Motivated by the increasing popularity of wildlife viewing and a growing emphasis on management for nontimber outputs, wildlife viewing demand was assessed. Specific objectives included determining factors affecting participation and frequency of use, and furthermore, deriving 2006 nationwide wildlife viewing consumer surplus estimates. With the travel cost method as the theoretical basis, the empirical estimation method employed was a two-step sample selection model that included a probit first step and a negative binomial second step. Consumer surplus per trip estimates ranged from $215.23 to $739.07 while aggregate national estimates ranged from $44.5 billion to $185.1 billion. Results reveal that age, race, and urban residence affect participation and frequency similarly. This research can help policymakers in particular better understand determinants of wildlife viewing participation and frequency. The value of wildlife viewing access can be used to justify funding initiatives aimed at protecting or managing for this use.

While worker flow analysis has grown in importance in many countries, Austria still lacks a specific longitudinal dataset as a prerequisite to perform similar analyses. For this reason, this article provides a coherent procedure to construct a longitudinal dataset based on the rotational panel structure of the Austrian quarterly LFS from 2004 to 2014. The procedure, which is available for researcher, is grounded on the discussion of several related and important issues inherent in constructing this sort of longitudinal data: First, it deals with the construction of the quarterly-matched dataset and the quality-of-measurement of several labour market variables. Second, the paper analyses non-response as a sample selection process, and shows that the selected (quarterly-matched) dataset causes biased estimates of worker flows. Third, the article proposes an iterative raking procedure to obtain survey weights as a bias-correcting device for any future analysis. Based on these adjustments, we present unbiased time-series of worker flows and transition rates, and conclude that the employment-unemployment margin is highly sensitive to economic shocks and that the Austrian labour market is additionally shaped by large movements within the participation margin. (authors' abstract) / Series: Department of Economics Working Paper Series

Thesis advisor: Arthur Lewbel / This thesis proposes two semiparametric estimators; one for heavily censored panel models and another one for binary-outcome sample selection models. The first chapter proposes a new panel data estimator, and applies it to investigate whether the key assumption underlying most twin studies is valid. Roughly, the assumption is that differences in twins' outcomes can on average be attributed to differences in observed treatments, possibly after conditioning on observable covariates. The empirical results here cast doubt on this assumption, by showing that a particular outcome, survival, varies by birth order, even after conditioning on health-at-birth characteristics. The proposed panel data estimator is the first one in the literature that simultaneously handles having an unknown error distribution, fixed effects, fixed T, fixed censoring point, and heavy (greater than 50%) censoring. These features are all required to adequately deal with the limitations of available census data on twins. The proposed estimator also allows for coefficients that vary by t, and for a censoring point that is an unknown but deterministic function of regressors. The second chapter proposes a new semiparametric estimator for binary-outcome selection models that does not impose any distributional assumption, nor specify the selection equation. The estimator, however, requires a special regressor satisfying a support restriction in the outcome equation and a variable satisfying the exclusion/inclusion restriction; the former should be continuous whereas the latter can be discrete. The estimators of Klein et al. (2011) and Escanciano et al. (2012) require optimization, but our estimator for the outcome equation has a closed-form expression with no need for any optimization (but the selection equation estimation may still need an optimization). We apply MLE and the proposed estimator to US presidential election data in 2008 and 2012 where Barack Obama won to see to what extent racism mattered; we use a prejudice variable as a measure of racism. Putting our empirical findings in advance, there is evidence that the white Democrats voted less for Obama due to prejudice, whereas the white Republicans acted in a more muted fashion (i.e., almost no change in voting due to racism) or voted more for Obama to escape the stigma of racism. We also found evidence of "own-race favor" by blacks. / Thesis (PhD) — Boston College, 2014. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

The current state-of-the-art, in terms of performance, for solving document image binarization is training artificial neural networks on pre-labelled ground truth data. As such, it faces the same issues as other, more conventional, classification problems; requiring a large amount of training data. However, unlike those conventional classification problems, document image binarization involves having to either manually craft or estimate the binarized ground truth data, which can be error-prone and time-consuming. This is where sample selection, the act of selecting training samples based on some method or metric, might help. By reducing the size of the training dataset in such a way that the binarization performance is not impacted, the required time spent creating the ground truth is also reduced. This thesis proposes a cluster-based sample selection method, based on previous work, that uses image similarity metrics and the relative neighbourhood graph to reduce the underlying redundancy of the dataset. The method is implemented with different clustering methods and similarity metrics for comparison, with the best implementation being based on affinity propagation and the structural similarity index. This implementation manages to reduce the training dataset by 46\% while maintaining a performance that is equal to that of the complete dataset. The performance of this method is shown to not be significantly different from randomly selecting the same number of samples. However, due to limitations in the random method, such as unpredictable performance and uncertainty in how many samples to select, the use of sample selection in document image binarization still shows great promise.

