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1st Author Surname1st Author NameAffiliationCountryOther Authors' Full NamesTitleKeywords

Date

(yyyy/mm)

Status

(w. link if available)

Document
LorencBorisBright LynxEstoniaArnout van Delden, Peter Struijs, and Li-Chun ZhangOn the Unit Problem in Business Statistics: Statement Paper Prepared for Participants' Discussion at EESW17
2017/09EESW17ENBES Unit Problem Statement.pdf
WallgrenAndersStatistics SwedenSweden

Britt
Wallgren

Business statistics and national accounts - what strategy and methods should we adopt?
2017/09EESW17Wallgren-EESW17-1.pdf
BrownGaryONSUKGareth JamesTransformation of ONS business surveys
2017/09EESW17EESW17 - Gary & Gareth.docx
RavindraDanielaStatistics CanadaCanada
Alternative Ways of Assessing Confidentiality of Economic Statistics at Statistics Canada
2017/09EESW17Southampton paper v3.pdf
AnderssonPer GöstaStockholm UniversitySweden
"Optimal" calibration weights under nonresponse
2017/09EESW17ENBES2017PGAndersson.pdf
HedlinDanStockholm UniversitySweden
Does nonresponse in business surveys matter?
2017/09EESW17Does nonresponse in business surveys matter Hedlin.pdf
IchimDanielaISTATItaly
On building statistical indicators at labour market area level
2017/09EESW17

ICHIM - EESW2017 - LMA indicators preliminary paper.docx

van DeldenArnoutStatistics NetherlandsThe Netherlands
Issues when integrating data sets with different unit types
2017/09EESW17ExtendedAbstractEESW2017_VanDelden_subm.docx
CamoesJorgeexcelcharts.comPortugal

Multi-chart
visualizations


2017/09EESW17Southampton Jorge Camoes.docx
BolkoIrenaUniversity of LjubljanaSloveniaMojca BavdažUser aspects of data visualization in official statistics
2017/09EESW17EESW17_Bolko_Bavdaz_Paper_Sent.pdf
VilaJoseDevStatSpainJose L.Cervera-FerriBehavioural levers to enhance data visualisation
2017/09EESW17VILA&CERVERA.pdf
LindblomAnnika

Statistics
Sweden

Sweden
A tool for sample selection to be used in a standardised production process
2017/09EESW17EESW17_StatSweden.docx
GrosEmmanuelINSEEFranceRonan Le GleutSample coordination and response burden for business surveys
2017/09EESW17EESW17 - Draft Ronan Le Gleut.pdf
SmeetsMarcStatistics NetherlandsThe NetherlandsHarm Jan BoonstraSampling coordination for business surveys at Statistics Netherlands
2017/09EESW17EESW17PaperMJESmeets.pdf
KlimanekTomaszStatistical Office in PoznańPolandMarcin SzymkowiakBig data techniques for supplementing statistical business registers
2017/09EESW17klimanek_szymkowiak.pdf
Deshaies-MoreaultCatherine

Statistics
Canada

CanadaBrett Harper, Wesley YungUse of Scanner Data for the Consumer Price Index at Statistics Canada
2017/09EESW17CPI_paper_final.docx
Noč RazingerMojcaStatistical Office of the Republic of SloveniaSlovenia
Surveys on prices at the Statistical Office of the Republic of Slovenia
2017/09EESW17Surveys on Prices at SURS_FinalDraft.docx
AramendiJorgeEUSTATSpainJavier San Vicente Automatic hotel prices collection on the Internet for the Tourism Survey in the Basque Country
2017/09EESW17ENBES17_Automatic hotel prices collection on the Internet for the Tourism Survey in the Basque Country.pdf
BavdažMojcaUniversity of LjubljanaSlovenia Deirdre Giesen, Simona Korenjak Černe, Tora Lofgren, Virginie Raymond-BlaessResponse Burden in Official Business Surveys: Measurement and Reduction Practices of National Statistical Institutes

Administrative burden; Data collection; Establishment surveys 

2015/12Published in Journal of Official StatisticsJOS_BavdazMo.pdf
LorencBorisStatistics SwedenSwedenWilhelmus Kloek, Linda Abrahamsson, Stephanie EckmanAn Analysis of Business Response Burden and Response Behaviour Using a Register of Data ProvisionBusiness surveys; Multi-level models; Models of survey participation2013/03Proceedings paper, NTTS 2013Paper
NedyalkovaDesislavaSwiss Federal Statistical OfficeSwitzerlandJohan Pea, Yves TilléSampling Procedures for Coordinating Stratified Samples: methods based on MicrostrataSample coordination; Stratified samples; Permanent random numbers; Microstrata 2008/12Published in International Statistical ReviewNedyalkova_et_al-2008-International_Statistical_Review.pdf 
ZhangLi-ChunStatistics NorwayNorwayNina Hagesæther

