IDEAS home Printed from https://ideas.repec.org/p/fip/fedmem/21.html

Comparisons of alternative identification schemes for the U.S. real GNP- unemployment level correlation: sensitivity analysis

Author

Listed:
  • Masanao Aoki

Abstract

The paper employs three different types of identifying restrictions to calculate the impulse responses for the trivariate series composed of the U.S. unemployment level, real GNP and the money stock. The first two are the zero restrictions, arising from the assumption of the delayed information pattern available in forming a money reaction function. The third assumes a particular simplified structural model. The paper shows that the impulse response patterns are generally insensitive to these alternative specifications. Similar exercises are carried out for the bivariate series composed of the U.S. and the unemployment level.

Suggested Citation

  • Masanao Aoki, 1989. "Comparisons of alternative identification schemes for the U.S. real GNP- unemployment level correlation: sensitivity analysis," Discussion Paper / Institute for Empirical Macroeconomics 21, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmem:21
    DOI: 10.21034/dp.21
    as

    Download full text from publisher

    File URL: https://www.minneapolisfed.org/research/dp/dp21.pdf
    File Function: Full Text
    Download Restriction: no
    File URL: https://libkey.io/10.21034/dp.21?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. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Bernanke, Ben S., 1986. "Alternative explanations of the money-income correlation," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 49-99, January.
    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. Evans, Charles L. & Marshall, David A., 2007. "Economic determinants of the nominal treasury yield curve," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1986-2003, October.
    2. Neto, Waldemiro Alcântara da Silva & Bacchi, Mirian Rumenos Piedade, 2014. "Growth of Brazilian Beef Production: effect of shocks of supply and demand," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(01), January.
    3. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.
    4. Corsi, Fulvio & Longo, Luigi & Cordoni, Francesco, 2025. "SVAR identification with nowcasted macroeconomic data," Journal of Economic Dynamics and Control, Elsevier, vol. 179(C).
    5. Paul Lau, Sau-Him, 2000. "On the validity and identification of long-run restrictions for a cointegrated system," Economic Modelling, Elsevier, vol. 17(4), pages 485-496, December.
    6. Gahn, Santiago José, 2021. "On the adjustment of capacity utilisation to aggregate demand: Revisiting an old Sraffian critique to the Neo-Kaleckian model," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 325-360.
    7. Fernando Ballabriga, 2002. "The development of quantitative empirical analysis in macroeconomics," European Economy - Economic Papers 2008 - 2015 168, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    9. Ben Fung & Rohit Gupta, "undated". "Searching for the Liquidity Effect in Canada," Staff Working Papers 94-12, Bank of Canada.
    10. Dermot Hodson, 2003. "The Exchange Rate as an Adjustment Mechanism - A Structural VAR Approach to the Case of Ireland," The Economic and Social Review, Economic and Social Studies, vol. 34(2), pages 151-172.
    11. Candelon, Bertrand & Luisi, Angelo & Roccazzella, Francesco, 2022. "Fragmentation in the European Monetary Union: Is it really over?," Journal of International Money and Finance, Elsevier, vol. 122(C).
    12. Blangiewicz, Maria & Charemza, Wojciech W., 1999. "East European Economic Reform: Some Simulations on a Structural Vector Autoregressive Model," Journal of Policy Modeling, Elsevier, vol. 21(5), pages 535-557, September.
    13. Tito Belchior Silva Moreira & Benjamin Miranda Tabak & Mario Jorge Mendonça & Adolfo Sachsida, 2016. "An Evaluation of the Non-Neutrality of Money," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-20, March.
    14. John B. Carlson & William T. Gavin & Katherine A. Samolyk, 1990. "The short-run dynamics of long-run inflation policy," Economic Review, Federal Reserve Bank of Cleveland, vol. 26(Q III), pages 26-35.
    15. Gouriéroux, Christian & Monfort, Alain & Renne, Jean-Paul, 2017. "Statistical inference for independent component analysis: Application to structural VAR models," Journal of Econometrics, Elsevier, vol. 196(1), pages 111-126.
    16. Kyungho Jang, 2008. "A Structural Vector Error Correction Model with Short-run and Long-run Restrictions," Korean Economic Review, Korean Economic Association, vol. 24, pages 199-232.
    17. Neaime, Simon & Gaysset, Isabelle & Badra, Nasser, 2018. "The eurozone debt crisis: A structural VAR approach," Research in International Business and Finance, Elsevier, vol. 43(C), pages 22-33.
    18. Etsuro Shioji, 1997. "Spanish monetary policy: A structural VAR analysis," Economics Working Papers 215, Department of Economics and Business, Universitat Pompeu Fabra.
    19. Piyachart Phiromswad, 2014. "Measuring monetary policy with empirically grounded identifying restrictions," Empirical Economics, Springer, vol. 46(2), pages 681-699, March.
    20. Li, Fengyun & Li, Xingmei & Zheng, Haofeng & Yang, Fei & Dang, Ruinan, 2021. "How alternative energy competition shocks natural gas development in China: A novel time series analysis approach," Resources Policy, Elsevier, vol. 74(C).

    More about this item

    Keywords

    ;
    ;

    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:fedmem:21. 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: Jannelle Ruswick The email address of this maintainer does not seem to be valid anymore. Please ask Jannelle Ruswick to update the entry or send us the correct address (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.