Institution: Graduate School der Fakultät Wirtschafts- und Sozialwissenschaften der Universität Hamburg
Dozent/in: Dr. Stefanie Kley, Universität Hamburg
Termin(e): Do., 20.11.14, Fr., 21.11.14, Do., 27.11.4, Fr., 28.11.14 jeweils 10-18 Uhr
Ort/Raum: Raum A 510, VMP 9
Anmeldung: Die Anmeldung ist vom 11.09.14 (13 Uhr) bis 22.10.14 (13 Uhr) über Geventis möglich.
Institution: see Organisers & Acknowledgements
Programme of study: International Research Workshop
Lecturer: Dr. Stephanie Eckman (Institute for Employment Research/IAB)
Date: Thursday, 02/10/14 from 09.30-18.00 h
Max. number of participants: 20
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
This course will cover various methods of sample selection, and their advantages and disadvantages. We will also discuss why it is important to analyze survey data using methods that account for its complex design, and how to do in Stata. Students should have had at least previous course in statistics – no prior knowledge of sampling theory is assumed, but students should be comfortable with statistical concepts such as hypothesis testing, variance, standard errors, confidence intervals, etc. In addition, basic knowledge of Stata is required.
You have to register for the 8th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Programme of study: International Research Workshop
Lecturer: Assoc. Prof. Dr. Nisar Ahmad, Assoc. Prof. Time Friedel Mietze & Prof. Dr. Torben Dall Schmidt (University of Southern Denmark/Department of Border Region Studies)
Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 14.30-18.00 h
Max. number of participants: 20
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
NB: Please bring your laptop computers with STATA installed on it.
The course is basically divided into two parts: Part 1) Analyzing panel data. Part 2) Spatial Data Analysis
Part 1): Structure of the Panel Data: This part of the course is an introduction to the panel data analysis and it provides some insights into why we use panel data. What kinds of models are available for panel data and how do we estimate such models. It also covers some extensions to the basic panel data models and finally there will be a session where you will learn how to estimate panel data using STATA.
Part 2): Spatial Data Analysis: In research fields such as regional science, quantitative sociology and business analysis as well as real estate, labor and health economics (to name just a few), researchers are increasingly aware of the fact that “space matters”. Thus, the goal of this workshop module is to equip participants with the basic knowledge about methods and tools currently available in “spatial statistics” and “spatial econometrics”. Besides presenting the general logic and theoretical foundations of these modeling approaches for variables with an explicit geographical context, a strong focus lies on illustrating the potential for applied work with these tools in the software package STATA. The module is structured as follows: After a brief introduction of the historical evolution of spatial data analysis, different research settings in economics and related research fields are outlined, which may call for the explicit use of spatial estimation techniques, for instance, in order to identify the importance of space-time autocorrelations and neighboring effects (spatial spillovers). Following this introduction, the concept of the spatial weighting matrix is introduced and statistical approaches to measure and visualize the degree of spatial dependence for a variable under study are presented. Moving from univariate to multivariate modeling techniques, the course then derives estimation techniques used in the field of spatial econometrics and links this theoretical knowledge with hands-on applications for different spatial datasets. Finally, to serve as an outlook on future research possibilities, state-of-the-art concepts such as spatial panel data models and spatial limited dependent variable models will be presented. Datasets and STATA ado-files will be provided ahead of the course and should be installed on the participants’ computers.
You have to register for the 8th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Programme of study: International Research Workshop
Lecturer:
SOEP: PD Dr. Elke Holst (German Institute for Economic Research/DIW Berlin)
ALLBUS: Dipl.-Soz. Michael Blohm (GESIS Leibniz Institute for the Social Sciences)
IAB Data: Dipl.-Vw. Stefan Seth (Institute for Employment Research/IAB)
Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 09.00-12.30 h
Max. number of participants: 20
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
The Socio-Economic Panel Study (SOEP) is a longitudinal study of private households in Germany. The panel provides information on all household members and was started in 1984. In 2011, there were more than 12,300 households with more than 21,000 persons sampled. Some of the many topics include household composition, occupational biographies, employment, earnings, health, wellbeing, integration, values, lifestyles, and personality. The course gives an overview of the data structure and the research designs facilitated by longitudinal household studies that go beyond conventional surveys (household analysis, intergenerational analysis, life course research, etc.). The course provides an applied introduction into the data retrieval via SOEPinfo.
Required: statistical knowledge, basic Stata or SPSS skills.
