I syftet att undersöka hur en skatte- och bidragsreform kan tänkas påverka utbudet av arbetskraft för ungdomar, modelleras en Discrete Choice nyttofunktion, där valet av antalet arbetstimmar begränsas till fem olika arbetstimmarsklasser. Modellen tar hänsyn till icke-linjära skatter och icke-konvexa budgetkurvor. I nyttomaximeringen tas även hänsyn till valet av socialbidrag. För att se effekten på ungdomarnas arbetstimmar används mikrosimuleringsmodellen FASIT som innehåller databaser över inkomster, skatte- och transfereringssystem. Finans- och Socialdepartementen använder modellen för att se reformers eventuella effekter på specifika grupper i samhället. Skattereformen innebär en höjning av grundavdraget och bidragsreformen en sänkning av socialbidraget. Syftet med reformerna är att öka inkomstdifferensen mellan att inte arbeta och att arbeta och därmed öka incitamenten till att vilja arbeta för ungdomar. För att kunna motivera en sådan reform, ska den inte försämra statens finanser, utan helst vara självfinansierad. Resultaten visar att en skatte- och bidragsreform av detta slag inte ökar ungdomarnas arbetstimmar signifikant. Däremot kommer användandet av socialbidrag minska med över 90 %, även om inte många ungdomar levde på socialbidrag innan reformen. För staten innebär en sådan här reform att både skatteinkomsterna minskar, p.g.a. grundavdragshöjningen och bidragsutgifterna minskar, till följd av mindre socialbidragsutbetalningar. Däremot, kommer inkomsterna att minska mer än utgifterna, så det blir svårt att berättiga reformen. / With the purpose of examining how a tax- and social assistance reform would affect the labor supply for Swedish youth, a Discrete Choice utility function is utilized, where the choice of working hours is restricted to five different sets of working hours. This model takes nonlinear taxes and nonconvex budget constraints into consideration and in the utility maximization the youth has to keep the choice of accepting the social assistance in mind. The effect on youth working hours is simulated in a micro simulation model, FASIT, which contains databases on Swedish incomes, taxes- and subsidies systems and is mostly used by the Swedish Ministry of Finance in order to investigate policy reforms’ affect on different groups in society. The tax reform implies an increase of the basic deduction and the subsidy reform implies a decrease of the amount of social assistance. The purpose of the reforms is to increase the income gap between not working and working and thereby increase the incentives of being willing to work. To be able to justify a reform like this, it must not be too expensive for the government, but preferably it should be self-financed. The results show that the reforms will not increase the working hours of the youth significantly. But at the same time the reform decreases the need of social assistance with over 90 %, although not a large part of the youth supported themselves through social assistance before the reform. For the government the reform will result in a decrease in tax revenues and a decrease in the subsidy cost. The problem is that the revenues will decrease much more than the costs; therefore the reform is difficult to justify.

<p>I syftet att undersöka hur en skatte- och bidragsreform kan tänkas påverka utbudet av arbetskraft för ungdomar, modelleras en Discrete Choice nyttofunktion, där valet av antalet arbetstimmar begränsas till fem olika arbetstimmarsklasser. Modellen tar hänsyn till icke-linjära skatter och icke-konvexa budgetkurvor. I nyttomaximeringen tas även hänsyn till valet av socialbidrag. För att se effekten på ungdomarnas arbetstimmar används mikrosimuleringsmodellen FASIT som innehåller databaser över inkomster, skatte- och transfereringssystem. Finans- och Socialdepartementen använder modellen för att se reformers eventuella effekter på specifika grupper i samhället.</p><p>Skattereformen innebär en höjning av grundavdraget och bidragsreformen en sänkning av socialbidraget. Syftet med reformerna är att öka inkomstdifferensen mellan att inte arbeta och att arbeta och därmed öka incitamenten till att vilja arbeta för ungdomar. För att kunna motivera en sådan reform, ska den inte försämra statens finanser, utan helst vara självfinansierad.</p><p>Resultaten visar att en skatte- och bidragsreform av detta slag inte ökar ungdomarnas arbetstimmar signifikant. Däremot kommer användandet av socialbidrag minska med över 90 %, även om inte många ungdomar levde på socialbidrag innan reformen. För staten innebär en sådan här reform att både skatteinkomsterna minskar, p.g.a. grundavdragshöjningen och bidragsutgifterna minskar, till följd av mindre socialbidragsutbetalningar. Däremot, kommer inkomsterna att minska mer än utgifterna, så det blir svårt att berättiga reformen.</p> / <p>With the purpose of examining how a tax- and social assistance reform would affect the labor supply for Swedish youth, a Discrete Choice utility function is utilized, where the choice of working hours is restricted to five different sets of working hours. This model takes nonlinear taxes and nonconvex budget constraints into consideration and in the utility maximization the youth has to keep the choice of accepting the social assistance in mind. The effect on youth working hours is simulated in a micro simulation model, FASIT, which contains databases on Swedish incomes, taxes- and subsidies systems and is mostly used by the Swedish Ministry of Finance in order to investigate policy reforms’ affect on different groups in society.</p><p>The tax reform implies an increase of the basic deduction and the subsidy reform implies a decrease of the amount of social assistance. The purpose of the reforms is to increase the income gap between not working and working and thereby increase the incentives of being willing to work. To be able to justify a reform like this, it must not be too expensive for the government, but preferably it should be self-financed.</p><p>The results show that the reforms will not increase the working hours of the youth significantly. But at the same time the reform decreases the need of social assistance with over 90 %, although not a large part of the youth supported themselves through social assistance before the reform. For the government the reform will result in a decrease in tax revenues and a decrease in the subsidy cost. The problem is that the revenues will decrease much more than the costs; therefore the reform is difficult to justify.</p>

