CASE - Center for Applied Statistics and Economics

CASE - Center for Applied Statistics and Economics Interdisciplinary Center at the Humboldt-Universität zu Berlin

Research

CASE is a center based at the School of Business and Econom-ics which offers an environment for interdisciplinary collabo-rative work on current economic challenges.

The interdisciplinary centre CASE was founded in 2001 at the School of Business and Economics of the Humboldt-Uni-versität zu Berlin. The stated aim of the centre is to tackle in-creasingly complex problems in the field of economics and associated areas with specialised knowledge, quantitative methods and the application of modern computer technol-ogy. Particularly significance is placed on an interdisciplinary approach where quantitative methods are combined with technical expertise and, as members of CASE come from a va-riety of disciplines, the technical expertise used is not limited to economics:

• Mathematics• Statistics and Econometrics• Law• Economics• Business Administration• Agriculture Forestry• Theology

To accomplish its aims CASE uses, as its framework, highly qualified scientists who are brought together and supported

CASE - Center for Applied Statistics and Economics

Economic Challenges

in their quantitative research project. In addition to individual research projects, regular interaction between members is also a priority and intense contact with external researchers is maintained. This is achieved firstly through the organisation of a significant number of annual scientific events to which well-known scientists are invited and, secondly, through weekly research seminars.

In an era of increasing complexity, the structural relationship between quantitative methods and technical expertise ena-bles CASE to offer application-oriented approaches using the most up-to-date techniques.

Research

CASE provides the ideal platform to solve contemporary eco-nometric challenges using interdisciplinary collaborations.


How does CASE work?

The research projects in the individual technical disciplines are the cornerstones of CASE. Every member initially brings his or her specific expertise to the centre. The diversity of the fields of specialisation involved enables CASE to research in a wide range of subject areas such as, weather risk, aging societies, crime or the property market. The individual CASE projects are categorised into three basic areas: Environment, Economy and Society.

The interdisciplinary quantitative focus of CASE shapes its basic framework. As a result of the comprehensive integration of the Institutes of Mathematics, Statistic and Econometrics, the latest quantitative technologies are applied to individual specialist areas and lead to practical applications. This interaction is enhanced by annual CASE conferences and meetings such as, the Humboldt-Princeton Conference with its theme of financial mathematics, or the weekly CASE Research Seminars. Furthermore, individual members have access to the Research Data Center (RDC), which provides a rich variety of data and a powerful computing platform for analysis.Both of these components of quantitative research provide the members of CASE access to a thoroughly comprehensive facility which none of the individual participating institutes would normally be able to provide alone.

Technical Expertise

Quantitative Methods


Expertise at the Humboldt-Universität

Institute of Mathematics

School of Business and Economics

Faculty of Agriculture and Horticulture

Environment Economics Society

Law School

Theology Faculty




Faculty of Agricul-ture and Horiculture


Quantitative Models and Methods

CASE - Topics

Risk Factor: Weather

Initial SituationCrop failure in agriculture caused by adverse weather presents insurance companies and reinsurers worldwide with enormous challenges because weather risk is often systematic in character. So in the case of adverse weather events, for example, a drought, whole regions or even whole countries are affected. As a result, the prerequisite of insurability, namely the independence of damaging events is compromised. Systematic weather risk is often cited as an explanation for the lack of offers by insurers for agriculture, or as grounds for higher state premium subsidies.

CASE MethodWith the establishment of new financial market products, which allow for the trading of weather risks, insurance companies basically have the possibility to transfer a proportion of their risk to the capital markets. This type of risk transfer can overcome the problems traditionally associated with classic reinsurance.

ObjectiveThe project examines the characteristics of the products provided by the financial markets. The emphasis is put on so-called weather bonds, where the return on capital employed is dependent on the value and characteristics of pre-defined weather indices.

Weather Bonds

Initial SituationThe demographic change in the German population has gained more and more relevance since the end of the 20th century. Changes in the structure of the population are decisive for numerous sociological, political and financial processes. The Germany pension system in particular is now facing very specific, new and complex challenges.

CASE MethodCASE is carrying out a stochastic population forecast for Germany, which is based on a multivariate analysis of mortality, fertility and migration. As part of this stochastic model not only will a “mean“ forecast for the future population-development be derived, but also an interval estimation of the relevant demographic factors, such as old-age dependency ratio or average lifeexpectancy. Furthermore the consequences of a new pension system, designed to supplement the existing official state pension system will also be examined. Half of the new pension system will be financed by a contribution system, while the other half will be realised through capital cover. These two elements mean that every pensioner will receive a guaranteed basic pension at the age of 67.

ObjectiveWith the use of this legally derived statistical model, it will be possible to save future generations the burden of rapidly increasing pension contributions. This cost reduction technique can, for example, be used to reduce ancillary labour costs.

