Policy integration, problem-solving, and the coronavirus disease crisis: lessons for policy design

The coronavirus disease pandemic has exposed differences in the capacity of governments around the world to integrate and coordinate different policy instruments into a coherent response. In this article, we conceptualize and empirically examine policy integration in responses to the coronavirus disease crisis in 35 countries. We then discuss how the interplay between restrictions, health protection, and economic policy has been articulated between, on the one hand, a policy design based on the complementarity of pro-public health and pro-economy measures, implying an integrated response, and, on the other, a policy design based on the perception of an inherent trade-off between the two. Finally, we discuss three implications from our analysis of policy integration against the coronavirus disease crisis for the post-COVID state: (a) the normalization and adaptation of integrated crisis responses; (b) the possible acceleration and “catching up” of problem-solving capacity as governments may use the crisis as an instance to put into place new social policies; and (c) policy integration as an accelerator of policy complexity and resistance against technocracy in the post-COVID state.

What has happened and what has not happened due to the coronavirus disease pandemic: a systemic perspective on policy change

The societal and policy transformations associated with the coronavirus disease pandemic are currently subject of intense academic debate. In this paper, we contribute to this debate by adopting a systemic perspective on policy change, shedding light on the hidden and indirect crisis effects. Based on a comprehensive analysis of policy agenda developments in Germany, we find that the pandemic led to profound shifts in political attention across policy areas. We demonstrate that these agenda gains and losses per policy area vary by the extent to which the respective areas can be presented as relevant in managing the coronavirus disease crisis and its repercussions. Moreover, relying on the analysis of past four economic crises, we also find that there is limited potential for catching up dynamics after the crisis is over. Policy areas that lost agenda share during crisis are unlikely to make up for these losses by strong attention gains once the crisis is over. Crises have hence substantial, long-term and so far, neglected effects on policymaking in modern democracies.

Frontier Technology, Trade, FDI, and TFP in the Electrical and Electronic Industries: Exporting or Processing Trade?

Does “openness” determine “catching-up” of establishments to frontier technology and total factor productivity (TFP) in Malaysia's electrical and electronic (E&E) industries? We contribute to this debate by applying a new measurement of processing trade intensity. Utilizing stochastic frontier analysis and Levinsohn and Pertrin (LP) TFP, we investigate determinants of technical efficiency (TE) and TFP. The results show that processing trade intensity and not export intensity determines TE and TFP for the overall sample and subsample of foreign establishments. In the processing trade subsample, export intensity is negatively related to TE and unrelated to TFP, obtaining an unconventional result that exporters are inefficient and not associated with TFP. The results show that higher foreign ownership shares of establishments are negatively associated with LP TFP.

Catching Up on Multilevel Modeling

This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel models. We first describe common use cases for clustered, longitudinal, and cross-classified designs, as well as their combinations. Using examples from both clustered and longitudinal designs, we then address issues of centering for observed predictor variables: its use in creating interpretable fixed and random effects of predictors, its relationship to endogeneity problems (correlations between predictors and model error terms), and its translation into multivariate multilevel models (using latent-centering within multilevel structural equation models). Finally, we describe novel extensions—mixed-effects location–scale models—designed for predicting differential amounts of variability.

Developing a National Innovation System in Small States

This study shares some empirical insights for adopting a national innovation system (NIS) to catalyze capacity building in small states with relatively low technology-based research and development resources. These countries may have to start further back than other nations; however, this chapter maintains that with the right NIS, latecomers can have the advantage of catching up economically. This study explores Brunei Darussalam's journey to catalyze innovation for sustainable economic growth, particularly digitalization and deep tech. The study found that establishing a national innovation ecosystem could be effective with national consensus and acceptance behind the approach. It emphasizes building critical infrastructures, institutions, and governance to promote efficient knowledge flow, talent development, digital literacy, and overall absorptive capacity. Because Brunei is a small state, coordinating and facilitating cohesive linkages among its key stakeholders can strategically mobilize change. As Brunei Darussalam embarks on such a trajectory, it must determine a relevant model.

Ethical Risks in the Cross Section of Extended Reality (XR), Geographic Information Systems (GIS), and Artificial Intelligence (AI)

The ethical risks which emerge from the cross section of artificial intelligence, extended reality, and geographic information systems could be examined in two broad categories of environmental and user-centric interactions of human beings with AI-curated mixed realities. These categories resonate with the capacity of AI to significantly impact the efficient application of extended reality technologies, while utilizing geodata and behavioral modelling to alter and transform experiences. While regulatory frameworks are catching up with the rights of users in the digital economy, the recently accelerated growth of immersive technologies provides further scenarios and use cases, which ought to be considered for their capacity to amplify biases, produce alternative realities, and affect human emotions.