New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

Essays in the Economics of Education

This dissertation is comprised of three essays in the economics of education. In the first essay, I examine how college students' major choice and major switching behavior responds to major-specific labor market shocks. The second essay explores the incidence and persistence of overeducation for workers in the United States. The final essay examines the role that students' cognitive and non-cognitive skills play in their transition from secondary to postsecondary education, and how the effect of these skills are moderated by race, gender, and socioeconomic status.

Multi-View Weighted Network

Extensive investigation has been conducted on network data, especially weighted network in the form of symmetric matrices with discrete count entries. Motivated by statistical inference on multi-view weighted network structure, this paper proposes a Poisson-Gamma latent factor model, not only separating view-shared and view-specific spaces but also achieving reduced dimensionality. A multiplicative gamma process shrinkage prior is implemented to avoid over parameterization and efficient full conditional conjugate posterior for Gibbs sampling is accomplished. By the accommodating of view-shared and view-specific parameters, flexible adaptability is provided according to the extents of similarity across view-specific space. Accuracy and efficiency are tested by simulated experiment. An application on real soccer network data is also proposed to illustrate the model.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

In two minds about screening: an investigation of cervical cancer prevention among Irish women

Cervical cancer is the second most common female cancer worldwide. Cervical screening programmes can reduce the incidence of cervical cancer by up to 80 percent if the invited women participate. Previous Irish research has associated screening attendance with subjective norms, anticipated regret, higher socio-economic status and education. Greater perceived screening barriers and lacking knowledge were associated with avoidance. These findings support a variety of expectancy-value theories of behaviour. They also suggest that expectancy-value theories could benefit from the inclusion of affective predictors of behaviour, like anticipated regret. In 2008 the Republic of Ireland introduced the National Cervical Screening Programme (NCSP). This research seeks to identify the predictors of participation in the NCSP. A systematic review of reviews showed that predictors of screening participation clustered into environmental and psychological influences. There is a gap in the evidence synthesis of associations with personal characteristics and health beliefs. Thematic analysis of focus group interviews confirmed the validity of many screening predictors identified by the systematic review and expectancy-value theories. A survey of these predictors suggested that reduced screening barriers might encourage first-time participation, while regular attendance requires greater endorsement of screening benefits and stronger subjective norm and intention. Positive attitude, rather than knowledge, appeared to be crucial for strong intention, so the final study piloted an experiment comparing the utility of positive attitude in strengthening intention to the utility of information provision. Despite lacking significant differences between conditions, content analysis of participant comments suggested that a full trial would be worthwhile, given purposive sampling and improved sample retention. These findings agree with previous Irish research on the importance of screening intention, although its association with attitude appeared to be stronger in the present research. The findings further indicate that future screening promotion should consider interventions based on patients’ experiences of screening.

The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.

The Moderating Role of Personality on Workplace Conflict and Outcomes

The purpose of this study was twofold. The first was to further clarify and expand or understanding of the relationship between interpersonal conflict, incivility, and their roles as stressors in the stressor-strain relationship. The second goal was to examine how neuroticism, extraversion, agreeableness, conscientiousness, trait anger, and sphere specific locus of control moderate the stressor-strain relationship between task conflict, relationship conflict, incivility and workplace and health outcomes. The results suggest that extraversion, neuroticism, conscientiousness, agreeableness, trait anger, and locus of control play significant roles in how workplace aggression affects individuals. These findings suggest that occupations that experience a high level of workplace aggression should consider incorporating these personality traits into their selection system as a way of limiting or reducing the effects workplace aggression can have on individual health, wellbeing, and job outcomes.

