The Value Of Play in Infant and Child Psychotherapy in a Group Attachment-Based Intervention (GABI)

There is growing interest in examining how attachment-based therapeutic interventions in early childhood can strengthen the bond between parent and child and prevent the transmission of intergenerational trauma. In recent decades, advances in attachment research have contributed to a greater understanding of how important the parent-child relationship is for a child’s well-being and subsequent years in life. This thesis explores the value of play in children’s therapy, specifically its use in dyadic play therapy as a therapeutic technique to strengthen the bond between parent and child. Two case studies from an attachment-based intervention are presented, and focus is given to the implicit nonverbal cues of communication expressed during the parent- child interaction in dyadic play. The value of play between the dyad is assessed from an attachment-based perspective and the correlation between the progression of play in relation to the quality of the parent-child attachment is explored. The therapeutic space of the case studies present play with two primary functions: play exposes the underlying relational dynamics of the parent-child relationship and it serves as the vehicle in which the parent and child can work together to create a shared meaning of their experience

Knowledge for a warmer world: a patent analysis of climate change adaptation technologies

Technologies can help strengthen the resilience of our economy against existential climate-risks. We investigate climate change adaptation technologies (CCATs) in US patents to understand (1) historical patterns and drivers of innovation; (2) scientific and technological requirements to develop and use CCATs; and (3) CCATs' potential technological synergies with mitigation. First, in contrast to mitigation, innovation in CCATs only slowly takes off, indicating a relatively low awareness of investors for solutions to cope with climate risks. Historical trends in environmental regulation, energy prices, and public support can be associated with patenting in CCATs. Second, CCATs form two main clusters: science-intensive ones in agriculture, health, and monitoring technologies; and engineering-intensive ones in coastal, water, and infrastructure technologies. Analyses of technology-specific scientific and technological knowledge bases inform directions for how to facilitate advancement, transfer and use of CCATs. Lastly, CCATs show strong technological complementarities with mitigation as more than 25% of CCATs bear mitigation benefits. While not judging about the complementarity of mitigation and adaptation in general, our results suggest how policymakers can harness these technological synergies to achieve both goals simultaneously

Does automation erode governments' tax basis? An empirical assessment of tax revenues in Europe

Decomposing taxes by source (labor, capital, sales), we analyze the impact of automation (1) on tax revenues, (2) the structure of taxation, and (3) identify channels of impact in 19 EU countries during 1995-2016. Robots and Information and Communication Technologies (ICT) are different technologies designed to automate manual (robots) or cognitive tasks (ICT). Until 2007, robot diffusion led to decreasing factor and tax income, and a shift from taxes on capital to goods. ICTs changed the structure of taxation from capital to labor. We find decreasing employment, but increasing wages and labor income. After 2008, robots have no effect but we find an ICT-induced increase in capital income, a rise of services, but no effect on taxation. Automation goes through different phases with different economic impacts which affect the amount and structure of taxes. Whether automation erodes taxation depends (a) on the technology type, (b) the stage of diffusion and (c) local conditions

How to accelerate green technology diffusion? An agent-based approach to directed technological change with coevolving absorptive capacity

Hötte K. How to accelerate green technology diffusion? An agent-based approach to directed technological change with coevolving absorptive capacity. Universität Bielefeld Working Papers in Economics and Management. Vol 01-2019. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2019.The window of opportunity for effective climate change mitigation is closing. Hence, it is decisive to understand how to accelerate the diffusion of climate friendly technologies. Path dependence of technological change is an explanation for sluggish diffusion even if a technology is superior in the long run. This paper studies the determinants of diffusion, learning and the coevolution of innovation and heterogeneous absorptive capacity. I show how the effectiveness of different market based climate policies depends on the type and strength of diffusion barriers. I introduce a macroeconomic agent-based model that is an eco-technology extended version Eurace@unibi model. Technology is heterogeneous by type (green or brown). Firms choose between types when acquiring capital goods and build up type-specific technological know-how that is needed to exploit the productive potential of capital. Path dependence is operationalized as accumulated diffusion barriers taking the form of inferior technical performance of supplied green capital and type-specific know-how of adopters. The barriers interrelate with positive feedback loops from market induced innovation dynamics and learning by doing, and analyze how these mechanisms explain path dependence and the emerging macroeconomic patterns of technology diffusion. Environmental taxes can outweigh a lower technical performance and subsidies perform better if lacking capabilities hinder firms to adopt a sufficiently mature technology

