Economic Policy Uncertainty, Accounting Robustness and Commercial Credit Supply - A Big Data Analysis Based on Accounts Receivable

Abstract

Abstract In this paper, a two-dimensional panel data model of economic policy uncertainty is investigated based on the individual fixed effects of panel quantile regression, and a nonparametric panel model with individual fixed effects is established. The unfolding of nonparametric penalized spline and the introduction of Bayesian in stratified quantile are utilized to construct regression models applicable to accounting robustness, respectively. In the empirical study, the economic policy uncertainty index, accounting robustness and commercial credit supply are measured respectively. The annual data of China’s Shenzhen and Shanghai A-share listed companies during the period from 2012 to 2021 were selected as the research basis, and Bayesian quantile regression was made on the basis of correlation analysis. The coefficient of commercial credit supply is found to be -0.0821, and the variable RD1 is negatively correlated with economic policy uncertainty. This regression result confirms hypothesis H1 of this paper, suggesting that private firms invest less in innovation when economic policy uncertainty is higher. In the test of economic policy uncertainty by type, the regression coefficients of RD2, EPU, and SIZE are negative, respectively -0.0368, −0.2124, and -0.1458, which indicates that fiscal policy, monetary policy, and exchange rate and capital account policy uncertainty are negatively correlated with the supply of business credit to enterprises. Based on this correlation, this study provides guidance for the development of business credit for enterprises.