Suchergebnisse

Successful descriptions of short-term nominal interest rates inertial behavior have frequently been obtained with small scale macro models in which a Central Banker minimizes a loss function embedding an argument labelled as interest rate smoothing. The rationale for this argument is not straightforward. Indeed, there has been a lively debate about it in the literature. In this paper we perform an empirical exercise to evaluate the relationship existing between private sector's rational expectations and interest rate gradualism. Our findings strongly support rational expectations as an element capable to remarkably reduce the importance of the interest rate smoothing weight in replicating the observed path of the federal funds rate. However, we find a predominance of adaptive expectations in shaping the paths of inflation ad output gap. Our results also suggest that the Fed has followed a 'Strict Inflation Targeting' strategy under Greenspan's regime.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these fundamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these undamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these undamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these fundamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these undamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these undamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value.

Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Acknowledgments -- Introduction -- PART ONE Engagement -- 1 Establishing a Working Alliance -- 2 Setting Expectations -- 3 Orienting and Onboarding -- PART TWO Assessment -- 4 Observation -- 5 Interviewing -- 6 Assessment Tools -- PART THREE Intervention -- 7 Crisis Management -- 8 Resistance to Change -- 9 Performance Issues -- PART FOUR Evaluation & -- Termination -- 10 Staff Development -- 11 Periodic Review and Performance Monitoring -- 12 Termination -- PART FIVE Self-Care -- 13 Boundaries -- 14 Vicarious Trauma and Secondary Traumatic Stress -- 15 Work-Life Balance -- Index.

