Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models

The performance in finite samples is examined of inference obtained by variants of the Arellano-Bond and the Blundell-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross-sectional heteroskedasticity. By simulation the effects are examined of using particular instrument strength enhancing reductions and transformations of the matrix of instrumental variables, of less robust implementations of the GMM weighting matrix, and also of corrections to the standard asymptotic variance estimates. We compare the root mean squared errors of the coefficient estimators and also the size of tests on coefficient values and of different implementations of overidentification restriction tests. Also the size and power of tests on the validity of the additional orthogonality conditions exploited by the Blundell-Bond technique are assessed over a pretty wide grid of relevant cases. Surprisingly, particular asymptotically optimal and relatively robust weighting matrices are found to be superior in finite samples to ostensibly more appropriate versions. Most of the variants of tests for overidentification restrictions show serious deficiencies. A recently developed modification of GMM is found to have great potential when the cross-sectional heteroskedasticity is pronounced and the time-series dimension of the sample not too small. Finally all techniques are employed to actual data and lead to some profound insights

IN SITU RHEOLOGY OF THE OCEANIC LITHOSPHERE ALONG THE HAWAI‘IAN RIDGE

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Mehrkernige, schwefelverbrückte Übergangsmetallverbindungen

Die vorliegende Arbeit befasst sich mit der Synthese und Reaktivität von löslichen, niedrignuklearen Übergangsmetall-Schwefel-Verbindungen. Die Umsetzung von Nickelperchlorat mit NaSH in Gegenwart von Phosphan- und gemischten Phosphan-Schwefel-Liganden führte zu trinuklearen, sulfidoverbrückten Komplexen. Mit Cobaltperchlorat und den Tetraazamakrocyclen [14]aneN<su

Unprecedented inequivalent metal coordination environments in a mixed-ligand dicobalt complex

Bimetallic complexes of the transition metals containing mixed diimine and dithiolate ligands are of fundamental interest on account of their intriguing electronic properties. Almost always, such complexes are isolated as species in which both the metal centers are in identical coordination environments - this means that the two metals often have identical redox properties. In contrast, mixed-diimine/dithiolate bimetallic complexes of the first row transition metals where the two metals are in dissimilar coordination environments are exceedingly rare, and are only known for nickel. Herein, we report the first ever example of a mixed-diimine/dithiolate dicobalt complex where the two cobalt centers are in different coordination environments. The synthesis of this compound is straightforward, and produces a complex in which the two cobalt centers display very different redox properties

Risco tóxico de resíduos de pesticidas em alimentos e toxicidade reprodutiva em ratos Wistar /

Orientador : Paulo Roberto DalsenterDissertaçăo (mestrado) - Universidade Federal do Paraná, Setor de Cięncias Biológicas, Programa de Pós-Graduaçăo em Farmacologia. Defesa: Curitiba, 2005Inclui bibliografi

Can unhealthy food purchases at checkout counters be discouraged by introducing healthier snacks? A real-life experiment in supermarkets in deprived urban areas in the Netherlands

Background: The checkout area in supermarkets is an unavoidable point of purchase where impulsive food purchases are likely to be made. However, the product assortment at the checkout counters is predominantly unhealthy. The aim of this real life experiment was to investigate if unhealthy food purchases at checkout counters in supermarkets in deprived urban areas in the Netherlands can be discouraged by the introduction of the Healthy Checkout Counter (HCC). In addition, we examined customers' perceptions towards the HCC. Methods: The HCC was an initiative of a leading supermarket chain in the Netherlands that consisted of displays with a selection of healthier snacks that were placed at the checkouts. We used a real life quasi-experimental design with 15 intervention and 9 control supermarkets. We also performed a cross-sectional customer evaluation in 3 intervention supermarkets using oral surveys to investigate customers' perceptions towards the HCC (n=134). The purchases of unhealthy and healthier snacks at checkouts were measured with sales data. Results: During the intervention period, customers purchased on average 1.7 (SD: 0.08) unhealthy snacks per 100 customers in the intervention supermarket and 1.4 (SD: 0.10) in the control supermarket. Linear regression analyses revealed no statistically significant difference in the change during the control and intervention period of sales of unhealthy snacks between the control and intervention supermarkets (B = - 0.008, 95% CI = - 0.15 to 0.14). The average number of healthier snacks purchased was 0.2 (SD: 0.3) items per 100 customers in the intervention supermarkets during the intervention period. Of the intervention customers, 41% noticed the HCC and 80% of them were satisfied or very satisfied with the intervention. Conclusions: This real life experiment in supermarkets showed that the placement of healthier snacks at checkouts did not lead to the substitution of unhealthy snack purchases with healthier alternatives. Although supermarket customers positively evaluated the HCC, future studies are needed to investigate other strategies to encourage healthier food purchases in supermarkets.</p

An experimental study of the intrinsic stability of random forest variable importance measures

BACKGROUND: The stability of Variable Importance Measures (VIMs) based on random forest has recently received increased attention. Despite the extensive attention on traditional stability of data perturbations or parameter variations, few studies include influences coming from the intrinsic randomness in generating VIMs, i.e. bagging, randomization and permutation. To address these influences, in this paper we introduce a new concept of intrinsic stability of VIMs, which is defined as the self-consistence among feature rankings in repeated runs of VIMs without data perturbations and parameter variations. Two widely used VIMs, i.e., Mean Decrease Accuracy (MDA) and Mean Decrease Gini (MDG) are comprehensively investigated. The motivation of this study is two-fold. First, we empirically verify the prevalence of intrinsic stability of VIMs over many real-world datasets to highlight that the instability of VIMs does not originate exclusively from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. Second, through Spearman and Pearson tests we comprehensively investigate how different factors influence the intrinsic stability. RESULTS: The experiments are carried out on 19 benchmark datasets with diverse characteristics, including 10 high-dimensional and small-sample gene expression datasets. Experimental results demonstrate the prevalence of intrinsic stability of VIMs. Spearman and Pearson tests on the correlations between intrinsic stability and different factors show that #feature (number of features) and #sample (size of sample) have a coupling effect on the intrinsic stability. The synthetic indictor, #feature/#sample, shows both negative monotonic correlation and negative linear correlation with the intrinsic stability, while OOB accuracy has monotonic correlations with intrinsic stability. This indicates that high-dimensional, small-sample and high complexity datasets may suffer more from intrinsic instability of VIMs. Furthermore, with respect to parameter settings of random forest, a large number of trees is preferred. No significant correlations can be seen between intrinsic stability and other factors. Finally, the magnitude of intrinsic stability is always smaller than that of traditional stability. CONCLUSION: First, the prevalence of intrinsic stability of VIMs demonstrates that the instability of VIMs not only comes from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. This finding gives a better understanding of VIM stability, and may help reduce the instability of VIMs. Second, by investigating the potential factors of intrinsic stability, users would be more aware of the risks and hence more careful when using VIMs, especially on high-dimensional, small-sample and high complexity datasets