Demography

CASE - Topics

Risk Factor: Ageing Society

Initial SituationPolice criminal investigation departments are often faced with a large number of possible investigative approaches when trying to solve complex crimes. Due to the evidence available at the scene of a crime, there are various scenarios for any crime and consequently a large number of possible suspects.

CASE MethodCASE assists with the disclosure of the age of offenders in sexually motivated murders. Predictions on the age of the offender, based on information found at the scene of a crime, are at the centre of this research project and help the police focus their investigations and thus improve their success rate. The theoretical background is based on the “Crime Scene Perspective“, which reveals that the events at the scene of a crime can only be solved by looking at the behaviour of perpetrator and victim and by taking into account the specific circumstances found at the scene of a crime. These three components are quantified for the analysis and the resultant data is then examined for structure. Subsequently the data will be illustrated with the use of graphical models.

ObjectiveThe objective is to enable the investigating authorities at the scene of a crime to bring uncovered evidence into a flexible model which has the capacity to determine the age of an offender.

Crime

CASE - Topics

Risk Factor: Crime

Initial SituationUnemployment has been a one of German society’s biggest challenges for more than three decades. Unemployment contributes to a wide range of economic, sociological and political problems. A detailed cause analysis is a premise for purposeful political measures for the reduction of unemployment.

CASE MethodCASE performs an analysis based on modern quantitative methods. Micro data sets enable a multiplicity of detailed analyses of population groups that, for example, are particularly often affected by unemployment to be inspected in detail. In this way a number of factors can be identified which contribute to an increased risk of unemployment. In addition, the data sets and methods enable the evaluation of political measures designed to reduce unemployment. The analysis of the impact of the employment market and market regulations on unemployment is also one of CASE’s focal points.

ObjectiveWith the help of econometric analyses the causes of unemployment are identified and action for its reduction recommended.

Employment Market

CASE - Topics

Risk Factor: Work

Initial SituationAre religions useful for a community or are they dangerous? This question cannot be answered simply. The influence of religion on the business mentality of a culture can also only be recognised with the help of detailed examination.

CASE MethodEver since Max Weber’s research on the influence of religious beliefs on economic mentality, many separate attempts have been made to empirically capture the relationship between religious and economic attitudes. This includes, for example, studies on “Islamic finance“, which at present is attracting a lot of attention. In this project the status of current research in international religious economics is documented and first class researchers brought together. A project entitled “Programme on Religion, Politics, and Economics“ sponsored by the Haniel-Stiftung (Foundation) is an appropriate platform for this fresh new direction in research.

ObjectiveThe objective of the programme is the documentation and coordination of religious economic research in Germany and the construction of an international network, designed to examine the question, if and how various religious cultures influence economic and business mentality.

CASE - Topics

Risk Factor: Religion

Economics of Religion

Initial SituationThe assessment of the value and performance of real estate for the benefit of purchasers and property owners is extremely difficult. In contrast to share values, property prices are not regularly fixed and published. Additionally, demand indicators found online are only of limited use because they can dramatically differ from actual selling prices. Moreover the heterogeneity of the property market is a big obstacle if different offers need be compared and summarised to accord with one global evaluation.

CASE MethodCASE is currently developing a statistical model designed to measure the relationship between price and other value defining factors such as location, plot size, floor space size and the construction year of a property. The data pool is extracted from the data on purchasing price by the Advisory Committee for Land Value (Gutachterausschuss für Grundstückswert (GAA)), which contains very detailed information about family home sales in Berlin. The varied information in the data is summarised by a hedonistic regression model and consequently the market value of a specific property can be forecast, based on its characteristics. The forecasting power of the model will be offered as an online service on the GAA website. Users of the service will receive instant, qualified price projections 24-hours-a-day based on the specifications and characteristics of a given property.

ObjectiveThe aim of this project is to constantly develop the forecast ability of the model, because an optimal compromise between the most detailed modelling possible (particularly location) and reliable estimation is sought after.

CASE - Topics

Risk Factor: Property

Real Estate

Initial SituationThe loss of market and finance liquidity is a relevant by-product of current financial crises. The volatility of liquidity and the systematic underestimation of liquidity risks have led to an in-tensification of several crises. It illustrates that the role of market liquidity and its implications for liquidity risk management have not yet been fully understood and solved in a satisfactory manner.

CASE MethodBased on high frequency financial market data and with the use of modern statistical and econometric methods, the empirical characteristics of market liquidity will be analysed and liquidity risk quantified. In order to cope with the high dimensionality of financial transaction data and order-book data, the focus will be on factor models, dimension reduction techniques and multivariate time series methods; in so doing various markets and securities can be exam-ined. In this context the emphasis will be on the analysis of market phases in which fundamen-tal information is processed.

