Estimating the Tobit Model with Serial Correlation: an Operational Approach

Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.

Gender-preferential intergenerational patterns in primary education attainment : a quantitative analysis of a case of rural Mindanao, the Philippines

The Philippines has achieved a relatively high standard of education. Previous researches, most of which deal with Luzon Island, have indicated that rural poverty alleviation began partly due to the increased investment in education. However, the suburban areas beyond Luzon Island have rarely been studied. This study examines a case from rural Mindanao, and investigates the determinants and factors associated with children's education, with a special focus on delays in schooling, which may be a cause of dropout and holdover incidences, as well as exploring gender-specific differential patterns. The result shows that after controlling other socioeconomic attributes, (1) delays in schooling, as well as years completed, are more favorable for girls than boys; (2) the level of maternal education is equally associated with the child(ren)’s education level regardless of their gender; and (3) paternal education is preferentially and favorably influential to the same-gender child(ren), i.e., son(s). To reduce the boy-unfriendly gender bias in primary education, this study suggests two future tasks, i.e., providing boy-specific interventions to enhance the magnitude of the father-son educational virtuous circle, and comparing the magnitude of gender-equal maternal education influence and boy-preferential paternal education influence to specify which effect is larger.

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

Size-composition of Annual Landings in the White Shrimp, Litopenaeus setiferus, Fishery of the Northern Gulf of Mexico, 1960–2006: Its Trend and Relationships with Other Fishery-dependent Variable

The potential for growth overfishing in the white shrimp, Litopenaeus setiferus, fishery of the northern Gulf of Mexico appears to have been of limited concern to Federal or state shrimp management entities, following the cataclysmic drop in white shrimp abundance in the 1940’s. As expected from surplus production theory, a decrease in size of shrimp in the annual landings accompanies increasing fishing effort, and can eventually reduce the value of the landings. Growth overfishing can exacerbate such decline in value of the annual landings. We characterize trends in size-composition of annual landings and other annual fishery-dependent variables in this fishery to determine relationships between selected pairs of these variables and to determine whether growth overfishing occurred during 1960–2006. Signs of growth overfishing were equivocal. For example, as nominal fishing effort increased, the initially upward, decelerating trend in annual yield approached a local maximum in the 1980’s. However, an accelerating upward trend in yield followed as effort continued to increase. Yield then reached its highest point in the time series in 2006, as nominal fishing effort declined due to exogenous factors outside the control of shrimp fishery managers. The quadratic relationship between annual yield and nominal fishing effort exhibited a local maximum of 5.24(107) pounds (≈ MSY) at a nominal fishing effort level of 1.38(105) days fished. However, annual yield showed a continuous increase with decrease in size of shrimp in the landings. Annual inflation-adjusted ex-vessel value of the landings peaked in 1989, preceded by a peak in annual inflation-adjusted ex-vessel value per pound (i.e. price) in 1983. Changes in size composition of shrimp landings and their economic effects should be included among guidelines for future management of this white shrimp

The dependent variable problem in quantitative studies of Active Labour Market Programmes: uncovering hidden dynamics?

The question of what explains variation in expenditures on Active Labour Market Programs (ALMPs) has attracted significant scholarship in recent years. Significant insights have been gained with respect to the role of employers, unions and dual labour markets, openness, and partisanship. However, there remain significant disagreements with respects to key explanatory variables such the role of unions or the impact of partisanship. Qualitative studies have shown that there are both good conceptual reasons as well as historical evidence that different ALMPs are driven by different dynamics. There is little reason to believe that vastly different programs such as training and employment subsidies are driven by similar structural, interest group or indeed partisan dynamics. The question is therefore whether different ALMPs have the same correlation with different key explanatory variables identified in the literature? Using regression analysis, this paper shows that the explanatory variables identified by the literature have different relation to distinct ALMPs. This refinement adds significant analytical value and shows that disagreements are at least partly due to a dependent variable problem of ‘over-aggregation’.