Ethnogenesis and Craniofacial Change in Japan from the Perspective of Nonmetric Traits

To examine population affinities in light of the ‘dual structure model’, frequencies of 21 nonmetric cranial traits were analyzed in 17 prehistoric to recent samples from Japan and five from continental northeast Asia. Eight bivariate plots, each representing a different bone or region of the skull, as well as cluster analysis of 21-trait mean measures of divergence using multidimensional scaling and additive tree techniques, revealed good discrimination between the Jomon-Ainu indigenous lineage and that of the immigrants who arrived from continental Asia after 300 BC. In Hokkaido, in agreement with historical records, Ainu villages of Hidaka province were least, and those close to the Japan Sea coast were most, hybridized with Wajin. In the central islands, clines were identified among Wajin skeletal samples whereby those from Kyushu most resembled continental northeast Asians, while those from the northernmost prefectures of Tohoku apparently retained the strongest indigenous heritage. In the more southerly prefectures of Tohoku, stronger traces of Jomon ancestry prevailed in the cohort born during the latest Edo period than in the one born after 1870. Thus, it seems that increased inter-regional mobility and gene flow following the Meiji Restoration initiated the most recent episode in the long process of demic diffusion that has helped to shape craniofacial change in Japan.

De controller als Businesspartner. Hoe beïnvloeden persoonskenmerken de ontwikkeling naar "Partner in Business"binnen de afdeling Financiën bij de provincie Gelderland?

Bij de provincie Gelderland is per 01-01-2009 een reorganisatie doorgevoerd waarbij o.a. de ondersteunende disciplines zoals Financiën zijn samengevoegd binnen één centrale afdeling. Binnen de afdeling Financiën is een team ‘Business control’ gevormd waarin de Financieel adviseurs zijn ondergebracht. Daarbij is vanaf 2009, in verschillende termen en bewoordingen, steeds de ambitie uitgesproken om van de “Financieel expert” naar “Partner in business” te groeien. De ervaring tot dusver laat zien dat deze ambitie in de praktijk moeizaam te realiseren is. Dit onderzoek richt zich op verschillende facetten die samenhangen met bovengenoemde ambitie. Daarbij richt het onderzoek zich vooral op de vraag wat de invloed daarbij is van de persoonskenmerken van de medewerkers. De onderzoeksvraag is: Hoe beïnvloeden de persoonskenmerken de ontwikkeling naar “Partner in Business” bij het team Business control binnen de afdeling Financiën bij de provincie Gelderland? Uit het literatuuronderzoek blijkt dat New Public Management (NPM) een belangrijke externe ontwikkelingen is voor de publieke sector. NPM heeft als doel om publieke organisaties meer resultaatgericht, meer gecoördineerd en efficiënter te laten werken. Bij NPM gaat het o.a. om begrippen als resultaatgerichtheid, output en efficiency. Aangezien de controller het management adviseert bij het efficiënt realiseren van de organisatiedoelstellingen is NPM van invloed op de (rol van) de controller. Een verandering in de rol van de controller is ook het gevolg van de veranderingen in de financiële functie. Uit diverse onderzoeken blijkt dat de controllersfunctie zich ontwikkelt van een administratieve, ten behoeve van het top-management controlerende functie, naar een beslissingsondersteunende functie voor alle geledingen van het management. Conijn et al. (2005) beschrijven de ontwikkeling in de financiële functie aan de hand van een denkmodel met daarin vier fasen met de bijbehorende archetypes Scorekeeper, Financial controller, Managementcontroller en Businesspartner. Naast deze ontwikkelingen zijn ook persoonsgerelateerde factoren van invloed op de rol van een controller binnen een organisatie. Vanuit de organisatiepsychologie worden de persoonlijke eigenschappen van mensen dikwijls in vijf verschillende dimensies gevat, ook wel ‘the big five’ genoemd. Het big five factor model gaat ervan uit dat elk persoon in meer of mindere mate de volgende vijf persoonlijke dimensies heeft: Extraversie, Meegaandheid, Zorgvuldigheid, Openheid en Emotionele stabiliteit. De situatie bij de provincie Gelderland is onderzocht aan de hand van een enquête. De enquête is uitgezet bij de 28 Financieel adviseurs met 17 representatieve respondenten. Hieruit blijkt dat de Financieel adviseurs bij de provincie Gelderland voornamelijk activiteiten verrichten die horen bij de rol van Financial controller en in mindere mate die van respectievelijk Managementcontroller, Businesspartner en Scorekeeper. Daarbij beschikken de Managementcontrollers en de Businesspartners meer over de persoonskenmerken Extraversie, Openheid en Emotionele stabiliteit dan de Scorekeepers en Financial controllers. De Scorekeepers beschikken juist het minst over deze drie persoonskenmerken ten opzichte van de andere drie typen controllers. Voor wat betreft de persoonskenmerken Zorgvuldigheid en Meegaandheid laten de resultaten van de enquête geen eenduidig beeld zien in de relatie tot de typen controllers die de Financieel adviseurs vervullen. Op basis van dit onderzoek en met inachtneming van het aantal van 17 respondenten bij de enquête, lijkt er een relatie te zijn tussen de persoonskenmerken van controllers en de rol die zij als controller vervullen. De rol van Businesspartner vraagt blijkbaar om een hoge mate van Extraversie, Openheid en Emotionele stabiliteit. Voor de provincie Gelderland betekent dit concreet dat bij de gewenste ontwikkeling van Financieel expert naar Partner in business rekening gehouden moet worden met de persoonskenmerken van de Financieel adviseurs. Hierdoor kan er een goede aansluiting tot stand worden gebracht tussen de controller als persoon en zijn/haar controllersrol binnen de organisatie. Kortom; de juiste persoon op de juiste plaats.

