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The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis

Received: 27 December 2017     Published: 28 December 2017
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Abstract

The main purpose of this paper is to investigate the relationship between business cycle volatility and country size and financial markets size within certain countries, using annual data for a sample of some typical countries having advanced financial market and those of China over 2000-2015. Then analyze the significance level of explaining variables and the type of effect. The main result reflects that for OECD countries, the impacts of population and stock market are all highest level significant and most keep stable after authors filter out the fluctuations, but for China population is a stable significant factor, while the influences of stock market depend on the data processing method and even the plus-minus and the significance of the regression coefficient can change due to the filter process and authors will elaborate the inner economic principles it reveals.

Published in International Journal of Economics, Finance and Management Sciences (Volume 5, Issue 6)
DOI 10.11648/j.ijefm.20170506.17
Page(s) 321-326
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Business Cycle Volatility, Country Size, Financial Market Size, Panel Data Analyses

References
[1] Nektarios Aslanidis; Charlotte Christiansen; Neophytos Lambertides; Christos S. Savva. Idiosyncratic Volatility Puzzle: Influence of Macro-Finance Factors [J]. Aarhus University in its series CREATES Research Papers with number 2014-45, 2014.
[2] Emiel F. S. van Bezooijen; Jacob A. Bikker. Discussion Paper Financial Structure and Macroeconomic Volatility a Panel Data Analysis [J]. Discussion Paper Series nr: 17-13, 2017.
[3] Burton G. Malkiel; Eugene. F. Fama. Efficient Capital Markets: A Review of Theory and Empirical Work [J]. The Journal of Finance. Pages 383–417 May 1970.
[4] Furceri. Country size and business cycle volatility [J]. Journal of the Japanese and international economies 21 (2007) 424–434, 2007.
[5] Jan Tinbergen. Statistical Testing of Business Cycle Theories: Part II: Business Cycles in the United States of America, 1919-1932 [M]. Agaton Press, 1968.
[6] Nam T. Vu. Stock market volatility and international business cycle dynamics: Evidence from OECD economies [J]. Journal of International Money and Finance 50 (2015) 1e15, 2015.
[7] Yung-Shun Tsai; Chun-Ping Chang; Shyh-Weir Tzang; The Impact of Stock Prices, Risks, and Business Cycle on Overconfidence [J]. 2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, 2016.
[8] Mark J. Holmes, Nabil Maghrebi. Financial market impact on the real economy: An assessment of asymmetries and volatility linkages between the stock market and unemployment rate [J]. The Journal of Economic Asymmetries 13(2016)1–7, 2016.
[9] Theofanis Papageorgiou; Panayotis G. Michaelides; Efthymios G. Tsionas. Business cycle determinants and fiscal policy: AP anel ARDL Approach for EMU. [J] The Journal of Economic Asymmetries 13(2016)57–68, 2016.
[10] Hodrick, Robert; Prescott, Edward C "Postwar U.S. Business Cycles: An Empirical Investigation". Journal of Money, Credit, and Banking [J]. 29 (1): 1–16. JSTOR 2953682, 1997.
[11] Rose, A. K.. Size really doesn’t matter: In search of a national scale effect. J. Japanese Int. Economies 4, 482–507. [J], 2006.
[12] Hausman, J. A. "Specification Tests in Econometrics" [J]. Econometrica. 46 (6): 1251–1271, 1978.
[13] Davide Furceri; Georgios Karras. Business cycle volatility and country zize; evidence for a sample of OECD countries [J], 2008.
[14] Jonathan McCarthy. Imperfect insurance and differing propensities to consume across households [J]. Journal of Monetary Economics, 1995.
[15] Simon Kuznets. Secular Movements in Production and Prices [M], 1930.
[16] S. Gomes; P. Jacquinot; R. Mestre; J. Sousa. Global policy at the zero lower bound in a large scale DSGE model. [J] Journal of International Money and Finance 134e153, 2015.
[17] Takamitsu Kurita. Markov-switching variance models and structural changes underlying Japanese bond yields: An inquiry into non-linear dynamics [J]. The Journal of Economic Asymmetries 13 (2016)74–80, 2016.
[18] Laurence Ball. Time-consistent policy and persistent changes in inflation [J]. Journal of Monetary Economics 36 (1995) 329-350, 1995.
Cite This Article
  • APA Style

    Shi Haoran, An Gang. (2017). The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis. International Journal of Economics, Finance and Management Sciences, 5(6), 321-326. https://doi.org/10.11648/j.ijefm.20170506.17

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    ACS Style

    Shi Haoran; An Gang. The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis. Int. J. Econ. Finance Manag. Sci. 2017, 5(6), 321-326. doi: 10.11648/j.ijefm.20170506.17

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    AMA Style

    Shi Haoran, An Gang. The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis. Int J Econ Finance Manag Sci. 2017;5(6):321-326. doi: 10.11648/j.ijefm.20170506.17

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  • @article{10.11648/j.ijefm.20170506.17,
      author = {Shi Haoran and An Gang},
      title = {The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis},
      journal = {International Journal of Economics, Finance and Management Sciences},
      volume = {5},
      number = {6},
      pages = {321-326},
      doi = {10.11648/j.ijefm.20170506.17},
      url = {https://doi.org/10.11648/j.ijefm.20170506.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20170506.17},
      abstract = {The main purpose of this paper is to investigate the relationship between business cycle volatility and country size and financial markets size within certain countries, using annual data for a sample of some typical countries having advanced financial market and those of China over 2000-2015. Then analyze the significance level of explaining variables and the type of effect. The main result reflects that for OECD countries, the impacts of population and stock market are all highest level significant and most keep stable after authors filter out the fluctuations, but for China population is a stable significant factor, while the influences of stock market depend on the data processing method and even the plus-minus and the significance of the regression coefficient can change due to the filter process and authors will elaborate the inner economic principles it reveals.},
     year = {2017}
    }
    

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    T1  - The Factors Affecting Business Cycle Volatility Based on Financial Market Size and Country Size Multiple-factor Analysis
    AU  - Shi Haoran
    AU  - An Gang
    Y1  - 2017/12/28
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    DO  - 10.11648/j.ijefm.20170506.17
    T2  - International Journal of Economics, Finance and Management Sciences
    JF  - International Journal of Economics, Finance and Management Sciences
    JO  - International Journal of Economics, Finance and Management Sciences
    SP  - 321
    EP  - 326
    PB  - Science Publishing Group
    SN  - 2326-9561
    UR  - https://doi.org/10.11648/j.ijefm.20170506.17
    AB  - The main purpose of this paper is to investigate the relationship between business cycle volatility and country size and financial markets size within certain countries, using annual data for a sample of some typical countries having advanced financial market and those of China over 2000-2015. Then analyze the significance level of explaining variables and the type of effect. The main result reflects that for OECD countries, the impacts of population and stock market are all highest level significant and most keep stable after authors filter out the fluctuations, but for China population is a stable significant factor, while the influences of stock market depend on the data processing method and even the plus-minus and the significance of the regression coefficient can change due to the filter process and authors will elaborate the inner economic principles it reveals.
    VL  - 5
    IS  - 6
    ER  - 

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Author Information
  • Department of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, China

  • Department of International Economics and Trade, School of Business Administration, Northeastern University, Shenyang, China

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