A Note on Proxy Variables and Instrument Variable Regression

This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

Time-dependent vascular regression and permeability changes in established human tumor xenografts induced by an anti-vascular endothelial growth factor/vascular permeability factor antibody

The hyperpermeability of tumor vessels to macromolecules, compared with normal vessels, is presumably due to vascular endothelial growth factor/vascular permeability factor (VEGF/VPF) released by neoplastic and/or host cells. In addition, VEGF/VPF is a potent angiogenic factor. Removal of this growth factor may reduce the permeability and inhibit tumor angiogenesis. To test these hypotheses, we transplanted a human glioblastoma (U87), a human colon adenocarcinoma (LS174T), and a human melanoma (P-MEL) into two locations in immunodeficient mice: the cranial window and the dorsal skinfold chamber. The mice bearing vascularized tumors were treated with a bolus (0.2 ml) of either a neutralizing antibody (A4.6.1) (492 μg/ml) against VEGF/VPF or PBS (control). We found that tumor vascular permeability to albumin in antibody-treated groups was lower than in the matched controls and that the effect of the antibody was time-dependent and influenced by the mode of injection. Tumor vascular permeability did not respond to i.p. injection of the antibody until 4 days posttreatment. However, the permeability was reduced within 6 h after i.v. injection of the same amount of antibody. In addition to the reduction in vascular permeability, the tumor vessels became smaller in diameter and less tortuous after antibody injections and eventually disappeared from the surface after four consecutive treatments in U87 tumors. These results demonstrate that tumor vascular permeability can be reduced by neutralization of endogenous VEGF/VPF and suggest that angiogenesis and the maintenance of integrity of tumor vessels require the presence of VEGF/VPF in the tissue microenvironment. The latter finding reveals a new mechanism of tumor vessel regression—i.e., blocking the interactions between VEGF/VPF and endothelial cells or inhibiting VEGF/VPF synthesis in solid tumors causes dramatic reduction in vessel diameter, which may block the passage of blood elements and thus lead to vascular regression.

An illustration of variable precision rough sets model:an analysis of the findings of the UK Monopolies and Mergers Commission

This paper introduces a new technique in the investigation of limited-dependent variable models. This paper illustrates that variable precision rough set theory (VPRS), allied with the use of a modern method of classification, or discretisation of data, can out-perform the more standard approaches that are employed in economics, such as a probit model. These approaches and certain inductive decision tree methods are compared (through a Monte Carlo simulation approach) in the analysis of the decisions reached by the UK Monopolies and Mergers Committee. We show that, particularly in small samples, the VPRS model can improve on more traditional models, both in-sample, and particularly in out-of-sample prediction. A similar improvement in out-of-sample prediction over the decision tree methods is also shown.