A domain outlier robust design and smooth estimation approach

Domain estimation; outlier robust; threshold sample; Winsorization; prediction2011/01Published in The Canadian Journal of StatisticsCJS2011-DomainOutlierDesignEstimation
ZhangLi-ChunUniversity of SouthamptonUnited KingdomAlison Pritchard

Short-term turnover statistics based on VAT and
Monthly Business Survey data sources



ManuscripttoVATregisterLZ-AP
JentoftSusieStatistics NorwayNorwayTora Löfgren, Anne Vedø, Li-Chun ZhangOn optimal sampling designs for price index surveys
2015/07ManuscriptPrice index paper 31 juli 2015
LuppesMartinStatistics Netherlands, Statistics DenmarkNetherlands, Denmark

Peter Bøegh Nielsen


Global Value Chains in official business statistics
2015/09EESW15201501Global Value Chains in official business statistics Martin Luppes, Peter Boegh Nielsen.pdf
StruijsPeteStatistics NetherlandsNetherlands
Statistical Units Delineation and the Quality of Business Statistics
2015/09EESW15201502Statistical Units Delineation and the Quality of Business Statistics Peter Struijs.pdf
VershaerenFranStatistics BelgiumBelgium
Exploration into the network structure of the Economy
2015/09EESW15201503Exploration into the network structure of the Economy Frank Verschaeren.pdf
BendowskaMartCentral Statistical Office of Poland, Statistical Office PoznanPolandMichał Chaber, Katarzyna Buhłak, Ada Bykowska-StaniewskaStatistical unit in Short term statistics (STS) in Poland
2015/09EESW15201504Statistical unit in Short term statistics (STS) in Poland Marta Bendowska, Katarzyna Buhłak, Ada Bykowska-Staniewska.pdf
HeljalaHannStatistics FinlandFinland
Improved consistency over unit types in an integrated business statistics production system
2015/09EESW15201505Improved consistency over unit types in an integrated business statistics production system Hanna Heljala.pdf
van DeldenArnouStatistics NetherlandsNetherlandsSander Scholtus, Joep BurgerEffect of classification errors on the accuracy of business statisticsregister-based statistics, audit sample, boostrap, misclassification, NACE2015/09EESW15201506Effect of classification errors on the accuracy of business statistics Arnout van Delden, Sander Scholtus and Joep Burger.pdf
SmithPauSouthampton Statistical Sciences Research InstituteUnited Kingdom
An application of weighting approaches to assess the sensitivity of business survey estimates to “the unit problem”
2015/09EESW15201507An application of weighting approaches to assess the sensitivity of business survey estimates to “the unit problem” Paul Smith.pdf
AssoulinDanieSwiss Federal Statistical OfficeSwitzerlandJann PotteratQuarterly Survey of Employment (JobStat) – how to take into account demographical changes in the enterprise population
2015/09EESW15201508Quarterly survey of employement (JobStat) – how taking into account demographical changes in the enterprise population Daniel Assoulin, Jann Potterat.pdf
MłodakAndrzeStatistical Office PoznanPoland
An application of complex measure to the model–based imputation in business statisticsmodel–based imputation, taxonomic measure of development, ratio imputation, multiple imputation, predictive mean matching, propensity score method2015/09EESW15201509An application of a complex measure to model–based imputation Andrzej Młodak.pdf
BeręsewiczMaciePoznan University of Economics, Statistical Office PoznanPoland
On the calibration approach and multiple imputation in the DG-1 business surveycalibration, imputation, prediction, missing data, business survey, reporting2015/09EESW15201510On the calibration approach and multiple imputation in Bresewicz Maciej.pdf
YungWesleStatistics CanadaCanadaMike Hidiroglou and Susana Rubin-BluerSmall Area Estimation for Business Surveys at Statistics Canada
2015/09EESW15201511Small Area Estimation for Business Surveys at Statistics Canada Wesley Yung, Mike Hidiroglou and Victor Estevao.pdf
NedyalkovaDesislavSwiss Federal Statistical OfficeSwitzerlandDaniel AssoulinSwiss Structural Business Statistics: Data Harmonization for the Construction of Full-time Equivalents
2015/09EESW15201512Swiss Structural Business Statistics Data Harmonization for the Construction of Full-time Equivalents Desislava Nedyalkova, Daniel Assoulin.pdf
SeriGiovanniItalian National Statistical InstituteItalyDaniela Ichim, Valeria Mastrostefano, Alessandra NurraExploiting the integration of businesses micro-data sources
2015/09EESW15201513Exploiting the integration of businesses micro-data sources Giovanni Seri, Daniela Ichim, Valeria Mastrostefano, Alessandra Nurra.pdf
LuziOriettaItalian National Statistical InstituteItalyTiziana Pichiorri, Roberta VarrialeEstimating SBS in the Italian Public Sector from multiple administrative data sources
2015/09EESW15201514Estimating Structural Business Statistics in the Italian Public Sector from multiple administrative data sources Orietta Luzi, Tiziana Pichiorri, Roberta Varriale.pdf
SnyderNancyUnited Nations Statistics Division
Ronald JansenLinking Business Registers with Trade Statistics
2015/09EESW15201515Linking Business Registers with Trade Statistics Nancy Snyder.pdf
ZhangLi-ChunStatistics NorwayNorwayTora Löfgren, Susie JentoftOptimal sampling design for price index surveys
2015/09EESW15201516On optimal sampling designs for price index surveys Li-Chun Zhang, Tora Löfgren, Susie Jentoft.pdf
WalkowskaKatarzynaCentral Statistical Office of PolandPolandAneta PlatekBusiness statistics in the CSO of Poland
2015/09EESW15201517Business statistics in the CSO of Poland Aneta Płatek, Katarzyna Walkowska.pdf
StåhlOliviaStockholm UniversitySweden
Partly model-based point estimation

