Scientific Programme

Last modified by Una Balode on 2026/04/29 09:40

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Draft programme

Please note that this is a draft program and is subject to change.

Monday, August 24, 2026 (Day 1)

Day Theme: Survey Design in Modern Official Statistics

Adaptation of survey designs to new data sources and changing data environments.

TimeActivitySpeaker
12.00-13.00Registration
13.00-13.15Welcome and opening remarks

Jeļena Voronova (Central Statistical Bureau of Latvia, representative of Latvia in BNU Network)

Jānis Valeinis (head of the Laboratory of Statistical Research and Data Analysis, University of Latvia)

Raimonds Lapiņš (Central Statistical Bureau of Latvia)

13.15-14.00

Session 1

Invited lectures

Chair: Jeļena Voronova

Representative of Eurostat (EUROSTAT)

Topic to be confirmed

14.00-14.45

Jānis Lapiņš (one of the founders of BNU Network)

Historical Aspects of the Establishment of the BNU Network  

14.45-15.20Break
15.20-15.40

Session 2

Contributed presentations with discussions

Chair: TBA

Open presentation slot

15.40-16.00Open presentation slot
16.00-16.20Open presentation slot
16.20-16.40

Speaker (Central Statistical Bureau of Latvia)

Survey Design and Implementation Challenges in a Light Commercial Vehicles Survey

16.40-17.00Walk to the opening reception venue
17.00-19.00Welcome event

Tuesday, August 25, 2026 (Day 2)

Day Theme: Machine Learning in Data Preparation and Analysis

Use of machine learning methods to improve data cleaning, integration, and statistical analysis.

TimeActivitySpeaker
8.00-9.00Registration
9.00-9.45

Session 3

Invited lectures

Chair:

Marco Puts (Statistics Netherlands)

Methodological foundations of using Machine Learning in official statistics

9.45-10.30Open presentation slot
10.30-11.00Break
11.00-11.20

Session 4

Contributed presentations with discussions

Chair: Maria Valaste

Open presentation slot
11.20-11.40Open presentation slot
11.40-12.00Open presentation slot
12.00-12.20Open presentation slot
12.20-12.40Open presentation slot
12.40-14.00Lunch break
14.00-14.45

Session 5

Invited lectures

Chair: Jānis Valeinis

Anastasija Tetereva (Erasmus University Rotterdam)

Tree-Based Methods for Survey Data and Beyond: Modeling Structured Heterogeneity with Interpretable ML

14.45-15.30

Henri Luomaranta-Helmivuo (Statistics Finland)

Topic to be confirmed

15.30-16.00

Group photo; guided tour of the House of Science

16.00-16.20Break
16.20-16.40

Session 6

Contributed presentations with discussions

Chair:

Open presentation slot
16.40-17.00Open presentation slot
17.00-17.20Open presentation slot
17.20-17.40Open presentation slot
17.40-18.00

Speaker (Unversity of Latvia)

Development of an automated method for household nucleus identification using machine learning algorithms

18.00-18.10Conclusions of the day
18.10-19.00Steering committee meeting

Wednesday, August 26, 2026 (Day 3)

Day Theme: Probability and Non-Probability Sampling

Methods for integrating different data sources to produce reliable and efficient statistical estimates from both probability and non-probability data.

TimeActivitySpeaker
9.00-9.45

Session 7

Invited lectures

Chair: Biruta Sloka

Danutė Krapavickaitė (Vilnius Gediminas Technical University)

 Non-Probability Samples – an Overview of the Problem

9.45-10.30

Kaja Sõstra (Statistics Estonia/Eurostat)

Developing transparent and harmonised publication thresholds for EU-LFS data dissemination

10.30-11.00Break
11.00-11.20

Session 8

Contributed presentations with discussions

Chair: Vilma Nekraisite-Liege

Speaker (Central Statistical Bureau of Latvia)

Nonresponse Bias Adjustment in Household Budget Survey Using Response Propensity Weighting

11.20-11.40

Speaker (Central Statistical Bureau of Latvia)

Income Imputation Challenges in Labour Force Survey: Methods and Practical Issues

11.40-12.00

Speaker (Central Statistical Bureau of Latvia)

Automating Imputation Processes in Construction Statistics: Methodological and Operational Challenges

