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Scientific and technological innovations have become increasingly important as we face the benefits and challenges of both globalization and a knowledge-based economy. Still, enrolment rates in STEM degrees are low in many European countries and consequently there is a lack of adequately educated workforce in industries. We believe that this can be mainly attributed to pedagogical issues, such as the lack of engaging hands-on activities utilized for science and math education in middle and high schools. In this paper, we report our work in the SciChallenge European project, which aims at increasing the interest of pre-university students in STEM disciplines, through its distinguishing feature, the systematic use of social media for providing and evaluation of the student-generated content. A social media-aware contest and platform were thus developed and tested in a pan-European contest that attracted $> {{700}}$ participants. The statistical analysis and results revealed that the platform and contest positively influenced participants STEM learning and motivation, while only the gender factor for the younger study group appeared to affect the outcomes (confidence level – ${\text{p}} ).

Purpose Methods and Materials Results Conclusion References Personal Information, Purpose: to evaluate qualitative and quantitative parameters of patients with medication-related osteonecrosis of the jaw (MRONJ) in ultra-short echo time (UTE) MRI and cone beam computed tomography...

In this paper, we use a Bayesian global vector autoregressive model to analyze the macroeconomic effects of a flattening of euro area yield curves. Our findings indicate positive effects on real activity and prices, both within the euro area as well as in neighboring economies. Spillovers transmit through an exchange rate channel and a broad financial channel. We complement our analysis by conducting a portfolio optimization exercise. Our results show that multi-step-ahead forecasts conditional on the euro area yield curve shock improve Sharpe ratios relative to other investment strategies.

The paper develops a global vector autoregressive model with time varying parameters and stochastic volatility to analyse whether international spillovers of US monetary policy have changed over time. The model proposed enables us to assess whether coefficients evolve gradually over time or are better characterized by infrequent, but large, breaks. Our findings point towards pronounced changes in the international transmission of US monetary policy throughout the sample period, especially so for the reaction of international output, equity prices and exchange rates against the US dollar. In general, the strength of spillovers has weakened in the aftermath of the global financial crisis. Using simple panel regressions, we link the variation in international responses to measures of trade and financial globalization. We find that a broad trade base and a high degree of financial integration with the world economy tend to cushion risks stemming from a foreign shock such as US tightening of monetary policy, whereas a reduction in trade barriers and/or a liberalization of the capital account increase these risks. (VLID)3406960

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable uncertainty. Sparsification has the potential to remove this uncertainty and improve forecasts. In this paper, we develop computationally simple methods which both shrink and sparsify TVP models. In a simulated data exercise we show the benefits of our shrink-then-sparsify approach in a variety of sparse and dense TVP regressions. In a macroeconomic forecast exercise, we find our approach to substantially improve forecast performance relative to shrinkage alone.

This paper uses a factor-augmented vector autoregressive model to examine the impact of monetary policy shocks on housing prices across metropolitan and micropolitan regions. To simultaneously estimate the model parameters and unobserved factors we rely on Bayesian estimation and inference. Policy shocks are identified using high-frequency suprises around policy announcements as an external instrument. Impulse reponse functions reveal differences in regional housing price responses, which in some cases are substantial. The heterogeneity in policy responses is found to be significantly related to local regulatory environments and housing supply elasticities. Moreover, housing prices responses tend to be similar within states and adjacent regions in neighboring states., Series: Working Papers in Regional Science

