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Paulina Karolina Pankowska

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I am a PhD candidate at the Vrije Universiteit Amsterdam and I work in the field of research methodology and official statistics. I conduct my research in collaboration with Netherlands Statistics. 

I have previously held various research positions in, among others, RAND Corporation and Maastricht University.

I am highly experienced in quantitative research methods and software and have a good understanding of qualitative methods. 

My interests lie in statistics, data analysis and econometrics, labour market studies, migration, higher education and social protection. 

I have been involved in research projects on, among others, the economic impacts of minimum wage, the economic impacts of migration in Europe for both the sending and receiving countries, comparative assessments of higher education policies in Europe and the impact of various social protection schemes on poverty reduction in Indonesia.



Error correction in the measurement of flexible labour

My research focuses on the application of latent class analysis to estimate error in the measurement of flexible labour contracts and the transition to permanent labour contracts. Flexible and permanent labour contracts are measured in the Labour Force Survey (LFS) and the Employment Register (ER). Both sources have repeated measurements of these variables, which makes estimation of the measurement error possible. 

The research answers the following questions:
1. Can LCA be applied to combine different sources and correct for measurement error?
2. What is the true number of flexible labour contracts, what is the true number of transitions from flexible to permanent labour contracts and vice versa?




I am a teaching assistant for a couple of Master's level courses focusing on quantitative research methods and statistics and which make use of the SPSS statistical package.


Education/Academic qualification

Quantitative research methods, University of Michigan, Ann Arbor

Public Policy, Master, UNU-MERIT

Public Policy, Master, Universiteit Maastricht

Economics and Business, Bachelor, Universiteit van Amsterdam

Social Sciences, The University of Melbourne


  • H Social Sciences (General)
  • Labour market research
  • Research methods
  • Survey methodology
  • Official statistics
  • Measurement error
  • Total Survey Error
  • Latent variable modelling
  • Hidden Markov Models
  • Big data
  • Machine Learning

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  • 2 Similar Profiles
Measurement errors Engineering & Materials Science
Measurement Error Mathematics
Hidden Markov models Engineering & Materials Science
Reconciliation Mathematics
Markov Model Mathematics
Inconsistent Mathematics
Linkage Mathematics
Statistics Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2014 2019

How linkage error affects hidden Markov models: a sensitivity analysis

Pankowska, P. K. P., Bakker, B. F. M., Oberski, D. L. & Pavlopoulos, D., 31 May 2019, In : Journal of Survey Statistics and Methodology.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Hidden Markov models
Markov Model
Sensitivity analysis
Sensitivity Analysis

Reconciliation of inconsistent data sources by correction for measurement error: The feasibility of parameter re-use

Pankowska, P. K. P., Bakker, B. F. M., Oberski, D. L. & Pavlopoulos, D., 9 Aug 2018, In : Statistical Journal of the IAOS. 34, 3, p. 317-329 13 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Measurement errors
Measurement Error

The effect of survey measurement error on clustering algorithms

Pankowska, P. K. P., Oberski, D. L. & Pavlopoulos, D., 2018.

Research output: Contribution to ConferencePaperAcademic

Measurement errors
Clustering algorithms
Pulse amplitude modulation
Data mining
Social sciences

Adapting to the new normal- Educating Syrian refugee children in Jordan

Culbertson, S., Ling, T., Henham, M. L., Corbett, J., Karam, R., Pankowska, P. K. P., Saunders, C. L., Bellasio, J. & Baruch, B., 2016, RAND Corporation.

Research output: Book / ReportReportPopular