An Examination of the Interplay between Total Factor Productivity in Retail Sub-industries in China Mainland
DOI:
https://doi.org/10.37134/geografi.vol11.2.1.2023Keywords:
Industrial autocorrelation, Retail sub-industry, Spatial econometrics, total factor productivity (TFP)Abstract
This research employs a spatial econometrics approach to investigate the interdependencies and dynamics of total factor productivity (TFP) within retail sub-industries in China Mainland by utilizing statistical data from 2013 and 2018. By constructing an adjacency matrix based on industry similarity, the study examines the impact of various factors on the industrial characteristics of retail sub-industries. These factors include total assets and the average number of engaged persons. The findings reveal significant industrial interdependence, variations among sub-industries, and the presence of a distinct retail industry cluster, albeit in a diminishing state. The study also highlights the dominance of capital investment output over labor input and identifies a stage of increasing returns in production inputs. The implications underscore the need to consider mutual influences between neighboring industries when formulating relevant policies.
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References
Anselin, L. (1988). Spatial econometrics: methods and models. Dordrecht, Kluwer Academic Publishers.
Anselin, L., & Florax, R. J. G. M. (1995). New directions in spatial econometrics: Introduction. New directions in spatial econometrics, 3-18.
Beck, N., Gleditsch, K. S., & Beardsley, K. (2006). Space Is More than Geography: Using Spatial Econometrics in the Study of Political Economy. International Studies Quarterly, 50(1), 27-44.
Feldman, M. P., & Kogler, D. F. (2010). Stylized facts in the geography of innovation. Handbook of the Economics of Innovation, 1, 381-410.
Giacomini, R., & Granger, C. W. J. (2004). Aggregation of space-time processes. Journal of econometrics, 118(1-2), 7-26.
Lesage, J. P. (2014). What Regional Scientists Need to Know about Spatial Econometrics. Review of Regional Studies, 44(1), 13-32.
Li, J., Tan, Q. M., & Bai, J. H. (2010). Spatial econometric analysis of regional innovation production in China: an empirical study based on static and dynamic spatial panel models. Management World, 7, 43-55.
Lynch, J. P., & Law, K. H. (2002). Market‐based control of linear structural systems. Earthquake engineering & structural dynamics, 31(10), 1855-1877.
Ngo, M. N., & Nguyen, L. D. (2020). Economic growth, total factor productivity, and institution quality in low-middle income countries in Asia. The Journal of Asian Finance, Economics and Business, 7(7), 251-260.
Schneider, J. W., & Borlund, P. (2007). Matrix comparison, Part 2: Measuring the resemblance between proximity measures or ordination results by use of the Mantel and Procrustes statistics. Journal of the American Society for Information Science and Technology, 58(11), 1596-1609.
Tobler, W. (2004). On the first law of geography: A reply. Annals of Association of American Geographers, 94(2), 304-310.
Wang, M., Xu, M., & Ma, S. (2021). The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity. Structural Change and Economic Dynamics, 59, 427-441.
Xie, L., Zhang, J., & Liu, X. (2011). Wage Agglomeration and Interaction in China's Industrial Industry. World Economy, (7), 3-26.
Zhang, C., Liu, T., Li, J., et al. (2023). Economic Growth Target, Government Expenditure Behavior, and Cities’ Ecological Efficiency—Evidence from 284 Cities in China. Land, 12(1), 182.
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Copyright (c) 2023 Xie Ailiang, Fauziah Che Leh, Norimah Rambeli
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