Almost everything that we do involves a choice. In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals with the purpose of gaining a better understanding of how choices are made and also to predict future choice responses. In many fields, the choices made by individuals will determine the effectiveness of policy. Understanding what drives people's choices and how these choices may change is critical for developing successful policy. Discrete choice modeling provides an analytical framework with which to analyze and predict how people's choices are influenced by their personal characteristics and by the different attributes of the alternatives available to them. In an ideal situation we would build discrete choice models using information from choices that people are observed to make, i.e., revealed preference (RP) information. From these data we can quantify the influence of particular variables in the real choice context; for example, how important is price in the decision to travel by train? There are, however, potential problems with these data. There might not be enough variation of the explanatory attributes; for example little price variation across alternatives. Furthermore, several attributes might be highly correlated e.g. price and quality. But the most important of all is the fact that it is not possible to observe choices for alternatives that do not yet exist; for example new programs and technologies. In cases where the data limits the information provided by real choices it may be appropriate to collect stated preference (SP) data, which is information on preferences provided from hypothetical choice situations. This dissertation provides several applications of discrete choice modeling using both raveled preferences and stated preference. Unlike the last two chapters which deal with the revealed preference, the first Chapter, uses stated preference data. This Chapter evaluates the impact of several attributes of monetary incentives on the decision of patients to participate in a new weight loss program. Since this program does not exist yet, revealed preference data were not available and stated preference data were collected. The attributes of interest in this study include magnitude, timing and form of payment. The goal is to see what level and what combination of these attributes provides greater impact on the reach of the program. We also account for preference heterogeneity by using a random parameter framework. Chapter 2 discusses another application of discrete choice models in event history models (also called survival analysis). In these type of models, the main goal is to use the history of happening an event to learn more about the effect of different factors on the probability of occurrence. The event of interest in our case is the birth. We use the birth history of rural women and try to model their decision to give birth over time. The ultimate goal is to evaluate the effect of health clinics and family planning program on this decision. The final Chapter considers the application of discrete choice modeling in an electoral framework. The 2005 presidential election in Iran is used to model the decisions of Iranian voters. Using this revealed preference data we try to learn more about the main factors evolved in both participation and in the candidate selection. / Ph. D.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第19031号 / 農博第2109号 / 新制||農||1031(附属図書館) / 学位論文||H27||N4913(農学部図書室) / 31982 / 京都大学大学院農学研究科生物資源経済学専攻 / (主査)教授 栗山 浩一, 教授 福井 清一, 准教授 秋津 元輝 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

The individuals with disabilities are disproportionately vulnerable to hazards. However, there is very little research inquiry focused on evacuation environments and the behavior of individuals with disabilities. The most widely applied computational method used to study how effective the built environment facilities emergency evacuations in individuals-based modeling. Current pedestrian evacuation models rarely include individuals with disabilities in their simulated populations due to there being very few empirical studies of the evacuation behavior of individuals with disabilities. As a result, the models do not replicate accurate patterns of pedestrian or evacuation behavior of a heterogeneous population, which results in the evacuation needs of individuals with disabilities being generally overlooked. To begin addressing this limitation, our research group at Utah State University (USU) has performed empirical research to observe the microscopic evacuation behavior of individuals with disabilities in heterogeneous population contexts. The purpose of this research was to: (1) develop and analyze evacuation curves to understand and assess evacuation strategies for heterogeneous populations, and (2) analyze the microscopic behavior of evacuees at exit doors necessary for developing credible and valid pedestrian and evacuation models. Doing so will contribute to evacuation models which replicate accurate patterns of pedestrian and evacuation behavior of heterogeneous populations, leading to the consideration of the evacuation needs of individuals with disabilities.