Die vorliegende Dissertation untersucht die Wechselwirkungen zwischen Medienberichterstattung über Inflation und den Inflationserwartungen von Haushalten. Seit dem Beginn der 2000er Jahre sind einige Modelle zur Überwindung der Grenzen von rationalen Erwartungen vorgeschlagen worden. Diese geben eine wichtige Annahme des rationalen Erwartungsbildungsparadigmas auf, wonach Haushalte immer alle aktuell verfügbaren Informationen verwenden um Einschätzungen über die Zukunft vorzunehmen. In dieser Dissertation testen wir daher, auf welche Informationen sich Haushalte beziehen wenn sie Erwartungen über die zukünftige Inflation bilden, wobei ein besonderes Augenmerk auf die Rolle der Medien gelegt wird. Zu Beginn untersuchen wir das bekannte Epidemiologie-Modell der Erwartungsbildung. Mit Hilfe von Umfragedaten zu Inflationserwartungen in den USA, sowie Daten zur Medienberichterstattung über Inflation in der New York Times zeigen wir, dass das Modell durchaus von den Daten gestützt wird. Haushalte passen ihre Erwartungen an die Meinungen von Experten an, wobei die Anpassungsgeschwindigkeit mit der Anzahl der Medienberichte ansteigt. Außerdem ist die Anpassungsgeschwindigkeit nicht immer gleich: Haushalte beziehen sich stärker auf Experten in Zeiten niedriger Inflation sowie während der Finanzkrise. Darüber hinaus können wir zeigen, dass sich auf der Mikroebene stärkere Medieneffekte finden lassen. Unterscheidet man Haushalte nach ihrer individuellen Informationswahrnehmungen, so lässt sich feststellen, dass Individuen die angeben, zuletzt Neuigkeiten über Inflation gehört zu haben, einem größeren Prognosefehler unterliegen und außerdem stärker auf Medienberichte reagieren. Außerdem scheint der Medieneffekt nichtlinear zu sein: Mit steigender Anzahl an Medienberichten über Inflation erhöht sich der Einfluss der Experten auf die Erwartungsbildung der Haushalte, wobei die Anpassung nur langsam von statten geht und vom durchschnittlichen Niveau der Berichterstattung abhängt. Im nächsten Kapitel wird das Epidemiologie-Modell auf verschiedene Haushaltsgruppen und Medien angewandt. Unter Verwendung von deutschen Daten versuchen wir ein wiederkehrendes Muster in Umfragen zu erklären, wonach sich die Inflationserwartungen je nach sozioökonomischem Hintergrund der Befragten unterscheiden. Zum Beispiel ist oft zu beobachten, dass Niedrigeinkommensbezieher größere Prognosefehler begehen. Wir testen ob sich dieses Muster dadurch erklären lässt, dass sich der Medienkonsum verschiedener Haushaltsgruppen unterscheidet. Wir können zeigen, dass sich der Medienkonsum in der Tat zwischen Einkommens-, Alters- und Berufsgruppen unterscheidet. Außerdem belegen wir, dass die Verwendung eines aus mehreren Einzelmedien aggregierten Medienindex irreführend sein kann. Berichterstattung über Inflation in der Tagesschau führt dazu, dass Haushalte in ihren Erwartungen stärker von Experten abweichen, während eine Ausweitung der Berichterstattung in BILD die Haushaltserwartungen den Expertenprognosen annähert. Schließlich ist es wichtig, zwischen der Anzahl an Medienberichten und einer Veränderung in der Einschätzung der verantwortlichen Journalisten zu unterscheiden. Während sich die Erwartungslücke der Haushalte erhöht wenn BILD die Inflationsentwicklung stark negativ darstellt, so führt eine negativere Berichterstattung in der Tagesschau dazu, dass sich die Haushaltserwartungen den Experten annähern. Im letzten Kapitel erweitern wir den Ansatz des Epidemiologie-Modells indem wir die Anzahl der Googlesuchanfragen nach Inflation einbeziehen. Googlesuchanfragen können als Proxy für die Informationsnachfrage von Nutzern interpretiert werden, wenn Haushalte dann im Internet nach Informationen suchen wenn sie mehr über die derzeitige oder zukünftige Preisentwicklung wissen wollen. Internetsuchdaten lassen sich daneben auch als Ergänzung zu durch Umfragen gemessenen Inflationserwartungen verstehen. Während Umfrageteilnehmer keinen Anreiz haben, ihre bestmögliche Inflationsschätzung anzugeben, so werden Haushalte nur nach Informationen im Internet suchen, wenn sie diese auch wirklich nutzen wollen. Wir zeigen dass die Anzahl der Googlesuchanfragen auf ökonomische Fundamentaldaten reagiert. Googlenutzer unterscheiden zwischen Gesamt- und Kerninflationsrate wobei ihre Reaktion asymmetrisch ist: Die Informationsnachfrage geht zurück wenn die Kernrate fällt, während in Zeiten historisch hoher Inflation die Informationsnachfrage ansteigt. Mittels VAR-Modellen finden wir, dass die Inflationserwartungen von Haushalten sowohl von TV-Nachrichten, Zeitungsartikeln als auch von der Zahl der Googlesuchanfragen abhängen, während der Feedbackeffekt von Erwartungen auf die Informationsnachfrage eher gering ist. Ungefähr 20% der prognostizierten Fehlerdekomposition der Inflationserwartungen lassen sich durch Googlesuchanfragen erklären. ; This dissertation explores the various links between news media coverage of inflation and the inflation expectations of households. Since the beginning of 2000, a number of alternative models of expectation formation have been proposed seeking to overcome the limits of rational expectations. A common feature of these new approaches consists in relaxing an important assumption of the rational expectations paradigm: that households use the latest available information set when forming beliefs about the future. Throughout this dissertation, we will thus test which kind of information households rely on when forecasting inflation, focusing in particular on the role of the news media. We start with testing the prominent epidemiology model of expectation formation. Using survey data on inflation expectations in the U.S., and news coverage of inflation in The New York Times, we provide empirical evidence supporting the epidemiology model. Households are found to adjust their beliefs to the average inflation forecast of experts, whereas the speed of adjustment rises in line with the number of news reports on inflation. The speed of updating varies significantly over time: households rely more on experts in periods of low inflation and during economic crises. Applying our analysis using both macro and micro survey data on expectations, we find that the news media effect is larger on the micro level. Looking at households with different news perceptions, we find that those who claim to have heard news on inflation commit larger forecast errors than other households while at the same time being more receptive to media reports. Finally, our results suggest that the media effect is nonlinear: An increasing number of news reports increases the impact from expert expectations, whereas the adjustment takes place only gradually and depends on a threshold level of news reports. The next chapter applies the framework of the epidemiology model to different household groups and news media sources. Using German data, we try to explain the stylized fact that households disagree considerably in their beliefs on future prices depending on their socioeconomic background. For example, low-income or unemployed households are often found to commit larger forecaster errors than high-income households. We test the hypothesis that these differences emerge from socioeconomic news exposure, meaning that households belonging to different socioeconomic groups read different newspapers. And since the media differ in the extent and the way they cover economic topics such as inflation, the information set of their corresponding readers will differ. Constructing an index of newspaper coverage and TV coverage, we indeed observe considerable heterogeneity in news consumption across income, age and occupation groups. Furthermore, we find that constructing an index of news reports by aggregating all available newspaper and TV reports can be misleading. Coverage of inflation in Tagesschau is found to increase the gap between households and professional forecasters, while a rising number of articles published in BILD brings households closer to the best available forecast. Finally, it is important to distinguish between the effects of a rise in the number of news reports and a change in the journalists' judgment of inflation. Whereas households' expectation gaps increase if BILD presents inflation in a negative way thereby possibly inducing a media bias, more negative coverage in Tagesschau narrows the gap between households and professional forecasters. In the final chapter, we extend the framework of the epidemiology model by including the number of Google search requests of inflation. This measure can be understood as a proxy for the demand of information in the sense that households will search for inflation on the web if they need do know more about the current or future price environment. Internet search data could also serve as a complement to inflation expectations measured by surveys. Whereas survey respondents do not have an incentive to provide their best forecast, households will only search for inflation if they really want to use this information. We find that the number of Google search requests reacts in a meaningful way to fundamental economic data. Google users distinguish between headline and core inflation and they react asymmetrically: the demand for information increases if core inflation falls whereas in periods of historically high inflation rates, the number of search requests is significantly larger. Estimating various Vector Autoregressive Models, we find that households' inflation forecasts are driven by TV reports, newspaper articles, and Google search requests, while the feedback effect from expectations on web searches is rather small and estimated less precisely. About 20% of the forecast error variance decomposition of households' inflation expectations can be explained by Google search requests.

