• Energy Research
• 2021-2025close
• 8. Economic growth close

Diese Dissertation beantwortet verschiedene politikrelevante ökonomische Fragen in den Bereichen Handelspolitik, Geldpolitik, sowie Rohstoffmärkte und Energieökonomik mit Hilfe von strukturellen Vektorautoregressionsmodellen (SVAR). SVARs stellen eine effektive Möglichkeit dar, die Beziehungen zwischen verschiedenen makroökonomischen und/oder Finanzmarkt-Variablen zu modellieren und werden verwendet, um die dynamischen kausalen Effekte von ökonomischen Schocks zu schätzen. Für jede ökonomische Fragestellung wird eine Identifikationsstrategie angewandt, die auf die betrachteten Daten und ihre statistischen Eigenschaften sowie die zugrundeliegenden Annahmen über ökonomische Mechanismen zwischen den betrachteten Zeitreihen zugeschnitten ist. Im Einzelnen besteht diese Dissertation aus vier Kapiteln. In den ersten beiden Kapiteln werden die Auswirkungen von Handelspolitik auf Finanzmärkte und auf die Makroökonomie geschätzt. Das dritte Kapitel liefert einen methodischen Beitrag zur SVAR-Literatur, der in einer Anwendung zu den Effekten von Geldpolitik dargestellt wird. Das letzte Kapitel verlässt die Felder der Handels- und Geldpolitik und wendet sich Rohstoffmärkten und der Energiewirtschaft zu, stützt sich dabei aber ebenfalls auf Zeitreihenmethoden. Es analysiert die Rolle von Metallen in der Energiewende. This dissertation answers various policy relevant economic questions in the fields of trade policy, monetary policy, and commodity markets and energy economics using structural vector autoregression (SVAR) models. SVARs constitute a parsimonious way to model the relations between different macroeconomic and/or financial variables and they are used to estimate the dynamic causal effects of economic shocks. For each economic question, this dissertation applies an identification strategy that is tailored to the relevant data and its statistical properties as well as the underlying assumptions about economic mechanisms among the regarded time series. Specifically, this dissertation consists of four chapters. The first two chapters estimate the effects of trade policy on financial markets and on the macroeconomy. The third chapter makes a methodological contribution to the SVAR literature in an application to monetary policy shocks. The final chapter moves away from trade and monetary policy to commodity markets and energy economics but also relies on time series methods. It analyzes the role of metals for the clean energy transition.

AbstractEmbedding sustainability in day‐to‐day operations necessitates employees' proactiveness beyond compliance with standardised management practices. Exchanging information on safety and environmental issues is acknowledged as a component of workers' proactive behaviours for sustainability embeddedness, which is hardly promoted by codified procedures. Accordingly, identifying leverages to stimulate information exchange is a primary objective for academics and practitioners. The study investigates drivers of information exchange on safety and environmental near misses by examining five situation‐related antecedents: rewards/reinforcements, organisational boundaries, social proactiveness, stakeholder salience and connectedness. The study relies on a mixed method approach, by combining social network analysis and a questionnaire survey conducted among four large Italian companies. The findings partially support the hypothesis of the study, highlighting rewards/reinforcements and connectedness as relevant antecedents of information exchange, while organisational boundaries only partially relate with information exchange. Surprisingly, stakeholder salience and social proactiveness do not emerge as significant drivers of information exchange. The study contributes to the debate on extra‐role pro‐sustainability behaviours and provides implications for managerial practice.

The article aims to identify the changes in the number of employees in European Union (EU) countries in the renewable energy sector in 2018 compared to 2014. EurObserv’ER yearbooks were the source of data on employment and capacity for selected renewable energy sources. The paper uses descriptive and pair-wise comparison methods. The largest decreases in employment were observed among countries that are leaders in the RES market (e.g., Germany, France). On the other hand, the greatest increases in employment were determined by source development opportunities in a given country, e.g., biofuels in Romania, Poland, Hungary, or Lithuania. The conducted pair-wise comparison indicated that the relation between the change in the ranking position and the change in the number of employees was significant for EU countries, whose ranking positions are both in the first (combination AA – I) and the second ten (combination CC – II) in the RES sector. Moreover, the results of the statistical analysis indicated a significant relationship and p-value significance in 11 out of 12 variables adopted for correlation, covering the number of employed and installed capacity in selected RES sectors in 2014 and 2018.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.

