IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v20y2011i3p574-588.html
   My bibliography  Save this article

Bayesian benchmarking with applications to small area estimation

Author

Listed:
  • G. Datta
  • M. Ghosh
  • R. Steorts
  • J. Maples

Abstract

No abstract is available for this item.

Suggested Citation

  • G. Datta & M. Ghosh & R. Steorts & J. Maples, 2011. "Bayesian benchmarking with applications to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 574-588, November.
    • Handle: RePEc:spr:testjl:v:20:y:2011:i:3:p:574-588
    DOI: 10.1007/s11749-010-0218-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11749-010-0218-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11749-010-0218-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gauri Sankar Datta & J. N. K. Rao & David Daniel Smith, 2005. "On measuring the variability of small area estimators under a basic area level model," Biometrika, Biometrika Trust, vol. 92(1), pages 183-196, March.
    2. Zellner, Arnold, 1988. "Bayesian analysis in econometrics," Journal of Econometrics, Elsevier, vol. 37(1), pages 27-50, January.
    3. Zellner, A., 1992. "Bayesian and Non-Bayesian Estimation using Balanced Loss Functions," Papers 92-20, California Irvine - School of Social Sciences.
    4. Pfeffermann, Danny & Barnard, Charles H, 1991. "Some New Estimators for Small-Area Means with Application to the Assessment of Farmland Values," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 73-84, January.
    5. Pfeffermann, Danny & Tiller, Richard, 2006. "Small-Area Estimation With StateSpace Models Subject to Benchmark Constraints," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1387-1397, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kubokawa, Tatsuya, 2013. "Constrained empirical Bayes estimator and its uncertainty in normal linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 377-392.
    2. Tatsuya Kubokawa & Mana Hasukawa & Kunihiko Takahashi, 2014. "On Measuring Uncertainty of Benchmarked Predictors with Application to Disease Risk Estimate," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 394-413, June.
    3. Rachel C. Nethery & Yue Yang & Anna J. Brown & Francesca Dominici, 2020. "A causal inference framework for cancer cluster investigations using publicly available data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1253-1272, June.
    4. Tatsuya Kubokawa & Mana Hasukawa & Kunihiko Takahashi, 2012. "On Measuring Uncertainty of Benchmarked Predictors with Application to Disease Risk Estimatee," CIRJE F-Series CIRJE-F-861, CIRJE, Faculty of Economics, University of Tokyo.
    5. Rebecca C. Steorts & Timo Schmid & Nikos Tzavidis, 2020. "Smoothing and Benchmarking for Small Area Estimation," International Statistical Review, International Statistical Institute, vol. 88(3), pages 580-598, December.
    6. Malay Ghosh & Rebecca Steorts, 2013. "Two-stage benchmarking as applied to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(4), pages 670-687, November.
    7. Malay Ghosh & Tatsuya Kubokawa & Yuki Kawakubo, 2014. "Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation," CIRJE F-Series CIRJE-F-918, CIRJE, Faculty of Economics, University of Tokyo.
    8. Zhang Junni L. & Bryant John, 2020. "Fully Bayesian Benchmarking of Small Area Estimation Models," Journal of Official Statistics, Sciendo, vol. 36(1), pages 197-223, March.
    9. Benavent, Roberto & Morales, Domingo, 2016. "Multivariate Fay–Herriot models for small area estimation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 372-390.
    10. Matthew R. Williams & Terrance D. Savitsky, 2021. "Uncertainty Estimation for Pseudo‐Bayesian Inference Under Complex Sampling," International Statistical Review, International Statistical Institute, vol. 89(1), pages 72-107, April.
    11. J. N. K. Rao, 2015. "Inferential issues in model-based small area estimation: some new developments," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(4), pages 491-510, December.
    12. Tatsuya Kubokawa & William E. Strawderman, 2011. "Admissibility and Minimaxity of Benchmarked Shrinkage Estimators," CIRJE F-Series CIRJE-F-809, CIRJE, Faculty of Economics, University of Tokyo.
    13. Hiromasa Tamae & Tatsuya Kubokawa, 2015. "Small Area Predictors with Dual Shrinkage of Means and Variances," CIRJE F-Series CIRJE-F-982, CIRJE, Faculty of Economics, University of Tokyo.
    14. Rao J. N. K., 2015. "Inferential Issues in Model-Based Small Area Estimation: Some New Developments," Statistics in Transition New Series, Polish Statistical Association, vol. 16(4), pages 491-510, December.
    15. Ghosh Malay, 2020. "Small area estimation: its evolution in five decades," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 1-22, August.
    16. Rebecca Steorts & M. Ugarte, 2014. "Comments on: “Single and two-stage cross-sectional and time series benchmarking procedures for small area estimation”," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 680-685, December.
    17. Tatsuya Kubokawa, 2012. "Mixed Effects Prediction under Benchmarking and Applications to Small Area Estimation," CIRJE F-Series CIRJE-F-832, CIRJE, Faculty of Economics, University of Tokyo.
    18. Danny Pfeffermann & Anna Sikov & Richard Tiller, 2014. "Single- and two-stage cross-sectional and time series benchmarking procedures for small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 631-666, December.
