Marketing Strategy of Private Enterprises Based on Bayesian Dynamic Panel Model of Machine Learning Algorithms

Abstract

Machine learning algorithms have attracted widespread attention in both industry and academia. This article mainly studies the marketing strategy decision-making of private listed enterprises based on Bayesian panel data model. By constructing a Bayesian static panel data model and a Bayesian dynamic panel data model, an empirical analysis was conducted on the debt financing decisions of private enterprises from two aspects: external financial environment and internal governance. The experimental results show that the MC error and standard deviation of parameter estimation for Bayesian static panel data model and Bayesian dynamic panel data model are both very small. This method contains more information, increases observation data and degrees of freedom. This article provides important theoretical guidance for the coordinated development of private listed enterprises and state-owned enterprises. It is conducive to promoting the coordinated development of the entire national economy.