Technology and jobs: A systematic literature review

Does technological change destroy or create jobs? New technologies may replace human workers, but can simultaneously create jobs if workers are needed to use these technologies or if new economic activities emerge. Furthermore, technology-driven productivity growth may increase disposable income, stimulating a demand-induced expansion of employment. To synthesize the existing knowledge on this question, we systematically review the empirical literature on the past four decades of technological change and its impact on employment, distinguishing between five broad technology categories (ICT, Robots, Innovation, TFP-style, Other). Overall, we find across studies that the labor-displacing effect of technology appears to be more than offset by compensating mechanisms that create or reinstate labor. This holds for most types of technology, suggesting that previous anxieties over widespread technology-driven unemployment lack an empirical base, at least so far. Nevertheless, low-skill, production, and manufacturing workers have been adversely affected by technological change, and effective up- and reskilling strategies should remain at the forefront of policy making along with targeted social support systems

Eurace@unibi-eco: A model of technology transitions. V1.1. Model documentation

Hötte K. Eurace@unibi-eco: A model of technology transitions. V1.1. Model documentation. Universität Bielefeld Working Papers in Economics and Management. Vol 08-2019. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2019.Purpose of this paper is the self-contained description of the green technology extension of the macroeconomic agent-based model Eurace@unibi. The original model is extended in mainly five dimensions: (1) There are two types of production technology, i.e. a green and a conventional. Technology is embodied in capital goods and in the technological capabilities of firms. (2) Employees are endowed with two types of evolving technology-specific skills that are needed to work effectively with specific capital goods. (3) Based on their technological capabilities and the market environment, consumption goods (CG) firms decide whether to invest in green or conventional capital. (4) An environmental accounting keeps track of the environmental impact of CG sector. (5) A policy module allows to investigate the impact of different diffusion policies. Main research areas covered by the model extension are directed technological change, innovation diffusion and technology substitution processes. A key feature of the model is endogenous, technology-specific absorptive capacity of heterogeneous technology adopters that evolves through learning. It is a comprehensive, macroeconomic model that allows to study the macroeconomic and distributional consequences of transition processes. The technical description of the model is complemented by a short summary and discussion of technology transition dynamics in a baseline simulation

Pluralist economics in an era of polycrisis

Interacting crises at economic, societal, ecological, and geopolitical levels reveal the fragility of connected global systems and give momentum to pluralist economic thinking as a suitable approach to address the complexity and uncertainty of today’s economy. This special issue (SI) explores how young economists, educated in this era, study economic phenomena through pluralist lenses. Due to the structure of interdependent crises and inherent uncertainty, pluralism of values, theory and methods may benefit the academic and policy debate on solutions for today’s political, social, and scientific challenges. Applied to the crisis context, this SI shows a range of research methods and interdisciplinary approaches, reflecting a shift in economic thinking that embraces the complexity, limited predictability, and fragility of socioeconomic systems. The SI aims to promote a dialogue across schools of economic thought to enhance our understanding and contribute to robust and inclusive policy

Data publication for: How to accelerate green technology diffusion? An agent-based approach to directed technological change with coevolving absorptive capacity