Skewed population, outliers, model-based approach, value modification, simple random

sampling, winsorization

2015/09EESW15201518Partly model-based point estimation Olivia Stahl.pdf
LavoieFrancineStatistics CanadaCanada
Statistics Canada’s Enterprise Portfolio Management (EPM) Program
2015/09EESW15201519Statistics Canada’s Enterprise Portfolio Management (EPM) Francine Lavoie.pdf
SandersonRiaOffice for National Statistics, UKUnited KingdomDenise Williams, Megan PopeDevelopments in measuring the burden placed on businesses responding to statistical surveys
2015/09EESW15201520Developments in measuring the burden placed on businesses responding to statistical surveys Ria Sanderson, Denise Williams, Megan Pope.pdf
SzkopAlinaStatistical Office PoznanPolandMateusz SmektalskiMeasuring representativeness of different data sources connected with short-term statistics
2015/09EESW15201521Measuring representativeness of different data sources connected with short-term statistics Alina Szkop, Mateusz Smektalski.pdf
Otero FrancoLauraBasque Statistical OfficeSpainPatxi Garrido EspinosaIntegration of survey and administrative data in structural services statistics
2015/09EESW15201522Integration of survey and administrative data in structural services statistics Laura Otero Franco, Patxi Garrido Espinosa.pdf
AhmadZahoorUniversity of Southampton, Statistics NorwayUnited Kingdom, NorwayLi-Chun ZhangModelling Progressive Data under Informative Reporting
2015/09EESW15201523Modelling Progressive Data Z. Ahmed, L.-C. Zhang.pdf
Saint-Pierre

Etienne

Statistics CanadaCanada
Integrated Business Statistics Program
2013/09EESW13201301Integrated Business Statistics Program.pdf
Snijkers

Ger

Statistics Netherlands, Statistics NorwayNetherlands, Norway

Gustav Haraldsen

Modernisation and Quality of Business Statistics: The NSI perspective
2013/09EESW13201302Modernisation and Quality of Business Statistics The NSI perspective.pdf
SalvadorMartaEUSTATSpainJorge Aramendi, Elena Goni, Anjeles Iztueta, Fernando TusellRenewing the Eustat Tourism Survey: new collection methods and design for more detailed estimatesTourism statistics, hot-deck imputation, time patterns; spatial and temporal disaggregation, XML-files, respondents burden2013/09EESW13201303Renewing the Eustat Tourism Survey new collection methods and design for more detailed estimates.pdf
Kowalewski

Jacek

Central Statistical Office of PolandPoland
Using a map of short term statistics in the process of organizing Business Surveys
2013/09EESW13201304Using a map of short term statistics in the process of organizing Business Surveys.pdf
Szymkowiak

Marcin

Central Statistical Office of PolandPoland
Some aspects of using calibration in Polish surveys
2013/09EESW13201305Some aspects of using calibration in Polish surveys.pdf
Varriale