Testing the psychometric properties of Kidscreen-27 with Irish children of low socio-economic status

Background

Kidscreen-27 was developed as part of a cross-cultural European Union-funded project to standardise the measurement of children’s health-related quality of life. Yet, research has reported mixed evidence for the hypothesised 5-factor model, and no confirmatory factor analysis (CFA) has been conducted on the instrument with children of low socio-economic status (SES) across Ireland (Northern and Republic).

Method

The data for this study were collected as part of a clustered randomised controlled trial. A total of 663 (347 male, 315 female) 8–9-year-old children (M = 8.74, SD = .50) of low SES took part. A 5- and modified 7-factor CFA models were specified using the maximum likelihood estimation. A nested Chi-square difference test was conducted to compare the fit of the models. Internal consistency and floor and ceiling effects were also examined.

Results

CFA found that the hypothesised 5-factor model was an unacceptable fit. However, the modified 7-factor model was supported. A nested Chi-square difference test confirmed that the fit of the 7-factor model was significantly better than that of the 5-factor model. Internal consistency was unacceptable for just one scale. Ceiling effects were present in all but one of the factors.

Conclusions

Future research should apply the 7-factor model with children of low socio-economic status. Such efforts would help monitor the health status of the population.

Influence des traits et troubles de personnalité sur l’intégration au travail de personnes aux prises avec un trouble mental grave

