IDEAS home Printed from https://ideas.repec.org/a/fip/fedmqr/y1984ifallnv.8no.4.html
   My bibliography  Save this article

Above-average national growth in 1985 and 1986

Author

Listed:
  • Robert B. Litterman

Abstract

No abstract is available for this item.

Suggested Citation

  • Robert B. Litterman, 1984. "Above-average national growth in 1985 and 1986," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
  • Handle: RePEc:fip:fedmqr:y:1984:i:fall:n:v.8no.4
    as

    Download full text from publisher

    File URL: http://www.minneapolisfed.org/research/QR/QR841.pdf
    Download Restriction: no

    File URL: http://www.minneapolisfed.org/research/common/pub_detail.cfm?pb_autonum_id=174
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas B. Fomby & William C. Gruben & James G. Hoehn, 1984. "Some time series methods of forecasting the Texas economy," Working Papers 8402, Federal Reserve Bank of Dallas.
    2. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    3. Robert B. Litterman & Richard M. Todd, 1982. "As the nation's economy goes, so goes Minnesota's," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 6(Spr / Sum).
    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. Hossain Amirizadeh & Richard M. Todd, 1984. "More growth ahead for Ninth District states," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    2. Terrence Kinal & Jonathan Ratner, 1986. "A VAR Forecasting Model of a Regional Economy: Its Construction and Comparative Accuracy," International Regional Science Review, , vol. 10(2), pages 113-126, August.
    3. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    4. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    5. Jean-Pierre Allegret & Alain Sand-Zantman, 2009. "Does a Monetary Union protect again shocks? An assessment of Latin American integration," Post-Print halshs-00371069, HAL.
    6. Gediminas Adomavicius & Jesse Bockstedt & Alok Gupta, 2012. "Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression," Information Systems Research, INFORMS, vol. 23(2), pages 397-417, June.
    7. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    8. Jarociński, Marek & Marcet, Albert, 2019. "Priors about observables in vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(2), pages 238-255.
    9. Espinosa Acuña, Óscar A. & Vaca González, Paola A. & Avila Forero, Raúl A., 2013. "Elasticidades de demanda por electricidad e impactos macroecon_omicos del precio de la energía eléctrica en Colombia || Elasticity of Electricity Demand and Macroeconomics Impacts of Electricity Price," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 16(1), pages 216-249, December.
    10. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
    11. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    12. Jean-Pierre Allegret & Alain Sand-Zantman, 2008. "Monetary Integration Issues in Latin America: A Multivariate Assessment," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 55(3), pages 279-308, September.
    13. Ford, Stephen A., 1986. "An Application Of Bayesian Vector Autoregression To The U.S. Turkey Market," Staff Papers 13982, University of Minnesota, Department of Applied Economics.
    14. Moratis, George, 2021. "Quantifying the spillover effect in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 38(C).
    15. Ho, Paul, 2023. "Global robust Bayesian analysis in large models," Journal of Econometrics, Elsevier, vol. 235(2), pages 608-642.
    16. Tadashi Yamada, 1985. "The Crime Rate and the Condition of the Labor Market: A Vector Autoregressive Model," NBER Working Papers 1782, National Bureau of Economic Research, Inc.
    17. Preston J. Miller & Thomas M. Supel & Thomas H. Turner, 1980. "Estimating the effects of the oil-price shock," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 4(Win).
    18. Marek Jarociński & Peter Karadi, 2020. "Deconstructing Monetary Policy Surprises—The Role of Information Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(2), pages 1-43, April.
    19. Korobilis, Dimitris, 2013. "Hierarchical shrinkage priors for dynamic regressions with many predictors," International Journal of Forecasting, Elsevier, vol. 29(1), pages 43-59.
    20. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.

    More about this item

    Statistics

    Access and download statistics

    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:fip:fedmqr:y:1984:i:fall:n:v.8no.4. 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: Kate Hansel (email available below). General contact details of provider: https://edirc.repec.org/data/cfrbmus.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.