Das interdisziplinäre Projektteam „Arbeitsfeld Tourismus-Integrativ“ (ArTiv) der Hochschule Luzern erstellte, mit Hilfe von Interviews mit Expertinnen, Experten und betroffenen Personen, eine Webpräsenz (www.tourismus-mitenand.ch). Das Ziel dieser Webpräsenz ist es, die Öffentlichkeit mit spezifischen Informationen sowie Videobeiträgen, für die Arbeitsintegration von Menschen mit körperlicher, psychischer oder kognitiver Beeinträchtigung in der Tourismusbranche, zu sensibilisieren. Zudem soll die Webpräsenz möglichst barrierefrei gestaltet sein, um auch für Menschen mit Einschränkungen angenehm bedienbar zu sein. Dieser Projektbericht bezieht sich auf die Evaluation der Webpräsenz. Hierbei soll, vor der Lancierung, überprüft werden, ob das Intendierte erreicht wird. Dies wird durch zwei unterschiedliche Arten der Informationsgewinnung erreicht. Zum einen durch eine Online- Umfrage für Fachkräfte sowie Arbeitgebende und zum Anderen durch die gemeinsame Nutzung der Plattform mit beeinträchtigten Menschen. Die Auswertung der Ergebnisse erfolgt nach Wolfgang Beywl sowie Horst Otto Mayer. Das Ziel dieser Evaluation ist es, dem ArTiv Projektteam eine Zusammenfassung der Veränderungsmöglichkeiten zukommen zu lassen. Diese werden dann, nach Möglichkeit, in die finale Gestaltung der Webpräsenz mit einfliessen. Zudem werden die Ergebnisse in diesem Bericht dokumentiert und Schlussfolgerungen sowie Perspektiven aufgezeigt., + Code Diss LU: hslusa pasa be + Fussnote: Projekt-Arbeit, Hochschule Luzern - Soziale Arbeit, Studienrichtung Sozialarbeit + NL-Code: NLLUHSA201811

In this paper, we provide a parsimonious means of estimating panel VARs with stochastic volatility. We assume that coefficients associated with domestic lagged endogenous variables arise from a finite mixture of Gaussian distribution. Shrinkage on the cluster size is introduced through suitable priors on the component weights and cluster-relevant quantities are identified through novel normal-gamma shrinkage priors. To assess whether dynamic interdependencies between units are needed, we moreover impose shrinkage priors on the coefficients related to other countries' endogenous variables. Finally, our model controls for static interdependencies by assuming that the reduced form shocks of the model feature a factor stochastic volatility structure. We assess the merits of the proposed approach by using synthetic data as well as a real data application. In the empirical application, we forecast Eurozone unemployment rates and show that our proposed approach works well in terms of predictions., Series: Department of Economics Working Paper Series

We develop a multivariate dynamic factor model that exploits euro area country-specific information on output and inflation for estimating an area-wide measure of the output gap. In the proposed multi-country framework we moreover allow for flexible stochastic volatility (SV) specifications for both the error variances and the innovations to the latent quantities in order to deal with potential changes in the commonalities of business cycle movements. By tracing the relative importance of the common euro area output gap component as a means to explaining movements in both output and inflation over time, the paper provides valuable insights in the evolution of the degree of synchronicity of the country-specific business cycles. In an out-of-sample forecasting exercise, the paper shows that the proposed approach performs well as compared to other well-known benchmark specifications.

We assess the relationship between model size and complexity in the time-varying parameter VAR framework via thorough predictive exercises for the Euro Area, the United Kingdom and the United States. It turns out that sophisticated dynamics through drifting coefficients are important in small data sets while simpler models tend to perform better in sizeable data sets. To combine best of both worlds, novel shrinkage priors help to mitigate the curse of dimensionality, resulting in competitive forecasts for all scenarios considered. Furthermore, we discuss dynamic model selection to improve upon the best performing individual model for each point in time., Series: Department of Economics Working Paper Series

In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian non-linear time series framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with their evolution being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at the home and foreign country. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time and a model approach that takes this empirical evidence seriously yields improvements in accuracy of density forecasts for most currency pairs considered., Series: Department of Economics Working Paper Series

The aim of this work is to investigate the β-Ti-phase-stabilizing effect of vanadium and iron added to Ti-6Al-4V powder by means of heterogeneous powder mixtures and in situ alloy-formation during laser powder bed fusion (L-PBF). The resulting microstructure was analyzed by metallographic methods, scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD). The mechanical properties were characterized by compression tests, both prior to and after heat-treating. Energy dispersive X-ray spectroscopy showed a homogeneous element distribution, proving the feasibility of in situ alloying by LPBF. Due to the β-phase-stabilizing effect of V and Fe added to Ti-6Al-4V, instead of an α’-martensitic microstructure, an α/β-microstructure containing at least 63.8% β-phase develops. Depending on the post L-PBF heat-treatment, either an increased upsetting at failure (33.9%) compared to unmodified Ti-6Al-4V (28.8%), or an exceptional high compressive yield strength (1857 ± 35 MPa compared to 1100 MPa) were measured. The hardness of the in situ alloyed material ranges from 336 ± 7 HV0.5, in as-built condition, to 543 ± 13 HV0.5 after precipitation-hardening. Hence, the range of achievable mechanical properties in dependence of the post-L-PBF heat-treatment can be significantly expanded in comparison to unmodified Ti-6Al-4V, thus providing increased flexibility for additive manufacturing of titanium parts.

