Monetary Policy, Global Liquidity and Commodity Price Dynamics

This paper examines the interactions between money, interest rates, goods and commodity prices at a global level. For this purpose, we aggregate data for major OECD countries and follow the Johansen/Juselius cointegrated VAR approach. Our empirical model supports the view that, when controlling for interest rate changes and thus different monetary policy stances, money (defined as a global liquidity aggregate) is still a key factor to determine the long-run homogeneity of commodity prices and goods prices movements. The cointegrated VAR model fits with the data for the analysed period from the 1970s until 2008 very well. Our empirical results appear to be overall robust since they pass inter alia a series of recursive tests and are stable for varying compositions of the commodity indices. The empirical evidence is in line with theoretical considerations. The inclusion of commodity prices helps to identify a significant monetary transmission process from global liquidity to other macro variables such as goods prices. We find further support of the conjecture that monetary aggregates convey useful information about variables such as commodity prices which matter for aggregate demand and thus inflation. Given this clear empirical pattern it appears justified to argue that global liquidity merits attention in the same way as the worldwide level of interest rates received in the recent debate about the world savings and liquidity glut as one of the main drivers of the current financial crisis, if not possibly more.Commodity prices, cointegration, CVAR analysis, global liquidity, inflation, international spillovers

Monetary Policy, Global Liquidity and Commodity Price Dynamics

This paper examines the interactions between money, interest rates, goods and commodity prices at a global level. For this purpose, we aggregate data for major OECD countries and follow the Johansen/Juselius cointegrated VAR approach. Our empirical model supports the view that, when controlling for interest rate changes and thus different monetary policy stances, money (defi ned as a global liquidity aggregate) is still a key factor to determine the long-run homogeneity of commodity prices and goods prices movements. The cointegrated VAR model fi ts with the data for the analysed period from the 1970s until 2008 very well. Our empirical results appear to be overall robust since they pass inter alia a series of recursive tests and are stable for varying compositions of the commodity indices. The empirical evidence is in line with theoretical considerations. The inclusion of commodity prices helps to identify a signifi cant monetary transmission process from global liquidity to other macro variables such as goods prices. We fi nd further support of the conjecture that monetary aggregates convey useful information about variables such as commodity prices which matter for aggregate demand and thus infl ation. Given this clear empirical pattern it appears justifi ed to argue that global liquidity merits attention in the same way as the worldwide level of interest rates received in the recent debate about the world savings and liquidity glut as one of the main drivers of the current fi nancial crisis, if not possibly more.Commodity prices; cointegration; CVAR analysis; global liquidity; infl ation; international spillovers

Global Liquidity and Commodity Prices: A Cointegrated VAR Approach for OECD Countries

This paper examines the interactions between money, consumer prices and commodity prices at a global level from 1970 to 2008. Using aggregated data for major OECD countries and a cointegrating VAR framework, we are able to establish long run and short run relationships among these variables while the process is mainly driven by global liquidity. According to our empirical findings, different price elasticities in commodity and consumer goods markets can explain the recently observed overshooting of commodity over consumer prices. Although the sample period is rather long, recursive tests corroborate that our CVAR fits the data very well.Commodity prices, cointegration, CVAR analysis, global liquidity, inflation, international spillovers

Predicting binding energies of astrochemically relevant molecules via machine learning

The behaviour of molecules in space is to a large extent governed by where they freeze out or sublimate. The molecular binding energy is thus an important parameter for many astrochemical studies. This parameter is usually determined with time-consuming experiments, computationally expensive quantum chemical calculations, or the inexpensive, but inaccurate, linear addition method. In this work we propose a new method based on machine learning for predicting binding energies that is accurate, yet computationally inexpensive. A machine learning model based on Gaussian Process Regression is created and trained on a database of binding energies of molecules collected from laboratory experiments presented in the literature. The molecules in the database are categorized by their features, such as mono- or multilayer coverage, binding surface, functional groups, valence electrons, and H-bond acceptors and donors. The performance of the model is assessed with five-fold and leave-one-molecule-out cross validation. Predictions are generally accurate, with differences between predicted and literature binding energies values of less than $\pm$20\%. The validated model is used to predict the binding energies of twenty one molecules that have recently been detected in the interstellar medium, but for which binding energy values are not known. A simplified model is used to visualize where the snowlines of these molecules would be located in a protoplanetary disk. This work demonstrates that machine learning can be employed to accurately and rapidly predict binding energies of molecules. Machine learning complements current laboratory experiments and quantum chemical computational studies. The predicted binding energies will find use in the modelling of astrochemical and planet-forming environments.Comment: Accepted in astronomy and astrophysic

Formation of the coherent heavy fermion liquid at the 'hidden order' transition in URu2Si2

In this article we present high-resolution angle-resolved photoemission (ARPES) spectra of the heavy-fermion superconductor URu$_2$Si$_2$. Measurements as a function of both excitation energy and temperature allow us to disentangle a variety of spectral features, revealing the evolution of the low energy electronic structure across the hidden order transition. Already above the hidden order transition our measurements reveal the existence of weakly dispersive states below the Fermi level that exhibit a large scattering rate. Upon entering the hidden order phase, these states transform into a coherent heavy fermion liquid that hybridizes with the conduction bands.Comment: 5 pages, 4 figure

Phase transition kinetics in austempered ductile iron (ADI) with regard to MO content

The phase transformation to ausferrite during austempered ductile iron (ADI) heat treatment can be significantly influenced by the alloying element Mo. Utilizing neutron diffraction, the phase transformation from austenite to ausferrite was monitored in-situ during the heat treatment. In addition to the phase volume fractions, the carbon enrichment of retained austenite was investigated. The results from neutron diffraction were compared to the macroscopic length change from dilatometer measurements. They show that the dilatometer data are only of limited use for the investigation of ausferrite formation. However, they allow deriving the time of maximum carbon accumulation in the retained austenite. In addition, the transformation of austenite during ausferritization was investigated using metallographic methods. Finally, the distribution of the alloying elements in the vicinity of the austenite/ferrite interface zone was shown by atom probe tomography (APT) measurements. C and Mn were enriched within the interface, while Si concentration was reduced. The Mo concentration in ferrite, interface and austentite stayed at the same level. The delay of austenite decay during Stage II reaction caused by Mo was studied in detail at 400 °C for the initial material as well as for 0.25 mass % and 0.50 mass % Mo additions