Made in China: Export competition and structural changes in the OECD countries

This paper assesses the existence and extent of transition cost for the OECD economies associated with the increasing Chinese competition in the export markets. We find that intensified Chinese competition is an important factor in explaining structural changes not only within the manufacturing sector but also of the economies as a whole. In our empirical analysis which is guided by a simple extension of the Melitz Model we employ panel data at multiple levels of aggregation. The data reveal considerable adverse effects on export volume and industry-specific output in OECD countries as a result of increased Chinese competition. These distortions originating from the export market also affect structural variables within the manufacturing industries. Even at a regional level, changes in socioeconomic indicators can be associated NEWLINE with intensified Chinese export competition. Within the framework of our NEWLINE theoretical model, the mechanisms behind these observations are the following: The increased Chinese competition leads to a decline in exports and overall output, implying a decrease in average productivity and wages. This induces the reallocation of labor to the low-wage service sector, which in turn results in a reduction of average household income

Sensorless Position Control of Piezoelectric Ultrasonic Motors:a Mechatronic Design Approach

This dissertation considers mechatronic systems driven by piezoelectric ultrasonic motors (PUM). The focus is set on optimal system design and sensorless position control. Mechatronic industry faces the challenge to deliver ever more efficient and reliable products while being confronted to increasingly short time to market demands and economic constraints driven by competition. Although optimal design strategies are applied to master this challenge, they do not entirely respond to the given circumstances, as often only local criteria are optimised. In order to obtain a globally optimal solution, the many subfunctions of a mechatronic system and their models must be interrelated and evaluated concurrently from the very beginning of the design process. In this context PUM have been used increasingly during the last decade for various positioning applications in the field of mechatronic systems, laboratory equipment, and consumer electronics where their performances are superior to conventional electromechanical drive systems based on DC or BLDC motors. The position of the mobile component must be controlled. In some cases open-loop control is a solution, but more often than not sensors are used as feedback device in closed-loop control. Sensors are expensive, large in size and add fragile hardware to the device that compromises its reliability. Thus, not only the superior performance is not fully exploited but also the economical feasibility of the PUM drive system is jeopardised. Replacing sensors by advanced control techniques is an approach to these problems that is well established in the field of BLDC motors. Those sensorless control strategies are not directly transferrable, because of the fundamentally different working principles of PUM. Hence, the research of sensorless closed-loop position control techniques applicable to PUM and their validation with digitally controlled functional models is the very topic of this thesis. We propose a dedicated design methodology to this statement of the problem. A core model of the mechatronic system is conceived as general and simple as possible. It then develops for the different interrelated views reflecting the mechanical, electromechanical, drive electronic, sensorial and digital control functions of the global system. Each one becoming more specific and detailed in this process, the different views still enable mutual constraint adjustments and the dynamic integration of results from the other views during the design process. Starting with the stator of the PUM, a view describes the mechanical displacement. An electric equivalent model is written such that power input from the drive electronics is related to the mechanical energy transmitted to the mechanics. The resulting differential equations are solved by the finite element method (FEM). Position feedback configurations in the mobile part of the PUM are modelled analytically in order to be implemented in digital control and their electrical implications are updated to the stator model. In this way, sensors do not necessarily materialise physically any more, but are distributed among the mechanical configuration, the drive electronics and the digital controller. With respect to the sensor data, the controller is not simply receiving finalised data on the measured system parameter, but rather implements the sensor itself in software. Finally, the position detection performance obtained with the aforementioned design methodology was evaluated with the example of mechatronic locking devices actuated by custom-made as well as OEM motors. Functional models of motors, electronics and digital controllers were used to identify the limits of the proposed methods, and suggestions for further research were deduced. These results contribute to the development of robust sensorless position controllers for PUM

