IDEAS home Printed from https://ideas.repec.org/p/fip/fedpwp/99-7.html
   My bibliography  Save this paper

A Bayesian VAR forecasting model for the Philadelphia Metropolitan Area

Author

Listed:
  • Theodore M. Crone
  • Michael P. McLaughlin

Abstract

Vector-autoregression (VAR) forecast models have been developed for many state economies, including the three states in the Third Federal Reserve District--Pennsylvania, New Jersey, and Delaware. This paper extends that work by developing a Bayesian VAR forecast model for the Philadelphia metropolitan area and the city of Philadelphia.

Suggested Citation

  • Theodore M. Crone & Michael P. McLaughlin, 1999. "A Bayesian VAR forecasting model for the Philadelphia Metropolitan Area," Working Papers 99-7, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:99-7
    as

    Download full text from publisher

    File URL: https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/1999/wp99-7.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ben S. Bernanke, 1990. "On the predictive power of interest rates and interest rate spreads," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 51-68.
    2. Theodore M. Crone & Sherry Delaney & Leonard O. Mills, 1992. "Vector-autoregression forecast models for the Third District states," Working Papers 92-19, Federal Reserve Bank of Philadelphia.
    3. Robert P. Inman, 1992. "Can Philadelphia escape its fiscal crisis with another tax increase?," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 5-20.
    4. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    5. Theodore M. Crone, 1997. "Where have all the factory jobs gone - and why?," Business Review, Federal Reserve Bank of Philadelphia, issue May, pages 3-18.
    6. Robert B. Litterman, 1984. "Above-average national growth in 1985 and 1986," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    7. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    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. Munehisa Kasuya & Tomoki Tanemura, 2000. "Small Scale Bayesian VAR Modeling of the Japanese Macro Economy Using the Posterior Information Criterion and Monte Carlo Experiments," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.

    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. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 763-782, June.
    2. Pami Dua & Nishita Raje & Satyananda Sahoo, 2004. "Interest Rate Modeling and Forecasting in India," Occasional papers 3, Centre for Development Economics, Delhi School of Economics.
    3. Francisco F. R. Ramos, 1996. "Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance," Econometrics 9601003, University Library of Munich, Germany.
    4. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, University Library of Munich, Germany.
    5. Ford, Stephen A., 1986. "A Beginner'S Guide To Vector Autoregression," Staff Papers 13527, University of Minnesota, Department of Applied Economics.
    6. Pami Dua & Anirvan Banerji & Stephen M. Miller, 2006. "Performance evaluation of the New Connecticut Leading Employment Index using lead profiles and BVAR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 415-437.
    7. David E. Runkle, 1989. "The U.S. economy in 1990 and 1991: continued expansion likely," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 13(Fall), pages 19-26.
    8. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    9. Peter C.B. Phillips, 1992. "Bayes Methods for Trending Multiple Time Series with an Empirical Application to the US Economy," Cowles Foundation Discussion Papers 1025, Cowles Foundation for Research in Economics, Yale University.
    10. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
    11. Pami Dua & Stephen Miller, 1995. "Forecasting and Analyzing Economic Activity with Coincident and Leading Indexes: The Case of Connecticut," Working papers 1995-05, University of Connecticut, Department of Economics.
    12. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    13. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    14. 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.
    15. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working Papers 200912, University of Pretoria, Department of Economics.
    16. David E. Runkle, 1988. "Why no crunch from the crash?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 12(Win), pages 2-7.
    17. Don H. Kim, 2008. "Challenges in macro-finance modeling," Finance and Economics Discussion Series 2008-06, Board of Governors of the Federal Reserve System (U.S.).
    18. Janine Aron & John Muellbauer, 2002. "Interest Rate Effects on Output: Evidence from a GDP Forecasting Model for South Africa," IMF Staff Papers, Palgrave Macmillan, vol. 49(Special i), pages 185-213.
    19. Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, pages 3-11.
    20. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.

    More about this item

    Keywords

    Forecasting; Philadelphia (Pa.);

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fedpwp:99-7. 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: Beth Paul (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.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.