IDEAS home Printed from https://ideas.repec.org/a/ijb/journl/v8y2009i3p201-211.html
   My bibliography  Save this article

Do the Chinese Bourses (Stock Markets) Predict Economic Growth?

Author

Listed:
  • Jeffrey E. Jarrett

    (Faculty of Management Science and Finance, University of Rhode Island, U.S.A.)

  • Xia Pan

    (Lingnan College, Sun Yat-sen University, Guangzhou, China)

  • Shaw Chen

    (Faculty of Management Science and Finance, University of Rhode Island, U.S.A.)

Abstract

We study the relationship between the Chinese macroeconomy and the Chinese stock markets, i.e., the bourses in Shanghai and Shenzhen. With this goal, we utilize multiple Granger causality and Geweke linear dependence and examine likelihood ratio statistics between two sectors of the Chinese economy: the Chinese economic prosperity score (EPS)¡Xand its departure from a "healthy level" (EPS-D)¡Xand composite indexes for Chinese securities markets¡XShanghai composite (SH) and Shenzhen composite (SZ). The data cover nine years. The authors found no evidence that SH and SZ Granger cause economic prosperity. The evidence supports the notions that Chinese stock markets respond greater to changes in EPS-D than to EPS and that the SZ is more sensitive to changes in the economy than the SH.

Suggested Citation

  • Jeffrey E. Jarrett & Xia Pan & Shaw Chen, 2009. "Do the Chinese Bourses (Stock Markets) Predict Economic Growth?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(3), pages 201-211, December.
    • Handle: RePEc:ijb:journl:v:8:y:2009:i:3:p:201-211
    as

    Download full text from publisher

    File URL: https://ijbe.fcu.edu.tw/assets/ijbe/past_issue/No.08-3/pdf/vol_8-3-2.pdf
    Download Restriction: no
    File URL: https://ijbe.fcu.edu.tw/assets/ijbe/past_issue/No.08-3/abstract/02.html
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ng, Lilian & Wu, Fei, 2007. "The trading behavior of institutions and individuals in Chinese equity markets," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2695-2710, September.
    2. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    3. Su, Dongwei & Fleisher, Belton M., 1999. "Why does return volatility differ in Chinese stock markets?," Pacific-Basin Finance Journal, Elsevier, vol. 7(5), pages 557-586, December.
    4. Sylviane GUILLAUMONT JEANNENEY & PING HUA & ZHICHENG LIANG, 2006. "Financial Development, Economic Efficiency, And Productivity Growth: Evidence From China," The Developing Economies, Institute of Developing Economies, vol. 44(1), pages 27-52, March.
    5. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    6. Eun, Cheol S. & Huang, Wei, 2007. "Asset pricing in China's domestic stock markets: Is there a logic?," Pacific-Basin Finance Journal, Elsevier, vol. 15(5), pages 452-480, November.
    7. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    8. Liang, Qi & Teng, Jian-Zhou, 2006. "Financial development and economic growth: Evidence from China," China Economic Review, Elsevier, vol. 17(4), pages 395-411.
    9. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    10. Geweke, John & Meese, Richard & Dent, Warren, 1983. "Comparing alternative tests of causality in temporal systems : Analytic results and experimental evidence," Journal of Econometrics, Elsevier, vol. 21(2), pages 161-194, February.
    11. Barnett,William A. & Geweke,John & Shell,Karl (ed.), 1989. "Economic Complexity: Chaos, Sunspots, Bubbles, and Nonlinearity," Cambridge Books, Cambridge University Press, number 9780521355636, January.
    12. Xia Pan, 2007. "The Linear Dependence And Feedback Spectra Between Stock Market And Economy," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(03), pages 437-447.
    13. Lemmens, Aurélie & Croux, Christophe & Dekimpe, Marnik G., 2008. "Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys," International Journal of Forecasting, Elsevier, vol. 24(3), pages 414-431.
    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. Kiryoung LEE & Chanik JO, 2018. "Forecasting Chinese Business Cycle Using Long-term Interest Rate Comovements," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 118-134, December.
    2. Lee, Kiryoung & Jeon, Yoontae, 2020. "Measuring Chinese consumers’ perceived uncertainty," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 51-70.

    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. Jank, Stephan, 2012. "Mutual fund flows, expected returns, and the real economy," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3060-3070.
    2. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    3. Bee-Hoong Tay & Pei-Tha Gan, 2016. "The Determinants of Investment Rewards: Evidence for Selected Developed and Developing Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1180-1188.
    4. Mohammad Enamul Hoque & Noor Azuddin Yakob, 2017. "Revisiting stock market development and economic growth nexus: The moderating role of foreign capital inflows and exchange rates," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1329975-132, January.
    5. Fredrik N. G. Andersson & Katarzyna Burzynska & Sonja Opper, 2016. "Lending for growth? A Granger causality analysis of China’s finance–growth nexus," Empirical Economics, Springer, vol. 51(3), pages 897-920, November.
    6. Jeffrey E. Jarrett & Tina Sun, 2011. "Association between new york and shanghai markets: evidence from the stock price indices," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 13(1), pages 132-147, July.
    7. Muhammad Ahad & Adeel Ahmad Dar & Muhammad Imran, 2019. "Does Financial Development Promote Industrial Production in Pakistan? Evidence from Combined Cointegration and Causality Approach," Global Business Review, International Management Institute, vol. 20(2), pages 297-312, April.
    8. Pan, Lei & Mishra, Vinod, 2018. "Stock market development and economic growth: Empirical evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 661-673.
    9. Shujie Yao & Dan Luo & Stephen Morgan, 2008. "Shanghai Stock Exchange Composite Index and Bank Stock Prices in China: A Causality Analysis," Discussion Papers 08/25, University of Nottingham, GEP.
    10. Khee Giap Tan & Randong Yuan & Sangiita Wei Cher Yoong, 2017. "Assessing Development Strategies of Jiangsu and Taiwan: A Geweke Causality Analysis," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-28, December.
    11. Ho, Sin-Yu & Njindan Iyke, Bernard, 2017. "Empirical Reassessment of Bank-based Financial Development and Economic Growth in Hong Kong," MPRA Paper 78920, University Library of Munich, Germany.
    12. Vassiki Sanogo & Richard K. Moussa, 2017. "Financial Reforms, Financial Development, and Economic Growth in the Ivory Coast," Economies, MDPI, vol. 5(1), pages 1-23, February.
    13. Kishor K. Guru-Gharana & Matiur Rahman & Anisul M. Islam, 2021. "Japan s Stock Market Performance: Evidence from Toda-Yamamoto and Dolado-Lutkepohl Tests for Multivariate Granger Causality," International Journal of Economics and Financial Issues, Econjournals, vol. 11(3), pages 107-122.
    14. Md Nain & Bandi Kamaiah, 2014. "Financial development and economic growth in India: some evidence from non-linear causality analysis," Economic Change and Restructuring, Springer, vol. 47(4), pages 299-319, November.
    15. Borlea Sorin Nicolae & Mare Codruta & Achim Monica Violeta & Puscas Adriana, 2016. "Direction of Causality Between Financial Development and Economic Growth. Evidence for Developing Countries," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 26(2), pages 1-22, June.
    16. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu & Kyophilavong, Phouphet, 2015. "Frequency domain causality analysis of stock market and economic activity in India," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 224-238.
    17. Croux, Christophe & Reusens, Peter, 2013. "Do stock prices contain predictive power for the future economic activity? A Granger causality analysis in the frequency domain," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 93-103.
    18. Mohammad Joarder & Monir Ahmed & Tahsina Haque & Syed Hasanuzzaman, 2014. "An empirical testing of informational efficiency in Bangladesh capital market," Economic Change and Restructuring, Springer, vol. 47(1), pages 63-87, February.
    19. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    20. Su, Chen & Brookfield, David, 2013. "An evaluation of the impact of stock market reforms on IPO under-pricing in China: The certification role of underwriters," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 20-33.

    More about this item

    Keywords

    Granger causality; Geweke linear dependence; likelihood ratio tests; vector autoregression;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements

    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:ijb:journl:v:8:y:2009:i:3:p:201-211. 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: Szu-Hsien Ho (email available below). General contact details of provider: https://edirc.repec.org/data/cbfcutw.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.