Correlates of Representation Errors in Internet Data Sources for Real Estate Market

Anenberg, E. and S. Laufer. 2017. “A More Timely House Price Index.” Review of Economics and Statistics 99(4): 722–734. Doi: https://doi.org/10.1162/REST_a_00634.10.1162/REST_a_00634Open DOISearch in Google Scholar

Beręsewicz, M. 2016. Internet Data Sources for Real Estate Market Statistics. PhD diss., Poznań University of Economics and Business. Available at: http://www.wbc.poznan.pl/dlibra/docmetadata?id=393454 (accessed February 2019).Search in Google Scholar

Beręsewicz, M. 2017. “A Two-Step Procedure to Measure Representativeness of Internet Data Sources.” International Statistical Review 85(3): 473–493. Doi: https://doi.org/10.1111/insr.12217.10.1111/insr.12217Open DOISearch in Google Scholar

Beręsewicz, M., R. Lehtonen, F. Reis, L. Di Consiglio, and M. Karlberg. 2018. An Overview of Methods for Treating Selectivity in Big Data Sources. Statistical Working Papers. Eurostat. Doi: https://doi.org./10.2785/312232.10.2785/312232Open DOISearch in Google Scholar

Brick, J.M. 2015. “Unit Nonresponse and Weighting Adjustments: A Critical Review.” Journal of Official Statistics 29(3): 329–353. Doi: https://doi.org/10.2478/jos-2013-0026.10.2478/jos-2013-0026Open DOISearch in Google Scholar

Buelens, B., P. Daas, J. Burger, M. Puts, and J. van den Brakel. 2014. Selectivity of Big Data. Discussion paper 201411. Statistics Netherlands, The Hague/Heerlen, The Netherlands. Available at: http://pietdaas.nl/beta/pubs/pubs/Selectivity_Buelens.pdf (accessed February 2019).Search in Google Scholar

Cavallo, A. 2013. “Online and Official Price Indexes: Measuring Argentina’s Inflation.” Journal of Monetary Economics 60(2): 152–165. Doi: https://doi.org/10.1016/j.jmoneco.2012.10.002.10.1016/j.jmoneco.2012.10.002Open DOISearch in Google Scholar

Chen, B., A. Shrivastava, and R.C. Steorts. 2018. “Unique entity estimation with application to the Syrian conflict.” The Annals of Applied Statistics 12(2): 1039–1067. Doi: https://doi.org/10.1214/18-AOAS1163.10.1214/18-AOAS1163Open DOISearch in Google Scholar

Chen, C., J. Wakefield, and T. Lumely. 2014. “The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation.” Spatial and Spatio-Temporal Epidemiology 11: 33–43. Doi: https://doi.org/10.1016/j.sste.2014.07.002.10.1016/j.sste.2014.07.002435736325457595Open DOISearch in Google Scholar

Citro, C.F. 2014. “From Multiple Modes for Surveys to Multiple Data Sources for Estimates.” Survey Methodology 40(2): 137–161.Search in Google Scholar

Daas, P.J., M.J. Puts, B. Buelens, and P.A. van den Hurk. 2015. “Big Data as a Source for Official Statistics.” Journal of Official Statistics 31(2): 249–262. Doi: https://doi.org/10.1515/jos-2015-0016.10.1515/jos-2015-0016Open DOISearch in Google Scholar

ESSnet Big Data. 2018. “ESSnet Big Data.” Available at: https://webgate.ec.europa.eu/fpfis/mwikis/essnetbigdata/index.php/ESSnet_Big_Data (accessed February 2018).Search in Google Scholar

Faraway, J.J., X. Wang, and Y.Y. Ryan. 2018. Bayesian Regression Modeling with INLA. Chapman/Hall/CRC.Search in Google Scholar

Fleishman, L. and Y. Gubman. 2015. “Mass Appraisal at the Census Level: Israeli Case.” Statistical Journal of the IAOS 31(4): 597–612. Doi: https://doi.org/10.3233/SJI-150939.10.3233/SJI-150939Open DOISearch in Google Scholar

