The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is one of the food assistance programs targeted at low-income women, infants and children up to age five by providing foods, nutrition education and other services. Recent updates in food packages provided by WIC include the addition of fruits, vegetables and whole wheat products as well as the removal of whole milk for women and children two years and older. This thesis concentrates on preschool children participants in the WIC program and their milk consumption habits prior to programmatic changes. Analyzing diet preferences of these children is crucial since a quarter of the population of children aged one thorough five participates in the WIC program; as well, they are not eligible to receive whole milk with WIC food packages after the implementation of revisions. The objective is to describe the profile of preschool WIC children and their milk consumption attributes based on the National Food and Nutrition (NATFAN) questionnaire designed and conducted by the Institute for Obesity Research and Program Evaluation at Texas A & M University before the release of the revised WIC food packages. Additionally, findings of the study are compared with the National Health and Nutrition Examination Survey (NHANES) 2005-2006 dataset results. Milk consumption preferences of WIC children are analyzed nationwide and impacts of race, ethnicity, regional, and other demographic characteristics are observed. Using both NATFAN and NHANES datasets provides a comparison of actual and self-reported participation outcomes. Discrete choice models were used in this analysis, in particular binary logit and multinomial logit models. The results of the thesis indicate that WIC preschool children mostly drink whole milk (36.17 percent) and 2 percent fat milk (49.94 percent). Two year old participants, children located in the South and participants whose caregivers are younger and less educated are more likely to consume whole milk. Caucasian children are less likely to choose whole milk and more likely to choose reduced fat milk; African Americans are more likely to select whole milk. Furthermore, diet preferences and knowledge of parents/caregivers play a major role on milk consumption of children. Children whose caregivers are willing to give low-fat milk to children aged two to five are less likely to drink whole milk.

Discrete choice models form a class of models widely used in econometrics for modelling the individual choice from a finite set of alternatives. The most widely used model is the multinomial logit model, implicitly assuming independence of irrelevant alternatives. A generalization is the nested multinomial logit model, relaxing this strong assurnp tion. Viewing both models as nonlinear regression models a set of diagnostics is derived. This includes a hat matrix, measures of leverage, influence and residuals and an approximation to the parameters for case deletion. In an example for the multinomid logit model a good performance of these diagnostics is observed and the parameter approximation by the proposed formula is better than a one step Newton-Raphson procedure. In an example for the nested logit model a constructed outlier with high influence is revealed by the measures of leverage and residual, but the parameter approximation is insufficient. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

"Cross-Border Contagion in the Banking Sector: The Case of Nordic Countries" by Lina Baronaite Abstract: The objective of the thesis is to estimate the degree of cross-border contagion among the Nordic banking sectors. It analyzes a sample of sixteen largest listed Nordic banks from January 2004 to January 2014. Using a multinomial logit model we test whether there is any degree of contagion among the four banking sectors, whether it is more pro- nounced for larger banks and whether the recent financial crisis has exacerbated it. Our results are in line with similar studies conducted for other countries. In particular, we find that a shock in one bank- ing sector is positively associated with an increase in shocks in another banking sector. Second, these shocks are larger and more significant for larger and more active international banks. Finally, the effect of the recent financial crisis has ambiguous effects on the cross-sectoral banking contagion. It appears that contagious links between some sec- tors weakened (Sweden and Denmark, Sweden and Finland). Other economies (Sweden and Norway) on the contrary became more depen- dent on each other. The results are robust to a wide variety of changes in specifications.

The purpose of this paper is to investigate how individuals with different characteristics make their choice-decisions when consuming STIGA table tennis blades, which are combinations of various attributes, such as price, control, attack, etc. It is expected that the general trend of choice behavior on this special commodity can be, at least to some extent, revealed. Data were collected using questionnaires sent to registered members of a table tennis club in China. The questionnaires included information and questions about individuals’ monthly income levels, ages, technique styles, etc. A multinomial logit model was then applied to analyze factors determining Chinese consumers’ choice behavior on STIGA table tennis blades. The results indicated that the main element influencing Chinese consumers’ choice of STIGA ping-pong blades was the technique style and other variables did not seem to influence the choice of table tennis blades. These results might be explained by the limited sample size as well as unmeasured and immeasurable factors. Thus, a more extensive research is needed to be conducted in the future.