Roberta

ISTATItaly
Predictive Mean Matching using a factor model, an application to the (Business) Multipurpose Survey
2013/09EESW13201306Predictive Mean Matching using a factor model, an application to the (Business) Multipurpose Survey.pdf
AramendiJorgeEUSTATSpainElena Goni, Anjeles Iztueta, Jose Miguel EscaladaSmall area estimation in Eustat: ICT survey in Enterprises of the Basque CountrySmall area estimate, Logistic regression model, Bootstrap2013/09EESW13201307Small area estimation in Eustat ICT survey in Enterprises of the Basque Country.pdf
ZimmermannThomasUniversität TrierGermanyRalf MünnichCoherent small area estimates for skewed business data
2013/09EESW13201308Coherent small area estimates for skewed business data.pdf
BannertMatthiasKOF Swiss Econimic InstitutSwitzerland
Reproducible Data Processing, Aggregation, Reporting and Storing of Business Tendency Survey Data in an Open Source Frameworkbusiness tendency surveys, cost cutting, reproducibility, transparency, aggregation, software architecture, reproducible research2013/09EESW13201309Reproducible Data Processing, Aggregation, Reporting and Storing of Business Tendency Survey Data in an Open Source Framework.pdf
LammersJohanStatistics NetherlandsNetherlands
Event driven processingEvent processing, Economic Demography, Proof of concept2013/09EESW13201310Event driven processing.pdf
SolariFabrizioISTATItalyLoredana Di ConsiglioWeighting and estimation methods: description in the Memobust handbook
2013/09EESW13201311Weighting and estimation methods description in the Memobust handbook.pdf
Nedyalkova

Desislava

Bundesamt für StatistikGermanyDaniel AssoulinConstruction of Full Time Equivalents for the register based Swiss Structural Business Statistics
2013/09EESW13201312Construction of Full Time Equivalents for the register based Swiss Structural Business Statistics.pdf
LuziOriettaISTATItalyDi Zio M., Oropallo F., Puggioni A., Sanzo R.Integrating administrative and survey data in the new Italian system for SBS: quality issues
2013/09EESW13201313Integrating administrative and survey data in the new Italian system for SBS quality issues.pdf
Zhang

Li-Chun

University of SouthamptonUnited KingdomAlison PritchardThe integration of survey and administrative data
2013/09EESW13201314The integration of survey and administrative data.pdf
WeinhardtMichaelGerman Institute for Economic Research, Universität BielefeldGermanyA. Meyermann, S. Liebig, J. SchuppDeterminants of Consent in the German SOEP Establishment Survey 2012
2013/09EESW13201315Determinants of Consent in the German SOEP Establishment Survey 2012.pdf
BavdazMojcaUniversity of LjubljanaSloveniaJaka LindičIncreasing relevance of Official Business Statistics using proven Business Approaches
2013/09EESW13201316Increasing relevance of Official Business Statistics using proven Business Approaches.pdf
Giesen

Deirdre

Statistics NetherlandsNetherlands

Joep Burger

Measuring and understanding response quality in the Structural Business Survey questionnairesQuestionnaire design, response process, perceived response burden2013/09EESW13201317Measuring and understanding response quality in the Structural Business Survey questionnaires.pdf
MeyermannAlexiaUniversität BielefeldGermany
The use of Behaviour Coding to analyse data quality in the SOEP Establishment Survey 2012
2013/09EESW13201318The use of Behaviour Coding to analyse data quality in the SOEP Establishment Survey 2012.pdf
Giesen

Deirdre

Statistics NetherlandsNetherlandsGer SnijkersCommuncation with businesses as data providers and data users. Overview of BLUE-ETS findings, proposal for best practices at NSIs and research agendaResponse burden, motivation, research2013/09EESW13201319Communcation with businesses as data providers and data users. Overview of BLUE-ETS findings proposal for best practices at NSIs and research agenda.pdf
LorencBorisStatistics SwedenSwedenAndreas Persson, Klas WibellStatistics as a motivational feedback in business surveys
2013/09EESW13201320Statistics as a motivational feedback in business surveys.pdf
Ichim

Daniela

ISTATItaly
Business Microdata Dissemination at ISTAT
2013/09EESW13201321Business Microdata Dissemination at ISTAT.pdf
Kloek

Wim

Eurostat
Sorina VâjuComparison of European news releases on businesses
2013/09EESW13201322Comparison of European news releases on businesses.pdf
Deroyon

Thomas

INSEEFrance
Missing data treatment in administrative fiscal sources in the French structural business statistics production system
2013/09EESW13201323Missing data treatment in administrative fiscal sources in the French structural business statistics production system.pdf

Pannekoek

Jeroen

Statistics NetherlandsNetherlandsSander Scholtus, Mark van der LooAutomatic data editing functions for establishment surveysautomatic editing, generalised systems, process design2013/09EESW13201324Automatic data editing functions for establishment surveys.pdf
SeriGiovanniISTATItaly
The Italian new survey on Enterprises Final Consumption of Energy Products (COEN) - 2011: an innovative editing procedure
2013/09EESW13201325The Italian new survey on Enterprises Final Consumption of Energy Products (COEN) 2011 an innovative editing procedure.pdf
Carbonneau

Jean-François

Statistics CanadaCanada
Development of an integrated business statistics program
2011/09EESW11201101Development of an integrated business statistics program.pdf
KloekWimEurostat

