Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set

We evaluate conditional predictive densities for U.S. output growth and inflationusing a number of commonly used forecasting models that rely on a large number ofmacroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used normality assumption fit actual realizationsout-of-sample. Our focus on predictive densities acknowledges the possibility that, although some predictors can improve or deteriorate point forecasts, they might have theopposite effect on higher moments. We find that normality is rejected for most modelsin some dimension according to at least one of the tests we use. Interestingly, however,combinations of predictive densities appear to be correctly approximated by a normaldensity: the simple, equal average when predicting output growth and Bayesian modelaverage when predicting inflation.

Performance assessment and league tables. Comparing like with like

We formulate performance assessment as a problem of causal analysis and outline an approach based on the missing data principle for its solution. It is particularly relevant in the context of so-called league tables for educational, health-care and other public-service institutions. The proposed solution avoids comparisons of institutions that have substantially different clientele (intake).

An adaptation of correspondence analysis for square tables

The application of correspondence analysis to square asymmetrictables is often unsuccessful because of the strong role played by thediagonal entries of the matrix, obscuring the data off the diagonal. A simplemodification of the centering of the matrix, coupled with the correspondingchange in row and column masses and row and column metrics, allows the tableto be decomposed into symmetric and skew--symmetric components, which canthen be analyzed separately. The symmetric and skew--symmetric analyses canbe performed using a simple correspondence analysis program if the data areset up in a special block format.

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.

The structural dynamics of US output and inflation: What explains the changes?

We examine the dynamics of US output and inflation using a structural time varyingcoefficient VAR. We show that there are changes in the volatility of both variables andin the persistence of inflation. Technology shocks explain changes in output volatility,while a combination of technology, demand and monetary shocks explain variations inthe persistence and volatility of inflation. We detect changes over time in the transmission of technology shocks and in the variance of technology and of monetary policyshocks. Hours and labor productivity always increase in response to technology shocks.

On the robust effects of technology shocks on hours worked and output

We analyze the effects of neutral and investment-specific technology shockson hours and output. Long cycles in hours are captured in a variety of ways.Hours robustly fall in response to neutral shocks and robustly increase inresponse to investment specific shocks. The percentage of the variance ofhours (output) explained by neutral shocks is small (large); the opposite istrue for investment specific shocks. News shocks are uncorrelated with theestimated technology shocks.

The structural dynamics of output growth and inflation: some international evidence

We examine the dynamics of output growth and inflation in the US, Euro area and UK using a structural time varying coefficient VAR. There are important similarities in structural inflation dynamics across countries; output growth dynamics differ. Swings in the magnitude of inflation and output growth volatilities and persistences are accounted for by a combination of three structural shocks. Changes over time in the structure of the economy are limited and permanent variations largely absent. Changes in the volatilities of structural shocks matter.

Inflation and output dynamics with firm-owned capital

We model firm-owned capital in a stochastic dynamic New-Keynesian generalequilibrium model à la Calvo. We find that this structure impliesequilibrium dynamics which are quantitatively di¤erent from the onesassociated with a benchmark case where households accumulate capital andrent it to firms. Our findings therefore stress the importance ofmodeling an investment decision at the firm level in addition to ameaningful price setting decision. Along the way we argue that the problemof modeling firm-owned capital with Calvo price-setting has not been solvedin a correct way in the previous literature.

A Gestão de Stock: O Fornecimento de OutPut como factor de redução de custo

O presente trabalho tem como objectivo mostrar a importância que a Gestão económica de Stock tem no processo de redução de custo, por via da implementação de um modelo. E para isso far-se-á um estudo de caso numa empresa inserida no ramo de transformação de pescado – FRESCOMAR. A metodologia adoptada para alcançar os objectivos propostos passou pela pesquisa bibliográfica, recolha de dados e de informação relevante junto da empresa e tratamento dos dados numa folha de Excel. O modelo de gestão de Stock a ser implementado depende essencialmente da componente procura, onde que para uma empresa com procura constante utiliza-se os modelos determinísticos e para uma com procura aleatória utiliza-se os modelos estocásticos (Nível de Encomenda e Revisão Cíclica). Nos modelos determinísticos temos 4 modelos diferenciados pela forma de reposição e a admissibilidade da procura. Com as informações recolhidas junto da empresa em estudo escolhemos implementar o modelo de reposição não instantânea com ruptura não permitida e obtivemos a optimização do Stock com níveis reduzidos de produção e consequentemente houve uma diminuição do custo. Com resultados obtiveram-se ainda valores da Quantidade Óptima a ser Produzida, do Stock Máximo e do Custo Total Óptimo por unidade de tempo. Devido a diversidade de produtos propomos à empresa a utilização da análise ABC para classificar os produtos reagrupando-os em classes A, B e C, conforme o peso no consumo de Stock.

Correspondence analysis of two transition tables

The case of two transition tables is considered, that is two squareasymmetric matrices of frequencies where the rows and columns of thematrices are the same objects observed at three different timepoints. Different ways of visualizing the tables, either separatelyor jointly, are examined. We generalize an existing idea where asquare matrix is descomposed into symmetric and skew-symmetric partsto two matrices, leading to a decomposition into four components: (1)average symmetric, (2) average skew-symmetric, (3) symmetricdifference from average, and (4) skew-symmetric difference fromaverage. The method is illustrated with an artificial example and anexample using real data from a study of changing values over threegenerations.

New reference tables and user-friendly Internet application for predicted heart weights.

BACKGROUND: Knowledge of normal heart weight ranges is important information for pathologists. Comparing the measured heart weight to reference values is one of the key elements used to determine if the heart is pathological, as heart weight increases in many cardiac pathologies. The current reference tables are old and in need of an update. AIMS: The purposes of this study are to establish new reference tables for normal heart weights in the local population and to determine the best predictive factor for normal heart weight. We also aim to provide technical support to calculate the predictive normal heart weight. METHODS: The reference values are based on retrospective analysis of adult Caucasian autopsy cases without any obvious pathology that were collected at the University Centre of Legal Medicine in Lausanne from 2007 to 2011. We selected 288 cases. The mean age was 39.2 years. There were 118 men and 170 women. Regression analyses were performed to assess the relationship of heart weight to body weight, body height, body mass index (BMI) and body surface area (BSA). RESULTS: The heart weight increased along with an increase in all the parameters studied. The mean heart weight was greater in men than in women at a similar body weight. BSA was determined to be the best predictor for normal heart weight. New reference tables for predicted heart weights are presented as a web application that enable the comparison of heart weights observed at autopsy with the reference values. CONCLUSIONS: The reference tables for heart weight and other organs should be systematically updated and adapted for the local population. Web access and smartphone applications for the predicted heart weight represent important investigational tools.