A5075138244- Monetary Policy and Economic Impact
- German Economic Analysis & Policies
- Muscle activation and electromyography studies
- Economic Policies and Impacts
- Prosthetics and Rehabilitation Robotics
- Robotic Locomotion and Control
- Financial Risk and Volatility Modeling
- Balance, Gait, and Falls Prevention
- Social and Demographic Issues in Germany
- European Monetary and Fiscal Policies
- Motor Control and Adaptation
- Forecasting Techniques and Applications
- Statistical Methods and Inference
- Italy: Economic History and Contemporary Issues
- Nanoparticles: synthesis and applications
- Public Administration and Political Analysis
- Complex Systems and Time Series Analysis
- Global Financial Crisis and Policies
- Manufacturing Process and Optimization
- Robot Manipulation and Learning
- Sociology and Education Studies
- European Socioeconomic and Political Studies
- Fiscal Policy and Economic Growth
- Economic and Social Issues
- Market Dynamics and Volatility
Technical University of Darmstadt
2017-2024
École Polytechnique Fédérale de Lausanne
2023
Merck (Germany)
2023
German Insurance Association
2019
Deutsche Bundesbank
2004-2016
Martin Marietta Materials (United States)
1980
British Steel (United Kingdom)
1979
In this article, we merge two strands from the recent econometric literature. First, factor models based on large sets of macroeconomic variables for forecasting, which have generally proven useful forecasting. However, there is some disagreement in literature as to appropriate method. Second, forecast methods mixed-frequency data sampling (MIDAS). This regression technique can take into account unbalanced datasets that emerge publication lags high- and low-frequency indicators, a problem...
Summary Mixed data sampling (MIDAS) regressions allow us to estimate dynamic equations that explain a low frequency variable by high variables and their lags. When the difference in frequencies between regressand regressors is large, distributed lag functions are typically employed model dynamics avoiding parameter proliferation. In macroeconomic applications, however, differences often small. such case, it might not be necessary employ functions. We discuss pros cons of unrestricted...
The recent devastating pandemic has drastically reminded humanity of the importance constant scientific and technological progress. A strong interdisciplinary dialogue between academic industrial scientists various specialties, entrepreneurs, managers public is paramount in triggering new breakthrough ideas which often emerge at interface disciplines. following sections, compiled by a highly diverse group authors, are summarizing recently achieved game-changing leaps science technology....
Abstract This paper discusses the forecasting performance of alternative factor models based on a large panel quarterly time series for German economy. One model extracts factors by static principal components analysis; second is dynamic obtained using frequency domain methods; third subspace algorithms state‐space models. Out‐of‐sample forecasts show that forecast errors are average smaller than simple autoregressive benchmark model. Among models, component and outperform in most cases...
SUMMARY This paper discusses pooling versus model selection for nowcasting with large datasets in the presence of uncertainty. In practice, a low‐frequency variable number high‐frequency indicators should account at least two data irregularities: (i) unbalanced missing observations end sample due to publication delays; and (ii) different sampling frequencies data. Two classes suited this context are factor models based on mixed‐data (MIDAS) regressions few predictors. The specification these...
Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in frequencies between regressand regressors is large, distributed lag functions are typically employed model dynamics avoiding parameter proliferation. In macroeconomic applications, however, differences often small. such case, it might not be necessary employ functions. this paper, we discuss pros cons of...
The project nanoGRAVUR (BMBF, 2015-2018) developed a framework for grouping of nanomaterials. Different groups may result each the three distinct perspectives occupational, consumer and environmental safety. properties, methods descriptors are harmonised between based on: Tier 1 intrinsic physico-chemical properties (what they are) or GHS classification non-nano-form (human tox, ecotox, physical hazards); 2 extrinsic release from nano-enabled products, in vitro assays with cells (where go;...
Adaptive motor control and seamless coordination of muscle actions in response to external perturbations are crucial maintaining balance during bipedal locomotion. There is an ongoing debate about the specific roles individual muscles underlying neural circuitry that humans employ maintain different perturbation scenarios. To advance our understanding human recovery, we conducted a study using portable Angular Momentum Perturbator (AMP). Unlike other push/pull systems, AMP can generate...
