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Investigating the Economic Relationship between Provinces in Vietnam:A Spatial Regression Approach

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  • Xuan Vinh Vo, Thi Tuan Anh Tran and Van Thang Nguyen

    (University of Economics Ho Chi Minh City)

Abstract

To develop provincial economies, it is necessary to focus on not only the internal resources of a province but also the relationship among provinces which can lead to the spillover effect throughout the country. This paper examines the economic relationship and spillover effect between provinces in Vietnam by spatial regression approach with data collected from 2010 to 2017 from statistical yearbooks. The results show that there exists a spatial correlation between provinces in terms of provincial gross domestic product, capital investment and labor force. The results also demonstrate that capital and labor factors not only affect the gross domestic product of the host province but also affect the neighboring ones. The finding implies the significant spillover effect between provinces.

Suggested Citation

  • Xuan Vinh Vo, Thi Tuan Anh Tran and Van Thang Nguyen, 2020. "Investigating the Economic Relationship between Provinces in Vietnam:A Spatial Regression Approach," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 45(1), pages 47-60, March.
  • Handle: RePEc:jed:journl:v:45:y:2020:i:1:p:47-60
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    References listed on IDEAS

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    More about this item

    Keywords

    The Economic Relationship between Provinces; Spillover Effect; Spatial Regression;
    All these keywords.

    JEL classification:

    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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