What makes business statistics different?
2011/09EESW11201102What makes business statistics different.pdf
GrafMoniqueSwiss Federal Statistical OfficeSwitzerlandJann PotteratConstruction of Full Time Equivalent for the Swiss Business Frame
2011/09EESW11201103Construction of Full Time Equivalent for the Swiss Business Frame.pdf
Luzi

Orietta

IstatItalyRinaldi M., Seri G., Guarnera U., De Giorgi V.Estimating structural business statistics based on administrative data: the case of the Italian small and medium enterprises
2011/09EESW11201104Estimating structural business statistics based on administrative data the case of the Italian small and medium enterprises.pdf
SnijkersGerStatistics Netherlands, US Census BureauNetherlands, United States of AmericaDiane K WillimackThe Missing Link: From Concepts to Questions in Economic SurveysConceptualisation and operationalisation, construct validity, measurement error, questionnaire design, pretesting2011/09EESW11201105The Missing Link From Concepts to Questions in Economic Surveys.pdf
MooreKenCentral Statistics OfficeIrelandSteve MacFeelyThe Pros and Cons of Automatic Data ExtractionEarnings, XML, response burden2011/09EESW11201106The Pros and Cons of Automatic Data Extraction.pdf
PärsonTiinaStatistics EstoniaEstonia
Annual Bookkeeping Report as the primary administrative source for the production of structural business statistics: current experiences and future plans
2011/09EESW11201107Annual Bookkeeping Report as the primary administrative source for the production of structural business statistics current experiences and future plans.pdf
BenderStefanInstitute for Employment ResearchGermanyAnja GruhlCombined Firm Data for Germany
2011/09EESW11201108Combined Firm Data for Germany.pdf
Olaeta GoirenaHaritzEUSTATSpainMarìa Victoria Garcìa Olea, Patxi GarridoUsing the Commercial Register to Reduce Response Burden in Economic Structural StatisticsCommercial Register, Reduction of Response Burden, Composite Estimation2011/09EESW11201109Using the Commercial Register to Reduce Response Burden in Economic Structural Statistics.pdf
Kowalewski

Jacek

Central Statistical OfficePoland
Possibilities of exploiting administrative data in short term statistics In Poland
2011/09EESW11201110Possibilities of exploiting administrative data in short term statistics In Poland.pdf
BiffignandiSilviaUniversity of Bergamo, IstatItalyAntonio Laureti, Giulio PeraniUsing survey data collection as a tool for improving the survey process
2011/09EESW11201111Using survey data collection as a tool for improving the survey process.pdf
LansgrundØyvindStatistics NorwayNorway
Seasonal Adjustments: Causes of Revisions
2011/09EESW11201112Seasonal Adjustments Causes of Revisions.pdf

van der Loo

MarkStatistics NetherlandsNetherlands

Edwin de Jonge, and Sander Scholtus

Correcting typing, rounding and sign errors in establishment data with R
2011/09EESW11201113Correcting typing, rounding and sign errors in establishment data with R.pdf

Griffioen

RobertStatistics NetherlandsNetherlandsArnout van Delden and Peter-Paul de WolfKey elements of quality frameworks, to be applied to statistical processes at NSI’s
2011/09EESW11201114Key elements of quality frameworks, to be applied to statistical processes at NSI’s.pdf
SandersonRiaon behalf of Work Package 3 of ESSnet on Admin Data

Methods for estimating Structural Business Statistics variables not available from administrative sources
2011/09EESW11201115Methods for estimating Structural Business Statistics variables not available from administrative sources.pdf
VerschaerenFrankStatistics Belgium, on behalf of Work Package 2 of ESSnet on Admin DataBelgium
Checking the Usefulness and Initial Quality of Administrative Data
2011/09EESW11201116Checking the Usefulness and Initial Quality of Administrative Data.pdf
Demetrio FalorsiPieroISTATItalyPaolo RighiOptimal Allocation in the Multi-way Stratification Design for Business Surveys
2011/09EESW11201117Optimal Allocation in the Multi-way Stratification Design for Business Surveys.pdf
SautoryOlivierINSEEFranceFabien GuggemosSampling coordination of business surveys conducted by INSEE
2011/09EESW11201118Sampling coordination of business surveys conducted by INSEE.pdf
QualitéLionelSwiss Federal Statistical OfficeSwitzerland
Return of experience on the Swiss survey coordination system
2011/09EESW11201119Return of experience on the Swiss survey coordination system.pdf
SeljakRudiStatistical Office of the Republic of SloveniaSloveniaPetra BlažičSampling error estimation - SORS practice
2011/09EESW11201120Sampling error estimation - SORS practice.pdf
HulligerBeatUniversity of Applied Sciences Northwestern Switzerland FHNWSwitzerland
A mixed mode survey on book prices among booksellers
2011/09EESW11201121A mixed mode survey on book prices among booksellers.pdf
Azula LazkanoIosuneEUSTAT, Economic StatisticsSpainPatxi Garrido, Haritz OlaetaSmall Area Estimations in the Industrial SurveyFixed Effects Models, Linear Mixed Models, Local Estimates, Coherence2011/09EESW11201122Small Area Estimations in the Industrial Survey.pdf
SalvadorMartaEUSTAT, Economic StatisticsSpainAlaitz Gallastegi, Patxi GarridoEstimation of GDP by municipalities
2011/09EESW11201123Estimation of GDP by municipalities.pdf
SchmidTimoUniversity TrierGermanyRalf Münnich, Thomas Zimmermann

