A shake table test of typical mediterranean reinforced concrete structures

This research investigates the ultimate earthquake resistance of typical RC moment resisting frames designed accordingly to current standards, in terms of ultimate energy absorption/dissipation capacity. Shake table test of a 2/5 scale model, under several intensities of ground motion, are carried out. The loading effect of the earthquake is expressed as the total energy that the quake inputs to the structure, and the seismic resistance is interpreted as the amount of energy that the structure dissipates in terms of cumulative inelastic strain energy.

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Volunteer Engagement: Does Engagement Predict the Degree of Satisfaction among New Volunteers and the Commitment of Those who have been Active Longer?

This study examines the concept of engagement in samples of volunteers from different non-profit organisations. Study 1 analyzes the psychometric properties of the abbreviated version of the Utrecht Work Engagement Scale (UWES) (Schaufeli, Bakker, & Salanova, 2006a). Two factorial structures are examined: one-dimensional and three-dimensional structures. Based on the Three-Stage Model of Volunteers’ Duration of Service (Chacón, Vecina, & Dávila, 2007), Study 2 investigates the relationship between engagement, volunteer satisfaction, and intention to remain in a sample of new volunteers and the relationship between engagement, organisational commitment, and intention to remain in a sample of veteran volunteers. Moderated mediation analysis is provided using duration of service as a moderator in order to set a splitting point between new and veteran volunteers. The results of the confirmatory factor analysis suggest that the three-factor model fits better to the data. Regarding the structural models, the first one shows that engagement is crucial to volunteer satisfaction during the first stage, while volunteer satisfaction is the key variable in explaining intention to continue. The second structural model shows that engagement reinforces the participant’s commitment to the organisation, while organizational commitment predicts intention to continue. Both models demonstrate a notable decline when samples are changed.

Psychometric behaviour of the strengths and difficulties questionnaire (SDQ) in the Spanish national health survey 2006

Background: The Strengths and Difficulties Questionnaire (SDQ) is a tool to measure the risk for mental disorders in children. The aim of this study is to describe the diagnostic efficiency and internal structure of the SDQ in the sample of children studied in the Spanish National Health Survey 2006. Methods: A representative sample of 6,773 children aged 4 to 15 years was studied. The data were obtained using the Minors Questionnaire in the Spanish National Health Survey 2006. The ROC curve was constructed and calculations made of the area under the curve, sensitivity, specificity and the Youden J indices. The factorial structure was studied using models of exploratory factorial analysis (EFA) and confirmatory factorial analysis (CFA). Results: The prevalence of behavioural disorders varied between 0.47% and 1.18% according to the requisites of the diagnostic definition. The area under the ROC curve varied from 0.84 to 0.91 according to the diagnosis. Factor models were cross-validated by means of two different random subsamples for EFA and CFA. An EFA suggested a three correlated factor model. CFA confirmed this model. A five-factor model according to EFA and the theoretical five-factor model described in the bibliography were also confirmed. The reliabilities of the factors of the different models were acceptable (>0.70, except for one factor with reliability 0.62). Conclusions: The diagnostic behaviour of the SDQ in the Spanish population is within the working limits described in other countries. According to the results obtained in this study, the diagnostic efficiency of the questionnaire is adequate to identify probable cases of psychiatric disorders in low prevalence populations. Regarding the factorial structure we found that both the five and the three factor models fit the data with acceptable goodness of fit indexes, the latter including an externalization and internalization dimension and perhaps a meaningful positive social dimension. Accordingly, we recommend studying whether these differences depend on sociocultural factors or are, in fact, due to methodological questions.

Developing an underlying inflation gauge for China. Bruegel Working Paper 2014/11, 9 October 2014

This paper develops a new underlying inflation gauge (UIG) for China which differentiates between trend and noise, is available daily and uses a broad set of variables that potentially influence inflation. Its construction follows the works at other major central banks, adopts the methodology of a dynamic factor model that extracts the lower frequency components as developed by Forni et al (2000) and draws on the experience of the People’s Bank of China in modelling inflation.

Revisiting the synthetic control estimator

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. The SC relies on the assumption that there is a weighted average of the control units that reconstruct the potential outcome of the treated unit in the absence of treatment. If these weights were known, then one could estimate the counterfactual for the treated unit using this weighted average. With these weights, the SC would provide an unbiased estimator for the treatment effect even if selection into treatment is correlated with the unobserved heterogeneity. In this paper, we revisit the SC method in a linear factor model where the SC weights are considered nuisance parameters that are estimated to construct the SC estimator. We show that, when the number of control units is fixed, the estimated SC weights will generally not converge to the weights that reconstruct the factor loadings of the treated unit, even when the number of pre-intervention periods goes to infinity. As a consequence, the SC estimator will be asymptotically biased if treatment assignment is correlated with the unobserved heterogeneity. The asymptotic bias only vanishes when the variance of the idiosyncratic error goes to zero. We suggest a slight modification in the SC method that guarantees that the SC estimator is asymptotically unbiased and has a lower asymptotic variance than the difference-in-differences (DID) estimator when the DID identification assumption is satisfied. If the DID assumption is not satisfied, then both estimators would be asymptotically biased, and it would not be possible to rank them in terms of their asymptotic bias.

