Modification of thin films induced by slow heavy ions analysed with PIXE and SRIM

In the present work the particle induced X-rays (PIXE) emitted during interaction of inert and active slow heavy (HI) ions with specially prepared thin films were measured. Kinematics of the interaction was simulated numerically with SRIM in grazing incident-exit angle geometry and in time sequence in order to determine dynamics of formation of the subsurface region damaged through implantation, sputtering and interface mixing. It was shown that the structure and composition of films and surfaces are not stable against HI irradiation due to preferential sputtering and implantation of ions and recoils and that dynamics of such a modification can be in-situ monitored with PIXE and analyzed with SRIM

Graphical Models for Structural Vector Autoregressions

In this paper a method to identify the causal structure associated with a VAR model is proposed. The structure is described by means of a graph, which provides a rigorous language to analyze the statistical and logical properties of causal relations. Under some general assumptions, causal relations are associated with a set of vanishing partial correlations among the variables that constitute them. In order to infer the causal structure among the contemporaneous variable, tests on vanishing partial correlations among the estimated residuals of a VAR are used, jointly with background knowledge. This method is applied to an updated version of the King et al. (1991) dataset and it allows to obtain an orthogonalization of the residuals coherent with the causal structure among the contemporaneous variables and alternative to the standard one, which is based on the Choleski factorization of the covariance matrix of the residuals. The impulse response functions calculated, with the method proposed here, for the King et al. (1991) model confirm their results about the fact that US macroeconomic data do not support the hypothesis that real permanent shocks are the dominant source of business-cycle fluctuations.Causality, Directed Acyclic Graphs, Identification Problem, Residuals Orthogonalization, Impulse Response Functions.

Review of High-Quality Random Number Generators

This is a review of pseudorandom number generators (RNG's) of the highest quality, suitable for use in the most demanding Monte Carlo calculations. All the RNG's we recommend here are based on the Kolmogorov-Anosov theory of mixing in classical mechanical systems, which guarantees under certain conditions and in certain asymptotic limits, that points on the trajectories of these systems can be used to produce random number sequences of exceptional quality. We outline this theory of mixing and establish criteria for deciding which RNG's are sufficiently good approximations to the ideal mathematical systems that guarantee highest quality. The well-known RANLUX (at highest luxury level) and its recent variant RANLUX++ are seen to meet our criteria, and some of the proposed versions of MIXMAX can be modified easily to meet the same criteria.Comment: 21 pages, 4 figure

Creativity and positive emotions in studying: Novel possibilities for improving students’ learning

Research on students’ learning identified that positive affect is a strong predictor of better academic performance even when statistically controlling for effects of prior academic performance and approaches to learning (e.g., Rogaten, Moneta & Spada, 2013). A variable that has been found to strongly link with positive affect in studying is use of creative cognition, which is the habit to deploy one’s own creative ability to an endeavour (Rogaten & Moneta, in press). Based on the broaden-and-build theory (Fredrickson, 1998), the mood-as-input model (Martin et al., 1993), the control-process model (Carver & Scheier, 2001), and self-determination theory (Deci & Ryan, 1985), it was hypothesised that positive affect will be both an antecedent and a consequence of use of creative cognition in studying. 130 university students completed the International Positive and Negative Affect Schedule - Short Form (I-PANAS-SF) and the Use of Creative Cognition Scale (UCCS) with reference to their overall studying experience in the first and second semesters of an academic year. A comparison of alternative structural equation models showed clear support for the reciprocal relationship between positive affect in studying and use of creative cognition in studying. This is the first study that found the longitudinal relationship between use of creative cognition in studying and subsequent positive affect in studying, which opens novel possibilities for interventions. Well-designed curricula, assessments and training programs that foster the use of creative cognition in studying may increase students’ positive affect and engagement in studying and, in turn, improve their learning and academic performance