Bei der M��llverbrennung fallen ca. 3 % des Abfallinputs als Flugasche an. Diese stellt einen gef��hrlichen Abfall dar und muss dementsprechend entsorgt werden. Da die derzeitigen Behandlungsbzw. Entsorgungsoptionen f��r diese Flugaschen alle mit verschiedenen Nachteilen verbunden sind, ist es das Ziel dieser Dissertation ein neues Verfahren zu entwickeln und dessen Umweltauswirkungen und Kosten mit dem Stand der Technik zu vergleichen. Das entwickelte Verfahren beinhaltet die thermische Behandlung von M��llverbrennungsflugasche zusammen mit brennbaren Abf��llen in bereits bestehenden M��llverbrennungsanlagen (MVA). In einem Versuch im Gro��ma��stab wurden in einem Zeitraum von 102 h bis zu 300 kg befeuchtete MVA-Flugasche pro Mg brennbare Abf��lle in einer MVA mit Drehrohrofen behandelt (Paper I). Die Ergebnisse der Analyse zeigten, dass die eingebrachte Flugasche nahezu vollst��ndig in die Drehrohrofenschlacke eingebunden wurde, wobei diese Schlacke weiterhin einen nicht-gef��hrlichen Abfall darstellte. Die Befeuchtung der Flugasche verhinderte erfolgreich die Emission von Staub w��hrend des Transports und der Lagerung. Allerdings verursachten Hydratationsreaktionen im befeuchteten Material einen Temperaturanstieg und die Bildung von Klumpen aus erh��rteter Flugasche im M��llbunker, die beide den kontinuierlichen und sicheren Betrieb der Anlage beeintr��chtigen. Als m��gliche L��sung f��r dieses Problem wurde die Aufbauagglomeration als Vorbehandlung untersucht. Ungef��hr 400 kg Flugaschepellets wurden hergestellt und in einem elektrisch beheizten Drehrohrofen im Pilotma��stab bei verschiedenen Temperaturen und Winkel behandelt (Paper II). Diese Versuche zeigten, dass sich MVA-Flugasche sehr gut f��r die Pelletierung eignet und die mechanischen Eigenschaften der so hergestellten Pellets eine weitere Verarbeitung erlauben. Eine thermische Behandlung bei 450 C f��r 10 min war bereits ausreichend um ein nicht-gef��hrliches Material zu erzeugen. Die Umweltauswirkungen der thermischen Behandlung von MVA-Flugasche zusammen mit brennbaren Abf��llen wurden mittels ��kobilanz bestimmt (Paper III). Insgesamt wurden sieben Szenarien f��r die Behandlung und Entsorgung von MVA-Flugasche erstellt und modelliert, wobei einige davon auch die Verwertung von Flugasche enthalten. Die Ergebnisse der ��kobilanz zeigten, dass die thermische Behandlung zusammen mit brennbaren Abf��llen mit niedrigeren Umweltauswirkungen als die Stabilisierung mit Zement verbunden ist. Das Szenario mit den niedrigsten Umweltauswirkungen ist jedoch f��r beide Betrachtungszeitr��ume die R��ckgewinnung von Metallen mittels W��sche mit saurem W��scherwasser. Da die Ergebnisse der ��kobilanz zeigten, dass die R��ckgewinnung von Ressourcen aus MVAFlugasche eine Option mit geringen Umweltauswirkungen ist, wurde eine Ressourcenklassifizierung nach der United Nations Framework Classification for Resources (UNFC) f��r MVA-Flugasche durchgef��hrt (Paper IV). Dazu wurde eine wirtschaftliche Bewertung aller Szenarien, die eine Rohstoffr��ckgewinnung enthalten, durchgef��hrt. Neben Investitionsund Betriebskosten wurden auch Umweltauswirkungen monetarisiert, um eine Beurteilung aus einer Makround Mikroperspektive durchzuf��hren. Die Ergebnisse dieser Analysen zeigten, dass die Verwertung von MVA-Flugasche in der Zementherstellung sowohl aus Mikroals auch aus Makroperspektive als kommerzielles Projekt aus beiden Perspektiven klassifiziert werden kann, w��hrend die Metallr��ckgewinnung nur aus der Makroperspektive ein kommerzielles Projekt darstellt. Schlagw��rter: Flugasche, Verbrennungsr��ckst��nde, M��llverbrennung, thermische Behandlung, ��kobilanz, Ressourcenklassifizierung, About 3 % of the waste input into a waste incineration plant arise as fly ash, which constitutes a hazardous waste and has to be disposed of accordingly. As the current municipal solid waste incineration (MSWI) fly ash management options are all associated with various disadvantages, this thesis aims at developing a novel fly ash treatment process and comparing its environmental and economic performance with other options known in the state of the art. The developed process comprises thermal treatment of MSWI fly ash together with combustible waste in existing MSWI plants. In a large-scale experiment, up to 300 kg moistened fly ash per Mg of combustible waste were treated in a rotary kiln hazardous waste incinerator for 102 h (Paper I). The inserted MSWI fly ash as well as bottom ash, fly ash and scrubber water from the rotary kiln were sampled and chemically analysed. The results from this analysis revealed that MSWI fly ash was almost completely transferred to the rotary kiln bottom ash, which, however, still constituted a nonhazardous waste. The moistening of fly ash effectively prevented dust emissions during transport and storage. However, hydration reactions in the moistened material caused a temperature increase and formation of lumps of hardened fly ash in the waste bunker, which both impair the continuous and safe operation of the incinerator. As a possible solution to this problem, agglomeration was investigated as pretreatment prior to insertion in the waste bunker. About 400 kg of pelletised MSWI fly ash were produced and treated in a pilot-scale electrically heated rotary kiln at different temperatures and angles (Paper II). These experiments showed that MSWI fly ash is well suitable for agglomeration and the mechanical properties of the pellets produced allow their further processing. Thermal treatment at 450 C for 10 min was already sufficient to generate a non-hazardous material, but treatment at higher temperatures leads to higher volatilisation of heavy metals. The environmental impact of thermal treatment of MSWI fly ash together with combustible waste was determined by life cycle assessment (LCA) (Paper III). Seven scenarios for the treatment and disposal of MSWI fly ash, some of them comprising recycling processes, were established and modelled within an LCA framework. The LCA results showed that thermal treatment together with combustible waste has a lower environmental impact than stabilisation with cement. The scenario with the lowest impact is the recovery of metals by washing with acidic scrubber water. As the results from LCA showed that resource recovery from MSWI fly ash has a low environmental impact, resource classification according to the United Nations Framework Classification for Resources (UNFC) was applied on MSWI fly ash (Paper IV). Thereby, an economic assessment of all scenarios comprising resource recovery was conducted. Monetary valuation of the LCA results was applied to subsequently combine the results from economic and environmental assessment and determine the resource potential from a public entitys macro perspective whereas the private investors micro perspective includes only the results from the economic assessment. Cement production could be classified as commercial project from both perspectives, while metal recovery constitutes a commercial project from the macro perspective only. Keywords: fly ash, combustion residue, waste incineration, thermal treatment, life cycle assessment, resource classification