Microfinance, Efficiency and Agricultural Production in Bangladesh

The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

Essays in taxation and savings

Esta tese é composta por três artigos. Dois deles investigam assuntos afeitos a tributação e o terceiro é um artigo sobre o tema “poupança”'. Embora os objetos de análise sejam distintos, os três possuem como característica comum a aplicação de técnicas de econometria de dados em painel a bases de dados inéditas. Em dois dos artigos, utiliza-se estimação por GMM em modelos dinâmicos. Por sua vez, o artigo remanescente é uma aplicação de modelos de variável dependente latente. Abaixo, apresenta-se um breve resumo de cada artigo, começando pelos dois artigos de tributação, que dividem uma seção comum sobre o ICMS (o imposto estadual sobre valor adicionado) e terminando com o artigo sobre poupança. O primeiro artigo analisa a importância da fiscalização como instrumento para deter a evasão de tributos e aumentar a receita tributária, no caso de um imposto sobre valor adicionado, no contexto de um país em desenvolvimento. O estudo é realizado com dados do estado de São Paulo. Para tratar questões relativas a endogeneidade e inércia na série de receita tributária, empregam-se técnicas de painel dinâmico. Utiliza-se como variáveis de controle o nível do PIB regional e duas proxies para esforço fiscal: a quantidade e o valor das multas tributárias. Os resultados apontam impacto significativo do esforço fiscal nas receitas tributárias. O artigo evidencia, indiretamente, a forma como a evasão fiscal é afetada pela penalidade aplicada aos casos de sonegação. Suas conclusões também são relevantes no contexto das discussões sobre o federalismo fiscal brasileiro, especialmente no caso de uma reforma tributária potencial. O segundo artigo examina uma das principais tarefas das administrações tributárias: a escolha periódica de contribuintes para auditoria. A melhora na eficiência dos mecanismos de seleção de empresas tem o potencial de impactar positivamente a probabilidade de detecção de fraudes fiscais, provendo melhor alocação dos escassos recursos fiscais. Neste artigo, tentamos desenvolver este mecanismo calculando a probabilidade de sonegação associada a cada contribuinte. Isto é feito, no universo restrito de empresas auditadas, por meio da combinação “ótima” de diversos indicadores fiscais existentes e de informações dos resultados dos procedimentos de auditoria, em modelos de variável dependente latente. Após calculados os coeficientes, a probabilidade de sonegação é calculada para todo o universo de contribuintes. O método foi empregado em um painel com micro-dados de empresas sujeitas ao recolhimento de ICMS no âmbito da Delegacia Tributária de Guarulhos, no estado de São Paulo. O terceiro artigo analisa as baixas taxas de poupança dos países latino-americanos nas últimas décadas. Utilizando técnicas de dados em painel, identificam-se os determinantes da taxa de poupança. Em seguida, faz-se uma análise contrafactual usando a China, que tem apresentado altas taxas de poupança no mesmo período, como parâmetro. Atenção especial é dispensada ao Brasil, que tem ficado muito atrás dos seus pares no grupo dos BRICs neste quesito. O artigo contribui para a literatura existente em vários sentidos: emprega duas amplas bases de dados para analisar a influência de uma grande variedade de determinantes da taxa de poupança, incluindo variáveis demográficas e de previdência social; confirma resultados previamente encontrados na literatura, com a robustez conferida por bases de dados mais ricas; para alguns países latino-americanos, revela que as suas taxas de poupança tenderiam a aumentar se eles tivessem um comportamento mais semelhante ao da China em outras áreas, mas o incremento não seria tão dramático.

Association between parental guilt and oral health problems in preschool children

Parents may feel guilty about their children's oral problems, which can affect their quality of life. The aim of this study was to assess the presence of parental guilt and its association with early childhood caries (EGG), traumatic dental injuries (TDI) and malocclusion (AMT) in preschool children. All 2 to 5 year-old children (N = 305), and their parents, seeking dental care at the University of Sao Paulo Dental School one-week Screening Programme, were asked to participate in the study, and 260 agreed. Children were examined by two calibrated dentists, and their parents answered a socioeconomic and ECOHIS questionnaire; the question on guilt was used as the dependent variable. Regression analyses examined the association between parental guilt and EGG, TDI, AMT and socioeconomic factors. A total of 35.8% of parents felt guilty. This was only associated with caries severity. No association was found between guilt and TDI, AMT or socioeconomic factors. EGG was present in 63.8% of the children; the mean (+/-sd) dmf-t score was 7.29 (+/-2.78). Thus, the number of parents feeling guilty increases with the increase of their children's dental caries severity. Parental guilt is related to caries but is not associated with TDI or AMT.

Association between parental guilt and oral health problems in preschool children

Parents may feel guilty about their children's oral problems, which can affect their quality of life. The aim of this study was to assess the presence of parental guilt and its association with early childhood caries (ECC), traumatic dental injuries (TDI) and malocclusion (AMT) in preschool children. All 2 to 5 year-old children (N = 305), and their parents, seeking dental care at the University of São Paulo Dental School one-week Screening Programme, were asked to participate in the study, and 260 agreed. Children were examined by two calibrated dentists, and their parents answered a socioeconomic and ECOHIS questionnaire; the question on guilt was used as the dependent variable. Regression analyses examined the association between parental guilt and ECC, TDI, AMT and socioeconomic factors. A total of 35.8% of parents felt guilty. This was only associated with caries severity. No association was found between guilt and TDI, AMT or socioeconomic factors. ECC was present in 63.8% of the children; the mean (± sd) dmf-t score was 7.29 (± 2.78). Thus, the number of parents feeling guilty increases with the increase of their children's dental caries severity. Parental guilt is related to caries but is not associated with TDI or AMT.

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^