Gelman, A., J. Hwang, and A. Vehtari. 2014. “Understanding Predictive Information Criteria for Bayesian Models.” Statistics and Computing 24(6): 997–1016. Doi: https://doi.org/10.1007/s11222-013-9416-2.10.1007/s11222-013-9416-2Search in Google Scholar

Heckman, J. 1979. “Sample Selection Bias as a Specification Error.” Econometrica 47: 153–161. Doi: https://www.jstor.org/stable/1912352.10.2307/1912352Search in Google Scholar

Held, L., B. Schrödle, and H. Rue. 2010. “Posterior and Cross-validatory Predictive Checks: A Comparison of MCMC and INLA.” In Statistical Modelling and Regression Structures: Festschrift in Honour of Ludwig Fahrmeir, edited by T. Kneib and G. Tutz, 91–110. Heidelberg: Physica-Verlag HD. Doi: https://doi.org/10.1007/978-3-7908-2413-1_6.10.1007/978-3-7908-2413-1_6Open DOISearch in Google Scholar

Hoekstra, R., O. ten Bosch, and F. Harteveld. 2012. “Automated Data Collection from Web Sources for Official Statistics: First Experiences.” Statistical Journal of the IAOS 28(3, 4): 99–111. Doi: https://doi.org/10.3233/SJI-2012-0750.10.3233/SJI-2012-0750Open DOISearch in Google Scholar

Ihlanfeldt, K.R. and J. Martinez-Vazquez. 1986. “Alternative Value Estimates of Owner-occupied Housing: Evidence on Sample Selection Bias and Systematic Errors.” Journal of Urban Economics 20(3): 356–369. Doi: https://doi.org/10.1016/0094-1190(86)90025-2.10.1016/0094-1190(86)90025-2Open DOISearch in Google Scholar

Japec, L., F. Kreuter, M. Berg, P. Biemer, P. Decker, C. Lampe, J. Lane, C. O’Neil, and A. Usher. 2015. “Big Data in Survey ResearchAAPOR Task Force Report.” Public Opinion Quarterly 79(4): 839–880. Doi: https://dx.doi.org/10.1093/poq/nfv039.10.1093/poq/nfv039Open DOISearch in Google Scholar

Kiel, K.A. and J.E. Zabel. 1999. “The Accuracy of Owner-provided House Values: The 1978–1991 American Housing Survey.” Real Estate Economics 27(2): 263–298. Doi: https://doi.org/10.1111/1540-6229.00774.10.1111/1540-6229.00774Open DOISearch in Google Scholar

Lindgren, F. and H. Rue. 2015. “Bayesian Spatial Modelling with R-INLA.” Journal of Statistical Software 63(19): 1–25. Doi: https://doi.org/10.18637/jss.v063.i19.10.18637/jss.v063.i19Search in Google Scholar

Lohr, S.L. and T.E. Raghunathan. 2017. “Combining Survey Data with Other Data Sources.” Statist. Sci. 32(2) (May): 293–312. Doi: https://doi.org/10.1214/16-STS584.10.1214/16-STS584Open DOISearch in Google Scholar

Lozano-Gracia, N. and L. Anselin. 2012. “Is the Price Right?: Assessing Estimates of Cadastral Values for Bogotá, Colombia.” Regional Science Policy & Practice 4(4): 495–508. Doi: https://doi.org/10.1111/j.1757-7802.2012.01062.x.10.1111/j.1757-7802.2012.01062.xOpen DOISearch in Google Scholar

Marra, G., R. Radice, T. Bärnighausen, S.N. Wood, and M.E. McGovern. 2017. “A Simultaneous Equation Approach to Estimating Hiv Prevalence with Nonignorable Missing Responses.” Journal of the American Statistical Association 112(518): 484–496. Doi: https://doi.org/10.1080/01621459.2016.1224713.10.1080/01621459.2016.1224713Open DOISearch in Google Scholar

Mercer, L., J. Wakefield, C. Chen, and T. Lumley. 2014. “A Comparison of Spatial Smoothing Methods for Small Area Estimation with Sampling Weights.” Spatial Statistics 8: 69–85. Doi: https://10.1016/j.spasta.2013.12.001.10.1016/j.spasta.2013.12.001406447324959396Search in Google Scholar

