. These findings offer actionable insights for policymakers aiming to stimulate economic growth in Ghana.