Recommended literature and pre-readings:
ALLBUS (Allgemeine Bevölkerungsumfrage der Sozialwissenschaften – German General Social Survey (GGSS)) is one of the foremost survey programs in Germany. It has been institutionalized as a part of GESIS – Leibniz Institute for the Social Sciences. The prototype for similar national data generation programs is the American General Social Survey (GSS).
Since 1980, ALLBUS/GGSS has provided a series of representative cross-sectional samples drawn from the adult population in Germany. These biennial surveys include partly replicative and partly innovative question modules and added value data for analyses of social structure, attitudes, values, and behavior in Germany. Moreover, users may find various possibilities for international comparisons. Currently, 19 ALLBUS/GGSS surveys (1980-2012) with a total of 57,723 respondents are available. A large part of the documentation has been translated into English.
In its first part the course gives an overview of the project as such. Basic sampling procedures, various question modules, and recent activities of the ALLBUS Research Data Center will be presented. The second part consists of hands-on exercises of chosen data. The analyses will be done primarily using Stata. Participants should have fundamental knowledge in data handling, in statistical data analysis and in using programs like Stata/SPSS via syntax. In addition, a report on the experience in ALLBUS/GGSS with Survey Nonresponse will be given.
Recommended literature and pre-readings:
The Institute for Employment Research in Nuremberg has available a wealth of micro data on the German labor market and offers access to it in its Research Data Center (FDZ). The course’s goal is to arouse the participants’ interest in FDZ data and to guide their first steps into analyzing them. The focus will be on two large administrative data sets, namely the Sample of Integrated Employment Biographies (SIAB) and the Establishment History Panel (BHP). In hands-on sessions we will explore, cleanse and prepare the data, calculate durations, and implement simple imputation procedures. The course will also cover in some detail the IAB Establishment Panel, the FDZ’s most important survey data set, and the Linked Employer-Employee Dataset of the IAB (LIAB); other FDZ data will also be presented, but rather cursorily.
FDZ website
Overview of FDZ data
Basic to medium Stata skills required for the tutorial.
You have to register for the 8th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Programme of study: International Research Workshop
Lecturer: Dipl.-Verw. Wiss. Tobias Gramlich (University of Duisburg-Essen)
Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 09.00-12.30 h
Max. number of participants: 20
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
Stata is a statistical program package widely used (not only) in the social and economical sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and to document these tasks to keep them reproducible.
For Beginners with no or very little Stata knowledge!
Course topics cover:
You have to register for the 8th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Program of study: International Research Workshop
Lecturer: Nisar Ahmad, Timo Friedel Mitze & Torben Dall Schmidt (University of Southern Denmark)
Date:
03.10.2013, 09:30 – 17:30
Room: n.s.
Max. number of participants: 20
Semester periods per week: n.s.
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
The course is basically divided into two parts: Part 1) Analyzing panel data. Part 2) Spatial Data Analysis
Part 1): Structure of the Panel Data:
This part of the course is an introduction to the panel data analysis and it provides some insights into why we use panel data. What kinds of models are available for panel data and how do we estimate such models. It also covers some extensions to the basic panel data models and finally there will be a session where you will learn how to estimate panel data using STATA.
Part 2): Spatial Data Analysis
In research fields such as regional science, quantitative sociology and business analysis as well as real estate, labor and health economics (to name just a few), researchers are increasingly aware of the fact that “space matters”. Thus, the goal of this workshop module is to equip participants with the basic knowledge about methods and tools currently available in “spatial statistics” and “spatial econometrics”. Besides presenting the general logic and theoretical foundations of these modeling approaches for variables with an explicit geographical context, a strong focus lies on illustrating the potential for applied work with these tools in the software package STATA. The module is structured as follows: After a brief introduction of the historical evolution of spatial data analysis, different research settings in economics and related research fields are outlined, which may call for the explicit use of spatial estimation techniques, for instance, in order to identify the importance of space-time autocorrelations and neighboring effects (spatial spillovers). Following this introduction, the concept of the spatial weighting matrix is introduced and statistical approaches to measure and visualize the degree of spatial dependence for a variable under study are presented. Moving from univariate to multivariate modeling techniques, the course then derives estimation techniques used in the field of spatial econometrics and links this theoretical knowledge with hands-on applications for different spatial datasets. Finally, to serve as an outlook on future research possibilities, state-of-the-art concepts such as spatial panel data models and spatial limited dependent variable models will be presented.
Datasets and STATA ado-files will be provided ahead of the course and should be installed on the participants’ computers.
You have to register for the 7th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Program of study: International Research Workshop
Lecturer: Elke Holst & Lea Kröger (SOEP at DIW)
Date:
01.10.2013, 09:00 – 12:30
02.10.2013, 09:00 – 12:30
Room: n.s.