Pfeffermann, D. 2015. “Methodological Issues and Challenges in the Production of Official Statistics: 24th Annual Morris Hansen Lecture.” Journal of Survey Statistics and Methodology 3(4): 425–483. Doi: https://dx.doi.org/10.1093/jssam/smv035.10.1093/jssam/smv035Open DOISearch in Google Scholar

R Core Team. 2017. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: www.R-project.org/ (accessed February 2019).Search in Google Scholar

Reid, G., F. Zabala, and A. Holmberg. 2017. “Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ.” Journal of Official Statistics 33(2): 477–511. Doi: https://doi.org/10.1515/jos-2017-0023.10.1515/jos-2017-0023Open DOISearch in Google Scholar

Riddles, M.K., J.K. Kim, and J. Im. 2016. “A Propensity-score-adjustment Method for Non-ignorable Nonresponse.” Journal of Survey Statistics and Methodology 4(2): 215–245. Doi: https://doi.org/10.1093/jssam/smv047.10.1093/jssam/smv047Open DOISearch in Google Scholar

Rue, H., S. Martino, and N. Chopin. 2009. “Approximate Bayesian Inference for Latent Gaussian Models Using Integrated Nested Laplace Approximations (with discussion).” Journal of the Royal Statistical Society B 71: 319–392. Doi: https://doi.org/10.1111/j.1467-9868.2008.00700.x.10.1111/j.1467-9868.2008.00700.xOpen DOISearch in Google Scholar

Sikov, A. 2018. “A Brief Review of Approaches to Non-ignorable Non-response.” International Statistical Review 86(3): 415–441. Doi: https://doi.org/10.1111/insr.12264.10.1111/insr.12264Open DOISearch in Google Scholar

Simpson, D., H. Rue, A. Riebler, T.G. Martins, S.H. Sørbye, et al. 2017. “Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors.” Statistical Science 32(1): 1–28. Doi: https://doi.org/10.1214/16-STS576.10.1214/16-STS576Open DOISearch in Google Scholar

Spiegelhalter, D.J., N.G. Best, B.P. Carlin, and A. Van Der Linde. 2002. “Bayesian Measures of Model Complexity and Fit.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64(4): 583–639. Doi: https://doi.org/10.1111/1467-9868.00353.10.1111/1467-9868.00353Open DOISearch in Google Scholar

Statistics Netherlands. 2018. Indicatoren bestaande woningen in verkoop. Available at: https://www.cbs.nl/nl-nl/onze-diensten/methoden/onderzoeksomschrijvingen/korte-onderzoeksbeschrijvingen/indicatoren-bestaande-woningen-in-verkoop (accessed November 2018).Search in Google Scholar

Steorts, R.C., R. Hall, and S.E. Fienberg. 2016. “A Bayesian Approach to Graphical Record Linkage and Deduplication.” Journal of the American Statistical Association 111(516): 1660–1672. Doi: https://doi.org/10.1080/01621459.2015.1105807.10.1080/01621459.2015.1105807Open DOISearch in Google Scholar

Sverchkov, M. and D. Pfeffermann. 2018. “Small Area Estimation Under Informative Sampling and Not Missing At Random Non-response.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 181(4): 981–1008. Doi: https://doi.org/10.1111/rssa.12362.10.1111/rssa.12362Open DOISearch in Google Scholar

Wallgren, A. and B. Wallgren. 2014. Register-based Statistics: Statistical Methods for Administrative Data. New York: Wiley.10.1002/9781118855959Search in Google Scholar

Watanabe, S. 2010. “Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory.” Journal of Machine Learning Research 11(Dec): 3571–3594. Available at: http://www.jmlr.org/papers/v11/watanabe10a.html (accessed February 2019).Search in Google Scholar

Zhang, L.-C. 2012. “Topics of Statistical Theory for Register-based Statistics and Data Integration.” Statistica Neerlandica 66(1): 41–63. Doi: https://doi.org/10.1111/j.1467-9574.2011.00508.x.10.1111/j.1467-9574.2011.00508.xOpen DOISearch in Google Scholar