This professorial dissertation thesis collects several empirical studies on tax distribution and tax reform in Germany. Chapter 2 deals with two studies on effective income taxation, based on representative micro data sets from tax statistics. The first study analyses the effective income taxation at the individual level, in particular with respect to the top incomes. It is based on an integrated micro data file of household survey data and income tax statistics, which captures the entire income distribution up to the very top. Despite substantial tax base erosion and reductions of top tax rates, the German personal income tax has remained effectively progressive. The distribution of the tax burden is highly concentrated and the German economic elite is still taxed relatively heavily, even though the effective tax rate for this group has significantly declined. The second study of Chapter 2 highlights the effective income taxation of functional income sources, such as labor income, business and capital income, etc. Using income tax micro data and microsimulation models, we allocate the individual income tax liability to the respective income sources, according to different apportionment schemes accounting for losses. We find that the choice of the apportionment scheme markedly affects the tax shares of income sources and implicit tax rates, in particular those of capital income. Income types without significant losses such as labor income or transfer incomes show higher tax shares and implicit tax rates if we account for losses. The opposite is true for capital income, in particular for income from renting and leasing. Chapter 3 presents two studies on business taxation, based on representative micro data sets from tax statistics and the microsimulation model BizTax. The first part provides a study on fundamental reform options for the German local business tax. We find that today’s high concentration of local business tax revenues on corporations with high profits decreases if the tax base is broadened by integrating more taxpayers and by including more elements of business value added. The reform scenarios with a broader tax base distribute the local business tax revenue per capita more equally across regional categories. The second study of Chapter 3 discusses the macroeconomic performance of business taxation against the background of corporate income. A comparison of the tax base reported in tax statistics with the macroeconomic corporate income from national accounts gives hints to considerable tax base erosion. The average implicit tax rate on corporate income was around 20 percent since 2001, and thus falling considerably short of statutory tax rates and effective tax rates discussed in the literature. For lack of detailed accounting data it is hard to give precise reasons for the presumptive tax base erosion. Chapter 4 deals with several assessment studies on the ecological tax reform implemented in Germany as of 1999. First, we describe the scientific, ideological, and political background of the ecological tax reform. Further, we present the main findings of a first systematic impact analysis. We employ two macroeconomic models, an econometric input-output model and a recursive-dynamic computable general equilibrium (CGE) model. Both models show that Germany’s ecological tax reform helps to reduce energy consumption and CO2 emissions without having a substantial adverse effect on overall economic growth. It could have a slightly positive effect on employment. The reform’s impact on the business sector and the effects of special provisions granted to agriculture and the goods and materials sectors are outlined in a further study. The special provisions avoid higher tax burdens on the energy-intensive production. However, they widely reduce the marginal tax rates and thus the incentives to energy saving. Though the reform of special provisions 2003 increased the overall tax burden of the energy-intensive industry, the enlarged eligibility for tax rebates neutralizes the ecologic incentives. Based on the Income and Consumption Survey of 2003, we have analyzed the distributional impact of the ecological tax reform. The increased energy taxes show a clear regressive impact relative to disposable income. Families with children face a higher tax burden relative to household income. The reduction of pension contributions and the automatic adjustment of social security transfers widely mitigate this regressive impact. Households with low income or with many children nevertheless bear a slight increase in tax burden. Refunding the eco tax revenue by an eco bonus would make the reform clearly progressive. / Diese Habilitationsschrift fasst verschiedene empirische Studien zu Steuerlastverteilung und Steuerreformen in Deutschland zusammen. In Kapitel 2 werden zwei Studien zur effektiven Einkommensteuerbelastung dargestellt. Die erste Studie analysiert die effektive Einkommensteuerbelastung auf der persönlichen Ebene, insbesondere bei Personen mit hohen Einkommen. Grundlage der Analyse ist ein integrierter Mikrodatensatz aus Haushaltserhebungen und Steuerstatistik, der die vollständige Einkommensverteilung zuverlässig abbildet. Trotz erheblicher Steuerbegünstigungen und Senkungen der Spitzensteuersätze wirkt die deutsche Einkommensteuer klar progressiv, auch wenn die Belastung der Top-Verdiener in den letzten Jahren deutlich gesunken ist. Die zweite Studie in Kapitel 2 analysiert die effektive Einkommensteuerbelastung von verschiedenen funktionalen Einkommensquellen. Auf Grundlage von steuerstatistischen Mikrodaten und Mikrosimulationsmodellen analysieren wir die Anteile der Einkunftsarten an der Steuerbelastung für verschiedene Aufteilungsregeln unter Berücksichtigung von Verlusten. Die Wahl der Aufteilungsregel wirkt sich spürbar auf den Steueranteil und die impliziten Steuersätze von Einkommensarten aus, wenn Verluste berücksichtigt werden, vor allem bei den Vermögenseinkommen. Kapitel 3 enthält zwei Studien zur Unternehmensbesteuerung, die auf repräsentativen Einzeldatensätzen der Steuerstatistik und dem Mikrosimulationsmodell BizTax basieren. Zunächst wird eine Mikrosimulationsanalyse zu grundlegenden Reformmodellen für die Gewerbesteuer vorgestellt. Die Ergebnisse zeigen, dass die starke Konzentration des Gewerbesteueraufkommens auf die Unternehmen mit höheren Gewinnen deutlich vermindert werden kann, wenn die Bemessungsgrundlagen verbreitert werden, durch Einbeziehung aller Unternehmen und eine Ausweitung auf weitere Komponenten der betrieblichen Wertschöpfung. Diese Reformszenarien verteilen das Steueraufkommen je Einwohner deutlich gleichmäßiger über die Regionen. In der zweiten Studie des Kapitels 3 analysieren wir das Unternehmensteueraufkommen vor dem Hintergrund der gesamtwirtschaftlichen Unternehmensgewinne. Ein Vergleich der steuerlichen Bemessungsgrundlagen mit den entsprechenden Unternehmensgewinnen der Volkswirtschaftlichen Gesamtrechnungen ergibt eine beträchtliche Besteuerungslücke. Die durchschnittliche effektive Unternehmensteuerbelastung dürfte sich seit 2001 um 20 Prozent bewegt haben. Dies ist deutlich niedriger als die nominalen tariflichen Steuersätze und die effektiven Steuersätze, die in der Literatur ermittelt werden. Mangels detaillierter statistischer Erfassung der steuerlichen Gewinnermittlung ist es derzeit nicht möglich, diese Besteuerungslücke genauer aufzuklären. In Kapitel 4 werden verschiedene Studien zur ökologischen Steuerreform dargestellt. Zunächst werden die wissenschaftlichen, ideologischen und politischen Hintergründe dieser Reform erläutert. Danach wird eine erste systematische Wirkungsanalyse dargestellt. Dabei werden zwei makroökonomische Modelle eingesetzt, ein ökonometrisches Input-Output-Modell und ein empirisches rekursiv-dynamisches allgemeines Gleichgewichtsmodell. Die Ergebnisse zeigen, dass die ökologische Steuerreform den Energieverbrauch und die CO2-Emissionen spürbar senken kann, ohne dass dies nennenswerte Wachstumseinbußen nach sich ziehen würde. Ferner löst die Reform leicht positive Beschäftigungseffekte aus. Die Wirkungen der ökologischen Steuerreform nach Wirtschaftsbereichen und die Wirkungen der Steuervergünstigungen für Landwirtschaft und Produzierendes Gewerbe werden in einer weiteren Studie analysiert. Die Steuervergünstigungen vermeiden höhere Belastungen in den energieintensiven Produktionsbereichen. Zugleich reduzieren sie die Grenzbelastungen und somit die Anreize zum Energiesparen in diesen Branchen weitgehend. Die Reform der Steuervergünstigungen hat zwar die Belastungen für die energieintensive Wirtschaft seit 2003 erhöht. Die zusätzlichen Anreizwirkungen wurden aber durch die Ausweitung des „Spitzenausgleichs“ konterkariert. Die Effekte der ökologischen Steuerreform auf die Einkommensverteilung wurden auf Grundlage der Einkommens- und Verbrauchsstichprobe 2003 untersucht. Die erhöhten Energiesteuern wirken klar regressiv bezogen auf das verfügbare Einkommen. Familien mit Kindern werden relativ stärker belastet. Die Senkung der Rentenbeiträge und die automatische Anpassung von Sozialleistungen mildern die regressive Belastungswirkung. Bei Haushalten mit niedrigen Einkommen oder bei Familien mit vielen Kindern bleiben jedoch Nettobelastungen bestehen. Eine Rückerstattung des Ökosteueraufkommens durch einen „Ökobonus“ würde die gesamten Verteilungswirkungen der Reform deutlich progressiv machen.

The study assessed the extent of child poverty in South Africa using five different policy scenarios, and modelled the impact on poverty and inequalities of people living in households with children using the Foster-Greer-Thorbecke (FGT) index of poverty measurement, including poverty rate P0, (headcount index ratio), poverty gap index P1, (the depth of poverty), and the severity of poverty P2 (squared poverty gap index). Societal welfare inequalities have been measured using the Gini co-efficient. In general, the scenario analysis was based on the 2007 population baseline and 2008 government policy rules. The results of the study clearly indicate that there is a positive correlation between cash transfer (Child Support Grant) and a reduction in poverty and the inequalities of people living in households with children in South Africa. An increase in the Child Support Grant amount and the number of child beneficiaries, in modelling, produced a positive effect in addressing increasing child poverty and vulnerability. In addition, the research process identified four interrelated gaps that hinder the successful implementation of the social welfare policies underlying the Child Support Grant to reduce the poverty and inequality profile of people living in households with children in South Africa. First, inadequate understanding of the constitutional rights of the child exists. Second, failure to use proven best practice of institutional arrangements and implementation modalities was identified. Third, lack of political will for the championship of a universal basic income grant (UBIG) is present. Fourth, insufficient research, monitoring and evaluation (M&E) and dissemination of best practices is done. Within the context of the abovementioned analysis, the study finally brings into focus general observations gained from the investigation and provides recommendations to policy makers and other stakeholders.

Many health geography studies, including the Ottawa Neighbourhood Study (ONS), have faced significant challenges uncovering local variation in patterns of community health in rural areas. This is due to the fact that sparsely populated rural areas make it difficult to define neighbourhoods that are representative of the social and resource utilization patterns of the individuals therein. Moreover, rural areas yield small samples from population-based regional health surveys and this leads to insufficient sample sizes for reliable estimation of health determinants and outcomes. In response to this issue this thesis combines geographical and statistical techniques which allow for the simulation of health variables within small areas and populations within rural Ottawa. This methodological approach combines the techniques of dasymetric mapping and statistical micro-simulation in an innovative way, which will allow health geography researchers to explore health determinants and health outcomes at small spatial scales in rural areas. Dasymetric mapping is used to generate a statistical population surface over Ottawa and then estimate socio-economic (SES) variables within small neighbourhood units within rural Ottawa. The estimated SES variables are then used as correlate variables to simulate health determinant and health outcome variables form the Canadian Community Health Survey (CCHS) using statistical micro-simulation. Through this methodology, simulations of specific health determinants and outcome can be investigated at small spatial scales within rural areas. Dasymetric mapping provided neighbourhood-level population estimates that were used to re-weight as set of SES variables that were correlates with those in the Canadian Community Health Survey (CCHS). These neighbourhood-level correlates allowed microsimulation and consequent spatial exploration of prevalence for smoking, binge drinking, obesity, self-rated mental health, and the presence of two or more chronic conditions. The methodology outlined in this paper, provides and innovative way of exploring health determinants and health outcomes in neighbourhoods for which population and health statistics are not traditionally collected at levels that would allow traditional statistical analyses of prevalence.

Idrottsparken roundabout in Norrkoping is located in the more dense part of the city.Congestion occurs in peak hours causing queue and extended travel time. This thesis aims to provide alternative model to reduce queue and travel time. Types ofobservation data are flow, length of queue, and travel time that are observed during peakhours in the morning and afternoon. Calibration process is done by minimising root meansquare error of queue, travel time, and combination both of them between observation andcalibrated model. SUMO version 0.14.0 is used to perform the microsimulation. There are two proposed alternatives, namely Scenario 1: the additional lane for right turnfrom East leg to North and from North leg to West and Scenario 2: restriction of heavy goodsvehicles passing Kungsgatan which is located in Northern leg of Idrottsparken roundaboutduring peak hours. For Scenario 1, the results from SUMO will be compared with AIMSUNin terms of queue and travel time. The result of microsimulation shows that parameters that have big influence in the calibrationprocess for SUMO are driver imperfection and driver’s reaction time, while for AIMSUN isdriver’s reaction time and maximum acceleration. From analysis found that the model of thecurrent situation at Idrottsparken can be represented by model simulation which usingcombination between root mean square error of queue and travel time in calibration andvalidation process. Moreover, scenario 2 is the best alternative for SUMO because itproduces the decrease of queue and travel time almost in all legs at morning and afternoonpeak hour without accompanied by increase significant value of them in the other legs. Thecomparison between SUMO and AIMSUN shows that, in general, the AIMSUN has higherchanges value in terms of queue and travel time due to the limited precision in SUMO forroundabout modelling.

To understand the factors that influence the spatio-temporal distribution of built space, and thus population in an urban area, play an extremely important role in our greater understanding of urban travel behaviour. Existing location of activity centres, especially home and work, strongly influences the short-term individual-level decisions such as mode of transportation, and long-term household-level decisions such as change in job and residential location. Conditions in the built space market also affect households’ and firms’ location and relocation decisions, and hence influence the general travel patterns in an urban area. This research addresses two very important, but at the same time, not very widely investigated dimensions that play a key role in the evolution of built space and population distribution: Markets and Decisions. A disequilibrium based microsimulation modelling framework is developed for the built space markets. This framework is then used to operationalize the Greater Toronto and Hamilton Area’s owner-occupied housing market within Integrated Land Use Transportation and Environment (ILUTE) modelling system. Simulation results captured heterogeneity in the transaction prices, due to type of dwellings and different market conditions, in a very disaggregate fashion. On the decisions side, this research first developed a generic multidimensional modelling framework that captures the behaviour of builders in terms of the supply of new built space. The where, when, how much, and what type of supply decisions were incorporated within a single framework. This modelling framework was then applied to estimate a model for the supply of new office space in the Greater Toronto Area (GTA). Estimation results indicated a risk taker behaviour on the builders’ part, while market conditions and supply of resources (labour, construction cost etc.) were also found to be important factors in decision making. In addition to that, this research also developed a comprehensive hedonic analysis for the asking rent of office space in the Greater Toronto Area. The effects of accessibility, quality, location, and market conditions on rent were explored. Data indicated a high degree of spatial heterogeneity and clustering effects. Spatial analysis techniques were incorporated within the hedonic framework to capture these effects. Estimation results indicated that access to transport infrastructure, distance from CBD, and vacancy rate were significant in explaining the variation in the rent.

To understand the factors that influence the spatio-temporal distribution of built space, and thus population in an urban area, play an extremely important role in our greater understanding of urban travel behaviour. Existing location of activity centres, especially home and work, strongly influences the short-term individual-level decisions such as mode of transportation, and long-term household-level decisions such as change in job and residential location. Conditions in the built space market also affect households’ and firms’ location and relocation decisions, and hence influence the general travel patterns in an urban area. This research addresses two very important, but at the same time, not very widely investigated dimensions that play a key role in the evolution of built space and population distribution: Markets and Decisions. A disequilibrium based microsimulation modelling framework is developed for the built space markets. This framework is then used to operationalize the Greater Toronto and Hamilton Area’s owner-occupied housing market within Integrated Land Use Transportation and Environment (ILUTE) modelling system. Simulation results captured heterogeneity in the transaction prices, due to type of dwellings and different market conditions, in a very disaggregate fashion. On the decisions side, this research first developed a generic multidimensional modelling framework that captures the behaviour of builders in terms of the supply of new built space. The where, when, how much, and what type of supply decisions were incorporated within a single framework. This modelling framework was then applied to estimate a model for the supply of new office space in the Greater Toronto Area (GTA). Estimation results indicated a risk taker behaviour on the builders’ part, while market conditions and supply of resources (labour, construction cost etc.) were also found to be important factors in decision making. In addition to that, this research also developed a comprehensive hedonic analysis for the asking rent of office space in the Greater Toronto Area. The effects of accessibility, quality, location, and market conditions on rent were explored. Data indicated a high degree of spatial heterogeneity and clustering effects. Spatial analysis techniques were incorporated within the hedonic framework to capture these effects. Estimation results indicated that access to transport infrastructure, distance from CBD, and vacancy rate were significant in explaining the variation in the rent.

The purpose of this thesis was to perform microsimulation analyses on intersections near Highway-Railroad Grade Crossings (HRGCs) to determine if controlling mean train speed and train speed variability would improve safety and reduce delays. This research focused on three specific areas. First, average vehicle delay was examined, and this delay was compared for seven specific train speed distributions, including existing conditions. Furthermore, each distribution was associated with train detectors that were placed at the distance the fastest train could travel during the given warning time. Second, pedestrian cutoffs were investigated. These cutoffs represented an occasion when the pedestrian phases were truncated or shortened due to railroad signal preemption. Finally, vehicle emissions were analyzed using a modal emissions model. A microscopic simulation model of the Wellborn Corridor in College Station, Texas was created using VISSIM. The model was run twenty times in each train speed distribution for each of three train lengths. Average vehicle delay was collected for three intersections, and delays were compared using the Pooled t-test with a 95% confidence interval. Comparisons were made between the distributions, and generally, distributions with higher mean train speeds were associated with lower average delay, and train length was not a significant factor. Unfortunately, pedestrian cutoffs were not specifically controlled in this project; therefore, no statistical conclusions can be made with respect to the pedestrian cutoff problem. However, example cases were devised to demonstrate how these cutoffs could be avoided. In addition, vehicle emissions were examined using the vehicle data from VISSIM as inputs for CMEM (Comprehensive Modal Emissions Model). For individual vehicles, as power (defined as the product of velocity and acceleration) increased, emissions increased. When comparing emissions from different train speed distributions, few significant differences were found. However, a scenario with no train was tested, and it was shown to have significantly higher emissions than three of the distributions with trains. Ultimately, this thesis shows that average vehicle delay and vehicle emissions could be lowered by specific train speed distributions. Also, work could be done to investigate the pedestrian cutoff problem.

In this research the problem of incident congestion on surface street networks is addressed. Microscopic simulation is used to simulate incident scenarios on various corridors in the Tampa Bay area. The effect of the three factors, namely, network, speed and signal strategies on the traffic flow is studied. The network performance is based on Highway Capacity Manual specified measures of effectiveness prepared by the Transportation Research Board. Three inherently different city corridors, high, medium and low volume, are used to test the strategies developed. The strategies investigated include varying speed limits during incidents and using pre-timed and semi-actuated signals that respond to real time traffic volumes. The effectiveness measures are total delay in vehicle minutes, average speed in miles per hour and average travel time in seconds. Different facilities on a network include intersections; both signalized and unsignalized, local highways and arterials. The outputs from the simulation model is used to set up a factorial design to study the interaction between network type, signal strategy and speed strategy with the measures of effectiveness being the response variables. This type of corridor analysis is unique and provides decision support for local transportation planning departments for making corridor enhancements. In most city, state or county planning departments road planning is merely based on projected traffic demand using existing static models and does not factor necessary adjustments for incidents. Another unique aspect of this research is that variable speed limits are tested on surface streets. Such a test is not available in the literature. With dynamic message signs, next generation communication networks for traffic signal control and ITS technologies available, it is possible to implement the strategies suggested in this research.

Activity-based travel demand model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. However, a critical dimension that is often missed in these models is that of vehicle type choice. The current dissertation addresses this issue head-on and contributes to the field of transportation planning in three major ways. First, this research develops a comprehensive vehicle micro-simulation framework that incorporates state-of-the-art household vehicle type choice, usage, and evolution models. The novelty of the framework developed is that it accommodates all the dimensions characterizing vehicle fleet/usage decisions, as well as accommodates all dimensions of vehicle transactions (i.e., fleet evolution) over time. The models estimated are multiple discrete-continuous models (vehicle type being the discrete component and vehicle mileage being the continuous component) and spatial discrete choice models that explicitly accommodate for multiple vehicle ownership and spatial interactions among households. More importantly, the vehicle fleet simulator developed in this study can be easily integrated within an activity-based microsimulation framework. Second, the vehicle fleet evolution and composition models developed in this dissertation are used to predict the vehicle fleet characteristics, annual mileage, and the associated fuel consumption and green-house gas (GHG) emissions for future years as a function of the built environment, demographics, fuel and related technology, and policy scenarios. This exercise contributes in substantial ways to the identification of promising strategies to increase the penetration of alternative-fuel vehicles and fuel-efficient vehicles, reduce energy consumption, and reduce greenhouse gas emissions. Lastly, this research captures several complex interactions between vehicle ownership, location, and activity-travel decisions of individuals by estimating 1) a joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length, and 2) an integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. The methodology used for estimating these models allows the specification and estimation of multi-dimensional choice model systems covering a wide spectrum of dependent variable types (including multinomial, ordinal, count, and continuous) and may be viewed as a major advance with the potential to lead to redefine the way activity-based travel model systems are structured and implemented. / text

Public transit is considered a cost-effective alternative to mitigate the effects of traffic gridlock through the implementation of innovative service designs, and deploying new smart systems for operations control and traveller information. Public transport planners use transit assignment models to predict passenger loads and levels of service. Existing transit assignment approaches have limitations in evaluating the effects of information technologies, since they are neither sensitive to the types of information that may be provided to travellers nor to the traveller’s response to that information. Moreover, they are not adequate for evaluating the impacts of Intelligent Transportation Systems (ITS) deployments on service reliability, which in turn affect passengers’ behaviour. This dissertation presents an innovative transit assignment framework, namely the MIcrosimulation Learning-based Approach to TRansit ASsignment – MILATRAS. MILATRAS uses learning and adaptation to represent the dynamic feedback of passengers’ trip choices and their adaptation to service performance. Individual passengers adjust their behaviour (i.e. trip choices) according to their experience with the transit system performance. MILATRAS introduces the concept of ‘mental model’ to maintain and distinguish between the individual’s experience with service performance and the information provided about system conditions. A dynamic transit path choice model is developed using concepts of Markovian Decision Process (MDP) and Reinforcement Learning (RL). It addresses the departure time and path choices with and without information provision. A parameter-calibration procedure using a generic optimization technique (Genetic Algorithms) is also proposed. A proof-of-concept prototype has been implemented; it investigates the impact of different traveller information provision scenarios on departure time and path choices, and network performance. A large-scale application, including parameter calibration, is conducted for the Toronto Transit Commission (TTC) network. MILATRAS implements a microsimulation, stochastic (nonequilibrium-based) approach for modelling within-day and day-to-day variations in the transit assignment process, where aggregate travel patterns can be extracted from individual choices. MILATRAS addresses many limitations of existing transit assignment models by exploiting methodologies already established in the areas of traffic assignment and travel behaviour modeling. Such approaches include the microsimulation of transportation systems, learning-based algorithms for modelling travel behaviour, agent-based representation for travellers, and the adoption of Geographical Information Systems (GIS). This thesis presents a significant step towards the advancement of the modelling for the transit assignment problem by providing a detailed operational specification for an integrated dynamic modelling framework – MILATRAS.