ObjectiveThe aim of this project is to obtain new knowledge on the statistical properties of liquidity and its implications on optimal trading strategies combined with the risk management of financial institutes. In addition, liquidity risk will be quantified and its influence on bonds and securities prices analysed.

CASE - Topics

Risk Factor: Liquidity

Solvency

Initial SituationWhich part of our brain is activated when we make risky decisions? Do these regions of the brain show more activity in risk-seeking individuals than in risk-averse individuals? These and many other questions are addressed by researchers in neuroeconomics and behavioural finance.

CASE MethodDue to the high-dimensionality and the high-frequency of neurological data gained from functional Magnetic Resonance Imaging (fMRI), the application of advanced statistical techniques is indispensable. A semiparametric factor model for dimension reduction, developed by CASE, is applied to the fMRI data set. This innovative method enables the analysis of dynamic changes in brain activity to be carried out over time without any a-priori information about the scanned regions. All statistical results are discussed with specialist in neurology and psychology.

ObjectiveThe goal of the project is to find a universal statistical method to analyse brain fMRI data which can distinguish between risk-seeking and risk-averse individuals simply by examining their brain activity.

CASE - Topics

Risk Factor: Neuroeconomics

Neuroeconomics

In cooperation with the School of Business and Economics, CASE is proud to present six Alexander von Humboldt prize winners, who have been distinguished for their creativity and whose work has substantially influenced their respective areas of expertise.


Humboldt Research Prize

Personalities

1995: Raymond Carroll(Texas A&M University)

“Semiparametric Modelling, Variance Function Estima-tion and Deconvolution Methods“

1999: Joel Horowitz(University of Iowa)

“Semiparametric Models and Internet-based Quanti-tative Methods“

2004: Francis Diebold (University of Pennsylvania)

“Dynamic and Predictions on Volatility“

2005: Stephen Stigler (University of Chicago)

“The Development of Sta-tistic in Germany“

2006: Jianqing Fan (Princeton University)

“Non-parametric Methods in Financial Econometrics“

2008: Ya’acov Ritov (Hebrew University)

“Complex Statistical Models“


Scientific Communication

Series of Events• Economic Risk Seminar - Financial Markets and Economic Risk

• Schumpeter Seminar - Macroeconomic Topics

• Mathematical Statistics Seminar - Stochastic and Mathematical Statistics

• Distinguished Lecture Series - Financial Statistics

• Hermann Otto Hirschfeld Lecture - Applied Statistics

• Econ Boot Camp - Student Workshop

Events during the Anniversary Year of Humboldt-Universität (2009/2010)• Demographic Risk Workshop

• 200 Years of Finance and Statistics

• Weather Derivatives Workshop

• Haniel Summer School on Religion, Politics and Economics

• Chinese Week

• Skill Demands and Wage Inequality Workshop

Promoting young researcher• Master programme in Statistics - CASE initiated the inception of this cross-university Gradu-

ate Degree Course and takes responsibility for a large portion of the teaching duties.

• Computer Museum – CASE maintains a museum, which showcases the early days of the computer-age to students and other interested parties.

The above events are organised in association with the Collaborative Research Center 649 “Economic Risk” and the School of Business and Economics.

Events


Contact Information

Prof. Dr. Wolfgang Härdle (Director)

Humboldt-Universität zu Berlin Wirtschaftswissenschaftliche Fakultät Lehrstuhl für Statistik Unter den Linden 6 10099 Berlin

Tel: +49 (0)30 2093-5630Fax: +49 (0)30 2093-5649E-Mail: [email protected]

Leslie Udvarhelyi (Secretariat)

Humboldt-Universität zu Berlin CASE - Center for Applied Statistics and Economics Unter den Linden 610099 Berlin


Prof. Dr. Nikolaus Hautsch (Deputy Director)

Humboldt-Universität zu Berlin Wirtschaftswissenschaftliche Fakultät Lehrstuhl für Ökonometrie Unter den Linden 6 10099 Berlin


Location

Humboldt-Universität zu BerlinCASE - Center for Applied Statistics and EconomicsSpandauer Straße 110178 Berlin


Imprint

Published by CASE - Center for Applied Statistics and Economics

Berlin 2010

Editors

Prof. Dr. Wolfgang HärdleStephan Stahlschmidt

Picture Credits

Heike Zappe (S. 1, 4)Bernd Prusowski (S. 4)Dmitry Nikolaev (S. 4)Reinalde Roick (S. 5)Wolfgang Härdle (S. 1, 2, 3, 6, 10, 12, 13)Prophoto XL (S. 7)bilderbox (S. 8)Terrance Emerson (S. 9)Sebastian Kaulitzki (S. 11)

CASE - Center for Applied Statistics and Economics

Documents

Transcript of CASE - Center for Applied Statistics and Economics