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| The Spatial Effect of Innovation Factors and Economic Resilience |
| Zhu Lin,Dong Fan |
| (School of Government,Beijing Normal University, Beijing 100875,China) |
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Abstract It is vital to improve economic resilience and build resilient cities for China's high-quality economic development. Previous studies on the measurement and influencing factors of China's economic resilience have generally shown that innovation capability is an important influence on regional economic resilience. However, the proxy variable selection of innovation capability in previous studies was generally limited to the number of patents or R&D investment of enterprises), and the interference of industrial structure heterogeneity on the result of resilience is often ignored in the measurement of economic resilience. Therefore, this paper selects four key indicators as the proxy variables of innovation elements from the macro and micro levels, and further analyzes the impact of innovation drivers on economic resilience; meanwhile,in order to eliminate the interference of industrial structure heterogeneity on the measurement results of economic resilience, this paper creatively uses the shift share method to extract industrial resilience from economic resilience, and compares the impact of innovation factors on different industrial resilience.#br#This study selects the period from the impact of Sino US trade friction in 2018 to the duration of the COVID-19 epidemic in 2021 as the sample interval for measuring China's economic resilience. It chooses a single dimensional variable elasticity evaluation model to measure the resilience of China's regional economy within the sample interval. However, the impact of different industries on economic resilience is ignored in the traditional economic resilience measurement model. When the impact of exogenous risks on different industries is heterogeneous, the weight of regional industrial structure will interfere with the measurement of regional economic resilience. Therefore, this paper uses the shift share decomposition method to divide the resilience characteristics into regional economic resilience and industrial resilience. In terms of the selection of innovation factor indicators, innovation drive is shown as the improvement of total factor productivity at the macro level and the growth of social innovation factors at the micro level. At the macro level, TFP is decomposed into the efficiency change index and technology change index, and they serve as the core explanatory variables of spatial effect research. At the micro level, the aggregation index of innovation input factors and the aggregation index of innovation output factors are selected as the micro proxy variables of innovation drive, and they are jointly incorporated into the spatial effect research model to study the spatial correlation between them and regional economic resilience.#br#Because regional economic resilience and innovation elements can flow freely at the spatial level, a spatial econometric model should be established to conduct empirical analysis and test on spatial relevance. First, the difference in per capita GDP between regions is used as an indicator to predict the economic distance between regions to build a spatial economic weight matrix, and on this basis, a spatial autocorrelation test model is determined. The test shows that if the variables have spatial autocorrelation, the linear regression model in classical econometrics will lead to errors in the test results, so a spatial econometric test model needs to be built.By the spatial Dubin model and geographic detector model, the empirical tests confirm that (1) China's regional economic resilience has a spatial correlation, and the closer the economic level is, the closer its economic resilience will be; (2) on the whole, innovative development can significantly enhance China's economic resilience, and this impact has a significant spatial spillover effect; (3) in terms of the sub-industries, the direct effect of scientific and technological innovation on the resilience enhancement of the secondary industry is significantly higher than that of other industries, and the spatial spillover effect on the resilience of the tertiary industry is most significant. However, the resilience growth of the primary industry mainly depends on the efficiency improvement brought about by large-scale development rather than technological progress.#br#On the basis of the above research conclusions, this paper reveals the important role of scientific technological development in the construction of resilient cities, and puts forward the innovative development policy driven by "scientific and technological innovation" and "institutional innovation", and suggests that regional economic resilience should be enhanced according to the regional factor endowment and industrial structure characteristics.#br#
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Received: 23 August 2022
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