Hötte K. Data publication for: How to accelerate green technology diffusion? An agent-based approach to directed technological change with coevolving absorptive capacity. Bielefeld University; 2019.# Updates: Check out the more recent versions of the rcode here: https://gitlab.ub.uni-bielefeld.de/khoette/rcode_eurace # Description The data publication contains all resources (data, code and statistical output) required to reproduce the results presented in "How to accelerate green technology diffusion? An agent-based approach to directed technological change with coevolving absorptive capacity" (Hötte 2019). Objective of this publication is the transparency, reproducibility and reusability of the simulation model and statistical analysis. The publication is composed of four directories: (1) The directory "model" allows the reader to understand the implementation of the simulation model (C-code), to reproduce the simulated data and to use the model for further studies. A conceptual description and technical documentation of the model is provided in the paper mentioned above. (2) The directory "experiment_directories_and_data" contains the simulated data that is presented and discussed in the paper. This data allows to reproduce exactly the statistical analyses presented in the paper and to check the general validity of the model. (3) The directory "rcode" contains the code that was used for the statistical analyses and makes the methods transparent for the reader. (4) The directory "results" contains the output files of the statistical analyses, e.g. plots and txt-output files documenting the regression analyses. Each directory contains a readme file with additional information about the content and instructions how to use it. ## Details on content of each subdirectory: ### (1) model: Simulation inputs The data provided should allow you to REPRODUCE the simulations, i.e. to produce your own simulation data that should exhibit the same patterns as those discussed in the paper. Before trying to run the model, I strongly recommend to check out the introductory and explanatory material provided by the developers of the original model: http://www.wiwi.uni-bielefeld.de/lehrbereiche/vwl/etace/Eurace_Unibi/ #### File content: - model files: model xml files and c code Extensions compared to "standard eurace@unibi": (Here only main modifications highlighted) - Cons_Goods_UNIBI: Production routine and investment decision modified. - Government_GREQAM: Eco policy module added. - Inv_Goods_Vintage: Adaptive pricing mechanism and endogenous innovation added/ modified. - Labour_UNIBI: Households skill endowment and learning. - Statistical_Office_UNIBI: Documentation of indicator variables. - my_library_functions.c: Running order of vintages adjusted by using costs. - its: initial population #### Acknowledgement: This model is a modified version of the Eurace@Unibi model, developed by Herbert Dawid, Simon Gemkow, Philipp Harting, Sander van der Hoog and Michael Neugart, as an extension of the research within the EU 6 th Framework Project Eurace. ### (2) experiment_directories_and_data: Simulated data (raw). This data allows you to perform STATISTICAL ANALYSES with the simulation output yourself. You may use these as input to the Rcode. Experiment folders contain simulation files and simulation output: - baseline - rand_barr - rand_pol34_fix_barr5 - rand_pol34_rand_barr15 In principle, you should be able to reproduce the simulated data with the code provided in "model" (Note that the model has stochastic components, hence it will not be EXACTLY the same but sufficiently similar). ### (3) rcode: This documentation makes the STATISTICAL METHODS used in the paper transparent. Sorry for the inefficient code. Check whether updates are available. - rcode: R scripts used for statistical analysis of simulation output ### (4) results: Output of analysed data. Here you find the output of the statistical analyses, i.e. regression output and wilcoxon test results in txt format and plots that are used in the paper. These files can be reproduced by the R code. The results are documented experimentwise, i.e. baseline, barrier strength, policy with fix barriers, policy with random barriers. #### Acknowledgement Particular gratitude is owed to Cord Wiljes for extensive support accompanying this data publication

