The impact of cleansing procedures for overlaps on estimation results : evidence for German administrative data

"Process-generated and administrative datasets have become increasingly important for labor market research over the past ten years. Major advantages of these data are large sample sizes as well as absence of retrospective gaps and unit non-responses. Nevertheless, the quality and validity of the information remains unclear and a lot of preparation and data cleansing is necessary before the data are analyzable. Unfortunately, only few researchers provide access to their cleansing procedures and therefore, also the impact of them on the results of the analyses is unidentified. This paper contributes to this subject and focuses on the variation of research results due to alternative data cleansing procedures. In particular, the paper uses the framework for data preparation suggested in an evaluation study by Wunsch and Lechner (2008) as a benchmark and then induces variation by developing different cleansing procedures for overlapping and parallel observations. The descriptive results show that the differences between the data sets (based on the different procedures) show various magnitudes on some attributes concerning time and personal characteristics. Similar results appear for the subsequent analysis of the treatment effects, which do not vary in the overall shape but in the magnitude especially during the lock-in effect. In sum the results of the analysis indicate that the empirical findings of the evaluation method are fairly robust to variations in the underlying cleansing procedure." (Author's abstract, IAB-Doku) ((en))Datenqualität, prozessproduzierte Daten, Datenaufbereitung, Integrierte Erwerbsbiografien

Testing the importance of cleansing procedures for overlaps inadministrative data : first evidence for Germany

"Process-generated and administrative datasets have become increasingly important for labour market research over the past ten years. Major advantages of this data are large sample sizes, absence of retrospective gaps and unit non-responses. Nevertheless, the quality and validity of the information remain unclear. This paper contributes to this subject, focusing on the variation of research results due to alternative data cleansing procedures. In particular, the paper uses the general set up for data cleaning proposed by Wunsch/Lechner (2008) in evaluating the outcome of training programmes in Germany. First results are limited to the sensitivity of the construction of the sample populations used for the counterfactual analysis. The results emphasize that sample construction seems to be robust to the scenario used for the data cleansing." (Author's abstract, IAB-Doku) ((en))Arbeitsmarktforschung, Wirkungsforschung, Forschungsmethode, prozessproduzierte Daten, Datenqualität, Validität, Datenaufbereitung, Stichprobenverfahren, Non Response

The outcome of coaching and training for self-employment : a statistical evaluation of non-financial support schemes for unemployed business founders in Germany

"This paper focuses on the question of whether improving the competence of new business founders by means of coaching and training programs enhances the duration of self-employment. In our analysis we focus on support activities that are provided in addition to a financial subsidy and which mainly focus on providing external expertise for founders who started a business from a position of unemployment. We find that the inflow into the related schemes is strongly determined by regional patterns and time while individual characteristics are less important. This reflects a particular regional specialization in the set-up of the promotion of selfemployment. A statistical matching approach is used to control for selectivity and is performed in a way that explicitly takes into account differences across regions and over time. The results show that treatment effects tend to be insignificant in statistical and economic terms. We also find evidence that external expertise reduces the duration of self-employment." (Author's abstract, IAB-Doku) ((en))Arbeitslose, Unternehmensgründung, Unternehmer, Coaching, arbeitsmarktpolitische Maßnahme - Erfolgskontrolle, Qualifizierungsmaßnahme, Unternehmenserfolg, Förderungsmaßnahme - Inanspruchnahme, regionale Faktoren, berufliche Selbständigkeit, Überbrückungsgeld, Integrierte Erwerbsbiografien, IAB-Betriebs-Historik-Panel

Cleansing procedures for overlaps and inconsistencies in administrative data: the case of German labour market data

'In den letzten zehn Jahren wurden prozessgenerierte und administrative Daten stetig wichtiger für die Arbeitsmarktforschung. Die größten Vorteile dieser Daten sind große Stichprobenumfänge, das Fehlen von Beobachtungslücken und Totalausfällen. Dennoch bleibt die Qualität und Validität der Informationen unklar. Diese Arbeit greift diesen Punkt auf und richtet den Schwerpunkt auf den Einfluss von alternativen Bereinigungsprozeduren auf Forschungsergebnisse. Insbesondere nutzt die vorliegende Arbeit die von Wunsch/ Lechner (2008) vorgeschlagenen Prozeduren der Datenaufbereitung bei der Evaluation von Programmen der aktiven Arbeitsmarktforschung in Deutschland. Die ersten Ergebnisse sind auf Sensitivitätsanalysen bei der Erstellung von Beobachtungsgruppen beschränkt. Die Ergebnisse zeigen, dass die Zusammensetzung der Gruppen robust gegenüber einer Änderung der Datenaufbereitung ist.' (Autorenreferat)'Process-generated and administrative datasets have become increasingly important for labor market research over the past ten years. Major advantages of this data are large sample sizes, absence of retrospective gaps and unit nonresponses. Nevertheless, the quality and validity of the information remain unclear. This paper contributes to this subject, focusing on the variation of research results due to alternative data cleansing procedures. In particular, the paper uses the general set up for data cleaning proposed by Wunsch/ Lechner (2008) in evaluating the outcome of training programs in Germany. First results are limited to the sensitivity of the construction of the sample populations used for the counterfactuals analysis. The results emphasize that sample construction seems to be robust to the scenario used for the data cleansing.' (author's abstract