This thesis examines inequality of educational opportunities (IEO) in the transition to higher education. IEO measures the difference in higher education entry rates across social groups. The theoretical framework lays on Boudon's decomposition of IEO into primary and secondary effects of stratification. Furthermore, the theoretical propositions of Maximally Maintained Inequality (MMI) and Effectively Maintained Inequality (EMI) were also assessed to gain further understanding of IEO. The longitudinal data for the empirical analysis was created for a student cohort by linking administrative records of Chile's national student register, standardised tests and higher education enrolment. The student cohort was followed through the 12-years of compulsory education up to the transition to higher education, a year after completing secondary education. The results from the empirical analysis showed that secondary effects were consistently predominant over primary effects, driving the overall IEO. On the other hand, controlling for school characteristics increased the relative importance of secondary effects. However, primary effects explained a large extent of IEO in the transition to traditional (most prestigious) universities, by the same token, in the transition to undergraduate programmes. Differences in parental education levels between secondary education completion and higher education transitions proved to be consistent with MMI. Likewise, the higher likelihood of less advantaged students to enrol in vocational colleges or vocational programmes, and the higher likelihood of advantaged students to enrol in traditional universities or undergraduate programmes, evidenced support for EMI. The modelling setting was based on non-linear mediation modelling, accounting for sample-selection in the student cohort, two-level cross-classification between primary and secondary schools, and multinomial outcomes for type of institution and programme. This thesis contributes to the educational attainment literature by finding evidence that, in emerging economies like Chile, educational inequality persists despite the sustained expansion of the educational system.

Consumer expenditure on food away from home in the United States has grown substantially in recent decades. Changes in the food service system, increased complexity of family structure, and the food policies made by government agencies have continued to influence the marketing, distribution, retailing, and demand for food products and the food industry. This study explores consumption behavior on food away from home (FAFH) and determines the differentiated impacts of economic and demographic variables on FAFH by type of meal and by type of facility among different household types. Each of the two systems of expenditures is estimated with two alternative econometric procedures to accommodate censoring in the dependent variables: the trivariate Tobit estimator and the multivariate sample selection estimator. Data for this study come from the 2008 and 2009 Consumer Expenditure Surveys, the most recent U.S. national household expenditure surveys conducted by the Bureau of Labor Statistics. Joint statistical significance of error correlations among equations justifies estimation of the sample selection systems. The opposite marginal effects on probabilities and expenditure levels of some variables highlight the advantage of the sample selection system over the Tobit system. Segmentation of the sample by household types is also justified with formal statistical tests. The empirical results indicate that the effects of demographic and socioeconomic factors on FAFH consumption vary by type of meal and by type of facility. Income, work hours, race, education, geographical region, and household composition are important factors. Food stamps have no impact on FAFH for married couples without children and single parenthood has conflicting effects on probabilities and conditional levels of expenditures.

Univ., Diss.--Genève, 2007.

Conducting representative surveys of older people is challenging. This thesis aims to analyze a) the characteristics of individuals at risk of being underrepresented in surveys of older people, b) the systematic errors likely to occur as a result of these selections, and c) whether these systematic errors can be minimized by weighting adjustments.   In Study I, we investigated a) who would be missing from a survey that excluded those living in institutions and that did not use indirect interviews, b) how prevalence rates would be affected by these exclusions, and c) whether post-stratifying the data by sex and age (weighting adjustment) would correct for any systematic measurement error. In Study II, we compared mortality and hospitalization rates in those who responded to a postal questionnaire with rates in the target population. In addition, we tested whether a weighting variable created with a number of auxiliary variables could correct for the differences.   In Study III, we followed a longitudinal cohort sample for 43 years. By recalculating baseline characteristics at each follow-up, we investigated how the sample changed after a) selective mortality and b) survey non-participation. In Study IV, we investigated whether the systematic non-participation that is likely to occur in surveys of older people affects the association between education and health. In sum, the results of these four studies show that people in the oldest age groups, women, those of low socioeconomic position, and those with the poorest health tend to be underrepresented in surveys of older people. This systematic underrepresentation might lead to an underestimation of poor health and function, a bias that is unlikely to be corrected by weighting adjustments, and to an underestimation of health inequality between educational groups. The results also show that the selective mortality that occurs in longitudinal samples might be compounded by selective non-participation among the most disadvantaged groups. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Manuscript.</p>

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Esse trabalho traz os resultados do retorno salarial de se investir em educação no Brasil e desagregado para cada Estado da Unidade da Federação. Diferentes técnicas econométricas foram estimadas, como Mincer, Mincer Adaptado, Método de Variáveis Instrumentais, Método de Heckman e por fim Metodologia de Hansen (2000) que permite inovar a idéia de não linearidade na equação de rendimento proposta por Jaccob Mincer estimada de forma endógena. A analise empírica foi feita com base nas PNAD´s de 2001 a 2008 com dados em dados cross-section. Os resultados apresentados diferenciam em magnitude de cada método econométrico utilizado em destaque o Método de Hansen que permitiu identificar limiares em que o retorno de se investir em educação muda a partir de certo nível de escolaridade quebrada a hipótese de linearidade. Implicando que a não consideração de tal hipótese pode acabar distorcendo a compreensão da função que a educação em si exerce, por exemplo, na distribuição de renda. / This paper presents the results of the wage return of investing in education in Brazil and the disaggregated for each member of the Office of the Federation. Others Different from econometric were estimated as Mincer, Mincer Adapted, All Variable Instrumental, Method of Heckman and finally Methodology Hansen (2000) to innovation to go from no linearity in the equation the revenue proposed by Mincer Jaccob estimated and endogen. The analysis empiric was based on PNAD´s from 2001 to 2008 data with data in cross-section. The presented results differ in magnitude for each method used econometric highlighted the method of which Hansen identified thresholds at which the return of investing in education change it from a certain point of education to broken hypothesis linearity. Implying that if consideration in such a hypothesis can end up distorting the understanding of the function what education the exercise it, for example, distribution the income.