Graph-Based Search Procedure for Vector Autoregressive Models

Vector Autoregressions (VARs) are a class of time series models commonly used in econometrics to study the dynamic effect of exogenous shocks to the economy. While the estimation of a VAR is straightforward, there is a problem of finding the transformation of the estimated model consistent with the causal relations among the contemporaneous variables. Such problem, which is a version of what is called in econometrics “the problem of identification,” is faced in this paper using a semi-automated search procedure. The unobserved causal relations of the structural form, to be identified, are represented by a directed graph. Discovery algorithms are developed to infer features of the causal graph from tests on vanishing partial correlations among the VAR residuals. Such tests cannot be based on the usual tests of conditional independence, because of sampling problems due to the time series nature of the data. This paper proposes consistent tests on vanishing partial correlations based on the asymptotic distribution of the estimated VAR residuals. Two different types of search algorithm are considered. A first algorithm restricts the analysis to direct causation among the contemporaneous variables, a second algorithm allows the possibility of cycles (feedback loops) and common shocks among contemporaneous variables. Recovering the causal structure allows a reliable transformation of the estimated vector autoregressive model which is very useful for macroeconomic empirical investigations, such as comparing the effects of different shocks (real vs. nominal) on the economy and finding a measure of the monetary policy shock.VARs, Problem of Identification, Causal Graphs, Structural Shocks

Business cycle synchronisation in East Asia

Against the background of the rapid inter- and intraregional integration of East Asia, we examine the extent and nature of synchronisation of business cycles in the region. We estimate various specifications of a dynamic common factor model for output growth of ten East Asian countries. A significant common factor is shared by all Asian countries considered, except China and Japan. The degree of synchronisation has fluctuated over time, with an upward trend particularly evident for the newly industrialised countries. Synchronisation appears to mainly reflect strong export synchronisation, rather than common consumption or investment dynamics. Cross-country spill-over effects explain only a small part of the comovement in the region. More importantly, a number of exogenous factors, such as the price of oil and the JPY-USD exchange rate, play an important role in synchronising activity. In addition, economic linkages with Europe and North America may also have contributed to the observed synchronisation. JEL Classification: E30, F00business cycles synchronisation, dynamic factor model, East Asia

Comparing shapes of engel curves

We measure how different the shapes of Engel curves are across 59 commodity groups. The same analysis is carried out for their derivatives and variances. While Engel curves possess a relatively homogeneous shape, significantly more heterogeneity is present in derivatives and when particular sub-classes of income are considered.Consumption, Kernel smoothing, Rank correlation, Curve shape

Exporting and productivity as part of the growth process: causal evidence from a data-driven structural VAR

This paper introduces a little known category of estimators - Linear Non-Gaussian vector autoregression models that are acyclic or cyclic - imported from the machine learning literature, to revisit a well-known debate. Does exporting increase firm productivity? Or is it only more productive firms that remain in the export market? We focus on a relatively well-studied country (Chile) and on already-exporting firms (i.e. the intensive margin of exporting). We explicitly look at the co-evolution of productivity and growth, and attempt to ascertain both contemporaneous and lagged causal relationships. Our findings suggest that exporting does not have any causal influence on the other variables. Instead, export seems to be determined by other dimensions of firm growth. With respect to learning by exporting (LBE), we find no evidence that export growth causes productivity growth within the period and very little evidence that exporting growth has a causal effect on subsequent TFP growth

More or Better ? Measuring Quality versus Quantity in Food Consumption

As people become richer they get the opportunity of consuming more but also qualitatively better goods. This holds for a basic commodity like food as well. We investigate food consumption in Russia, taking into account both expenditure and nutrition value in terms of calories. We analyze how food consumption patterns change with increasing income by estimating both "quantity Engel curves" and "quality Engel curves". The former describe the functional dependence of calories consumed on total expenditure. The latter trace out the dependence of price per calorie as a proxy for quality on total expenditure. We compare income elasticities of quantity with income elasticities of quality. In these Russian data for years 2000-2002 the reaction of quality to changes in income is significantly stronger than the reaction of quantity to income changes suggesting that Russian households tend to choose higher quality food items as income rises.Food consumption patterns, calorie intake, income elasticity decomposition, Engel curves, method of average derivatives