Integrated employment biographies sample IEBS : handbook for the IEBS in the 2008 version

"The IEBS is a random sample drawn from the Integrated Employment Biographies (IEB) of the IAB. The IEB are not to be understood as a self-contained dataset but as a procedure for merging data from four different sources for the purpose of data quality control and for drawing samples such as the IEBS. The four data sources are - the IAB Employee History (BeH) with observations of employment subject to social security taken from the social security notification procedure, - the Benefit Recipient History (LeH) with observations of receipt of unemployment benefit, unemployment assistance and maintenance allowance, - the Participants-in-Measures History File (MTH) with observations of participation in employment and training measures and - the Applicant Pool Data (BewA) with job-search observations. The most important changes compared with the 2005 version of the IEBS are: Updating of the loading status and inclusion of new variables; the variable 'grund' is recoded in the variable spectrum; the missing values are recoded uniformly to the value -7; reforms of district territories in Saxony-Anhalt and Thuringia result in new district numbers from 2007." (Author's abstract, IAB-Doku) ((en)) Additional Information Here you can find the German version.Forschungsdatenzentrum, Integrierte Erwerbsbiografien, Daten - Modell

Do Firms Benefit from Active Labour Market Policies?

This paper investigates the link between variation in the supply of workers who participate in spe­cific types of active labour market policies (ALMPs) and firm performance using a new exception­ally informative German employer-employee data base. For identification we ex­ploit that German local employment agencies (LEAs) have a high degree of autonomy in determining their own mix of ALMPs and that firms' hiring regions overlap only imperfectly with the areas of responsibility of the LEAs. Our results indicate that in general firms do not benefit from ALMPs and in some cases may even be harmed by certain programs, in particular by sub­sidized employment and longer training programs. These findings complement the negative assessment of the cost-effectiveness of ALMPs from the empirical literature on the effects for participants

Datengenese zweier Datenkonzepte : MTG (Maßnahme-Teilnahme-Grunddatei) und ISAAK (Instrumente Aktiver Arbeitsmarktpolitik). Eine Betrachtung ausgewählter Fälle am Beispiel der Förderung im Rahmen des ESF-BA-Programms

"Der Beitrag dokumentiert die Datengenese der für wissenschaftliche Zwecke aufbereiteten Teilnahmemeldungen der Bundesagentur für Arbeit am Beispiel von Förderleistungen im Rahmen des ESF-Programms. 2004 und 2005 wurden systematische Änderungen in den datenliefernden Fachverfahren der Bundesagentur für Arbeit eingeführt. Diese Umstellung hatte eine neue Datenstruktur für die Erfassung von Maßnahmeteilnahmen durch das IAB zur Folge. Dies bedeutet, dass die Maßnahmeteilnahmen seit 2005 nicht mehr über die (alte) MTG-Struktur (MTG: Maßnahme-Teilnahme-Grunddatei) aufbereitet werden, sondern über eine neue Datenbasis namens ISAAK (Instrumente Aktiver Arbeitsmarktpolitik). Ein Vergleich zeigt, dass die Datenmengen bei ISAAK umfangreicher sind. Dies liegt zum einen an dem Ziehungsverfahren bei ISAAK, dass auch ältere Datenstände durch eine vollständige Neuladung aktualisiert. Zum anderen dürfte es damit zu tun haben, dass bisherige Regeln keine Verwendung mehr finden. In der MTG wurden Sätze nur dann als gültig angenommen, wenn auch ein Zugangssatz existiert - unabhängig davon ob Bestandssätze und Abgangssätze existieren. Die Ergebnisse lassen keinen materiellen Bruch in den Datenreihen zwischen ISAAK und MTG erwarten." (Autorenreferat, IAB-Doku)europäischer Sozialfonds, Bundesagentur für Arbeit, Beschäftigungspolitik, wissenschaftliche Begleitung, Wirkungsforschung, arbeitsmarktpolitische Maßnahme, IAB-Maßnahmeteilnehmergrunddatei, Teilnehmer - Statistik, Datengewinnung - Methode, integrierte Erwerbsbiografien

