IDEAS home Printed from https://ideas.repec.org/a/arp/ijefrr/2016p155-160.html
   My bibliography  Save this article

Can the Disparity between GDP and GDP Forecast Cause Economic Instability? The Recent Japanese Case

Author

Listed:
  • Yutaka Kurihara

    (Professor, Department of Economics, Aichi University, Japan)

Abstract

This paper investigates the link between forecast disparity and macroeconomic instability that results from the data revision of GDP and inflation in Japan. The recent Japanese case, which reflects the unconventional monetary policy conducted since 2013, is also examined. The empirical results show that such disparities do not cause economic instability; however, they have have done so after the unconventional and drastic monetary policy was conducted. On the other hand, exchange rates impacted economic stability for the total period. For the first part of the period under study (from 2000 to 2012), currency appreciation caused instability; however, for the more recent period, depreciation has caused such instability. Recently, macroeconomic instability has been linked with exchange rate movements.

Suggested Citation

  • Yutaka Kurihara, 2016. "Can the Disparity between GDP and GDP Forecast Cause Economic Instability? The Recent Japanese Case," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 2(8), pages 155-160, 08-2016.
    • Handle: RePEc:arp:ijefrr:2016:p:155-160
    as

    Download full text from publisher

    File URL: http://www.arpgweb.com/pdf-files/ijefr2(8)155-160.pdf
    Download Restriction: no
    File URL: http://www.arpgweb.com/?ic=journal&journal=5&month=08-2016&issue=8&volume=2
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jacopo Cimadomo, 2012. "Fiscal Policy in Real Time," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(2), pages 440-465, June.
    2. Jacopo Cimadomo, 2016. "Real-Time Data And Fiscal Policy Analysis: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 302-326, April.
    3. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    4. Domenico Giannone & Jérôme Henry & Magdalena Lalik & Michele Modugno, 2012. "An Area-Wide Real-Time Database for the Euro Area," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1000-1013, November.
    5. Berardi, Michele & Duffy, John, 2015. "Real-Time, Adaptive Learning Via Parameterized Expectations," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 245-269, March.
    6. Bernoth, Kerstin & Hughes Hallett, Andrew & Lewis, John, 2015. "The Cyclicality Of Automatic And Discretionary Fiscal Policy: What Can Real-Time Data Tell Us?," Macroeconomic Dynamics, Cambridge University Press, vol. 19(1), pages 221-243, January.
    7. Ulf Von Kalckreuth & Guntram B. Wolff, 2011. "Identifying Discretionary Fiscal Policy Reactions with Real-Time Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1271-1285, September.
    8. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    9. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    10. Michael Pedersen, 2013. "Extracting GDP signals from the monthly indicator of economic activity: Evidence from Chilean real-time data," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(1), pages 1-16.
    11. Ansgar Belke & Jens Klose, 2011. "Does the ECB Rely on a Taylor Rule During the Financial Crisis? Comparing Ex-post and Real Time Data with Real Time Forecasts," Economic Analysis and Policy, Elsevier, vol. 41(2), pages 147-171, September.
    12. John Lewis, 2013. "Fiscal policy in Central and Eastern Europe with real time data: cyclicality, inertia and the role of EU accession," Applied Economics, Taylor & Francis Journals, vol. 45(23), pages 3347-3359, August.
    13. Joelle Liebermann, 2014. "Real-Time Nowcasting of GDP: A Factor Model vs. Professional Forecasters," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(6), pages 783-811, December.
    14. Capek Jan, 2015. "Estimating DSGE model parameters in a small open economy: Do real-time data matter?," Review of Economic Perspectives, Sciendo, vol. 15(1), pages 89-114, March.
    15. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    16. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
