## 4 How the Statistical Analysis Display Demonstrates Each Hypothesis  
Three hypotheses are proposed in this paper: H1: Digital transformation is induced to ESG performance; H2: in industries with high monopoly degree, digital transformation is not monopolized to ESG performance; H3: under the same industry, the same region or common institutional investors, technology has a spillover effect. In order to test these three hypotheses, this paper adopts the most commonly used method in the field of economic management research: using econometric theory to construct the OLS model. The method of testing the coefficients of the variables constructed in this paper to determine their quantitative relationship is analyzed to provide data support for the three hypotheses. H2 and H3 are proposed on the basis of H1. The purpose is to reveal the heterogeneous impact of digital transformation on enterprise ESG performance more comprehensively so as to provide theoretical guidance for enterprises to make better use of digital technology to improve ESG performance and for the government to formulate relevant policies.  
Taking the test of H1 as an example, according to the OLS model designed in this paper, the data is input into the STATA software(Version number: 17.0 MP--Parallel  
\begin{table}
\begin{tabular}{c c c c} \hline
**Variable Type** & **Variable Name** & **Variable Symbol** & **Variable Declaration** \\ \hline variable being explained & ESG rating & _ESG_ & Bloomberg ESG DiscIsclosure Index \\ \hline explanatory variables & digital transformation & _Ludigital_ & Digital word frequency of listed companies \\ \hline company scale & _Lusize_ & Natural logarithm of year-end total assets \\ \hline assets-liability ratio & _Lev_ & Year-end total liabilities/year-end total assets \\ \hline operating income growth rate & _Growth_ & Operating income of this year/operating income of the previous year-1 \\ \hline cash flow ratio & _Cashflow_ & Net cash flow from operating activities divided by total assets \\ \hline book-market ratio & _Mb_ & Total year-end assets/market value \\ \hline rate of return on total assets & _Rau_ & Net profit/average balance of total assets \\ \hline proportion of the largest shareholder & _Fsh1_ & proportion of the largest shareholder \\ \hline proportion of independent directors & _Dlzb_ & Number of independent \\  & & directors Board of Directors \\ \hline Is it a’ Big Four’ audit & _Big4_ & Whether four audit firms \\ \hline listed years & _Lnage_ & Ln (current year – listing year + 1) \\ \hline year & _Yar_ & Year of sample \\ \hline industry & _Indu_ & CSRC 2012 industry classification, manufacturing \\  & & take two codes, other industries with categories \\ \hline \end{tabular}
\end{table}
Table 1: Variable definition.  
Edition; Creator: [PERSON]; Location: College Station, TX, USA), and the code is written according to the model to perform the regression operation. In order to ensure that the results will not be occasional errors due to the selection of OLS methods, this paper further implements the other five OLS regression methods to ensure that the results are general conclusions, which solves the problem of reliability of regression results at the technical level. Furthermore, at the data level, this paper continues to write the programs of Heckman Two-Step Method, Lag 1 and 2, Instrumental Variable Method: Two-Stage Regression, PSM-OLS and PSM-DID Estimation in STATA software. At the same time, seven popular robustness tests are used to perform regression on the data cleaned according to the corresponding methods. The results of the main regression did not receive the impact of the problem from the data level. Therefore, the regression results ensure that the hypothesis derived from the theoretical logic is also valid in practice. It should be noted that data analysis tests are not the logical deduction itself but the result of logical deduction.