Spatial robust small area estimation applied on business data


2011/09EESW11201124Spatial robust small area estimation applied on business data.pdf 
MuseuxJean-MarcEurostat
Axel Behrens, Marc Chovino, Claudia Junker, Jan Planovsky, Hartmut SchroerModernising European business statistics' infrastructure
2009/09EESW09 2009S1_1_Museux_Et_Al_final.pdf
BrandMartinUK Office for National StatisticsUnited Kingdom
Methodological Issues Arising for the Office for National Statistics from the Recession
2009/09EESW09 2009S1_2_Brand.pdf
KiemaSuiviStatistics FinlandFinland
Compilation of first estimates of turnover indices in recession - managing dissimilar fluctuations of small and large enterprises
2009/09EESW09 2009S1_3_Kiema.pdf
BrionPhilippeINSEE, Business statistics directorateFranceEmmanuel Gros

Methodological issues related to the reengineering of the French structural business statistics


2009/09EESW09 2009S2_1_Brion_Gros.pdf
SturmRolandFederal Statistical Office of Germany (Destatis)Germany
A motivational model for running a statistical business registerstatistical business register, infrastructure, production process, statistical surveys2009/09EESW09 2009S2_2_Sturm.pdf
HetheyTanjaInstitute for Employment Research (IAB), Columbia UniversityGermany, United States of AmericaJohannes F. SchmiederUsing Worker Flows in the Analysis of Establishment Turnover: Evidence from Germany
2009/09EESW09 2009S2_3_Hethey_Schmieder.pdf
HaslingerAloisStatistics AustriaAustriaNorbert RainerCalculating Business Demography Statistics based on Administrative Data
2009/09EESW09 2009S2_4_Haslinger_Rainer.pdf
ZhangLi-ChunStatistics NorwayNorway
Coordination of business surveys
2009/09EESW09 2009S3_1_Zhang.pdf
SalaminPaul-AndréSwiss Federal Statistical OfficeSwitzerland
Measuring the performance of a sample coordination system
2009/09EESW09 2009S3_2_Salamin.pdf
KowalewskiJacekStatistical Office in PoznańPoland
Model of optimization of statistical surveys
2009/09EESW09 2009S3_3_Kowalewski.pdf
LaukkanenTimoStatistics FinlandFinland
Linking administrative and survey data - employment variable for enterprises and establishments in Finnish Business Register
2009/09EESW09 2009S3_4_Laukkanen.pdf
BiffignandiSilviaUniversity of Bergamo, IstatItalyLeopoldo Nascia, Alessandro ZeliSurvey and Administrative Data Mix in a Business Survey
2009/09EESW09 2009S4_1_ Biffignandi_Nascia_Zeli.pdf
LuziOriettaIstatItalyGiulio Perani, Giovanni SeriFiscal data supporting Research and Development statistics
2009/09EESW09 2009S4_2_Luzi_Perani_Seri.pdf
IchimDanielaIstatItalyCristina Casciano, Giovanni SeriA linkage experiment between survey business data and administrative data
2009/09EESW09 2009S4_3_Ichim_Casciano_Seri.pdf
Konold

Michael

Research Data Centre of the Federal Statistical Office of GermanyGermany
Cross-institutional Integration of Business Data: Results of the German KombiFiD Project
2009/09EESW09 2009S4_4_Konold.pdf
ArielAdelaideStatistics NetherlandsNetherlandsArnout van Delden, Ivo Beuken, and Magda Slootbeek-van LaarLinking multiple sources to produce economic statistics at Statistics Netherlands
2009/09EESW09 2009S5_1_Ariel_EtAl.pdf
GodenhjelmPetriStatistics FinlandFinland
Usability principles in testing questions for establishment surveys
2009/09EESW09 2009S5_2_Godenhjelm.pdf
HartwigPiaStatistics SwedenSweden
How to use edit staff debriefings in questionnaire design
2009/09EESW09 2009S5_3_Hartwig.pdf
AelenFrankStatistics NetherlandsNetherlandsRoos SmitTowards an efficient data editing strategy for economic statistics at Statistics Netherlands
2009/09EESW09 2009S5_4_Aelen_Smit.pdf
BlackOleUK Office for National StatisticsUnited Kingdom
Improving validation for business surveys – the Eden Project
2009/09EESW09 2009S6_1_Black.pdf
HedlinDanStatistics SwedenSweden
Theory of selective editing with score functions
2009/09EESW09 2009S6_2_Hedlin.pdf
Luis do Nascimento Silva

