Effectiveness of data correction rules in process-produced data : the case of educational attainment

"The use of process-produced data plays a large and growing role in empirical labor market research. To address data problems, previous research have developed deductive correction rules that make use of within-person information. We test data reliability and the effectiveness of different correction rules for information about educational degrees as reported in German register data. Therefore we use the unique dataset ALWA-ADIAB, which combines interview data and process-produced data from exactly the same individuals. This approach enables us to assess how effective the existing correction rules are and whether they manage to eliminate structural biases. In sum, we can state that simple editing rules based on logic assumptions are suitable for improving the quality of process-produced data, but they are not able to correct for structural biases." (Author's abstract, IAB-Doku) ((en))

[1]  Nils Drews,et al.  Qualitätsverbesserung der Bildungsvariable in der IAB-Beschäftigtenstichprobe 1975-2001 (Improving the quality of the education variable in the IAB Employment Sample 1975-2001) , 2006 .

[2]  U. Fachinger,et al.  Empirische Forschungsvorhaben zur Alterssicherung: Einige kritische Anmerkungen zur aktuellen Datenlage , 2011 .

[3]  Nina Baur,et al.  Mixing process-generated data in market sociology , 2011 .

[4]  B. Matthes,et al.  Working and learning in a changing world: Part I: Overview of the study - March 2011 (Second, updated version) , 2011 .

[5]  Thomas Kruppe Die Förderung beruflicher Weiterbildung: Eine mikroökonometrische Evaluation der Ergänzung durch das ESF-BA-Programm , 2006 .

[6]  M. Antoni,et al.  ALWA New Life Course Data for Germany , 2011 .

[7]  D. Hochfellner,et al.  Biographical Data of Social Insurance Agencies in Germany Improving the Content of Administrative Data , 2012 .

[8]  John Rust,et al.  How Large is the Bias is Self-Reported Disability? , 2000 .

[9]  K. Røed,et al.  Administrative registers - Unexplored reservoirs of Scientific Knowledge? , 2003 .

[10]  Effects of changes in data collection mode on data quality in administrative data : the case of participation in programmes offered by the German employment agency , 2009 .

[11]  P. Johansson,et al.  Misreporting in register data on disability status: evidence from the Swedish Public Employment Service , 2009 .

[12]  M. Antoni,et al.  ALWA-ADIAB - Linked individual Survey and Administrative Data for Substantive and Methodological Research , 2012 .

[13]  Stefan Seth,et al.  The Sample of Integrated Labour Market Biographies , 2010 .

[14]  Donald B. Rubin,et al.  Multiple Imputation of Industry and Occupation Codes in Census Public-use Samples Using Bayesian Logistic Regression , 1991 .

[15]  John Rust,et al.  How Large is the BIas in Self-Reported Disability Status? , 1999 .

[16]  Frauke Kreuter,et al.  Nonresponse and Measurement Error in Employment Research: Making Use of Administrative Data , 2010 .

[17]  C. Bollinger,et al.  I didn't tell, and I won't tell: dynamic response error in the SIPP , 2005 .

[18]  Britta Matthes,et al.  Improving retrospective life course data by combining modularized self-reports and event history calendars: experiences from a large scale survey , 2013 .

[19]  J. Wagner Daten des IAB-Betriebspanels und Firmenpaneldaten aus Erhebungen der Amtlichen Statistik – substitutive oder komplementäre Inputs für die Empirische Wirtschaftsforschung? , 2014 .

[20]  P. Davies,et al.  Measurement Issues Associated with Using Survey Data Matched with Administrative Data from the Social Security Administration , 2009, Social security bulletin.

[21]  Mario Bossler Sorting within and across establishments: the immigrant-native wage differential in Germany , 2014 .

[22]  The Impact of Cleansing Procedures for Overlaps on Estimation Results - Evidence for German Administrative Data , 2010 .

[23]  Tanja Hethey-Maier,et al.  Das Betriebs-Historik-Panel (BHP) 1975-2008: Handbuch Version 1.0.2 (Establishment-History-Panel (BHP) 1975-2008) , 2010 .

[24]  Kevin B. Moore,et al.  Differences in Income Estimates Derived from Survey and Tax Data , 2008 .

[25]  Measurement Error and Misclassification , 2007 .

[26]  Bernd Fitzenberger,et al.  Imputation Rules to Improve the Education Variable in the Iab Employment Subsample , 2005, Journal of Contextual Economics – Schmollers Jahrbuch.

[27]  Minh Huynh,et al.  Are Earnings Inequality and Mobility Overstated? The Impact of Nonclassical Measurement Error , 2006, The Review of Economics and Statistics.

[28]  Thomas Buttner,et al.  Multiple Imputation of Right-Censored Wages in the German IAB Employment Sample Considering Heteroscedasticity , 2008 .

[29]  Laura Wichert,et al.  Which Factors Safeguard Employment? An Analysis with Misclassified German Register Data , 2010 .

[30]  Dirk Oberschachtsiek,et al.  Cleansing procedures for overlaps and inconsistencies in administrative data : the case of German labour market data , 2009 .