IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/113437.html
   My bibliography  Save this paper

AS-AD Curves: An Analysis Using the BQ and OLS Methods

Author

Listed:
  • Wan, Cihang
  • Ji, Yangyang
  • Luo, Youliang
  • Zhang, Tianyu

Abstract

The demand and supply shocks in the U.S. and China are analyzed using the Blanchard and Quah (BQ) and ordinary least squares (OLS) methods. For the U.S. data, the aggregate supply (AS) curve has a positive slope, whereas the aggregate demand (AD) curve has a negative slope. However, the two methods yield inverse results when data from China are analyzed. In the BQ method, the AS curve slope is negative and AD curve slope is positive, indicating a “slope puzzle.” In the OLS method, no “slope puzzle” is present.

Suggested Citation

  • Wan, Cihang & Ji, Yangyang & Luo, Youliang & Zhang, Tianyu, 2022. "AS-AD Curves: An Analysis Using the BQ and OLS Methods," MPRA Paper 113437, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:113437
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/113437/1/MPRA_paper_113437.pdf
    File Function: original version
    Download Restriction: no

    File URL: https://mpra.ub.uni-muenchen.de/114203/1/MPRA_paper_113437.pdf
    File Function: revised version
    Download Restriction: no
    ---><---

    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. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    3. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    4. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    5. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    6. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    7. Cover, James Peery & Enders, Walter & Hueng, C. James, 2006. "Using the Aggregate Demand-Aggregate Supply Model to Identify Structural Demand-Side and Supply-Side Shocks: Results Using a Bivariate VAR," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(3), pages 777-790, April.
    8. Cho, Dongchul, 2012. "Aggregate demand gap based on a simple structural VAR model," Economics Letters, Elsevier, vol. 114(2), pages 228-234.
    9. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    10. Sen Zhang & Yangyang Ji & Tianye Lin, 2019. "The relative price of investment goods, the price level, and the "slope puzzle"," CEMA Working Papers 609, China Economics and Management Academy, Central University of Finance and Economics.
    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. Sen Zhang & Yangyang Ji & Tianye Lin, 2019. "The relative price of investment goods, the price level, and the "slope puzzle"," CEMA Working Papers 609, China Economics and Management Academy, Central University of Finance and Economics.
    2. Netsunajev, Aleksei, 2013. "Reaction to technology shocks in Markov-switching structural VARs: Identification via heteroskedasticity," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 51-62.
    3. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    4. Gubler, Matthias & Hertweck, Matthias S., 2013. "Commodity price shocks and the business cycle: Structural evidence for the U.S," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 324-352.
    5. Steffen Elstner & Lars P. Feld & Christoph M. Schmidt, 2018. "The German Productivity Paradox - Facts and Explanations," CESifo Working Paper Series 7231, CESifo.
    6. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    7. Tomislav Globan & Vladimir Arčabić & Petar Sorić, 2016. "Inflation in New EU Member States: A Domestically or Externally Driven Phenomenon?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(1), pages 154-168, January.
    8. Bachmann, Rüdiger & Zorn, Peter, 2020. "What drives aggregate investment? Evidence from German survey data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    9. Paul Beaudry & Fabrice Collard & Patrick Feve & Alain Guay & Franck Portier, 2022. "Dynamic Identification in VARs," Working Papers 22-08, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    10. Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 455-467.
    11. Rujin, Svetlana, 2019. "What are the effects of technology shocks on international labor markets?," Ruhr Economic Papers 806, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    12. Fabio Canova & David Lopez-Salido & Claudio Michelacci, 2010. "The effects of technology shocks on hours and output: a robustness analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 755-773.
    13. Fabio Canova & David Lopez-Salido & Claudio Michelacci, 2009. "The ins and outs of unemployment: An analysis conditional on technology shocks," Economics Working Papers 1213, Department of Economics and Business, Universitat Pompeu Fabra, revised Jan 2012.
    14. Furlanetto Francesco & Sveen Tommy & Weinke Lutz, 2020. "Technology and the two margins of labor adjustment: a New Keynesian perspective," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-18, January.
    15. Holly, S. & Petrella, I., 2008. "Factor demand linkages and the business cycle: Interpreting aggregate fluctuations as sectoral fluctuations," Cambridge Working Papers in Economics 0827, Faculty of Economics, University of Cambridge.
    16. Shingo Watanabe, 2012. "The Role Of Technology And Nontechnology Shocks In Business Cycles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1287-1321, November.
    17. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    18. Ferraresi Tommaso & Roventini Andrea & Semmler Willi, 2019. "Macroeconomic Regimes, Technological Shocks and Employment Dynamics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 599-625, August.
    19. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    20. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.

    More about this item

    Keywords

    slope puzzle; BQ method; OLS;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:pra:mprapa:113437. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.