<p>In this dissertation, I discuss two important factors in individuals' decision-making processes: subjective expectation bias and time-inconsistent preferences. In Chapter I, I look at how individuals' own subjective expectations about certain future events are different from what actually happens in the future, even after controlling for individuals' private information. This difference, which is defined as the expectation bias in this paper, is found to have important influence on individuals' choices. Specifically, I look into the relationship between US elderly's subjective longevity expectation biases and their smoking choices. I find that US elderly tend to over-emphasize the importance of their genetic makeup but underestimate the influence of their health-related choices, such as smoking, on their longevity. This finding can partially explain why even though US elderly are found to be more concerned with their health and more forward-looking than we would have concluded using a model which does not allow for subjective expectation bias, we still observe many smokers. The policy simulation further confirms that if certain public policies can be designed to correct individuals' expectation biases about the effects of their genes and health-related choices on their longevity, then the average smoking rate for the age group analyzed in this paper will go down by about 4%.</p><p>In Chapter II, my co-author, Hanming Fang, and I look at one possible explanation to the under-utilization of preventive health care in the United States: procrastination. Procrastination, the phenomenon that individuals postpone certain decisions which incur instantaneous costs but bring long-term benefits, is captured in economics by hyperbolic discount factors and the corresponding time-inconsistent preferences. This chapter extends the semi-parametric identification and estimation method for dynamic discrete choice models using Hotz and Miller's (1993) conditional choice probability approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We implement the proposed estimation method to US adult women's decisions of undertaking mammography tests to evaluate the importance of present bias and naivety in the under-utilization of mammography, controlling for other potentially important explanatory factors such as age, race, household income, and marital status. Preliminary results show evidence for both present bias and naivety in adult women's decisions of undertaking mammography tests. Using the parameters estimated, we further conduct some policy simulations to quantify the effects of the present bias and naivety on the utilization of preventive health care in the US.</p> / Dissertation

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

此篇文章探討，使用離散選擇模型(discrete choice model)中的邏輯模型(logit model)分析，若資料具有遺漏值(incomplete-data)，比較將具有遺漏值樣本值皆移除與使用多重插補方法補值之參數估計結果。 本文使用的多重差補法為Buuren(2007)等人所提出的Multiple Imputation by Chained Equation(MICE)多重插補方法進行補值，並使用Rubin(1987)所提出的方法合併參數估計結果。從模擬結果之參數偏誤盒狀圖可知插補後參數估計與設定參數差異不大，另外插補次數對於參數估計結果影響不大，且在遺漏比例(missing percentage)大時，參數估計結果比起將具有遺漏值樣本直接移除的參數估計較為穩定。 另外使用實際資料分析，發現具有遺漏值樣本直接移除的參數估標準差比起插補後參數估計標準差大的趨勢，與模擬結果相同。 / This paper focuses on using discrete choice logit model to analyze incompleted data. To deal with the incompleted data, complete case analysis and multiple imputation are used, and compare the result of parameter estimates of the two methods. The method of multiple imputation which this paper used is Multiple Imputation by Chained Equation (MICE). With the estimates from multiple imputed data sets, using Rubin’s method (1987) to pool the estimates. The simulation shows that after imputing the missing values, the estimates from the imputed data are not much difference from the real parameters. The number of imputation does not effect the estimates much. With larger missing percentage, the estimates from the imputed data is more robust than the estimates from the complete case analysis. In real data analysis, the standard deviation of estimates from using complete case analysis are bigger than imputed data, this result is the same with the simulation.

In recent decades, economists are gradually showing their interests in the study of happiness. They even put forward some challenges to the traditional theories. In contrast, studies on Chinese happiness problem are not enough in terms of breadth and depth.  This paper used the data provided by China General Social Survey to conduct an empirical analysis. The model author adopted is Ordered Discrete Choice model. In the empirical section, author analyzed the impact of income, macroeconomic variables, etc.  Ultimately, based on the empirical results, author proposed some policy recommendations and further study suggestions.

[pt] Este artigo investiga o impacto da provisão pública na concorrência dentro do setor de ensino superior brasileiro. Desenvolvemos e estimamos um modelo empírico de demanda por ensino superior que incorpora instituições gratuitas e restrições de escolha do consumidor. Nosso modelo produz padrões de substituição mais realistas do que um modelo logit sem restrições, indicando que a seletividade é uma dimensão essencial da diferenciação de produtos. Mostramos que os programas públicos mais seletivos exercem pressão competitiva comparável aos programas privados mais seletivos, mas os programas públicos menos seletivos exercem mais pressão competitiva do que os programas privados menos seletivos. Nossas estimativas da resposta de oferta das instituições privadas sugerem que, na ausência de programas públicos, as mensalidades seriam cerca de 7 por cento mais altas. Esses resultados fornecem informações importantes sobre a dinâmica competitiva do ensino superior brasileiro e destacam o papel da provisão pública na promoção da concorrência nesse setor. / [en] This paper investigates the impact of public provision on competition within the Brazilian higher education sector. We develop and estimate an empirical model of demand for higher education that incorporates tuition-free institutions and consumer choice constraints. Our model produces more realistic substitution patterns than a logit model without constraints, indicating that selectivity is an essential dimension of product differentiation. We find that the most selective public programs exert comparable competitive pressure to the most selective private programs, but the least selective public programs exert more competitive pressure than the least selective private programs. Our estimates of the supply response of private institutions suggest that, in the absence of public programs, tuitions would be about 7 percent higher. These findings provide important insights into the competitive dynamics of Brazilian higher education and highlight the role of public provision in promoting competition in this sector.