    17. Rafael Cusinato & André Minella & Sabino Silva Pôrto Júnior, 2013. "Output gap in Brazil: a real-time data analysis," Empirical Economics, Springer, vol. 44(3), pages 1113-1127, June.
    18. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
    19. Stefano Neri & Tiziano Ropele, 2012. "Imperfect Information, Real‐Time Data and Monetary Policy in the Euro Area," Economic Journal, Royal Economic Society, vol. 122(561), pages 651-674, June.
    20. Baetje, Fabian & Friedrici, Karola, 2016. "Does cross-sectional forecast dispersion proxy for macroeconomic uncertainty? New empirical evidence," Economics Letters, Elsevier, vol. 143(C), pages 38-43.
    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. Yutaka Kurihara, 2017. "Recent monetary policy effects on Japanese macroeconomy," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 5(5), pages 12-17, October.
    2. Baetje, Fabian & Friedrici, Karola, 2016. "Does cross-sectional forecast dispersion proxy for macroeconomic uncertainty? New empirical evidence," Economics Letters, Elsevier, vol. 143(C), pages 38-43.
    3. Aldama, Pierre & Creel, Jérôme, 2022. "Real-time fiscal policy responses in the OECD from 1997 to 2018: Procyclical but sustainable?," European Journal of Political Economy, Elsevier, vol. 73(C).
    4. Emilia Tomczyk, 2013. "End of sample vs. real time data: perspectives for analysis of expectations," Working Papers 68, Department of Applied Econometrics, Warsaw School of Economics.
    5. Martin Slanicay & Jan Čapek & Miroslav Hloušek, 2016. "Some Notes On Problematic Issues In Dsge Models," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 61(210), pages 79-100, July - Se.
    6. Pierre Aldama & Jérôme Creel, 2020. "Asymmetric Macroeconomic Stabilization And Fiscal Consolidation In The Oecd And The Euro Area," SciencePo Working papers Main hal-03403071, HAL.
    7. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
    8. Jacopo Cimadomo, 2016. "Real-Time Data And Fiscal Policy Analysis: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 302-326, April.
    9. Jan Capek, 2014. "Historical Analysis of Monetary Policy Reaction Functions: Do Real-Time Data Matter?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(6), pages 457-475, December.
    10. repec:wrk:wrkemf:35 is not listed on IDEAS
    11. repec:hal:spmain:info:hdl:2441/5a3rl1um0d9rdbe3itnk6f8m89 is not listed on IDEAS
    12. repec:spo:wpmain:info:hdl:2441/5a3rl1um0d9rdbe3itnk6f8m89 is not listed on IDEAS
    13. Asimakopoulos, Stylianos & Lalik, Magdalena & Paredes, Joan & Salvado García, José, 2023. "GDP revisions are not cool: the impact of statistical agencies’ trade-off," Working Paper Series 2857, European Central Bank.
    14. Michael P. Clements, 2014. "Anticipating Early Data Revisions to US GDP and the Effects of Releases on Equity Markets," ICMA Centre Discussion Papers in Finance icma-dp2014-06, Henley Business School, University of Reading.
    15. Smets, Frank & Warne, Anders & Wouters, Raf, 2013. "Professional forecasters and the real-time forecasting performance of an estimated new keynesian model for the euro area," Working Paper Series 1571, European Central Bank.
    16. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    17. De Jong, Jasper F.M. & Gilbert, Niels D., 2020. "Fiscal discipline in EMU? Testing the effectiveness of the Excessive Deficit Procedure," European Journal of Political Economy, Elsevier, vol. 61(C).
    18. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
    19. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
    20. Heimberger, Philipp, 2023. "The cyclical behaviour of fiscal policy: A meta-analysis," Economic Modelling, Elsevier, vol. 123(C).
    21. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
    22. Pilar Poncela & Eva Senra, 2017. "Measuring uncertainty and assessing its predictive power in the euro area," Empirical Economics, Springer, vol. 53(1), pages 165-182, August.
    23. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.

    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:arp:ijefrr:2016:p:155-160. 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: Managing Editor (email available below). General contact details of provider: http://www.arpgweb.com/?ic=journal&journal=5&info=aims .

    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.