Cross-Domain Multitask Learning with Latent Probit Models

Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain transforms, and the shared probit classifier in the common domain. To learn meaningful task relatedness and avoid over-fitting in classification, we introduce sparsity in the domain transforms matrices, as well as in the common classifier. We derive theoretical bounds for the estimation error of the classifier in terms of the sparsity of domain transforms. An expectation-maximization algorithm is derived for learning the LPM. The effectiveness of the approach is demonstrated on several real datasets.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

La perspectiva de género en el análisis de la satisfacción laboral: una aplicación empírica mediante modelos logit y probit

[ES] La influencia que las características individuales del personal de una empresa ejercen sobre su nivel de satisfacción laboral ha sido ampliamente analizada en la literatura al respecto, dedicando una especial atención a la variable edad pero también al género como un elemento determinante de los niveles de satisfacción de los recursos humanos. En numerosas investigaciones se constata que las mujeres presentan un nivel superior de satisfacción al de los varones.

Forecasting UK real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.

Intellectual property and competition as complementary policies: a test using an ordered probit model

Este Artigo Testa a Proposição da Teoria Econômica de que Propriedade Intelectual e Defesa da Concorrência são Políticas Complementares. um Modelo Probit Ordenado é Utilizado para Estimar os Efeitos Marginais do Uso e Qualidade do Enforcement dos Direitos de Propriedade Intelectual em uma Medida da Gravidade dos Problemas Relacionados À Concorrência. os Resultados Obtidos Reforçam a Noção de que as Políticas de Concorrência e Propriedade Intelectual não são Contraditórias.

Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

Application of a Bivariate Probit Model to Investigate the Intended Evacuation from Hurricane

With evidence of increasing hurricane risks in Georgia Coastal Area (GCA) and Virginia in the U.S. Southeast and elsewhere, understanding intended evacuation behavior is becoming more and more important for community planners. My research investigates intended evacuation behavior due to hurricane risks, a behavioral survey of the six counties in GCA under the direction of two social scientists with extensive experience in survey research related to citizen and household response to emergencies and disasters. Respondents gave answers whether they would evacuate under both voluntary and mandatory evacuation orders. Bivariate probit models are used to investigate the subjective belief structure of whether or not the respondents are concerned about the hurricane, and the intended probability of evacuating as a function of risk perception, and a lot of demographic and socioeconomic variables (e.g., gender, military, age, length of residence, owning vehicles).

The effects of linguistic factors on student performance on economics multiple choice questions

This paper proposes a framework to analyse performance on multiple choice questions with the focus on linguistic factors. Item Response Theory (IRT) is deployed to estimate ability and question difficulty levels. A logistic regression model is used to detect Differential Item Functioning questions. Probit models testify relationships between performance and linguistic factors controlling the effects of question construction and students’ background. Empirical results have important implications. The lexical density of stems affects performance. The use of non-Economics specialised vocabulary has differing impacts on the performance of students with different language backgrounds. The IRT-based ability and difficulty help explain performance variations.

Superstars and disloyal football fans : factors influencing attraction to competition

Purpose – The purpose of this paper is to examine the effect of superstars (and other factors) on football fans’ attraction to competition (i.e. disloyal behavior). Design/methodology/approach – A proprietary data set including archival data on professional German football players and clubs as well as survey data of more than 900 football fans is used. The hypotheses are tested with two-sample mean-comparison t-tests and multivariate probit models. Findings – This study provides evidence that superstars both attract new fans and contribute to the retention of existing fans. While the presence of superstars, team loyalty and team identification prevent football fans from being attracted to competition, the team's recent performance seems to have no effect. Fans who select their favorite player from a competing team rather choose superstars, young players, players who are known for exemplary behavior and defenders. Originality/value – This paper contributes to existing research by expanding the list of antecedents of disloyalty and by being the first to employ independent, quantitative data for the assessment of superstar characteristics in the context of team loyalty.