In this paper we forecast daily returns of cryptocurrencies using a wide variety of different econometric models. To capture salient features commonly observed in financial time series like rapid changes in the conditional variance, nonnormality of the measurement errors and sharply increasing trends, we develop a timevarying parameter VAR with tdistributed measurement errors and stochastic volatility. To control for overparametrization, we rely on the Bayesian literature on shrinkage priors, which enables us to shrink coefficients associated with irrelevant predictors and/or perform model specification in a flexible manner. Using around one year of daily data, we perform a realtime forecasting exercise and investigate whether any of the proposed models is able to outperform the naive random walk benchmark. To assess the economic relevance of the forecasting gains produced by the proposed models we, moreover, run a simple trading exercise. (VLID)3669986

We propose a straightforward algorithm to estimate large Bayesian time-varying parameter vector autoregressions with mixture innovation components for each coefficient in the system. The computational burden becomes manageable by approximating the mixture indicators driving the time-variation in the coefficients with a latent threshold process that depends on the absolute size of the shocks. Two applications illustrate the merits of our approach. First, we forecast the US term structure of interest rates and demonstrate forecast gains relative to benchmark models. Second, we apply our approach to US macroeconomic data and find significant evidence for time-varying effects of a monetary policy tightening.

We propose a dynamic factor model with time-varying parameters and stochastic volatility to analyze the relationship between global factors and country-specific capital flow dynamics. Studying a global sample of 43 countries from 1994 until 2015, we show that global co-movement of macroeconomic, financial and capital flow variables can explain a major share of country-specific capital flow volatility and that the impact of these variables has become even more important since the 2008-2009 global financial crisis. Our results indicate that country-specific changes in capital flows are strongly affected by fluctuations in global financial cycles and - to some extent - by global real business cycles. There is some evidence that countries with higher foreign exchange reserves, flexible exchange rates, lower public indebtedness or more developed domestic stock markets may better shield themselves from the global financial cycle.

In this paper, we explore the relationship between state-level household income inequality and macroeconomic uncertainty in the United States. Using a novel large-scale macroeconometric model, we shed light on regional disparities of inequality responses to a national uncertainty shock. The results suggest that income inequality decreases in most states, with a pronounced degree of heterogeneity in terms of shapes and magnitudes of the dynamic responses. By contrast, some few states, mostly located in the West and South census region, display increasing levels of income inequality over time. We find that this directional pattern in responses is mainly driven by the income composition and labor market fundamentals. In addition, forecast error variance decompositions allow for a quantitative assessment of the importance of uncertainty shocks in explaining income inequality. The findings highlight that volatility shocks account for a considerable fraction of forecast error variance for most states considered. Finally, a regression-based analysis sheds light on the driving forces behind differences in state-specific inequality responses., Series: Working Papers in Regional Science

This paper proposes a hierarchical modeling approach to perform stochastic model specification in Markov switching vector error correction models. We assume that a common distribution gives rise to the regime-specific regression coefficients. The mean as well as the variances of this distribution are treated as fully stochastic and suitable shrinkage priors are used. These shrinkage priors enable to assess which coefficients differ across regimes in a flexible manner. In the case of similar coefficients, our model pushes the respective regions of the parameter space towards the common distribution. This allows for selecting a parsimonious model while still maintaining sufficient flexibility to control for sudden shifts in the parameters, if necessary. In the empirical application, we apply our modeling approach to Euro area data and assume that transition probabilities between expansion and recession regimes are driven by the cointegration errors. Our findings suggest that lagged cointegration errors have predictive power for regime shifts and these movements between business cycle stages are mostly driven by differences in error variances.

In this study interest centers on regional differences in the response of housing prices to monetary policy shocks in the US. We address this issue by analyzing monthly home price data for metropolitan regions using a factor-augmented vector autoregression (FAVAR) model. Bayesian model estimation is based on Gibbs sampling with Normal-Gamma shrinkage priors for the autoregressive coefficients and factor loadings, while monetary policy shocks are identified using high-frequency surprises around policy announcements as external instruments. The empirical results indicate that monetary policy actions typically have sizeable and significant positive effects on regional housing prices, revealing differences in magnitude and duration. The largest effects are observed in regions located in states on both the East and West Coasts, notably California, Arizona and Florida., Series: Working Papers in Regional Science

This paper develops a global vector autoregressive (GVAR) model with time-varying parameters and stochastic volatility to analyze whether international spillovers of US monetary policy have changed over time. The proposed model allows assessing whether coefficients evolve gradually over time or are better characterized by infrequent, but large breaks. Our findings point towards pronounced changes in the international transmission of US monetary policy throughout the sample period, especially so for the reaction of international output, equity prices, and exchange rates against the US dollar. In general, the strength of spillovers has weakened in the aftermath of the global financial crisis. Using simple panel regressions, we link the variation in international responses to measures of trade and financial globalization. We find that a broad trade base and a high degree of financial integration with the world economy tend to cushion risks stemming from a foreign shock such as a US monetary policy tightening, whereas a reduction in trade barriers and/or a liberalization of the capital account increase these risks.