Pedro

University of Southampton, UK Office for National StatisticsUnited KingdomDaniel Lewis, Alaa Al-Hamad, Ping ZongInvestigating selective editing ideas towards improving editing in the UK Retail Sales Inquiry
2009/09EESW09 2009S6_3_Silva EtAl.pdf
NorbergAndersStatistics SwedenSweden
Editing at Statistics Sweden – Yesterday, today and tomorrow
2009/09EESW09 2009S6_4_Norberg.pdf
OuwehandPimStatistics NetherlandsNetherlandsBarry Schouten, Vincent de HeijRepresentativity indicators for business surveys based on population totals
2009/09EESW09 2009S8_1_Ouwehand_Schouten_deHeij.pdf
Lotrič Dolinar

Aleša

University of Ljubljana, Statistical Office of the Republic of SloveniaSloveniaRudi Seljak, Mojca BavdažImpact of SMEs and fast-growing companies on survey estimates
2009/09EESW09 2009S8_2_Dolinar_Seljak_Bavdaz.pdf
AssoulinDanielSwiss Federal Statistical OfficeSwitzerland
Choosing an imputation method for large firms
2009/09EESW09 2009S8_3_Assoulin.pdf
Hoveid

Øyvind

Norwegian Agricultural Economics Research InstituteNorway
Semi-parametric estimation of weights: Fuzzy post-strati cation
2009/09EESW09 2009S8_4_Hoveid.pdf
LorencBorisStatistics SwedenSweden
An Analysis of Business Response Burden and Response Behaviour Using a Register of Data Provisionmulti-level models, models of survey participation2016/06Conference presentation (ICES-V)21062016_1550_Lorenc.pdf
BuenoEdgar

Dan Hedlin, Per Gösta Andersson

A comparison of stratied simple random sampling and sampling with probability proportional to size


2017/09EESW17link
GrosEmmanuelINSEEFranceRonan le Gleut

The impact of profiling on sampling: how to optimize sample design when statistical units differ  from data collection units



2017/09EESW17link

Fizzala

ArnaudINSEEFrance
Adaptations of Winsorization caused by profiling
2017/09EESW17link
Zimmermann

Thomas

DeStatisGermany

Using auxiliary data sources in the structural survey in the service sector


2017/09EESW17link
Geurden-SlisMargreetCBSNetherlandsGer Snijkers

The effect of communication measures for the survey on international trade in goods



2017/09EESW17link
SnijkersGerCBSNetherlands

Questionnaire communication to collect financial data from large non-financial enterprises


2017/09EESW17link
StewartJordanONSUK

Ian Sidney, Emma Timm

Paradata as an aide to questionnaire design:
Improving quality and reducing burden


2017/09EESW17link
LorencBorisBright LynxEstonia
Embedded Editing: Is There a Limit?
2017/09EESW17link
TuckerAdamONSUK

Measuring, managing and reporting respondent burden at the Office for National Statistics, UK


2017/09EESW17link

Martinuč

Alenka

Statistical Office of the
Republic of Slovenia

Slovenia

Vojko Šegan

What is the most appropriate way to measure response burden?


2017/09EESW17link
NedyalkovaDesislavaSwiss Federal Statistical OfficeSwitzerlandLionel Qualité

Response burden measurement for business surveys and the Swiss coordination system



2017/09EESW17link
AramendiJorgeEUSTATSpainJavier San Vicente Donor selection by multiple Tree-Based Models for Imputation
2017/09EESW17link
HaagOlivierINSEEFrance

How to improve the quality of the statistics
by combining different statistical units


2017/09EESW17link
SturmRolandFederal Statistical OfficeGermany

“The unit problem” – what can the statistical business register contribute? (DRAFT)


