• Journal of Geographical Sciences
  • Vol. 30, Issue 8, 1363 (2020)
Kan ZHOU1、*, Baoyin LIU2, and Jie FAN1、2
Author Affiliations
  • 1Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2Institute of Science and Development, CAS, Beijing 100190, China
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    DOI: 10.1007/s11442-020-1786-8 Cite this Article
    Kan ZHOU, Baoyin LIU, Jie FAN. Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan, China in 2008[J]. Journal of Geographical Sciences, 2020, 30(8): 1363 Copy Citation Text show less

    Abstract

    The border areas of the Tibetan Plateau and the neighboring mountainous areas have a high incidence of earthquakes with a magnitude greater than Ms 5.0, as well as having a dense distribution of geological disasters such as collapses, landslides, and debris flows. Revealing the post-disaster economic development and recovery process is very important for enhancing disaster prevention and response capacity in order to formulate control policies and recovery methods for post-disaster economic reconstruction based on economic resilience. Using long-term socioeconomic data and the autoregressive integrated moving average (ARIMA) model, this paper calculated the economic resilience index of the areas most severely affected by the Wenchuan Earthquake of 2008 and adopted the improved variable returns to scale (VRS) date envelopment analysis (DEA) model and the Malmquist productivity index to analyze the efficiency and effect of annual post-disaster recovery. The results show that: (1) the economic resilience index of the areas most severely affected by the Wenchuan Earthquake was 0.877. The earthquake resulted in a short-term economic recession in the affected areas, but the economy returned to pre-quake levels within two years. In addition, the industrial economy was less resilient than agriculture and the service industry. (2) The comprehensive economic recovery efficiency of the disaster-stricken area in the year following the disaster was 0.603. The comprehensive efficiency, the pure technical efficiency, and the scale efficiency of the plain and hilly areas were significantly greater than those of the plateau and mountain areas. (3) The annual fluctuation in total factor productivity (TFP) following the disaster was considerable, and the economic recovery efficiency decreased significantly, resulting in a short-term economic recession. The TFP index returned to steady state following decreases of 33.7% and 15.2%, respectively, in the two years following the disaster. (4) The significant decrease in the post-disaster recovery efficiency was caused mainly by technological changes, and the renewal of the production system was the leading factor in determining the economic resilience following the disaster. With the decline in the scale of economic recovery following the earthquake, long-term economic recovery in the disaster-stricken areas depended mainly on pure technical efficiency, and the improvement in the latter was the driving force for maintaining the long-term growth of the post-disaster economy. Therefore, according to the local characteristics of natural environment and economic system, the disaster-stricken areas need to actively change and readjust their economic structures. At the same time, attention should be paid to updating the production system to enhance the level of technological progress and give full play to the scale effects of large-scale capital, new facilities, human resources, and other investment factors following the disaster so as to enhance the impact of economic resilience and recovery efficiency in response to the disaster.
    ${{Y}_{t}}=c+{{\alpha }_{1}}{{Y}_{t-1}}+{{\alpha }_{2}}{{Y}_{t-2}}+\cdots +{{\alpha }_{p}}{{Y}_{t-p}}+\varepsilon {{\alpha }_{t}}+{{\beta }_{1}}{{\varepsilon }_{t-1}}+{{\beta }_{2}}{{\varepsilon }_{t-2}}+\cdots +{{\beta }_{q}}{{\varepsilon }_{t-q}}$ (1)

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    $R=S/(S+\Delta S)=\underset{{{t}_{2}}}{\overset{{{t}_{1}}}{\mathop \int }}\,f(t)dt/\underset{{{t}_{2}}}{\overset{{{t}_{1}}}{\mathop \int }}\,{f}'(t)dt$ (2)

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    $\begin{cases} \min \left( \theta -\varepsilon \left( \underset{I=1}{\overset{I}{\mathop \sum }}\,{{s}^{-}}-\underset{O=1}{\overset{O}{\mathop \sum }}\,{{s}^{+}} \right) \right) \\ s.t.\underset{n=1}{\overset{N}{\mathop \sum }}\,{{x}_{ni}}{{\lambda }_{n}}+{{s}^{-}}=\theta x_{i}^{n}\ \ \ \ \ \ \ \ \ \ \ i=1,2\ldots I \\ \underset{n=1}{\overset{N}{\mathop \sum }}\,{{y}_{no}}{{\lambda }_{n}}-{{s}^{+}}=y_{o}^{n}~~~~~~~~~~~~~~~~~~o=1,2\ldots O \\ {{\lambda }_{n}}\ge 0\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ n=1,2\ldots N \\ \end{cases}$. (3)

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    $M({{x}^{t+1}},{{y}^{t+1}},{x}',{y}')=\sqrt{\frac{{D}'({{x}^{t+1}},{{y}^{t+1}})}{{D}'({x}',{y}')}\times \frac{{{D}^{t+1}}({{x}^{t+1}},{{y}^{t+1}})}{{{D}^{t+1}}({x}',{y}')}}$ (4)

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    $\begin{align} & M({{x}^{t+1}},{{y}^{t+1}},{x}',{y}')=\frac{{{D}^{t+1}}({{x}^{t+1}},{{y}^{t+1}}\text{ }\!\!|\!\!\text{ }VRS)}{{{D}^{t}}({{x}^{t}},{{y}^{t}}\text{ }\!\!|\!\!\text{ }VRS)}\times \frac{{{D}^{t+1}}({{x}^{t+1}},{{y}^{t+1}}\text{ }\!\!|\!\!\text{ }CRS)}{{{D}^{t+1}}({{x}^{t+1}},{{y}^{t+1}}\text{ }\!\!|\!\!\text{ }VRS)}\times \\ & \ \ \ \frac{{{D}^{t}}({{x}^{t}},{{y}^{t}}\text{ }\!\!|\!\!\text{ }VRS)}{{{D}^{t}}({{x}^{t}},{{y}^{t}}\text{ }\!\!|\!\!\text{ }CRS)}\times \sqrt{\frac{{{D}^{t}}({{x}^{t+1}},{{y}^{t+1}})}{{{D}^{t+1}}({{x}^{t+1}},{{y}^{t+1}})}\times \frac{{{D}^{t}}({{x}^{t}},{{y}^{t}})}{{{D}^{t+1}}({{x}^{t}},{{y}^{t}})}} \\ & \ \ \ =pech\times sech\times techch \\ \end{align}$ (5)

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    Kan ZHOU, Baoyin LIU, Jie FAN. Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan, China in 2008[J]. Journal of Geographical Sciences, 2020, 30(8): 1363
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