12.00-12.20

Biruta Sloka (University of Latvia (UL))

Use of Official Statistics Survey’s (EU-SILC, Labour Force Survey, ICT-Individuals Survey, etc) Micro Data in Studies and Research

12.20-12.40Open presentation slot
12.40-14.00Lunch break
14.00-15.00Trip to the main building of University of Latvia
15.00-16.00

Meeting with University of Latvia management on statistical analysis support

Round table discussions

16.00-16.15Break
16.15-17.00Guided tour of the main building of the University of Latvia
17.30-20.00Guided tour in Riga

Thursday, August 27, 2026 (Day 4)

Day Theme: Small Area Estimation and Nonparametric Approaches

Development of detailed statistics using small-area models and classical, robust, and nonparametric statistical methods.

TimeActivitySpeaker
9.00-9.45

Session 9

Invited lectures

Chair: Danutė Krapavickaitė

Tomasz Żądło (University of Economics in Katowice)

Fundamentals and Recent Developments in Small Area Estimation

9.45-10.30Open presentation slot
10.30-11.00Break
11.00-11.20

Session 10

Contributed presentations with discussions

Chair: Thomas Laitila

 

Speaker (Central Statistical Bureau of Latvia)

Small Area Estimation Approaches for Measuring Undeclared Employment

11.20-11.40

Anželika Ņesterova (Faculty of Science and Technology, UL)

Small Area Estimation for Household Budget Survey: Producing Reliable Estimates for Municipal Domains

11.40-12.00Open presentation slot
12.00-12.20Open presentation slot
12.20-12.40Open presentation slot
12.40-14.00Lunch break
14.00-14.45

Session 11

Invited lectures

Chair:

Volodymir Sarioglo (Institute for Demography and Social Studies)

Population Sample Surveys in Ukraine during Wartime: Challenges and Lessons

14.45-15.30Open presentation slot
15.30-16.00Break
16.00-16.20

Session 12

Contributed presentations with discussions

Chair:

Jānis Valeinis (Laboratory of Statistical Research and Data Analysis, UL)

Potential of robust and nonparametric methods in survey sampling (tbc)

16.20-16.40

Emīls Siliņš (Laboratory of Statistical Research and Data Analysis, UL)

Topic to be confirmed

16.40-17.00

Sofiia Lukashevych (Laboratory of Statistical Research and Data Analysis, UL)

Topic to be confirmed

17.00-17.20Open presentation slot
17.20-17.40Open presentation slot
17.40-17.50Conclusions of the day
18.30-21.00Farewell party

Friday, August 28, 2026 (Day 5)

Day Theme: AI and Automation in Statistical Production

Application of AI and automation to improve the efficiency and quality of statistical production processes.

TimeActivitySpeaker
9.00-9.45

Session 13

Invited lectures

Chair:

Marcin Szymkowiak ((Poznan University of Economics and Business)

A joint calibration approach for totals and quantiles for probability and nonprobability samples

9.45-10.30Open presentation slot
10.30-11.00Break
11.00-11.20

Session 14

Contributed presentations with discussions

Chair:

 

Open presentation slot
11.20-11.40Open presentation slot
11.40-12.00Open presentation slot
12.00-12.20Open presentation slot
12.20-12.40Open presentation slot
12.40-13.00Closing remarksProgramme & Organising committees

Last updated 27.04.2026.


Call for Papers

The workshop invites contributions on methodological and applied aspects of survey sampling in modern data environments. Topics include, but are not limited to:

  • Survey sampling design, stratification, clustering, multi-stage and rotation sampling
  • Adaptive and responsive survey designs and modern data collection strategies
  • Sampling frames, coverage diagnostics, and frame maintenance
  • Nonresponse mechanisms, response propensity modelling, and use of paradata
  • Survey estimation methods: weighting, calibration, model-assisted estimation, and variance estimation
  • Treatment of missing data: imputation and machine-learning approaches
  • Integration of survey data with administrative registers and alternative data sources
  • Data fusion and combining probability and non-probability samples
  • Small area estimation, spatial methods, and domain estimation
  • Machine learning and AI applications in survey statistics
  • Automated workflows and reproducible pipelines for survey production
  • Quality assessment, total survey error, and methodological challenges in modern survey statistics