Energy balance climate models and general equilibrium optimal mitigation policies

In a general equilibrium model of the world economy, we develop a two-dimensional energy balance climate model featuring heat diffusion and anthropogenic forcing driven by global fossil fuel use across the sphere of the Earth. This introduces an endogenous location dependent temperature function, driving spatial characteristics, in terms of location dependent damages resulting from local temperature anomalies into the standard climate-economy framework. We solve the social planner's problem and characterize the competitive equilibrium for two polar cases differentiated by the degree of market integration. We define optimal taxes on fossil fuel use and how they may implement the planning solution. Our results suggest that if the implementation of international transfers across latitudes is not possible then optimal taxes are in general spatially non-homogeneous and may be lower at poorer latitudes. The degree of spatial differentiation of optimal taxes depends on heat transportation. By employing the properties of the spatial model, we show by numerical simulations how the impact of thermal transport across latitudes on welfare can be studied.     

The institutional embeddedness of local inter-firm networks: a leverage for business creation

There is an increasing concern for the notion of ‘embeddedness’ of economic activity; yet the conceptualization of the concept and its operationalization remain underdeveloped. First, embeddedness may concern, on the one hand, the structure of relations that tie economic actors together (structural embeddedness) and, on the other hand, the social strands supplementing economic strands in each relation (substantive embeddedness). In this paper, a network framework is outlined which proposes several layers or ‘orders’ of embeddedness. Focusing on small firms, the point of departure is individual exchange relationships as personal ties combining economic and social concerns. First-order embeddedness concerns the localized business networks created by combining these dyadic relations. Second-order embeddedness is achieved when considering also the memberships of business persons in economic and social local institutions while third-order embeddedness concerns the special cases where these institutions bridge gaps between firms. The network model is operationalized and applied to a small Swedish industrial (furniture) community, its firms and economic/social institutions. The findings generally support the applicability of the model and demonstrate the supplementarity of different layers/orders of embeddedness. Further research challenges are deduced and implications for practitioners are provided.     

Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data

This paper discusses a factor model for short-term forecasting of GDP growth using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm, combined with a principal components estimator. We discuss some in-sample properties of the estimator in a real-time environment and propose alternative methods for forecasting quarterly GDP with monthly factors. In the empirical application, we use a novel real-time dataset for the German economy. Employing a recursive forecast experiment, we evaluate the forecast accuracy of the factor model with respect to German GDP. Furthermore, we investigate the role of revisions in forecast accuracy and assess the contribution of timely monthly observations to the forecast performance. Finally, we compare the performance of the mixed-frequency model with that of a factor model, based on time-aggregated quarterly data.     

Framing the field of international human resource management research

This article presents an overarching framework of the international human resource management field. The framework has four different levels: Macro (encompassing countries, regions and industries), the Multinational Corporation, Unit (typically subsidiary) and Individual (including teams, employees and their family members). At each level, we make a distinction between Influencing Factors, the HRM Function (encompassing both the HR department and HR policies and practices), Proximal Outcomes and Distant Outcomes of HRM. The framework allows us to examine existing research and suggest avenues for future work.     

Innovation and the circular economy: A systematic literature review

The circular economy emerged as an alternative model to the linear system, which now appears to be reaching its physical limitations. To transition to a circular economy, companies must not only be aware of but also engage in more sustainable practices. For such a transition, companies must rethink and innovate their business models and the ways they propose value to their clients while simultaneously considering environmental and social facets. This systematic literature review sought to map out from the company perspective the key topics interrelated with innovation and the circular economy, describing the internal and external factors to consider in such transition processes. Key lines of research were identified, and suggestions for future research and for facilitating movement toward a circular economy are provided. This work contributes to deepening the literature by identifying the priority areas concerning the circular economy and encouraging future research that meets international standards of excellence.     

Some general points on the $$I^2$$-measure of heterogeneity in meta-analysis

Meta-analysis has developed to be a most important tool in evaluation research. Heterogeneity is an issue that is present in almost any meta-analysis. However, the magnitude of heterogeneity differs across meta-analyses. In this respect, Higgins’ \(I^2\) has emerged to be one of the most used and, potentially, one of the most useful measures as it provides quantification of the amount of heterogeneity involved in a given meta-analysis. Higgins’ \(I^2\) is conventionally interpreted, in the sense of a variance component analysis, as the proportion of total variance due to heterogeneity. However, this interpretation is not entirely justified as the second part involved in defining the total variation, usually denoted as \(s^2\), is not an average of the study-specific variances, but in fact some other function of the study-specific variances. We show that \(s^2\) is asymptotically identical to the harmonic mean of the study-specific variances and, for any number of studies, is at least as large as the harmonic mean with the inequality being sharp if all study-specific variances agree. This justifies, from our point of view, the interpretation of explained variance, at least for meta-analyses with larger number of component studies or small variation in study-specific variances. These points are illustrated by a number of empirical meta-analyses as well as simulation work.