Essays in macroeconometrics

The knowledge of the current state of the economy is crucial for policy makers, economists and analysts. However, a key economic variable, the gross domestic product (GDP), are typically colected on a quartely basis and released with substancial delays by the national statistical agencies. The first aim of this paper is to use a dynamic factor model to forecast the current russian GDP, using a set of timely monthly information. This approach can cope with the typical data flow problems of non-synchronous releases, mixed frequency and the curse of dimensionality. Given that Russian economy is largely dependent on the commodity market, our second motivation relates to study the effects of innovations in the russian macroeconomic fundamentals on commodity price predictability. We identify these innovations through a news index which summarizes deviations of offical data releases from the expectations generated by the DFM and perform a forecasting exercise comparing the performance of different models.

Benthic foraminifera in the Arctic Ocean

We examine the quantitative composition of benthic foraminiferal assemblages of Rose Bengal-stained surface samples from 37 stations in the Laptev Sea, and combine this data set with an existing data set along a transect from Spitsbergen to the central Arctic Ocean. Foraminiferal test accumulation rates, diversity, faunal composition and statistically defined foraminiferal associations are analysed for living (Rose Bengal-stained) and dead foraminifers. We compare the results of several benthic foraminiferal diversity indices and statistically defined foraminiferal associations, including Fisher's alpha and Shannon-Wiener diversity indices, Q-mode principal component analysis and correspondence analysis. Diversity and faunal density (standing stock) of living benthic foraminifers are positively correlated to trophic resources. In contrast, the accumulation rate of dead foraminifers (BFAR) shows fluctuating values depending on test disintegration processes. Foraminiferal associations defined by Q-mode principal component analysis and correspondence analysis are comparable. The factor values of the correspondence analysis allow a quantitative correlation between the foraminiferal fauna and the local carbon flux, which may be used as a tool to estimate changes in primary productivity.

Oxygen isotope and paleomagnetic stratigraphy of sediment core V28-239

Core Vema 28-238 preserves an excellent oxygen isotope and magnetic stratigraphy and is shown to contain undisturbed sediments deposited continuously through the past 870,000 yr. Detailed correlation with sequences described by Emiliani in the Caribbean and Atlantic Ocean is demonstrated. The boundaries of 22 stages representing alternating times of high and low Northern Hemisphere ice volume are recognized and dated. The record is interpreted in terms of Northern Hemisphere ice accumulation, and is used to estimate the range of temperature variation in the Caribbean.

Dynamic Management of Loyalty Program Strategies

Thesis (Ph.D.)--University of Washington, 2016-06

Returns from investing in Australian equity superannuation funds, 1991-1999

In this analysis of investment manager performance, two questions are addressed. First, do managers that actively trade stocks create value for investors? Second, can the multifactor model of Gruber capture the cross-section of average fund returns for the Australian setting? The answers from this study are as follows: as an industry, investment managers destroyed value for superannuation investors for the period 1991 through 1999, under-performing passive portfolio returns by 2.80-4.00 per cent per annum on a risk-unadjusted basis and 0.50-0.93 per cent per annum on a risk-adjusted basis. Evidence is provided in support of the four-factor model of Gruber; however, the model fails to capture the impact of investment style for the Australian setting. The findings suggest that Australian superannuation investors would transform their retirement savings into retirement income more efficiently through the use of passive alternatives to the stock selection problem.

A genetic investigation of the covariation among Inspection Time, Choice Reaction Time, and IQ subtest scores

Information processing speed, as measured by elementary cognitive tasks, is correlated with higher order cognitive ability so that increased speed relates to improved cognitive performance. The question of whether the genetic variation in Inspection Time (IT) and Choice Reaction Time (CRT) is associated with IQ through a unitary factor was addressed in this multivariate genetic study of IT, CRT, and IQ subtest scores. The sample included 184 MZ and 206 DZ twin pairs with a mean age of 16.2 years (range 15-18 years). They were administered a visual (pi-figure) IT task, a two-choice RT task, five computerized subtests of the Multidimensional Aptitude Battery, and the digit symbol substitution subtest from the WAIS-R. The data supported a factor model comprising a general, three group (verbal ability, visuospatial ability, broad speediness), and specific genetic factor structure, a shared environmental factor influencing all tests but IT, plus unique environmental factors that were largely specific to individual measures. The general genetic factor displayed factor loadings ranging between 0.35 and 0.66 for the IQ subtests, with IT and CRT loadings of -0.47 and -0.24, respectively. Results indicate that a unitary factor is insufficient to describe the entire relationship between cognitive speed measures and all IQ subtests, with independent genetic effects explaining further covariation between processing speed (especially CRT) and Digit Symbol.