Abstract Balancing the upper body is pivotal for upright and efficient gait. While models have identified potentially useful characteristics of biarticular thigh muscles postural control body, experimental evidence their specific role lacking. Based on theoretical findings, we hypothesised that muscle activity would increase strongly in response to upper-body perturbations. To test this hypothesis, used a novel Angular Momentum Perturbator (AMP) that, contrast existing methods, perturbs...
<title>Abstract</title> Adaptive motor control and seamless coordination of muscle actions in response to external perturbations are crucial maintaining balance during bipedal locomotion. There is an ongoing debate about the specific roles individual muscles underlying neural circuitry that humans employ maintain different perturbation scenarios. To advance our understanding human recovery, we conducted a study using portable Angular Momentum Perturbator (AMP). Unlike other push/pull...
In human and animal motor control several sensory organs contribute to a network of pathways modulating the motion depending on task phase execution generate daily tasks such as locomotion. To better understand individual joint contribution reflex in locomotor tasks, we developed neuromuscular model that describes hopping movements. this model, consider influence proprioceptive length (LFB), velocity (VFB) force feedback (FFB) leg extensor muscle stability, performance efficiency (metabolic...
This paper compares different ways to estimate the current state of economy using factor models that can handle unbalanced datasets. Due release lags business cycle indicators, data unbalancedness often emerges at end multivariate samples, which is sometimes referred as 'ragged edge' data. Using a large monthly dataset German economy, we compare performance in presence ragged edge: static and dynamic principal components based on realigned data, Expectation-Maximisation (EM) algorithm Kalman...
In human locomotion, the complex structure of body is controlled such that conceptual models (e.g., spring-loaded-inverted-pendulum model) can describe significant features. This suggests interplay control and musculoskeletal systems projects into a low-dimensional space to perform different movements. Such simplification involve splitting task modular subproblems (locomotor subfunctions) be solved individually. Here, we asked how two locomotor subfunctions, namely stance balance, could...
Summary This paper discusses a large-scale factor model for the German economy, Following recent literature, data set of 121 time series is used to determine factors by principal component analysis. The enter linear dynamic GDP. To evaluate its empirical properties, compared with alternative univariate and multivariate models. These simpler models are based on regression techniques considerably smaller sets. Empirical forecast tests show that almost always encompasses rivals. Moreover,...
This paper compares two single-equation approaches from the recent nowcast literature: Mixed-data sampling (MIDAS) regressions and bridge equations. Both approach are used to a low-frequency variable such as quarterly GDP growth by higher-frequency business cycle indicators. Three differences between discussed: 1) MIDAS is direct multi-step nowcasting tool, whereas equations based on iterated forecasts; 2) employ empirical weighting of high-frequency predictor observations with functional...
This paper discusses a large-scale factor model for the German economy. Following recent literature, data set of 121 time series is used via principal component analysis to determine factors, which enter dynamic GDP. The compared with alternative univariate and multivariate models. These models are based on regression techniques considerably smaller sets. Out-of-sample forecasts show that prediction errors than rival However, these advantages not statistically significant, as test equal...
Abstract: The amputee’s well-being and mobility are distinclty related to socket fit resulting biomechanical interaction between residual limb prosthetic socket. Understanding the dynamic interactions at interface may lead new standards. This paper introduces a physically-motivated reduced model of interface, describing allows investigate sensitivity changes specific parameters in an isolated matter. A simulation study shows how stress distribution if friction coefficients varied which might...
This paper considers factor forecasting with national versus withinternational data. We forecast German GDP based on a large set of about 500 time series, consisting data as well from Euro-area and G7 countries. For estimation, we consider standard principal components variable preselection prior to estimation using targeted predictors following Bai Ng [Forecasting economic series predictors, Journal Econometrics 146 (2008), 304-317]. The results are follows: Forecasting without favours the...