Stichprobe der Integrierten Erwerbsbiografien IEBS : Handbuch für die IEBS in der Fassung 2008

"Bei der IEBS handelt es sich um eine Zufallsstichprobe aus den Integrierten Erwerbsbiografien (IEB) des IAB. Die IEB sind nicht als geschlossener Datensatz zu verstehen, sondern als Verfahren der Zusammenspielung von Daten aus vier unterschiedlichen Quellen zur Prüfung der Datenqualität, sowie zur Ziehung von Stichproben wie der IEBS. Bei den vier Datenquellen handelt es sich um - die Beschäftigten-Historik (BeH) mit Spells zu sozialversicherungspflichtiger Beschäftigung aus dem Meldeverfahren, - die Leistungsempfänger-Historik (LeH) mit Spells zum Empfang von Arbeitslosengeld, Arbeitslosenhilfe und Unterhaltsgeld, - die Maßnahme-Teilnehmer-Historiken (MTH) mit Spells zu Maßnahmeteilnahmen und - Arbeitsuchenden und Bewerberangebotsdaten (BewA) mit Spells zur Arbeitsuche. Die Datenlage hat sich seit dem Ladestand der IEBS 2005 erheblich geändert. Grundsätzlich sind alle Meldungen aktuell nachgeladen worden. Zudem sind neue Ausprägungen beim Erwerbsstatus (insbesondere durch neue Maßnahmeteilnahmen) und im Status nach Abgang, sowie im Abgangsgrund entstanden. In einigen Fällen konnten die bisherigen Ausprägungen nicht vollständig beibehalten werden. Der vorliegende Datensatz beinhaltet keine SGB II-Meldungen. Die IEBS 2008 basiert auf der IEBVersion 7.02." (Autorenreferat, IAB-Doku) Additional Information Anlage 1 zum FDZ-Datenreport Nr. 3/2009: Fallzahlen Anlage 2 zum FDZ-Datenreport Nr. 3/2009: Codebook und LabelsForschungsdatenzentrum, Integrierte Erwerbsbiografien, Daten - Modell

The Impact of Cleansing Procedures and Coding Decisions for Overlaps on Estimation Results – Evidence from German Administrative Data

Process-generated and administrative datasets have become increasingly important for labor market research over the past ten years. Their major advantages are large sample sizes and the absence of retrospective gaps and unit non-response. Nevertheless, the quality and validity of these types of data remains unclear, and a great deal of preparation and data cleansing is necessary before the data can be analyzed. Unfortunately, few researchers explicitly describe the cleansing procedures or coding decisions used for this purpose, thus leaving their impact on the results unclear. The present paper focuses on the variation in research results resulting from different cleansing and coding procedures. The paper uses the framework of data preparation proposed by Wunsch / Lechner (2008) as a benchmark, and induces variation by developing different cleansing procedures and coding decisions for overlapping and parallel observations. The descriptive results show that the data sets (resulting from the different procedures) show varying ranges of difference for some attributes related to time and personal characteristics. Similar results emerge from the subsequent analysis of treatment effects, which do not vary in overall shape but in magnitude, especially during the lock-in effect. In sum, the results indicate that the empirical findings of evaluation studies based on matching algorithms are fairly robust to variations in the underlying method of data preparation.Received: September 30, 2010Accepted: January 21, 201

The Impact of Cleansing Procedures and Coding Decisions for Overlaps on Estimation Results – Evidence from German Administrative Data

Process-generated and administrative datasets have become increasingly important for labor market research over the past ten years. Their major advantages are large sample sizes and the absence of retrospective gaps and unit non-response. Nevertheless, the quality and validity of these types of data remains unclear, and a great deal of preparation and data cleansing is necessary before the data can be analyzed. Unfortunately, few researchers explicitly describe the cleansing procedures or coding decisions used for this purpose, thus leaving their impact on the results unclear. The present paper focuses on the variation in research results resulting from different cleansing and coding procedures. The paper uses the framework of data preparation proposed by Wunsch/Lechner (2008) as a benchmark, and induces variation by developing different cleansing procedures and coding decisions for overlapping and parallel observations. The descriptive results show that the data sets (resulting from the different procedures) show varying ranges of difference for some attributes related to time and personal characteristics. Similar results emerge from the subsequent analysis of treatment effects, which do not vary in overall shape but in magnitude, especially during the lock-in effect. In sum, the results indicate that the empirical findings of evaluation studies based on matching algorithms are fairly robust to variations in the underlying method of data preparation.