Health expenditures in the OECD: A political economy analysis using structural breaks

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Uptake of agri-environmental schemes in the Less-Favoured Areas of Greece: The role of corruption and farmers' responses to the financial crisis

Vine-growing in the Less-Favoured Areas of Greece is facing multiple challenges that might lead to its abandonment. In an attempt to maintain rural populations, Rural Development Schemes have been created that offer the opportunity to rural households to maintain or expand their farming businesses including vine-growing. This paper stems from a study that used data from a cross-sectional survey of 204 farmers to investigate how farming systems and farmers’ perception of corruption, amongst other socio-economic factors, affected their decisions to continue vine-growing through participation in Rural Development Schemes, in three remote Less-Favoured Areas of Greece. The Theory of Planned Behaviour was used to frame the research problem with the assumption being that an individual’s intention to participate in a Scheme is based on their prior beliefs about it. Data from the survey were reduced and simplified by the use of non-linear principal component analysis. The ensuing variables were used in selectivity corrected ordered probit models to reveal farmers’ attitudes towards viticulture and rural development. It was found that economic factors, perceived corruption and farmers’ attitudes were significant determinants on whether to participate in the Schemes. The research findings highlight the important role of perceived corruption and the need for policies that facilitate farmers’ access to decision making centres.

Mudanças no rural nordestino: uma análise dos determinantes da pluriatividade nas famílias rurais nordestinas, no ano de 2011

This study aims to the evaluate the determinants for rural households northeastern be pluriactive, in 2011. For this, at first, we conducted a review of national and international literature in order to get beyond the theoretical part which refers to the study of pluriactivity identify possible determinants of the phenomenon. In this rescue, it was the observed determinants could be macroeconomic in nature and / or microeconomics. Therefore, it became necessary to describe the characteristics of the region under study, the Northeast. In order to identify the determinants were two estimated Probit models, one based on the literature review and the second with a variable characteristic of the Northeast, the transfers. For this, we used the PNAD in 2011. The results indicate both the microeconomic determinants are : gender, race, age, years of education, hours worked, number of family members, per capita income, transfer the macroeconomic in nature: living conditions (water, energy, sanitation ), housing location. In addition to identifying the determinants, the Econometric model allows to know the probability of each variable on the dependent variable, which stood out: the transfer variable, gender, per capita income, number of family members, housing conditions and housing location. Therefore, it is concluded that it is the set of determinants (macro and micro) allow rural families become northeastern pluriactive. However, one can not fail to consider may also have other determinants were not captured due to the availability of data, which may be indications for future studies. In summary, the pluriactivity in the Brazilian Northeast is a phenomenon distinct from found in Europe and southern Brazil. It is a pluriactivity survival that is part of the strategies of rural households in the Northeast to ensure their social reproduction amid the poverty of the region

Modelos lineares generalizados mistos na avaliação genética da prenhez precoce na raça Nelore

This study aimed to use the generalized linear models with probit and logit link function to evaluate early pregnancy, and to observe the effects on genetic variability and on sire selection when different ages are adopted in the definition of this trait. Early pregnancy was studied at 15 (EP15), and 21 (EP21) months. The analysis was done in R software. Pearson correlations (PC), between genetic predicted values and percentage of bulls in common considering only 10% of bulls with higher genetic values (TOP 10), between classification by logit and probit models and in each model among EP15 and EP21, were calculated. The heritability for EP15 and EP21 were close between models, except for EP15 using probit link function. PC and TOP10 among models were high. The Akaike and Bayesian criteria reported was similar between models. TOP10, considering the same model, among EP15-EP21 were moderated between EP15-EP21.

Ecuador: return from migration and entrepreneurship in Loja

Drawing on data from a survey of returning migrants, this study examines the factors behind the decision to launch a business in Loja, Ecuador. The possible explanations fall under various headings: demographic characteristics, work experience abroad, reasons for returning, current situation, intention to re-emigrate, and activity before, during and after migration. The study also considers different concepts of “entrepreneur”, as own-account worker and as employer. The results are analysed, first, using univariate tests and then estimating probit models. The variables most closely associated with a high probability of starting a business after returning from migration are entrepreneurial experience during the migration, and the fact of having returned voluntarily, as well as having worked in the host country in agriculture or the hospitality sector. Having university training and having worked in public administration before migrating are negative factors. Other influential variables are age and the wage or salary received abroad, but these are more nuanced.

Latent residual analysis in binary regression with skewed link

Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset.