Surveys are commonly tailored to produce estimates of aggregate statistics with a desired level of precision. This may lead to very small sample sizes for subpopulations of interest, defined geographically or by content, which are not incorporated into the survey design. We refer to subpopulations where the sample size is too small to provide direct estimates with adequate precision as small areas or small domains. Despite the small sample sizes, reliable small area estimates are needed for economic and political decision making. Hence, model-based estimation techniques are used which increase the effective sample size by borrowing strength from other areas to provide accurate information for small areas. The paragraph above introduced small area estimation as a field of survey statistics where two conflicting philosophies of statistical inference meet: the design-based and the model-based approach. While the first approach is well suited for the precise estimation of aggregate statistics, the latter approach furnishes reliable small area estimates. In most applications, estimates for both large and small domains based on the same sample are needed. This poses a challenge to the survey planner, as the sampling design has to reflect different and potentially conflicting requirements simultaneously. In order to enable efficient design-based estimates for large domains, the sampling design should incorporate information related to the variables of interest. This may be achieved using stratification or sampling with unequal probabilities. Many model-based small area techniques require an ignorable sampling design such that after conditioning on the covariates the variable of interest does not contain further information about the sample membership. If this condition is not fulfilled, biased model-based estimates may result, as the model which holds for the sample is different from the one valid for the population. Hence, an optimisation of the sampling design without investigating the implications for model-based approaches will not be sufficient. Analogously, disregarding the design altogether and focussing only on the model is prone to failure as well. Instead, a profound knowledge of the interplay between the sample design and statistical modelling is a prerequisite for implementing an effective small area estimation strategy. In this work, we concentrate on two approaches to address this conflict. Our first approach takes the sampling design as given and can be used after the sample has been collected. It amounts to incorporate the survey design into the small area model to avoid biases stemming from informative sampling. Thus, once a model is validated for the sample, we know that it holds for the population as well. We derive such a procedure under a lognormal mixed model, which is a popular choice when the support of the dependent variable is limited to positive values. Besides, we propose a three pillar strategy to select the additional variable accounting for the design, based on a graphical examination of the relationship, a comparison of the predictive accuracy of the choices and a check regarding the normality assumptions.rnrnOur second approach to deal with the conflict is based on the notion that the design should allow applying a wide variety of analyses using the sample data. Thus, if the use of model-based estimation strategies can be anticipated before the sample is drawn, this should be reflected in the design. The same applies for the estimation of national statistics using design-based approaches. Therefore, we propose to construct the design such that the sampling mechanism is non-informative but allows for precise design-based estimates at an aggregate level.

The classic Capital Asset Pricing Model and the portfolio theory suggest that investors hold the market portfolio to diversify idiosyncratic risks. The theory predicts that expected return of assets is positive and that reacts linearly on the overall market. However, in reality, we observe that investors often do not have perfectly diversified portfolios. Empirical studies find that new factors influence the deviation from the theoretical optimal investment. In the first part of this work (Chapter 2) we study such an example, namely the influence of maximum daily returns on subsequent returns. Here we follow ideas of Bali et al. (2011). The goal is to find cross-sectional relations between extremely positive returns and expected average returns. We take account a larger number of markets worldwide. Bali et al. (2011) report with respect to the U.S. market a robust negative relation between MAX (the maximum daily return) and the expected return in the subsequent time. We extent substantially their database to a number of other countries, and also take more recent data into account (until end of 2009). From that we conclude that the relation between MAX and expected returns is not consistent in all countries. Moreover, we test the robustness of the results of Bali et al. (2011) in two time-periods using the same data from CRSP. The results show that the effect of extremely positive returns is not stable over time. Indeed we find a negative cross-sectional relation between the extremely positive returns and the average returns for the first half of the time series, however, we do not find significant effects for the second half. The main results of this chapter serve as a basis for an unpublished working paper Yuan and Rieger (2014b). While in Chapter 2 we have studied factors that prevent optimal diversification, we consider in Chapter 3 and 4 situations where the optimal structure of diversification was previously unknown, namely diversification of options (or structured financial products). Financial derivatives are important additional investment form with respect to diversification. Not only common call and put options, but also structured products enable investors to pursue a multitude of investment strategies to improve the risk-return profile. Since derivatives become more and more important, diversification of portfolios with dimension of derivatives is of particularly practical relevance. We investigate the optimal diversification strategies in connection with underlying stocks for classical rational investors with constant relative risk aversion (CRRA). In particular, we apply Monte Carlo method based on the Black-Scholes model and the Heston model for stochastic volatility to model the stock market processes and the pricing of the derivatives. Afterwards, we compare the benchmark portfolio which consists of derivatives on single assets with derivatives on the index of these assets. First we compute the utility improvement of an investment in the risk-free assets and plain-vanilla options for CRRA investors in various scenarios. Furthermore, we extend our analysis to several kinds of structured products, in particular capital protected notes (CPNs), discount certificates (DCs) and bonus certificates (BCs). We find that the decision of an investor between these two diversification strategies leads to remarkable differences. The difference in the utility improvement is influenced by risk-preferences of investors, stock prices and the properties of the derivatives in the portfolio. The results will be presented in Chapter 3 and are the basis for a yet unpublished working paper Yuan and Rieger (2014a). To check furthermore whether underlyings of structured products influence decisions of investors, we discuss explicitly the utility gain of a stock-based product and an index-based product for an investor whose preferences are described by cumulative prospect theory (CPT) (Chapter 4, compare to Yuan (2014)). The goal is that to investigate the dependence of structured products on their underlying where we put emphasis on the difference between index-products and single-stock-products, in particular with respect to loss-aversion and mental accounting. We consider capital protected notes and discount certificates as examples, and model the stock prices and the index of these stocks via Monte Carlo simulations in the Black-Scholes framework. The results point out that market conditions, particularly the expected returns and volatility of the stocks play a crucial role in determining the preferences of investors for stock-based CPNs and index-based CPNs. A median CPT investor prefers the index-based CPNs if the expected return is higher and the volatility is lower, while he prefers the stock-based CPNs in the other situation. We also show that index-based DCs are robustly more attractive as compared to stock-based DCs for CPT investors.

Legalisation cannot be fully explained by interest politics. If that were the case, the attitudes towards legalisation would be expected to be based on objective interests and actual policies in France and Germany would be expected to be more similar. Nor can it be explained by institutional agency, because there are no hints that states struggle with different normative traditions. Rather, political actors seek to make use of the structures that already exist to guar-antee legitimacy for their actions. If the main concern of governmental actors really is to accumulate legitimacy, as stated in the introduction, then politicians have a good starting position in the case of legalisation of illegal foreigners. Citizens" negative attitudes towards legalisation cannot be explained by imagined labour market competition; income effects play only a secondary role. The most important explanatory factor is the educational level of each individual. Objective interests do not trigger attitudes towards legalisation, but rather a basic men-tal predisposition for or against illegal immigrants who are eligible for legalisation. Politics concerning amnesties are thus not tied to an objectively given structure like the socio-economic composition of the electorate, but are open for political discretion. Attitudes on legalising illegal immigrants can be regarded as being mediated by beliefs and perceptions, which can be used by political agents or altered by political developments. However, politicians must adhere to a national frame of legitimating strategies that cannot be neglected without consequences. It was evident in the cross-country comparison of political debates that there are national systems of reference that provide patterns of interpretation. Legalisation is seen and incorporated into immigration policy in a very specific way that differs from one country to the next. In both countries investigated in this study, there are fundamental debates about which basic principles apply to legalisation and which of these should be held in higher esteem: a legal system able to work, humanitarian rights, practical considerations, etc. The results suggest that legalisation is "technicized" in France by describing it as an unusual but possible pragmatic instrument for the adjustment of the inefficient rule of law. In Germany, however, legalisation is discussed at a more normative level. Proponents of conservative immigration policies regard it as a substantial infringement on the rule of law, so that even defenders of a humanitarian solution for illegal immigrants are not able to challenge this view without significant political harm. But the arguments brought to bear in the debate on legalisation are not necessarily sound because they are not irrefutable facts, but instruments to generate legitimacy, and there are enough possibilities for arguing and persuading because socio-economic factors play a minor role. One of the most important arguments, the alleged pull effect of legalisation, has been subjected to an empirical investigation. In the political debate, it does not make any dif-ference whether this is true or not, insofar as it is not contested by incontrovertible findings. In reality, the results suggest that amnesties indeed exert a small attracting influence on illegal immigration, which has been contested by immigration friendly politicians in the French par-liament. The effect, however, is not large; therefore, some conservative politicians may put too much stress on this argument. Moreover, one can see legalisation as an instrument to restore legitimacy that has slipped away from immigration politics because of a high number of illegally residing foreigners. This aspect explains some of the peculiarities in the French debate on legalisation, e.g. the idea that the coherence of the law is secured by creating exceptional rules for legalising illegal immigrants. It has become clear that the politics of legalisation are susceptible to manipulation by introducing certain interpretations into the political debate, which become predominant and supersede other views. In this study, there are no signs of a systematic misuse of this constellation by any certain actor. However, the history of immigration policy is full of examples of symbolic politics in which a certain measure has been initiated while the actors are totally aware of its lack of effect. Legalisation has escaped this fate so far because it is a specific instrument that is the result of neglecting populist mechanisms rather than an ex-ample of a superficial measure. This result does not apply to policies concerning illegal immi-gration in general, both with regard to concealing a lack of control and flexing the state- muscles.

For the first time, the German Census 2011 will be conducted via a new method the register based census. In contrast to a traditional census, where all inhabitants are surveyed, the German government will mainly attempt to count individuals using population registers of administrative authorities, such as the municipalities and the Federal Employment Agency. Census data that cannot be collected from the registers, such as information on education, training, and occupation, will be collected by an interview-based sample survey. Moreover, the new method reduces citizens' obligations to provide information and helps reduce costs significantly. The use of sample surveys is limited if results with a detailed regional or subject-matter breakdown have to be prepared. Classical estimation methods are sometimes criticized, since estimation is often problematic for small samples. Fortunately, model based small area estimators serve as an alternative. These methods help to increase the information, and hence the effective sample size. In the German Census 2011 it is possible to embed areas on a map in a geographical context. This may offer additional information, such as neighborhood relations or spatial interactions. Standard small area models, like Fay-Herriot or Battese-Harter-Fuller, do not account for such interactions explicitly. The aim of our work is to extend the classical models by integrating the spatial information explicitly into the model. In addition, the possible gain in efficiency will be analyzed.

Weltweit untersuchen viele Wissenschaftler die Ursachen für die Entstehung und Ausdehnung industrieller Cluster. Die Ergebnisse dieser Bemühungen sind in zahlreichen empirischen Studien dokumentiert worden. Die Mehrheit der Arbeiten legt ihren Fokus auf die Entwicklung einer präzisen Messmethodik für die Konzentrationsstärke. Hierzu ist ein breites Instrumentarium an Maßzahlen bereits verfügbar und lässt sich je nach Forschungsziel erkenntnisbringend einsetzen. Dennoch bleibt die Trennung zwischen unterschiedlichen geographischen Grundmustern unzureichend. Insbesondere trifft dies auf unterschiedliche Typen der Konzentration zu. Die vorliegende Arbeit bietet eine umfassende Konzentrationsanalyse des Wirtschaftsstandorts Deutschland auf unterschiedlichen regionalen und sektoralen Aggregationsebenen. Dabei verfolgt sie das Ziel, durch eine detaillierte Untersuchung der räumlichen Verteilungsmuster der wirtschaftlichen Aktivität einen Beitrag zur Erklärung der Ansiedlungsstrukturen der einzelnen Wirtschaftszweige zu leisten. Hierfür wird eine gänzlich neue Methodik entwickelt, die das Identifizieren einer breiteren Palette an geographischen Grundmustern sowohl statisch als auch dynamisch zulässt. Da die Unterscheidung zwischen verschiedenen Typen der Konzentration bisher kaum Gegenstand wissenschaftlicher Untersuchung war, stößt der hier verfolgte Ansatz auf ein relativ neues Forschungsfeld vor. Die Existenz unterschiedlicher Typen bzw. Formen der Konzentration beruht auf einer einfachen Überlegung: Neben städtisch konzentrierten Wirtschaftszweigen muss es zwangsläufig auch ländlich konzentrierte Wirtschaftszweige geben. Hiervon ausgehend werden sieben geographische Grundmuster identifiziert. Neben dem dispersen und dem zufälligen Grundmuster wird zwischen fünf verschiedenen Typen der Konzentration unterschieden. Die Identifikation der einzelnen Grundmuster erfolgt auf Basis des Rangkorrelationskoeffizienten von Goodman-Kruskal. Dem entwickelten Ansatz wird mithilfe bivariater Konfidenzregionen eine exakte und durch statistische Signifikanz fundierte Aussagekraft verliehen. Des Weiteren wird im Rahmen der Arbeit festgestellt, dass ein Vernachlässigen der unterschiedlichen geographischen Grundmuster in inhaltlich irreführenden und fragwürdigen Konzentrationsvergleichen münden kann. Parallel dazu werden acht Indizes zur Erfassung der Konzentrationsstärke behandelt. Sie werden hinsichtlich der Datenanforderungen in drei Gruppen unterteilt und im Hinblick auf ihre Verlässlichkeit und Aussagekraft ausführlich untersucht. Die empirische Konzentrationsanalyse belegt für alle drei Gruppen, dass die durchschnittliche Konzentration der deutschen Wirtschaftsgruppen von 1995 bis 2010 kontinuierlich gefallen ist. Darüber hinaus wird in der Arbeit gezeigt, dass die Wirtschaftszweige in Deutschland sehr unterschiedlichen Konzentrationstypen folgen und dass weder die traditionellen noch die komplexen, distanzbasierten Maßzahlen imstande sind, zwischen verschiedenen Typen der Konzentration zu unterscheiden.