This dissertation contains two essays on the effect of welfare reform on child- birth, marriage, and divorce. In the first essay, I exploit the cross state variation in welfare reform implementation to identify its effect on birth rates. The results from multinomial logit models suggest that the welfare reform significantly increased the probability of marital births. The out-of-wedlock birth rates decreased but this effect is not significant. The strong work incentives decrease birth rates in both marital and non-marital statuses suggesting that bearing a child is not appealing for women who are more progressive in careers. However, the most aggressive welfare policy significantly increases marital birth as expected. Birth rates among teenage girls are not affected by the welfare reform. I further investigate the effect of the family cap policy. Using a semi-natural experiment, I compare the birth rate of women who already have had a second or higher order birth (treatment group) to women who have had one child (comparison group), in states with and without family caps. The difference in difference estimates reveal a strictly negative effect of family caps on the higher order birth rates as expected. In the second essay, I use reduced-form estimation and cross-state variation in timing of reform adoption to extract both mechanical and behavioral effects of welfare reform on marriage and divorce likelihood. I construct a flow measure of marriage and divorce by matching individuals in the Current Population Survey from March 1988B to 2002 and observing changes in marital status. I introduce a converse matching procedure to detect women who are not in the survey for two consecutive years. I find that the welfare reform has a significantly negative effect on marriage rates and an insignificant effect on divorce rates. The Difference-in-Difference estimates suggest that marriage among disadvantaged women is negatively affected by the welfare reform. I also provide a theoretical model to decompose the effect of welfare reform on marriage due to each of the components of the reform, i.e., time limits, work sanctions, earnings disregards, and maximum cash benefits. My results provide a novel explanation for the effects of work incentives and welfare restrictions on marriage.

The ginger industry is one of the key industries identified by the Fiji government in its diversification strategy to accommodate the remnants of the withdrawal of the European Union’s sugar preferences. There is considerable pressure on small industries such as ginger in search of ways in which they can be made to operate efficiently and sustain the economy. Expansion of commercial agriculture into marginal land which is unsustainable adds enormous pressure on land causing soil erosion. Coupled with this is the quality issue which is a serious problem of ginger production and has reduced its competitiveness over the years. This study focuses on two types of losses in ginger production to provide an integrated approach to policy making and computing production losses. One is the observable output loss at the farm site that is not sold due to sub-standard quality related to disease and the other is the unobserved output loss due to inefficient production. The research attempts to answer the question of whether the Fiji ginger farmers are producing efficiently, and at what levels. The relative importance of each input in ginger production is examined. The study undertakes to determine the effects of key variables on farm efficiency. Also examined is the overall farm profiles based on the efficiency rankings of the ginger producers. Furthermore, this research attempts to determine factors that influence soil erosion, and those that influence the observed ginger loss. Using cross-sectional data from a ginger farm survey conducted in June 2007, this research estimates a stochastic production frontier which incorporates soil erosion as an input in the framework. Very few studies have looked at the impact of soil erosion in this context; hence, this study fills the gap by incorporating land quality in the analysis. Farms were found to produce at 69% of their maximum potential output and soil erosion resulted in 6.8% loss in ginger output. This also implies that using the same resources, technology and farming techniques efficiently can lead to a 31% increase in output. While unobserved loss to farm income is a 27% (F$4.6m) increase over the observable loss at farm site, the revenue loss to the whole industry is at least 30% (F$5.07m). Profit was a key determinant of both losses, but staying on farm, slope of land, manure use and hot water treatment affected the observed but not unobserved loss. Although farmer education had no effect on both losses, it was important for undertaking soil conservation. Fiji is in a good position to increase production as education, age and experience of farmers were not significant determinants of efficiency. Thus, displaced farmers from sugar cane farming (given serious concerns of the viability of that industry) can be encouraged to move with ease into ginger as an alternative livelihood. Lastly, the study highlights some practical implication which calls for an integrated package of policies related to use of best farming techniques, land tenure and, agricultural extension and support services for sustainable agricultural growth.

