All Times ET
Keywords: Dynamic relations, state space models, mixed effects, online prediction, new energy vehicles
In the race to reach the objectives outlined in the Paris Agreement, the development of new energy vehicles (NEVs) plays a critical role in carbon emission reduction and air pollution control. Research and development (R&D) performance has a strong positive effect on the promotion of NEVs, which is associated with external and internal corporate economic factors like public subsidies and leverage. We propose a mixed effects state space model (MESSM) for multivariate longitudinal variables based on NEV firms registered in Shanghai and Shenzhen Stock Exchanges from 2010 to 2020, revealing dynamic relationships within and between economic factors for R&D performance and conducting online predictions at the corporate level. The explicit expressions for the underlying evolving process give the state space model interpretability and flexibility, and extensions to incorporate mixed effects further improve dynamic modeling by borrowing information between individual companies. The findings from this first application of MESSM to economic research support timely company decisions and enhance the overall R&D performance in the NEV industry, demonstrated in applications by suggesting conservative corporate strategy capitalizing on subsidies for a randomly selected company. Our study not only sheds light on the economic repercussions of COVID-19 on individual corporations, but also builds a novel pipeline for future practice and applications with possibility for extensions to similar industries.