Max. number of participants: 25
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
The Socio-Economic Panel Study (SOEP) is a longitudinal study of private households in Germany. The panel provides information on all household members and was started in 1984. In 2011, there were more than 12,000 households with more than 21,000 persons sampled. Some of the many topics include household composition, occupational biographies, employment, earnings, health, well being, integration, values, lifestyles, and personality. The course gives an overview of the data structure and the research designs facilitated by longitudinal household studies that go beyond conventional surveys (household analysis, intergenerational analysis, life course research, etc.). In hands-on sessions using Stata, the course provides an applied introduction into the data retrieval, the construction of longitudinal data files, and illustrates some exemplary analyses.
SOEP@DIW Berlin website:
http://www.diw.de/soep (deutsch) or http://www.diw.de/en/soep (english)
Reading the SOEP Desktop Campanion is a prerequisite for participation.
You have to register for the 7th International Research Workshop to participate in this course.
Institution: see Organisers & Acknowledgements
Program of study: International Research Workshop
Lecturer: Elke Holst (SOEP at DIW) and Andrea Schäfer (University of Bremen)
Date:
01.10.2012, 14:00 – 17:30
02.10.2012, 14:00 – 17:30
Room: n.s.
Max. number of participants: 25
Credit Points: 5 CP for participating in the whole IRWS
Language of instruction: English
Contents:
The Socio-Economic Panel Study (SOEP) is a longitudinal study of private households in Germany. The panel provides information on all household members and was started in 1984. In 2010, there were almost 11,000 households, and more than 19,000 persons sampled. Some of the many topics include household composition, occupational biographies, employment, earnings, health, well being, integration, values, lifestyles, and personality. The course gives an overview of the data structure and the research designs facilitated by longitudinal household studies that go beyond conventional surveys (household analysis, intergenerational analysis, life course research, etc.). In hands-on sessions using Stata, the course provides an applied introduction into the data retrieval, the construction of longitudinal data files, and illustrates some exemplary analyses.
SOEP@DIW Berlin website:
http://www.diw.de/soep (deutsch) or http://www.diw.de/en/soep (english)
Reading the SOEP Desktop Campanion is a prerequisite for participation.
You have to register for the 6th International Research Workshop to participate in this course.
LIS is seeking applications for two additional staff persons:
The positions involve harmonising and documenting microdata in the areas of income, labor, demographics, and wealth, as well as contributing to the conceptual framework of harmonising cross-national microdata. All staff also participate in LIS training and pedagogical activities.
Applicants should submit a cover letter, curriculum vitae, and the names of three references (with contact information). Send applications via email, attention Caroline de Tombeur, at admin@lisdatacenter.org.
Required background:
Applicants should have an advanced university degree (Master’s degree or equivalent) in the social sciences, economics, statistics or a related field. A first-level university degree in combination with qualifying work experience may be accepted in place of an advanced degree.
Applicants should also have the following:
Priority will be given to applicants with work experience related to:
Review of applications will start immediately. Applications will be considered until the positions are filled.
Institution: Helmut-Schmidt-Universität, Fakultät Wirtschafts- und Sozialwissenschaften
Studiengang: Doktorandenweiterbildung
Dozent: Daniel Horgos (HSU Hamburg)
Termin(e): 11., 12. und 13.10.2011, 09:00 Uhr – 17:00 Uhr
Raum: H.1/2161 (EDV-Raum Fakultät WiSo)
Max. Teilnehmerzahl: 25
Semester-Wochen-Stunden: k.A.
Credit Points: k.A.
Unterrichtssprache: Deutsch
Beschreibung:
Der Kurs richtet sich an Volkswirte und Betriebswirte, die ihre Kenntnisse in empirischer Wirtschaftsforschung vertiefen möchten. Die Teilnehmer werden die Grundlagen des Statistikprogramms Stata kennenlernen, mit dem Ziel, selbstständig eigene empirische Analysen durchführen zu können. Anhand verschiedener Daten wird im Rahmen des Kurses gezeigt, wie die ökonometrischen Methoden der linearen Regression, der Zeitreihenanalyse und der Panel-Daten Analyse mit Stata durchgeführt werden können. Ausserdem wird auf das das Erstellen von deskriptiven Statistiken und Grafen eingegangen. An verschiedenen Stellen werden auch ökonometrische Grundlagen (wie zum Beispiel die lineare Regressionsanalyse) wiederholt.
Bitte melden Sie sich für den Workshop bis zum 26.09.2011 über die Lernplattform Ilias an:
http://iliascluster.unibw-hamburg.de/ilias4/goto_unibw_crs_61340.html