Bien que le travail soit bénéfique et souhaité par une majorité de personnes aux prises avec un trouble mental grave (TMG), les études réalisées auprès de cette clientèle montrent des taux d’emploi d’environ 10 à 20%. Parmi les services visant le retour au travail, les programmes de soutien à l’emploi (PSE) se sont montrés les plus efficaces avec des taux de placement en emploi standard oscillant entre 50 et 60%, sans toutefois garantir le maintien en emploi. Plusieurs études ont tenté de cerner les déterminants de l’obtention et du maintien en emploi chez cette population sans toutefois s’intéresser à la personnalité, et ce, bien qu’elle soit reconnue depuis toujours comme un déterminant important du fonctionnement des individus. De plus, peu de questionnaires d’évaluation de la personnalité selon le modèle de la personnalité en cinq facteurs (FFM) ont été utilisés auprès d’une clientèle avec un TMG et ceux-ci ont montré des propriétés psychométriques ne respectant pas des normes reconnues et acceptées. Cette thèse porte sur les liens entre la personnalité et l’intégration au travail chez les personnes avec un TMG. La première partie vise la validation d’un outil de mesure de la personnalité selon le FFM afin de répondre aux objectifs de la deuxième partie de la thèse. À cet effet, deux échantillons ont été recrutés, soit 259 étudiants universitaires et 141 personnes avec un TMG. Des analyses factorielles confirmatoires ont mené au développement d’un nouveau questionnaire à 15 items (NEO-15) dont les indices d’ajustement, de cohérence interne et de validité convergente respectent les normes établies, ce qui en fait un questionnaire bien adapté à la mesure de la personnalité normale dans des contextes où le temps d’évaluation est limité. La deuxième partie présente les résultats d’une étude réalisée auprès de 82 personnes aux prises avec un TMG inscrites dans un PSE et visant à identifier les facteurs d’obtention et de maintien en emploi chez cette clientèle, particulièrement en ce qui concerne la contribution des éléments normaux et pathologiques de la personnalité. Les résultats de régressions logistiques et de régressions de Cox (analyses de survie) ont démontré que l’historique d’emploi, les symptômes négatifs et le niveau de pathologie de la personnalité étaient prédictifs de l’obtention d’un emploi standard et du délai avant l’obtention d’un tel emploi. Une autre série de régressions de Cox a pour sa part démontré que l’esprit consciencieux était le seul prédicteur significatif du maintien en emploi. Malgré certaines limites, particulièrement des tailles d’échantillons restreintes, ces résultats démontrent la pertinence et l’importance de tenir compte des éléments normaux et pathologiques de la personnalité dans le cadre d’études portant sur l’intégration au travail de personnes avec un TMG. De plus, cette thèse a permis de démontrer l’adéquation d’un nouvel instrument de mesure de la personnalité auprès de cette clientèle. Des avenues futures concernant la réintégration professionnelle et le traitement des personnes avec un TMG sont discutées à la lumière de ces résultats.

Méthodes de Bootstrap pour les modèles à facteurs

Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement.

Estudo Preliminar das Propriedades Psicométricas do Inventário de Lateralidade de Edinburgh numa Amostra de Adultos da População Portuguesa

Introdução: A lateralidade é a diferença na capacidade de controlo entre os dois lados do corpo. Os métodos utilizados para avaliar a lateralidade manual incluem a observação efetiva do uso do membro dominante ou a aplicação de inventários respondidos pelo próprio indivíduo avaliado. O Inventário de Lateralidade de Edinburgh (EHI) é o instrumento mais utilizado para avaliar a lateralidade manual. Apesar do seu uso amplo, em Portugal não existem estudos que avaliem a sua validade e fidedignidade. Objetivos: Estudar as propriedades psicométricas do Inventário de Lateralidade de Edinburgh numa amostra da população portuguesa. Métodos: A amostra é constituída por 290 pessoas (135 homens e 155 mulheres), com idades compreendidas entre os 18 e os 65 anos. Todos os participantes preencheram uma declaração de consentimento informado e uma bateria de testes neuropsicológicos Resultados: A média no EHI foi de 62,36 (DP = 38,00). Os resultados demonstraram que das seis variáveis sociodemográficas (idade, sexo, escolaridade, zona de residência, regiões e profissão) três apresentaram ter influência significativa nas pontuações do EHI: idade, zona de residência e regiões. A confiabilidade e a estabilidade temporal do EHI apresentaram resultados adequados. A análise fatorial confirmatória mostrou que o modelo não é melhor explicado por um fator. Para dois fatores o modelo continua a não ser adequado. Conclusão: Apesar de termos obtido uma boa consistência interna não nos é possível considerar este teste como o mais adequado para medir o constructo da lateralidade. / Introduction: The handedness is the difference in the control capacity between the two sides of the body. The methods used to evaluate the manual handedness include the effective observation of the use of dominant member or application of inventories answered by the person assessed. The Edinburgh Handedness Inventory (EHI) is the most used to evaluate manual handedness. Even though being widely used, in Portugal there are no studies that measure its validity and reliability. Objective: To study the psychometric properties of Edinburgh Handedness Inventory in a Portuguese sample. Methods: The sample consists of 290 people (135 men and 155 women), aged between 18 and 65 years. All participants filled an informed consent form and a battery of neuropsychological tests. Results: The average in EHI was 62.36 (SD = 38.00). The results showed that 3 of 6 sociodemographic variables showed significant influence in EHI scores. The reliability and temporal stability of EHI were adequate. Confirmatory factor analysis showed that the model is not better explained by one factor. A two-factor model was not also suitable. Conclusion: Even though we got a good internal consistency we cannot consider this test as the most appropriate for measuring the handedness construct.