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No / The existing empirical literature on foreign direct investment (FDI) entry strategies tends to allow a binary choice between wholly owned enterprises (WOEs) and equity joint ventures (EJVs) or between greenfield investment and acquisition only. The current study specifies a multinomial logit model for the choice from all four FDI entry modes in China. Five hypotheses are developed based on transaction cost economics and tested on a data set covering 10,607 foreign investment projects in China. A foreign investor seems to prefer the WOE mode given its large investment commitment, a high level of the host country's experience in attracting FDI, a good specific industrial location, and a high asset intensity in the host industry. If the conditions of host country experience and good specific location are not met, the EJV and the joint stock company (JSC) modes seem to be of greater use. A good specific location also makes the contractual joint venture (CJV) a preferable entry mode. Compared with overseas Chinese investors from Hong Kong, Macao, and Taiwan, other foreign investors prefer EJVs over WOEs and CJVs. The results have important implications for managers.

The number of elderly is increasing; to meet their transportation needs, it is important to clearly understand their travel patterns and preferences. Since travel patterns and preferences depend on socio-demographic and other factors, it is essential to identify these factors first to understand the travel behavior of the elderly. The main purpose of this thesis is to analyze the travel patterns and preferences of the elderly age 65 and above using 2009 National Household Travel Survey (NHTS) data. This thesis presents a detailed descriptive analysis of 2009 NHTS data to understand the travel patterns of the elderly. Along with a descriptive analysis, a multinomial logit model and a mixed- multinomial logit model are estimated to explore the factors associated with the overall travel preferences of the elderly and to identify individuals among the elderly who are the least mobile and at risk for social isolation. The analysis results indicate the differences in the trip characteristics between the elderly and non-elderly. Variation is found even among the different groups of the elderly. The model estimation results show the presence of different travel preferences among the elderly and identify those individuals among the elderly who are immobile for longer periods (e.g., a week) and at risk for social isolation. Elderly individuals with different travel preferences should be considered separately in research to determine the appropriate outcomes that can help transportation planners and policy makers improve planning and policy related to elderly individuals.

This thesis compares different approaches to estimating budgets for Kuhn-Tucker (KT) demand systems, more specifically for the multiple discrete-continuous extreme value (MDCEV) model. The approaches tested include: (1) The log-linear regression approach (2) The stochastic frontier regression approach, and (3) arbitrarily assumed budgets that are not necessarily modeled as a function of decision maker characteristics and choice-environment characteristics. The log-linear regression approach has been used in the literature to model the observed total expenditure as way of estimating budgets for the MDCEV models. This approach allows the total expenditure to depend on the characteristics of the choice-maker and the choice environment. However, this approach does not offer an easy way to allow the total expenditure to change due to changes in choice alternative-specific attributes, but only allows a reallocation of the observed total expenditure among the different choice alternatives. To address this issue, we propose the stochastic frontier regression approach. The approach is useful when the underlying budgets driving a choice situation are unobserved, but only the expenditures on the choice alternatives of interest are observed. The approach is based on the notion that consumers operate under latent budgets that can be conceived (and modeled using stochastic frontier regression) as the maximum possible expenditure they are willing to incur. To compare the efficacy of the above-mentioned approaches, we performed two empirical assessments: (1) The analysis of out-of-home activity participation and time-use (with a budget on the total time available for out-of-home activities) for a sample of non-working adults in Florida, and (2) The analysis of household vehicle type/vintage holdings and usage (with a budget on the total annual mileage) for a sample of households in Florida. A comparison of the MDCEV model predictions (based on budgets from the above mentioned approaches) demonstrates that the log-linear regression approach and the stochastic frontier approach performed better than arbitrarily assumed budgets approaches. This is because both approaches consider heterogeneity in budgets due to socio-demographics and other explanatory factors rather than arbitrarily imposing uniform budgets on all consumers. Between the log-linear regression and the stochastic frontier regression approaches, the log-linear regression approach resulted in better predictions (vis-à-vis the observed distributions of the discrete-continuous choices) from the MDCEV model. However, policy simulations suggest that the stochastic frontier approach allows the total expenditures to either increase or decrease as a result of changes in alternative-specific attributes. While the log-linear regression approach allows the total expenditures to change as a result of changes in relevant socio-demographic and choice-environment characteristics, it does not allow the total expenditures to change as a result of changes in alternative-specific attributes.