    19. Kreutzmann, Ann-Kristin & Marek, Philipp & Salvati, Nicola & Schmid, Timo, 2019. "Estimating regional wealth in Germany: How different are East and West really?," Discussion Papers 35/2019, Deutsche Bundesbank.
    20. Ryan Janicki & Andrew Vesper, 2017. "Benchmarking techniques for reconciling Bayesian small area models at distinct geographic levels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 557-581, November.
    21. Marius Stefan & Michael Hidiroglou, 2021. "Benchmarked Estimators for a Small Area Mean Under a Onefold Nested Regression Model," International Statistical Review, International Statistical Institute, vol. 89(1), pages 108-131, April.
    22. M. Giovanna Ranalli & Giorgio E. Montanari & Cecilia Vicarelli, 2018. "Estimation of small area counts with the benchmarking property," METRON, Springer;Sapienza Università di Roma, vol. 76(3), pages 349-378, December.
    23. Malay Ghosh, 2020. "Small area estimation: its evolution in five decades," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 1-22, August.
    24. Elaheh Torkashvand & Mohammad Jafari Jozani & Mahmoud Torabi, 2016. "Constrained Bayes estimation in small area models with functional measurement error," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 710-730, December.
    25. J. N. K. Rao, 2015. "Inferential Issues In Model-Based Small Area Estimation: Some New Developments," Statistics in Transition New Series, Polish Statistical Association, vol. 16(4), pages 491-510, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Malay Ghosh & Tatsuya Kubokawa & Yuki Kawakubo, 2014. "Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation," CIRJE F-Series CIRJE-F-918, CIRJE, Faculty of Economics, University of Tokyo.
    2. Chuanming Gao & Kajal Lahiri, 2000. "A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometric Society World Congress 2000 Contributed Papers 0230, Econometric Society.
    3. M. D. Ugarte & A. F. Militino & T. Goicoa, 2008. "Adjusting economic estimates in business surveys," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(11), pages 1253-1265.
    4. Zhang Junni L. & Bryant John, 2020. "Fully Bayesian Benchmarking of Small Area Estimation Models," Journal of Official Statistics, Sciendo, vol. 36(1), pages 197-223, March.
    5. Tatsuya Kubokawa & William E. Strawderman, 2011. "Admissibility and Minimaxity of Benchmarked Shrinkage Estimators," CIRJE F-Series CIRJE-F-809, CIRJE, Faculty of Economics, University of Tokyo.
    6. Harm Jan Boonstra & Jan A. Van Den Brakel & Bart Buelens & Sabine Krieg & Marc Smeets, 2008. "Towards small area estimation at Statistics Netherlands," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 21-49.
    7. Marius Stefan & Michael Hidiroglou, 2021. "Benchmarked Estimators for a Small Area Mean Under a Onefold Nested Regression Model," International Statistical Review, International Statistical Institute, vol. 89(1), pages 108-131, April.
    8. Danny Pfeffermann & Anna Sikov & Richard Tiller, 2014. "Single- and two-stage cross-sectional and time series benchmarking procedures for small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 631-666, December.
    9. Andreea L. Erciulescu & Jean D. Opsomer, 2022. "A model‐based approach to predict employee compensation components," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1503-1520, November.
    10. Kubokawa, Tatsuya & Nagashima, Bui, 2012. "Parametric bootstrap methods for bias correction in linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 1-16.
    11. Àlex Costa & Albert Satorra & Eva Ventura, 2003. "An empirical evaluation of small area estimators," Economics Working Papers 674, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 2003.
    12. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 435-452, December.
    13. repec:csb:stintr:v:17:y:2016:i:1:p:9-24 is not listed on IDEAS
    14. Erciulescu Andreea L. & Fuller Wayne A., 2016. "Small Area Prediction Under Alternative Model Specifications," Statistics in Transition New Series, Polish Statistical Association, vol. 17(1), pages 9-24, March.
    15. Steel, Mark F. J., 1991. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 83-117.
    16. Stefano Marchetti & Luca Secondi, 2017. "Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 215-234, March.
    17. Marcet, Albert & Jarociński, Marek, 2010. "Autoregressions in small samples, priors about observables and initial conditions," Working Paper Series 1263, European Central Bank.
    18. Lixia Diao & David D. Smith & Gauri Sankar Datta & Tapabrata Maiti & Jean D. Opsomer, 2014. "Accurate Confidence Interval Estimation of Small Area Parameters Under the Fay–Herriot Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 497-515, June.
    19. Tatsuya Kubokawa & Shonosuke Sugasawa & Malay Ghosh & Sanjay Chaudhuri, 2014. "Prediction in Heteroscedastic Nested Error Regression Models with Random Dispersions," CIRJE F-Series CIRJE-F-939, CIRJE, Faculty of Economics, University of Tokyo.
    20. Domingo Morales, 2014. "Comments on: Single and two-stage cross-sectional and time series benchmarking procedures for small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 674-679, December.
    21. Md. Mizanur Rahman & Deluar J. Moloy & Md. Sifat Ar Salan, 2021. "Evaluating the Approaches of Small Area Estimation Using Poverty Mapping Data," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 10(2), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:20:y:2011:i:3:p:574-588. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.