IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v20y2019i4p113-134n10.html
   My bibliography  Save this article

Estimation Of Income Characteristics For Regions In Poland Using Spatio-Temporal Small Area Models

Author

Listed:
  • Jędrzejczak Alina

    (Institute of Statistics and Demography, Faculty of Economics and Sociology, University of Łódź, Łódź, Poland .)

  • Kubacki Jan

    (Centre of Mathematical Statistics, Statistical Office in Łódź, Łódź, Poland .)

Abstract

The paper presents the comparison of estimation results for spatial and spatiotemporal small area models. The study was carried out for income-related variables drawn from the Polish Household Budget Survey and explanatory variables from the Polish Local Data Bank for the years 2003-2013. The properties of EBLUPs (Empirical Best Linear Unbiased Predictors) based on spatiotemporal models, which utilize spatial correlation between neighbouring areas as well as historical data, were compared and contrasted with EBLUPs based on spatial models obtained separately for each year and with EBLUPs based on the Rao-Yu model. The computations were performed using sae, sae2 and spdep packages for R-project environment. In the case of sae package, the eblupFH, eblupSFH and the eblupSTFH functions were used for point estimation along with the mseFH, mseSFH and the pbmseSTFH functions for the MSE estimation, whereas the eblupRY function was applied for the purposes of sae2 package. The precision of direct estimators was guaranteed by the adoption of the Balanced Repeated Replication method. The results of the analysis demonstrate that a visible reduction of the estimation error was achieved for the implemented spatiotemporal small-area models, especially when significant spatial and time autocorrelations were observed. These results are even more valuable than those achieved by the means of the Rao-Yu model. In the computations, three author-defined functions were adopted, which not only enabled the author to perform the extract of random effects for spatial, spatiotemporal and Rao-Yu models, but also made it possible to obtain their decomposition with respect to spatial and temporal parts, thus creating a novel solution. The comparison was carried out using choropleth maps for spatial effects and distributions of temporal random effects for the considered years.

Suggested Citation

  • Jędrzejczak Alina & Kubacki Jan, 2019. "Estimation Of Income Characteristics For Regions In Poland Using Spatio-Temporal Small Area Models," Statistics in Transition New Series, Statistics Poland, vol. 20(4), pages 113-134, December.
    • Handle: RePEc:vrs:stintr:v:20:y:2019:i:4:p:113-134:n:10
    DOI: 10.21307/stattrans-2019-037
    as

    Download full text from publisher

    File URL: https://doi.org/10.21307/stattrans-2019-037
    Download Restriction: no
    File URL: https://libkey.io/10.21307/stattrans-2019-037?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
    ---><---

    References listed on IDEAS

    as
    1. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    2. Jan Kubacki & Alina Jędrzejczak, 2016. "Small Area Estimation Of Income Under Spatial Sar Model," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 365-390, September.
    3. Marhuenda, Yolanda & Molina, Isabel & Morales, Domingo, 2013. "Small area estimation with spatio-temporal Fay–Herriot models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 308-325.
    4. Monica Pratesi & Nicola Salvati, 2008. "Small area estimation: the EBLUP estimator based on spatially correlated random area effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(1), pages 113-141, February.
    Full references (including those not matched with items on IDEAS)

    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. Alina Jędrzejczak & Jan Kubacki, 2019. "Estimation Of Income Characteristics For Regions In Poland Using Spatio-Temporal Small Area Models," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 113-134, December.
    2. Jan Pablo Burgard & Domingo Morales & Anna-Lena Wölwer, 2022. "Small area estimation of socioeconomic indicators for sampled and unsampled domains," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 287-314, June.
    3. Tomasz Ża̧dło, 2015. "On longitudinal moving average model for prediction of subpopulation total," Statistical Papers, Springer, vol. 56(3), pages 749-771, August.
    4. Alina Jędrzejczak & Jan Kubacki, 2016. "Small Area Estimation of Income Under Spatial Sar Model," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(3), pages 365-390, September.
    5. Szymkowiak Marcin & Młodak Andrzej & Wawrowski Łukasz, 2017. "Mapping Poverty at the Level of Subregions in Poland Using Indirect Estimation," Statistics in Transition New Series, Statistics Poland, vol. 18(4), pages 609-635, December.
    6. Shonosuke Sugasawa & Tatsuya Kubokawa & J. N. K. Rao, 2018. "Small area estimation via unmatched sampling and linking models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 407-427, June.
    7. Marcin Szymkowiak & Andrzej Młodak & Łukasz Wawrowski, 2017. "Mapping Poverty At The Level Of Subregions In Poland Using Indirect Estimation," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 609-635, December.
    8. Andrzej Młodak, 2021. "k-Means, Ward and Probabilistic Distance-Based Clustering Methods with Contiguity Constraint," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 313-352, July.
    9. Kordos Jan, 2016. "Development of Small Area Estimation in Official Statistics," Statistics in Transition New Series, Statistics Poland, vol. 17(1), pages 105-132, March.
    10. Jan Kordos, 2016. "Development Of Smallarea Estimation In Official Statistics," Statistics in Transition New Series, Polish Statistical Association, vol. 17(1), pages 105-132, March.
    11. Kubacki Jan & Jędrzejczak Alina, 2016. "Small Area Estimation of Income under Spatial Sar Model," Statistics in Transition New Series, Statistics Poland, vol. 17(3), pages 365-390, September.
    12. repec:csb:stintr:v:17:y:2016:i:1:p:105-132 is not listed on IDEAS
    13. Jan Kubacki & Alina Jędrzejczak, 2016. "Small Area Estimation Of Income Under Spatial Sar Model," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 365-390, September.
    14. Guohuan Su & Adam Mertel & Sébastien Brosse & Justin M. Calabrese, 2023. "Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    15. Kuschnig, Nikolas, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Paper Series 318, WU Vienna University of Economics and Business.
    16. María Dolores Esteban & María José Lombardía & Esther López-Vizcaíno & Domingo Morales & Agustín Pérez, 2020. "Small area estimation of proportions under area-level compositional mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 793-818, September.
    17. Yogi Vidyattama & Robert Tanton & Nicholas Biddle, 2015. "Estimating small-area Indigenous cultural participation from synthetic survey data," Environment and Planning A, , vol. 47(5), pages 1211-1228, May.
    18. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    19. Dian Handayani & Henk Folmer & Anang Kurnia & Khairil Anwar Notodiputro, 2018. "The spatial empirical Bayes predictor of the small area mean for a lognormal variable of interest and spatially correlated random effects," Empirical Economics, Springer, vol. 55(1), pages 147-167, August.
    20. Marcos-Martinez, Raymundo & Measham, Thomas G. & Fleming-Muñoz, David A., 2019. "Economic impacts of early unconventional gas mining: Lessons from the coal seam gas industry in New South Wales, Australia," Energy Policy, Elsevier, vol. 125(C), pages 338-346.
    21. Meilan An & Jeffrey Vitale & Kwideok Han & John N. Ng’ombe & Inbae Ji, 2021. "Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea," IJERPH, MDPI, vol. 18(8), pages 1-13, April.

    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:vrs:stintr:v:20:y:2019:i:4:p:113-134:n:10. 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: Peter Golla (email available below). General contact details of provider: https://stat.gov.pl/en/ .

    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.