Despite a large literature documenting that the efficacy of monetary policy depends on how inflation expectations are anchored, many monetary policy models assume: (1) the inflation target of monetary policy is constant; and, (2) the inflation target is known by all economic agents. This paper proposes an empirical specification with two policy shocks: permanent changes to the inflation target and transitory perturbations of the short-term real rate. The public sector cannot correctly distinguish between these two shocks and, under incomplete learning, private perceptions of the inflation target will not equal the true target. The paper shows how imperfect policy credibility can affect economic responses to structural shocks, including transition to a new inflation target - a question that cannot be addressed by many commonly used empirical and theoretical models. In contrast to models where all monetary policy actions are transient, the proposed specification implies that sizable movements in historical bond yields and inflation are attributable to perceptions of permanent shocks in target inflation.

Despite a large literature documenting that the efficacy of monetary policy depends on how inflation expectations are anchored, many monetary policy models assume: (1) the inflation target of monetary policy is constant; and, (2) the inflation target is known by all economic agents. This paper proposes an empirical specification with two policy shocks: permanent changes to the inflation target and transitory perturbations of the short-term real rate. The public sector cannot correctly distinguish between these two shocks and, under incomplete learning, private perceptions of the inflation target will not equal the true target. The paper shows how imperfect policy credibility can affect economic responses to structural shocks, including transition to a new inflation target - a question that cannot be addressed by many commonly used empirical and theoretical models. In contrast to models where all monetary policy actions are transient, the proposed specification implies that sizable movements in historical bond yields and inflation are attributable to perceptions of permanent shocks in target inflation.

