Page 296 - Special Topic Session (STS) - Volume 4
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STS587 Guangwu C.
                  economic  issues,  especially  since  Chinese  regions  exhibit  a  considerable
                  degree of heterogeneity in terms of economic development.
                      In addition, using IELab technology to update tables annually or generate
                  subnational Chinese MRIOs for any year becomes a less labour-intensive task
                  and can be based on the latest official data as well as other available data
                  sources. The Chinese IELab currently includes the longest and latest data from
                  1978 to 2016 and can support central and local governments in designing and
                  testing specific policies for any region or sector in China as well as to evaluate
                  previously  implemented  policies  in  order  to  guide  policy  adjustments  and
                  refinements. Other topical policy applications include modelling the impacts
                  of China’s abolition of the decades-long one-child since 2015 and the Chinese
                  government’s 4-trillion-yuan stimulus package in 2008 for bolster the slowing
                  economy during global financial crisis.

                  References
                  1.  Leontief, W.W., 1936. Quantitative Input and Output Relations in the
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                  2.  Ghosh, A., 1958. Input-Output Approach in an Allocation System.
                      Economica 25, 58-64.
                  3.  Leontief, W., 1949, "Recent Developments in the Study of Interindustrial
                      Relationships"[J], The American Economic Review: 211-225.
                  4.  Lenzen, M., K. Kanemoto, D. Moran, and A. Geschke. 2012a. Mapping the
                      Structure of the World Economy. Environmental Science & Technology
                      46(15): 8374-8381.
                  5.  Lenzen, M., D. Moran, K. Kanemoto, B. Foran, L. Lobefaro, and A. Geschke.
                      2012b. International Trade Drives Biodiversity Threats in Developing
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                  6.  Chen, G., Wiedmann, T., Hadjikakou, M., Cheng, M., Xu, L. & Wang, Y.
                      (2019a). Method for assessing Airbnb’s direct, indirect and induced
                      carbon footprint. MethodX (forthcoming).
                  7.  Chen, G., Zhu, Y., Wiedmann, T., Yao, L., Xu, L. & Wang, Y. (2019b). Urban-
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                  8.  Cheng, M., Chen, G., Wiedmann, T., Hadjikakou, M., Xu, L. & Wang, Y.
                      (2019). Sharing economy and sustainability: assessing Airbnb’s diect,
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