Economic Shocks in the Fisheries Sector and Maritime Piracy

For a panel of 109 coastal countries we show that negative economic shocks in the fisheries sector are associated with an increase in maritime piracy. Our identification strategy uses the variation in the phytoplankton abundance off the individual countries' coasts, measured by satellite data, as a source of such shocks. We find that plankton abundance is positively related to fish catches but negatively associated with the incidence of piracy, onset and the absolute number of pirate attacks. Our instrumental variable estimates indicate that a one percent increase in fish catches reduces the risk of piracy occurring by one percentage point

Chinese Export Competition, Declining Exports and Adjustments at the Industry and Regional Level in Europe

We analyze how a set of 22 European countries are affected by increased Chinese export competition between 1995 and 2008. Employing product level data, we document a reduction in the export volume of European countries due to increased Chinese export competition. This alteration in the export sector induces changes within the manufacturing industries, especially a decline in employment. The analysis using more aggregated, regional level data, shows that the industry sector as whole declines resulting, amongst others, in an increased unemployment rate. The importance of Chinese export competition for Europe is attributable to its high export intensity

Chinese Export Competition, Declining Exports and Adjustments at the Industry and Regional Level in Europe

We analyze how a set of 22 European countries are affected by increased Chinese export competition between 1995 and 2008. Employing product level data, we document a reduction in the export volume of European countries due to increased Chinese export competition. This alteration in the export sector induces changes within the manufacturing industries, especially a decline in employment. The analysis using more aggregated, regional level data, shows that the industry sector as whole declines resulting, amongst others, in an increased unemployment rate. The importance of Chinese export competition for Europe is attributable to its high export intensity

How resilient are former CBT patients with generalized anxiety disorder in times of COVID-19? A follow-up study considering post-treatment depressive symptoms

Background: Research suggested that preexisting mental disorders, particularly generalized anxiety disorder (GAD), might increase the already elevated risk of responding to the COVID-19 pandemic with mental health impairments. The present follow-up study investigated the course of GAD symptoms during the pandemic in former outpatients (N = 86) of two randomized controlled trials who were treated with cognitive behavioral therapy (CBT) up to eight years ago. Methods: GAD symptomatology was examined as the probability for a “well month”, that is, a month with no or minimal symptoms, as assessed by the Longitudinal Interval Follow-Up Evaluation (LIFE), taking the periods pre-pandemic, early pandemic, lockdown, and post-lockdown into account, and considering depressive symptoms post-treatment as its predictor. Results: Generalized linear mixed models revealed lower odds ratios for a “well month” during the early pandemic period and higher odds ratios post-lockdown compared with pre-pandemic. Post-treatment depressive symptoms proved to be a significant predictor since pandemic onset. Strategies learned in CBT were analyzed for their applicability and helpfulness in coping with worries during the pandemic. Six particularly helpful strategies were identified by participants. Limitations: Although attrition was comparably low with no indication of an association between missingness and primary outcomes, bias cannot be ruled out. Conclusions: The findings provide preliminary support for the resilience of former CBT patients with GAD during COVID-19, for the long-term relevance of CBT strategies, and for post-treatment depressive symptoms as risk factors for exacerbation of GAD symptoms since the onset of the COVID-19 pandemic

Sensorless Speed Control of Traveling Wave Ultrasonic Motor

Ultrasonic motors are a good alternative to electromagnetic motors in medical robotics, since they are electromagnetically compatible. Estimating speed instead of using encoders reduces cost and dimension of the robot on the one hand and increases reliability on the other hand. However, no sensorless speed controller is yet industrialized. Analytical models of the traveling wave ultrasonic motor being too complex to be exploited for sensorless control purpose, we suggest speed estimation based on artificial neural networks. The artificial neural network is designed based on a sensitivity analysis using design of experiments methods. Factorial designs have been chosen to find out the effects of each input factor, but also the effect of their interactions. First results show that speed estimation using artificial neural networks is a promising approach. The artificial neural network optimized with design of experiments methods is a valid model of the traveling wave ultrasonic motor to estimate speed