Implementing a circular economy aimed at reusing resources is becoming increasingly important for industry. Microalgae fit within a circular economy by being able to bioremediate nutrient waste and as a source of biomass for several commercial applications. Here, we report a novel validation of a circular economy concept using microalgae at a relevant industrial scale with a new two-phase process. During the first phase biomass was grown autotrophically, biomass was then concentrated using membrane technology for the second phase where mixotrophic conditions were applied to boost growth further. Microalgae cultures were able to grow (13.8 g/L), uptake and bioremediate nutrients (Nitrogen > 134 mg/L/day) from an anaerobic digestion side-stream (digestate), obtaining high quality microalgae biomass (>45% protein content) suitable for use as animal feed, closing the circular economy loop for industrial applications.

Abstract Computable general equilibrium models are becoming popular for simulating emissions trading systems. However, these models make various assumptions about the production structure and the possibilities of substituting energy for productive factors or inputs. Therefore, this study aims to analyze how different options to incorporate energy into the nested production structure of a computable general equilibrium model affect the obtained impacts when an emissions trading system is implemented. A flexible computable general equilibrium model called ECOMODEL is developed, which is the first model that allows choosing any of the three nested production structures most used in the literature (KEL-M, KL-EM, or KLE-M). The Chilean economy is used as a case study since there is a current database with high disaggregation of the energy sector for calibrating the computable general equilibrium model. The results show that the simulated impacts with KEL-M and KL-EM structures are the best when elasticities of substitution equal to the values ​​most frequently used in previous studies are chosen. However, the KEL-M structure that considers energy as a substitute for capital provides overly optimistic environmental results when high elasticities of substitution are used, obtaining the lowest reduction in Gross Domestic Product and the lowest price of the emissions trading system. Furthermore, the KLE-M structure gives unrealistic results regardless of the elasticities of substitution used. In consequence, a KL-EM nested production structure should be prioritized to simulate an emissions trading system since it provides realistic results and is less sensitive to the values of the elasticities of substitution.

The aim of this study was to determine whether emotional labor behavior has an effect on job satisfaction, and if there is an effect, to reveal whether communicative rational action has a moderator effect. This research was carried out in the banking sector. The sample group consisted of administrators of foreign capital bank managers (427) at all levels in Turkey. The collected data were analyzed with the IBM SPSS 21 program. Multiple regression analysis and SPSS PROCESS v3.5 (model1) methods were used in the analysis. According to the analysis, the three sub-dimensions of communicative rational action (practical-rational action, rational communication, and rational action) have a moderator role in the effect of emotional labor and job satisfaction. The other two sub dimensions (value–rational–action and firm family) do not have a moderator role in this effect. In the analysis made according to the total score of communicative rational action, the moderator role of communicative rational action in the effect of emotional labor and job satisfaction was determined. As a result of the research and analysis, it was determined that emotional labor has a positive effect on the phenomenon of job satisfaction.

Abstract Coal energy landscapes have changed dramatically over the last decades, including geographic shifts in production and consumption, technological changes that have reduced labour demand and led to relatively new mining practices (e.g. invasive mountain-top approaches), changed economic footprints, a shutdown of capacities or a complete end of mining in many regions with massive impacts on regional and local economies, community well-being, social capital, et cetera. Then the Covid-19 pandemic and Russia´s invasion of Ukraine have fundamentally affected the global economy, disrupted energy markets, and shattered existing estimates about development trends, challenging the progress and speed of the low-carbon energy transition and coal phase-out. This article provides a brief reflection on the changing landscapes of coal and their possible futures, and serves as an introduction to the Special Issue of Moravian Geographical Reports on “The death of coal in the energy transition? Regional perspectives”.