IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v27y2008i4-6p596-609.html
   My bibliography  Save this article

A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation

Author

Listed:
  • R. Bernardini Papalia

Abstract

This article introduces a maximum entropy-based estimation methodology that can be used both to represent the uncertainty of a partial-incomplete economic data generation process and to consider the direct influence of learning from repeated samples. Then, a composite cross-entropy estimator, incorporating information from a subpopulation based on a small sample and from a population with a larger sample size, is derived. The proposed estimator is employed to estimate the local area expenditure shares of a sub population of Italian households using a system of censored demand equations.

Suggested Citation

  • R. Bernardini Papalia, 2008. "A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 596-609.
    • Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:596-609
    DOI: 10.1080/07474930801960469
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960469
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474930801960469?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. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    2. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, September.
    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. Rosa Bernardini Papalia & Enrico Ciavolino, 2015. "Developing a composite index by using spatial latent modelling based on information theoretic estimation," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 989-997, May.
    2. Rosa Bernadini Papalia & Silvia Bertarelli, 2013. "Identification and Estimation of Club Convergence Models with Spatial Dependence," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 37(6), pages 2094-2115, November.
    3. Esteban Fernández-Vázquez & Blanca Moreno, 2017. "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, vol. 19(4), pages 349-370, October.
    4. Esteban Fernández-Vázquez, 2014. "Estimating the effect of technological factors from samples affected by collinearity: a data-weighted entropy approach," Empirical Economics, Springer, vol. 47(2), pages 717-731, September.
    5. Rosa Bernardini Papalia & Silvia Bertarelli, 2013. "Nonlinearities in economic growth and club convergence," Empirical Economics, Springer, vol. 44(3), pages 1171-1202, June.
    6. Rosa Bernardini Papalia & Silvia Bertarelli & Carlo Filippucci, 2011. "Human capital, technological spillovers and development across OECD countries," Working Papers 15, AlmaLaurea Inter-University Consortium.
    7. Rosa Bernardini Papalia, 2011. "An information theoretic approach to ecological inference in presence of spatial heterogeneity and dependence," ERSA conference papers ersa11p317, European Regional Science Association.

    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. Ole Boysen, 2019. "When does specification or aggregation across consumers matter for economic impact analysis models? An investigation into demand systems," Empirical Economics, Springer, vol. 56(1), pages 137-172, January.
    2. Noland, Marcus & Robinson, Sherman & Wang, Tao, 2000. "Modeling Korean Unification," Journal of Comparative Economics, Elsevier, vol. 28(2), pages 400-421, June.
    3. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    4. J. K. Pappalardo, 2022. "Economics of Consumer Protection: Contributions and Challenges in Estimating Consumer Injury and Evaluating Consumer Protection Policy," Journal of Consumer Policy, Springer, vol. 45(2), pages 201-238, June.
    5. Rajeev K. Goel & Shoji Haruna, 2021. "Unmasking the demand for masks: Analytics of mandating coronavirus masks," Metroeconomica, Wiley Blackwell, vol. 72(3), pages 580-591, July.
    6. Lee, Jonq-Ying & Brown, Mark G. & Schwartz, Brooke, 1986. "The Demand For National Brand And Private Label Frozen Concentrated Orange Juice: A Switching Regression Analysis," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(1), pages 1-7, July.
    7. Richard Chisik & Nazanin Behzadan & Harun Onder & Apurva Sanghi, 2016. "Aid, Remittances, the Dutch Disease, Refugees, and Kenya," Working Papers 062, Toronto Metropolitan University, Department of Economics.
    8. Hirte, Georg & Tscharaktschiew, Stefan, 2018. "The impact of anti-congestion policies and the role of labor-supply margins," CEPIE Working Papers 04/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    9. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    10. Brito Paulo & Marini Giancarlo & Piergallini Alessandro, 2016. "House prices and monetary policy," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 251-277, June.
    11. Ugo Colombino & Nizamul Islam, 2021. "Combining microsimulation and optimization to identify optimal universalistic tax-transfer rule," LISER Working Paper Series 2021-06, Luxembourg Institute of Socio-Economic Research (LISER).
    12. Smith, Lisa C. & Chavas, Jean-Paul, 1999. "Supply response of West African agricultural households," FCND discussion papers 69, International Food Policy Research Institute (IFPRI).
    13. Gregory J. Colman & Dahlia K. Remler, 2008. "Vertical equity consequences of very high cigarette tax increases: If the poor are the ones smoking, how could cigarette tax increases be progressive?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(2), pages 376-400.
    14. James L Swofford, 2000. "Microeconomic foundations of an optimal currency area," Review of Financial Economics, John Wiley & Sons, vol. 9(2), pages 121-128, December.
    15. Bernard M. S. van Praag & Nico L. van der Sar, 1988. "Household Cost Functions and Equivalence Scales," Journal of Human Resources, University of Wisconsin Press, vol. 23(2), pages 193-210.
    16. Bates, John J., 2024. "Pivoting from a known base when predicting choices using logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    17. Hyeok Lee & Yong Kyun Kim, 2018. "The effects of external shocks on the Korean economy: CGE model-based analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-14, December.
    18. Junichi Minagawa & Thorsten Upmann, 2019. "Price Effects on Compound Commodities," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(2), pages 630-646, April.
    19. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    20. Albert van der Horst & Arjan Lejour & Bas Straathof, 2006. "Innovation policy; Europe or the member states?," CPB Document 132.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    21. Richards, Timothy J. & Patterson, Paul M., 2000. "New Varieties And The Returns To Commodity Promotion: The Case Of Fuji Apples," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 29(1), pages 1-14, 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:taf:emetrv:v:27:y:2008:i:4-6:p:596-609. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.