Bank Regulation, Risk Management, and Compliance is a concise yet comprehensive treatment of the primary areas of US banking regulation – micro-prudential, macroprudential, financial consumer protection, and AML/CFT regulation – and their associated risk management and compliance systems. The book's focus is the US, but its prolific use of standards published by the Basel Committee on Banking Supervision and frequent comparisons with UK and EU versions of US regulation offer a broad perspective on global bank regulation and expectations for internal governance. The book establishes a conceptual framework that helps readers to understand bank regulators' expectations for the risk management and compliance functions. Informed by the author's experience at a major credit rating agency in helping to design and implement a ratings compliance system, it explains how the banking business model, through credit extension and credit intermediation, creates the principal risks that regulation is designed to mitigate: credit, interest rate, market, and operational risk, and, more broadly, systemic risk. The book covers, in a single volume, the four areas of bank regulation and supervision and the associated regulatory expectations and firms' governance systems. Readers desiring to study the subject in a unified manner have needed to separately consult specialized treatments of their areas of interest, resulting in a fragmented grasp of the subject matter. Banking regulation has a cohesive unity due in large part to national authorities' agreement to follow global standards and to the homogenizing effects of the integrated global financial markets. The book is designed for legal, risk, and compliance banking professionals; students in law, business, and other finance-related graduate programs; and finance professionals generally who want a reference book on bank regulation, risk management, and compliance. It can serve both as a primer for entry-level finance professionals and as a reference guide for seasoned risk and compliance officials, senior management, and regulators and other policymakers. Although the book's focus is bank regulation, its coverage of corporate governance, risk management, compliance, and management of conflicts of interest in financial institutions has broad application in other financial services sectors.

In the passing 20 years, China's urban housing market has been experiencing a rapid development period. As an essential pillar industry, the housing sector drives the development of over 60 industries and even contributes dramatically to the whole economy. The rapid development pace of the housing sector is mainly due to the rapid growth of the investment in housing industry, which leads to the significant rising of land price and housing price. However, the housing market is special compared with other markets. The unique characteristics of housing determine the housing market embodies its own special characteristics. Both of the special characteristics lead to the phenomenon of the simultaneous existing of market failure and policy failure. Hence, it is of great importance for the government to intervene in the housing market to achieve the policy goal of sustainable social development and equity chance of home ownership. Generally, there are 4 types of control tools that the government could take to regulate the housing industry, namely financial tools, fiscal tools, land policy and administrative policy, the mechanism and effectiveness of which is largely differentiated from each other. Firstly, as a capital-intensive industry, the supply and demand of housing are inseparable from financial support. The impact of financial policy on housing market is achieved by means of deposit rate and loan rate. However, since the financial tools is more obvious on housing supply and the expectation that continuous growing of housing price of residents is strong, the effectiveness of the financial control tools is not obvious on controlling the housing price. Secondly, fiscal policies, mainly tax, have an impact on the housing market, but there is a certain amount of time lag of the control tools of tax no matter in the regulation of the structure of housing market or in the regulation of the supply and demand of housing. The effectiveness of tax is obvious since it directly affects the cost of the developers and the buyers. Thirdly, land policy affects the housing market by controlling the amount of land supply or arranging different land uses to inhibit or encourage housing demand. However, from the practical effect of land policy on the control of housing price, the actual result is relatively poor because the land price doesn't effectively control the housing price. Finally, administrative policy is the special characteristic of macro-control tools in China, and affects the housing market by controlling the development and transaction process. The effectiveness is direct and manifest but differs among the districts. Overall, due to the low efficiency of the government, the administrative interference in the housing market did not achieve the expected market reaction. The analysis of the macro control tools and the effectiveness on controlling the housing price in China could provide enlightenments for the further making and implementation of housing control tools. ; published_or_final_version ; Housing Management ; Master ; Master of Housing Management