Antitrust and the entry of technology start-ups: Causal inference based on double machine learning

反垄断法与科技企业进入—基于双重机器学习的因果推断

Abstract

Technological innovation is a crucial support for achieving high-quality economic development, with technology enterprises being the main agents of such innovation. Encouraging the entry of technology start-ups is a vital measure to stimulate technological innovation and complete the transformation of the economic dynamics from old to new energy. Therefore, in the current situation where external technological blockades are becoming increasingly severe, how to promote the entry of technology start-ups has become key to China’s breakthrough in overcoming the critical core technology “bottleneck” dilemma. Based on the matching data of the national industrial and commercial enterprise registration information database and the city level data from 2004 to 2020, this paper takes the implementation of Antitrust Law in 2008 as a quasi-natural experiment, and uses the double machine learning model to identify the impact of antitrust on the entry of technology start-ups and its internal mechanism. This paper finds that the implementation of Antitrust Law significantly promotes the entry of technology start-ups, and the above promotion effect is more significant in east cities, developed cities and cities with better transportation infrastructure. Mechanism analyses show that Antitrust Law promotes the entry of technology start-ups by improving the innovation ecosystem, optimizing the business environment and boosting the level of venture capital. Further analyses show that the entry of technology start-ups brought about by the implementation of Antitrust Law can drive high-quality economic development in cities. The above conclusions can provide enlightenment for policy guidance on cultivating technology start-ups and achieving high-quality economic development. The marginal contributions of this paper are as follows: First, this study enriches the research on the microeconomic consequences of the Antitrust Law. The economic consequences of competition policy have always been a hot topic in academia. Existing literature has mostly focused on the impact of the Antitrust Law on internal business decisions of enterprises, while research on enterprise dynamics such as the entry of technology start-ups is relatively scarce. Second, this paper employs cutting-edge methods to enhance the effectiveness of policy evaluation. Existing literature often uses parametric methods to assess policy effects, inevitably facing the “curse of dimensionality” and model specification bias issues. This paper leverages the advantages of machine learning algorithms in high-dimensional, non-parametric prediction, using a double machine learning method for causal inference. This approach not only better mitigates endogeneity issues but also overcomes the regularization bias of machine learning methods, thereby more accurately assessing the microeconomic effects of the Antitrust Law. Third, this paper deeply analyzes the impact mechanism of the Antitrust Law on the entry of technology start-ups. Specifically, this paper reveals the internal mechanisms by which the Antitrust Law affects the entry of technology start-ups from three aspects: improving the innovation ecosystem, optimizing the business environment, and enhancing the level of venture capital, which helps to deeply understand the channels through which the Antitrust Law affects the dynamics of technology start-up entry.