2017/09EESW17link
LammersJohanCBSNetherlands

Improves on profiling Enterprises


2017/09EESW17link
SmithPaul A.University of SouthamptonUKWesley YungA review and evaluation of the use of longitudinal approaches in business surveys
2019/10Published in Longitudinal and Life Course Studieshttps://doi.org/10.1332/175795919X15694142999134 (open access)
SimkinsAileenONSUKPaul A. Smith, Martin BrandFinancial crisis and
recession: how
ONS has addressed
the statistical and
analytical challenges
2010/01Published in Economic and Labour Market Reviewhttps://webarchive.nationalarchives.gov.uk/20151014010055/http://www.ons.gov.uk/ons/rel/elmr/economic-and-labour-market-review/no--1--january-2010/financial-crisis-and-recession--how-ons-has-addressed-the-statistical-and-analytical-challenges.pdf
AngottiRobertoItalian National Institute for Public Policy Analysis, INAPPItalyGiulio PeraniSurveying intangible investments of firms before and after the pandemic: the INAPP experience with new methodologies and new data sources
2021/10EESW21link
DelaneyJillianCentral Statistics OfficeIrelandPaul A. SmithSampling for business price indices, with applications in Ireland
2021/10EESW21link
BelakEvaStatistical Office of the Republic of SloveniaSloveniaAndreja Garbas, Vesna Ilič, Marko Sluga, Matevž MezeRevision and testing of the Investment survey questionnaire
2021/10EESW21link
Šuštar KožuhLauraStatistical Office of the Republic of SloveniaSlovenia
Data collection in the light of COVID-19
2021/10EESW21link
MoreiraAlmiroStatistics PortugalPortugalAntónio Portugal, Bruno Lima, João Poças, Jorge Magalhães, Paula Cruz, Salvador Gil, Sofia RodriguesThe use of electronic invoice data in COVID time
2021/10EESW21link
 BornaisKimStatistics CanadaCanada
Canadian Survey on Business Conditions: an experience in crowdsourcing for economics statistics
2021/10EESW21link
NieuwenhuijsRobertStatistics NetherlandsNetherlandsGer Snijkers, Derk van Wijk A method to automatically collect financial data from businesses in the SBS questionnaire
2021/10EESW21link
Gómez PérezJoséStatistics NetherlandsNetherlandsGer SnijkersTesting a new method for automating business data collection of official statistics through APIs
2021/10EESW21link
IparraguirreAnderEUSTATSpainJorge AramendiWeb crawling and scraping to reduce response burden
2021/10EESW21link
ChevalierClémentSFSOSwitzerlandLionel QualitéSwiss earning structure survey (ESS): revision of the weighting method
2021/10EESW21link
BeręsewiczMaciejPoznan University of Economics & Business, and Statistical Office in PosnanPolandHerman Cherniaiev, Pater RobertImproving and extending job vacancy survey by administrative and online data
2021/10EESW21link
IchimDanielaISTATItalyFrancesca Tartamella, Lucia CoppolaIntegrating business information into the correction of entrepreneurs’ income
2021/10EESWlink
van DeldenArnoutStatistics NetherlandsNetherlandsMartijn de Winter, Koert van BemmelIdentifying and evaluating COVID effects on short-term statistics
2021/10EESWlink
SluiskesMarijeStatistics NetherlandsNetherlandsMark van der Loo, Jeroen PannekoekA systematic comparison between ratio and random forest-based imputation methods for business survey data
2021/10EESWlink
BeaulieuMartinStatistics CanadaCanadaDanielle Lebrasseur, Roxanne GagnonMeasuring and communicating quality for programs using administrative data sources exclusively
2021/10EESW21link
RodriguesSofiaStatistics PortugalPortugalAlmiro Moreira, Paulo SaraivaThe creation of the Fast and Exceptional Enterprise Survey in COVID time
2021/10EESWlink
JosipovićBrankoStatistical Office of the Republic of SerbiaSerbia
Rapid Survey System
2021/10EESW21link
O’CallaghanSorcha Central Statistics OfficeIrelandColin HanleySigns of life activity indicators in Ireland using administrative data
2021/10EESW21link
FoleyPatrickCentral Statistics OfficeIreland
Seasonal adjustment of Irish official statistics during the current COVID-19 crisis
2021/10EESW21link
OlaetaHaritzEUSTATSpainJorge AramendiAdapting seasonal adjustment procedures in uncertain times 
2021/10EESW21link
MatthewsSteveStatistics CanadaCanada
Seasonal adjustment during the COVID-19 pandemic: Statistics Canada’s approach
2021/10EESW21link
BuitenGertStatistics NetherlandsNetherlands
Interfirm networks: a brief introduction
2021/10EESW21link
BuitenGertStatistics NetherlandsNetherlandsEdwin de JongeInterfirm network analysis and policy applications
2021/10EESW21link
PijpersFrankStatistics NetherlandsNetherlands
Approaches to network (re)construction 
2021/10EESW21link
MeirinhosVictorONSUKElliott PhillipsIntermediate consumption and the development of a business to business transaction matrix
2021/10EESW21link
van DeldenArnoutStatistics NetherlandsNetherlandsMartijn de Winter, Koert van BemmelIdentifying and evaluating COVID19 effects on short-term statistics
2022/03online workshop

ENBES_COVID19_PPT_V2.pptx






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