Data publication for: Skill transferability and the adoption of new technology

Hötte K. Data publication for: Skill transferability and the adoption of new technology. Bielefeld University; 2019.This data publication contains all material used in Hötte, K., 2019, "Skill transferability and the adoption of new technology: A learning based explanation for patterns of diffusion". It is composed of (1) the simulation model are required inputs to reproduce the results, (2) simulated data presented in the article, (3) R-scripts that were used for the statistical analyses, (4) selected results and graphics that are partly used in the article and partly supplementary. Please check for software updates (concerning the model and [R code](https://gitlab.ub.uni-bielefeld.de/khoette/rcode_eurace)) on gitlab. If you are only interested in the programming code, I recommend to check out gitlab first because this data publication consumes a lot of disk-space due to the large amount of simulated data (~16Gb). If you have questions, do not hesitate to send me an email: kerstin.hoette[at]uni-bielefeld.de ### Background: Abstract of the underlying research paper Technological capabilities are decisive to make effectively use of new machinery and capital goods. Firms and employees accumulate these capabilities when working with specific machinery. Radical innovation differs by technology type and pre-existing capabilities may be imperfectly transferable across types. In this paper, I address the implications of cross-technology transferability of capabilities for firm-level technology adoption and macroeconomic directed technological change. I propose a microeconomically founded model of technological learning that is based on empirical and theoretical insights of the innovation literature. In a simulation study using the ABM Eurace@unibi-eco and applied to the context of green technology diffusion, it is shown that a high transferability of knowledge has ambiguous effects. It accelerates the diffusion process initially, but comes of the cost of technological stability and specialization. For firms, it is easy to adopt, but also easy to switch back to the conventional technology type. It is shown how different types of policies can be used to stabilize the diffusion process. The framework of analysis is used to derive a general characterization of technologies that may provide guidance for future empirical analyses. ### More detailed overview of the content: See also readme files in the subfolders. #### model: Simulation inputs The data provided should allow you to REPRODUCE the simulations, i.e. to produce your own simulation data that should exhibit the same patterns as those discussed in the paper. - model files: model xml files and c code Extensions compared to "standard eurace@unibi": (Here only main modifications highlighted) - Cons_Goods_UNIBI: Production routine and investment decision modified. - Government_GREQAM: Eco policy module added. - Inv_Goods_Vintage: Adaptive pricing mechanism and endogenous innovation added/ modified. - Labour_UNIBI: Households skill endowment and learning. - Statistical_Office_UNIBI: Documentation of indicator variables. - my_library_functions.c: Running order of vintages adjusted by using costs. - its: initial population #### experiment_directories_and_data: Simulated data (raw). This data allows you to perform STATISTICAL ANALYSES with the simulation output yourself. You may use these as input to the Rcode. Experiment folders contain simulation files and simulation output - baseline -> With intermediate techn. difficulty and distance - difficulty -> 3 discrete levels of chi^{dist} - distance -> 3 discrete levels of chi^{int} monte_carlo_exp: - both_learning_at_random_3_barr -> Monte Carlo analysis (MC) with fix barrier and randomly drawn learning parameters - both_learning_at_random_random_barr -> MC with random learning and random barrier at max 10 pct, serves as policy baseline - rand_learn_rand_pol_rand_barr10 -> Policy experiment In principle, you should be able to reproduce the simulated data (Note that the model has stochastic components, hence it will not be EXACTLY the same but sufficiently similar). #### rcode: This documentation makes the STATISTICAL METHODS used in the paper transparent. Sorry for the inefficient code. - rcode: R scripts used for statistical analysis of simulation output #### selected_results Output of analysed data and additional time series plots. Here, you find additional time series that are not presented in the main article, some descriptive statistics and the ouput of statistical tests and analyses, i.e. regression output and wilcoxon test results in txt format and plots that are used in the paper. These files can be reproduced by the R code. ### Acknowledgements The author gratefully acknowledges the achievements and provision of free statistical software maintained by the R programming community. This work uses a modified version of the Eurace@Unibi model, developed by Herbert Dawid, Simon Gemkow, Philipp Harting, Sander van der Hoog and Michael Neugart, as an extension of the research within the EU 6th Framework Project Eurace. Particular gratitude is owed to Herbert Dawid for uncomplicated and efficient support. Further, many thanks to the center for research data for support and the provision of excellent infrastructure. Particular thanks to Cord Wiljes

Skill transferability and the stability of transition pathways. A learning-based explanation for patterns of diffusion

Hötte K. Skill transferability and the stability of transition pathways. A learning-based explanation for patterns of diffusion. Universität Bielefeld Working Papers in Economics and Management. Vol 09-2019. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2019.Technological know-how is necessary to make effectively use of new machinery and capital goods. Firms and employees accumulate technology-specific knowledge when working with specific machinery. Radical innovation differs by technology type and pre-existing knowledge may be imperfectly transferable across types. In this paper, I address the implications of cross-technology transferability of skills for firm-level technology adoption and its consequences for the direction of macroeconomic technological change. I propose a microeconomically founded model of technological learning that is based on empirical and theoretical insights of the innovation literature. In a simulation study using the macroeconomic ABM Eurace@unibi-eco and applied to the context of green technology diffusion, it is shown that a high transferability of knowledge has ambiguous effects. It accelerates the diffusion process initially, but comes of the cost of technological stability and specialization in the long run. For firms, it is easy to adopt, but also easy to switch back to the conventional technology type. It is shown how different types of policies can be used to stabilize a technological transition pathway. The findings are summarized in a general taxonomic framework to characterize technologies. It represents a bottom-up approach to the study of technology transitions