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| Technological Progress Bias, Innovation Factor Allocation and Economic Resilience |
| Kuang Min,Fan Fengchun |
| (School of Public Administration, Sichuan University, Chengdu 610000, China) |
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Abstract Technological progress is not only the main source of domestic industrial economic growth, but also the core driving force of China′s social economic growth. The impact of technological progress on production efficiency and economic resilience is reflected in both the speed of technological development and the direction of technological progress. Some scholars even believe that the impact of the direction of technological progress is far greater than the speed of technological progress. Within the accounting framework of standard economic growth, the assumption for long-term stability of factor share and factor output elasticity makes technological progress appeat Hicks-neutral, and the whole source of social economic growth is attributed to neutral technological progress. However, the Kaldor′s “Stylized Facts” that factor share and factor output elasticity are fixed is not supported by empirical evidence. Technological progress in modern economic system shows stronger bias characteristics.#br# Can a bias towards technological progress make China′s economy more resilient? If the effect is confirmed, what is the underlying mechanism? Does the bias of technological progress have nonlinear characteristics on the improvement of economic resilience? To answer the above questions, there is the need to conduct empirical tests by sorting out relevant research results and combining with the status quo of China′s social economic development. Hence this study selects the panel data of 31 provincial-level administrative regions from 2006 to 2020 to analyze the impact of technological progress bias on economic resilience from the perspective of transmission mechanism and nonlinear characteristics. It constructs an estimation model for the influence of technological progress bias on two dimensions of economic resilience (adaptation capacity of economic adjustment and transformation capacity of economic innovation), and conducts an empirical analysis on the sample data on this basis. Then, in order to explore whether there is a nonlinear effect biased by technological progress in the boosting process of economic resilience, the study draws on the cross-sectional threshold method to accurately analyze the heterogeneous impact of independent variables on dependent variables in different intervals through the threshold model. On the one hand, the threshold model can empirically test whether there is a threshold effect between the technological progress bias and the two dimensions of economic resilience, so as to learn whether there is a nonlinear relationship between them. On the other hand, if there is indeed a threshold effect between the two dimensions, the number of thresholds between the technological progress bias and the two dimensions of economic resilience can be determined, and the nonlinear relationship between the two dimensions is confirmed. By summarizing the academic division type, the study divides the technological progress bias into four dimensions and constructs the threshold regression model of technology progress towards each dimension and the two dimensions of economic resilience.#br# The empirical results show that technological progress bias has a significant positive impact on economic resilience, and this conclusion still holds after robustness and endogeneity tests. Technological progress bias can significantly improve the two dimensions of economic resilience: economic adjustment and adaptation capacity, and economic innovation and transformation capacity, and capital-biased technological progress has a greater effect on strengthening economic resilience. In terms of mechanism, the allocation of innovation factors is an important mechanism affecting the effect of technological progress bias on economic resilience. Technological progress bias can promote economic resilience by optimizing the allocation of innovation factors. The threshold model shows that the technological progress bias index and its sub-dimensions have no nonlinear relationship with economic adjustment and adaptation capacity, but have nonlinear relationship with economic innovation and transformation capacity.#br# Therefore, it is necessary to guide the course of technological development reasonably to give full play to the positive efficiency of technological progress，make full use of the synergy of “efficient market” and “effective government” to optimize allocation schemes of innovative element， and fend off potential risks through technological innovation, innovative thinking and innovative mechanisms to strengthen economic resilience. Meanwhile it is vital to improve the policy supply system for industrial economic development to remove institutional barriers typically associated with the segmentation of factor markets, so as to promote the rapid flow and efficient allocation of factors of production.#br#
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Received: 27 May 2022
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