2026-10-13T02:37:59Z https://www.scidb.cn/oai

10.57760/sciencedb.37844 2026-05-22T17:12:41Z

2026-05-22 Dual Pilot Policy and Corporate Green Innovation Quality-Efficiency Dataset of A-Share Listed Companies (2010–2022) doi:10.57760/sciencedb.37844 en This dataset aims to explore the effect of the "dual pilot" policy on corporate green innovation. Considering data integrity and availability, we finally select the data of A-share listed companies from 2010 to 2022 as the initial sample and conduct the following screening: (1) Eliminate ST and *ST listed company samples; (2) Exclude samples from the financial industry; (3) Remove samples with missing data of core variables. A small number of missing values are supplemented by the interpolation method. To avoid the interference of extreme values, continuous variables are winsorized at the 1% and 99% quantile levels. After screening, a total of 29,916 valid observations are obtained.1. Explained VariableReferring to the commonly adopted construction method of patent indicators for corporate green innovation research, this study takes patent applications rather than patent grants as the measurement indicator. The number of green utility model patent applications is selected as the proxy variable for strategic green innovation (Green1), and the number of green invention patent applications is adopted as the proxy variable for substantial green innovation (Green2), both of which are processed by logarithmic transformation. The patent data for measuring green innovation is sourced from the professional database of the National Intellectual Property Administration of the People's Republic of China.2. Explanatory VariablePolicy synergy of low-carbon city and new energy demonstration city (did). This paper adopts the interaction term of the "dual pilot" policy dummy variable (treat) and the policy implementation time dummy variable (post) as the explanatory variable. If the city where the enterprise is located is designated as a dual pilot city and the time is in the policy implementation year and subsequent years, the value is assigned as 1; otherwise, it is 0. The data of low-carbon cities is obtained from the National Development and Reform Commission, and the data of new energy demonstration cities is collected from the official website of the National Energy Administration.3. Mechanism VariablesExecutive Green Background (EGB)Executives whose resumes contain keywords such as environment, environmental protection, renewable energy, clean energy, ecology, low carbon, sustainability, energy conservation and green are identified as having an environmental background. On this basis, the number of executives with environmental backgrounds is counted. Given that some enterprises have zero such executives, this variable is measured by the natural logarithm of the number of environmental executives plus one.Corporate Social Responsibility (CSR)The corporate CSR data is derived from the CSR measurement sub-indicators in the China Stock Market & Accounting Research (CSMAR) Database, including shareholder protection, creditor protection, employee protection, supplier protection and other dimensions. Enterprises score 1 point for outstanding performance in each sub-category and 0 point otherwise. The overall CSR level is constructed by summing up the total scores. A higher CSR score indicates that the enterprise maintains better relations with stakeholders and makes greater investment in social capital.Organizational Slack (Slack)The arithmetic average of three indicators, namely current ratio, equity liability ratio and income-expense ratio, is used to measure organizational slack. Among them: the current ratio refers to the ratio of current assets to current liabilities; the equity liability ratio is the ratio of owners' equity to total liabilities; the income-expense ratio is calculated as the ratio of the sum of selling expenses, administrative expenses and financial expenses to operating revenue.4. Control Variables(1) Firm Age (Age): measured by the natural logarithm of the number of years since the firm’s establishment plus one;(2) Leverage (Lev): measured by the logarithm of the ratio of total liabilities to total assets in the current year;(3) Capital Intensity (CAP): measured by the ratio of total assets to operating revenue;(4) Return on Assets (ROA): measured by the ratio of net profit to total assets;(5) Board Size (Board): measured by the natural logarithm of the number of board members;(6) Proportion of Independent Directors (Indep): measured by the ratio of independent directors to the total number of board members;(7) Managerial Shareholding Ratio (Mshare): measured by the ratio of managerial shareholdings to total share capital;(8) Tobin’s Q (TobinQ): measured by the ratio of corporate market value to total assets.Relevant data such as corporate financial statements and governance structure are all sourced from the CSMAR Database. Low-carbon City; New Energy Demonstration City; Policy Synergy; Quality and Efficiency Improvement of Green Innovation Ding Xiaozhou Han Rui Li Panpan Hu Yucai PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank