• DocumentCode
    2243651
  • Title

    The Relationship between Rural Infrastructure and Economic Growth Based on Partial Least-Squares Regression

  • Author

    Shang, Wei ; Zhang, Yuke

  • Author_Institution
    Sch. of Econ., Hebei Univ., Baoding, China
  • Volume
    2
  • fYear
    2009
  • fDate
    30-31 May 2009
  • Firstpage
    127
  • Lastpage
    130
  • Abstract
    The rural infrastructure plays an increasingly important role in economic growth. This paper extends the partial least-square (PLS) method into rural infrastructure analysis. Because the economic factors which influent rural infrastructure usually are multicollinearity, PLS can avoids this problem. PLS extracts variables one by one from few sample data. Under the control of modeling, it makes fully use of the useful information contained in the raw data. The experiments show that this method is feasible in analysis of the relationship between infrastructure and rural economic than OLS or ANN.
  • Keywords
    economics; least squares approximations; regression analysis; artificial neural network; economic factors; economic growth; multi-collinearity; ordinary least squares; partial least-squares regression; rural infrastructure; Artificial neural networks; Data mining; Economic forecasting; Electronic mail; Investments; Parameter estimation; Production; Productivity; Reactive power; Roads; ANN; Multi-collinearity; PLS; rural Infrastructure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking and Digital Society, 2009. ICNDS '09. International Conference on
  • Conference_Location
    Guiyang, Guizhou
  • Print_ISBN
    978-0-7695-3635-4
  • Type

    conf

  • DOI
    10.1109/ICNDS.2009.112
  • Filename
    5116701