IDEAS home Printed from https://ideas.repec.org/p/ags/ucbecw/198659.html
   My bibliography  Save this paper

Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model

Author

Listed:
  • Tobias, Justin
  • Zellner, Arnold

Abstract

In this article we extend previous BMOM results by showing how information about a variance parameter and its relation to regression coefficients produces a rich class of postdata densities for regression parameters. Prediction and model selection techniques are also described. We also discuss the well-documented link between cross-entropy and the average log odds and then use this criterion in an experiment to compare results obtained from BMOM and Bayes approaches using data generated from known models.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Tobias, Justin & Zellner, Arnold, 1998. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," CUDARE Working Papers 198659, University of California, Berkeley, Department of Agricultural and Resource Economics.
    • Handle: RePEc:ags:ucbecw:198659
    DOI: 10.22004/ag.econ.198659
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/198659/files/agecon-cal-833.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.198659?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Palm, F. & Zellner, A., 1991. "To combine or not to combine? issues of combining forecasts," LIDAM Discussion Papers CORE 1991022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    3. Diebold, Francis X. & Lamb, Russell L., 1997. "Why are estimates of agricultural supply response so variable?," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 357-373.
    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. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    2. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(01), pages 1-14, April.
    3. LaFrance, J. T. & Beatty, T. K. M. & Pope, R. D. & Agnew, G. K., 2002. "Information theoretic measures of the income distribution in food demand," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 235-257, March.
    4. Wu, Ximing, 2003. "Calculation of maximum entropy densities with application to income distribution," Journal of Econometrics, Elsevier, vol. 115(2), pages 347-354, August.
    5. Carter Richard A. L. & Zellner Arnold, 2004. "The ARAR Error Model for Univariate Time Series and Distributed Lag," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(1), pages 1-44, March.
    6. LaFrance, Jeffrey T., 1999. "An Econometric Model of the Demand for Food and Nutrition," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2z5516c2, Department of Agricultural & Resource Economics, UC Berkeley.
    7. Kleibergen, Frank & Zivot, Eric, 2003. "Bayesian and classical approaches to instrumental variable regression," Journal of Econometrics, Elsevier, vol. 114(1), pages 29-72, May.
    8. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
    9. Scott Atkinson & Jeffrey Dorfman, 2005. "Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings," Journal of Productivity Analysis, Springer, vol. 23(3), pages 359-382, July.
    10. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
    11. Traoré, Fousseini, 2013. "Estimating the supply elasticity of cotton in Mali with the Nerlove Model: A bayesian method of moments approach," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 94(3).
    12. Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
    13. Zellner, Arnold, 2006. "S. James Press And Bayesian Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 10(5), pages 667-684, November.
    14. Rodney W. Strachan & Herman K. van Dijk, 2014. "Divergent Priors and Well Behaved Bayes Factors," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(1), pages 1-31, March.
    15. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(4), pages 947-987, August.
    16. Gao, Chuanming & Lahiri, Kajal, 2002. "A note on the double k-class estimator in simultaneous equations," Journal of Econometrics, Elsevier, vol. 108(1), pages 101-111, May.
    17. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    18. Zellner, Arnold, 2007. "Some aspects of the history of Bayesian information processing," Journal of Econometrics, Elsevier, vol. 138(2), pages 388-404, June.
    19. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.
    20. Agee, Mark D. & Atkinson, Scott E. & Crocker, Thomas D. & Williams, Jonathan W., 2014. "Non-separable pollution control: Implications for a CO2 emissions cap and trade system," Resource and Energy Economics, Elsevier, vol. 36(1), pages 64-82.
    21. R. A. L. Carter & A. Zellner, 2002. "The ARAR Error Model for Univariate Time Series and Distributed Lag Models," University of Western Ontario, Departmental Research Report Series 20025, University of Western Ontario, Department of Economics.
    22. Golan Amos, 2003. "An Information Theoretic Approach for Estimating Nonlinear Dynamic Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-26, December.
    23. Zellner, Arnold, 2010. "Bayesian shrinkage estimates and forecasts of individual and total or aggregate outcomes," Economic Modelling, Elsevier, vol. 27(6), pages 1392-1397, November.

    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. Arnold Zellner, 2003. "Some Recent Developments in Econometric Inference," Econometric Reviews, Taylor & Francis Journals, vol. 22(2), pages 203-215.
    2. Zellner, Arnold & Tobias, Justin & Ryu, Hang, 1998. "Bayesian Method of Moments (BMOM) Analysis of Parametric and Semiparametric Regression Models," CUDARE Working Papers 198660, University of California, Berkeley, Department of Agricultural and Resource Economics.
    3. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    4. Marsh, Thomas L. & Mittelhammer, Ronald C., 2001. "Adaptive Truncated Estimaton Applied To Maximum Entropy," 2001 Annual Meeting, July 8-11, 2001, Logan, Utah 36169, Western Agricultural Economics Association.
    5. Müller, Marc & Sanfo, Safietou & Laube, Wolfram, 2013. "Impact of Changing Seasonal Rainfall Patterns on Rainy-Season Crop Production in the Guinea Savannah of West Africa," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151208, Agricultural and Applied Economics Association.
    6. Severini, Simone & Valle, Stefano, 2008. "The Abrogation Of Set Aside And The Increase Of Cereal Prices: Can They Revert The Decline Of Cereal Production Generated By Decoupling?," 109th Seminar, November 20-21, 2008, Viterbo, Italy 44782, European Association of Agricultural Economists.
    7. Axel Tonini & Roel Jongeneel, 2009. "The distribution of dairy farm size in Poland: a markov approach based on information theory," Applied Economics, Taylor & Francis Journals, vol. 41(1), pages 55-69.
    8. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    9. Zografos, K. & Nadarajah, S., 2005. "Expressions for Rényi and Shannon entropies for multivariate distributions," Statistics & Probability Letters, Elsevier, vol. 71(1), pages 71-84, January.
    10. Amina Al Naabi & Shekar Bose, 2020. "Do Regulatory Measures Necessarily Affect Oman’s Seafood Export-Supply?," SAGE Open, , vol. 10(3), pages 21582440209, August.
    11. Greg Seymour & Maria S. Floro, 2016. "Identity, Household Work, and Subjective Well-Being among Rural Women in Bangladesh," Working Papers id:11520, eSocialSciences.
    12. Frank Fuller & John Beghin & Scott Rozelle, 2007. "Consumption of dairy products in urban China: results from Beijing, Shangai and Guangzhou," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(4), pages 459-474, December.
    13. Barkhordar, Zahra A., 2019. "Evaluating the economy-wide effects of energy efficient lighting in the household sector of Iran," Energy Policy, Elsevier, vol. 127(C), pages 125-133.
    14. 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.
    15. Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
    16. 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.
    17. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    18. Alberto Díaz Dapena & Esteban Fernández Vázquez & Fernando Rubiera Morollón & Ana Viñuela, 2021. "Mapping poverty at the local level in Europe: A consistent spatial disaggregation of the AROPE indicator for France, Spain, Portugal and the United Kingdom," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 63-81, February.
    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. Lecca, Patrizio & Swales, Kim & Turner, Karen, 2011. "Rebound Effects from Increased Efficiency in the Use of Energy by UK Households," SIRE Discussion Papers 2011-34, Scottish Institute for Research in Economics (SIRE).
    21. Laureti, Tiziana & Secondi, Luca & Biggeri, Luigi, 2014. "Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach," Economics of Education Review, Elsevier, vol. 42(C), pages 147-164.

    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:ags:ucbecw:198659. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dabrkus.html .

    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.