Business cycle measurement with some theory

A method to evaluate cyclical models not requiring knowledge of the DGP and the exact specificationof the aggregate decision rules is proposed. We derive robust restrictions in a class of models; use someto identify structural shocks in the data and others to evaluate the class or contrast sub-models. Theapproach has good properties, even in small samples, and when the class of models is misspecified. Themethod is used to sort out the relevance of a certain friction (the presence of rule-of-thumb consumers)in a standard class of models.

Biased representation of homothetic preferences on homogeneous sets

In the homogeneous case of one-dimensional objects, we show that any preference relation that is positive and homothetic can be represented by a quantitative utility function and unique bias. This bias may favor or disfavor the preference for an object. In the first case, preferences are complete but not transitive and an object may be preferred even when its utility is lower. In the second case, preferences are asymmetric and transitive but not negatively transitive and it may not be sufficient for an object to have a greater utility for be preferred. In this manner, the bias reflects the extent to which preferences depart from the maximization of a utility function.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Microfabrics in carbonate mylonites along a large-scale shear zone (Helvetic Alps)

Carbonate mylonites with varying proportions of second-phase minerals were collected at positions of increasing metamorphic grade along the basal thrust of the Morcles nappe (Helvetic nappes, Switzerland). Variations of temperature, stress, and strain rate, changes in chemistry of solid and fluid phases, and differing degrees of strain localization and annealing were tracked by measuring the shapes, mean sizes, and size distributions of both matrix and second-phase grains, as well as crystal preferred orientation (CPO) of the matrix. Field structures suggest that strain rate was constant along the fault. The mean and distribution of the calcite grain sizes were affected most profoundly by temperature: Increased temperature, presumably accompanied by decreased stress, correlated with larger mean sizes and wider size distributions. At a given location, the matrix grains in mylonites with more second-phase particles are, on average, smaller, have narrower size distributions, and have more elongate shapes. For example, mylonites with 50 vol.% of second phases have matrix grain sizes half that of pure mylonites. Changes in calcite chemistry and the presence of synkinematic fluids seemed to influence microfabric only weakly. Temporal variations in conditions, such as exhumation-induced cooling, apparently provoke changes in temperature, stress, and strain rate along the nappe. These changes result in further strain localization during retrograde conditions and cause the grain size to be reduced by an additional 50%. The matrix CPO strengthens with increasing temperature or strain, but weakens and rotates with increasing second-phase content, These fabric changes suggest differing rates of grain growth, grain size reduction, and development of CPO owing to variations in the deformation conditions and, perhaps, mechanisms. To interpret natural mylonite structures or to extrapolate mechanical data to natural situations requires careful characterization of the microfabric, and, in particular, second-phase minerals. (c) 2007 Elsevier B.V, All rights reserved.

Strategy communication and measurement systems

Organizations often face the challenge of communicating their strategiesto local decision makers. The difficulty presents itself in finding away to measure performance wich meaningfully conveys how to implement theorganization's strategy at local levels. I show that organizations solvethis communication problem by combining performance measures in such away that performance gains come closest to mimicking value-added asdefined by the organization's strategy. I further show how organizationsrebalance performance measures in response to changes in their strategies.Applications to the design of performance metrics, gaming, and divisionalperformance evaluation are considered. The paper also suggests severalempirical ways to evaluate the practical importance of the communicationrole of measurement systems.

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

Measurement and explanation of socioeconomic inequality in health with longitudinal data

This paper presents a method for the measurement of changes in health inequality and income-related health inequality over time in a population.For pure health inequality (as measured by the Gini coefficient) andincome-related health inequality (as measured by the concentration index),we show how measures derived from longitudinal data can be related tocross section Gini and concentration indices that have been typicallyreported in the literature to date, along with measures of health mobilityinspired by the literature on income mobility. We also show how thesemeasures of mobility can be usefully decomposed into the contributions ofdifferent covariates. We apply these methods to investigate the degree ofincome-related mobility in the GHQ measure of psychological well-being inthe first nine waves of the British Household Panel Survey (BHPS). Thisreveals that dynamics increase the absolute value of the concentrationindex of GHQ on income by 10%.

Biased quantitative measurement of interval ordered homothetic preferences

We represent interval ordered homothetic preferences with a quantitative homothetic utility function and a multiplicative bias. When preferences are weakly ordered (i.e. when indifference is transitive), such a bias equals 1. When indifference is intransitive, the biasing factor is a positive function smaller than 1 and measures a threshold of indifference. We show that the bias is constant if and only if preferences are semiordered, and we identify conditions ensuring a linear utility function. We illustrate our approach with indifference sets on a two dimensional commodity space.

Validation of methane measurement using headspace-GC-MS and quantification by a stable isotope-labeled internal standard generated in situ.

A previous study has shown the possibility to identify methane (CH4 ) using headspace-GC-MS and quantify it with a stable isotope as internal standard. The main drawback of the GC-MS methods discussed in literature for CH4 measurement is the absence of a specific internal standard necessary to perform quantification. However, it becomes essential to develop a safer method to limit the manipulation of gaseous CH4 and to precisely control the injected amount of gas for spiking and calibration by comparison with external calibration. To avoid the manipulation of a stable isotope-labeled gas, we have chosen to generate a labeled gas as an internal standard in a vial on the basis of the formation of CH4 by the reaction of Grignard reagent methylmagnesium chloride with deuterated water. This method allows precise measurement of CH4 concentrations in gaseous sample as well as in a solid or a liquid sample after a thermodesorption step in a headspace vial. A full accuracy profile validation of this method is then presented.

Integration of high-resolution geophysical data for the characterization of alluvial aquifers : new approaches and implications for hydrological predictions

Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.