Estudo Preliminar das Propriedades Psicométricas e dos Dados Normativos da Forma Geral das Matrizes Progressivas de Raven numa Amostra da Comunidade

Objetivo: Estudar as propriedades psicométricas e os dados normativos da Forma Geral das Matrizes Progressivas de Raven numa amostra da comunidade da população portuguesa. Método: A amostra é constituída por 697 pessoas (314 homens e 383 mulheres), com idades compreendidas entre os 12 e os 90 anos. Todos os participantes preencheram uma declaração de consentimento informado e uma bateria de testes neuropsicológicos, incluindo a Forma Geral das Matrizes Progressivas de Raven (FG-MPR), Teste de Memória de 15-Item de Rey, Escala de Autoavaliação de Ansiedade de Zung, Bateria de Avaliação Frontal e Figura Complexa de Rey. Resultados: A média na FG-MPR foi de 44,47 (DP = 10,78). Os resultados demonstraram que todas as variáveis sociodemográficas (idade, sexo, escolaridade, profissão, regiões e tipologia de áreas urbanas), exceto o estado civil, apresentaram ter influência significativa nas pontuações da FG-MPR. A confiabilidade e a estabilidade temporal da FG-MPR revelaram-se adequadas. A análise fatorial exploratória e confirmatória mostrou que o modelo para um fator não é adequado. Um modelo a quatro fatores continua a não ser adequado. Conclusão: Os dados do presente estudo sugerem que se trata de um instrumento com potencialidades na sua utilização junto da população portuguesa. / Purpose: To study the psychometric properties and date normative of the Raven’s Standard Progressive Matrices in a Portuguese community sample. Method: The sample consists of 697 people (314 men and 383 women), aged between 12 and 90 years. All participants filled an informed consent form and a battery of neuropsychological tests, which included Raven’s Standard Progressive Matrices (RSPM), Rey 15-Item Memory Test, Zung Self-Rating Anxiety Scale, Frontal Assessment Battery, and Rey Complex Figure Test. Results: The average in RSPM was 44.47 (SD = 10.78). The results showed that all of the sociodemographic variables (age, sex, education, profession, region, and typology of urban areas), with the exception of civil status, showed significant influence on RSPM scores. The reliability and temporal stability of RSPM were adequate. Exploratory and Confirmatory factor analysis showed that the model is not better explained by one factor. A two-factor model was not also suitable. Conclusion: The data from this study suggest that it is an instrument with potential for its use among the Portuguese population.

Future Earnings Growth Volatility and the Value Premium

The value premium is well established in empirical asset pricing, but to date there is little understanding as to its fundamental drivers. We use a stochastic earnings valuation model to establish a direct link between the volatility of future earnings growth and firm value. We illustrate that risky earnings growth affects growth and value firms differently. We provide empirical evidence that the volatility of future earnings growth is a significant determinant of the value premium. Using data on individual firms and characteristic-sorted test portfolios, we also find that earnings growth volatility is significant in explaining the cross-sectional variation of stock returns. Our findings imply that the value premium is the rational consequence of accounting for risky earnings growth in the firm valuation process.