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Does Growth Cause Financial Deregulation in China? An Instrumental Variables Approach

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  • He, Qichun

Abstract

Following Miguel et al. (2004), we use temperature and hours of sunshine variations as instrumental variables for economic growth in 27 Chinese provinces during 1981--98. Our 2SLS (Two-stage least squares) regression finds that growth has no significant effect on financial deregulation after controlling for predetermined home-bias political variable, population size, and time and province effects. Moreover, the home-bias political variable has a significant effect on financial deregulation, which shows that political and cultural factors are important driving forces in determining the path and logic of Chinese financial deregulation. The results hold up when we use GMM (Generalized method of moments) to deal with heteroskedasticity. The results are also robust in LIML (Limited information maximum likelihood) estimation that deals with weak instruments.

Suggested Citation

  • He, Qichun, 2011. "Does Growth Cause Financial Deregulation in China? An Instrumental Variables Approach," MPRA Paper 34449, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:34449
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    References listed on IDEAS

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    8. Michael P. Murray, 2006. "Avoiding Invalid Instruments and Coping with Weak Instruments," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 111-132, Fall.
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    Cited by:

    1. Gang Chen & Brett Inder & Paula Lorgelly & Bruce Hollingsworth, 2013. "The Cyclical Behaviour Of Public And Private Health Expenditure In China," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1071-1092, September.

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    More about this item

    Keywords

    Financial Deregulation; Growth; Causality;
    All these keywords.

    JEL classification:

    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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