“In recent years, the academic and business communities have paid close attention to economic policy uncertainty. Indeed, the greatest certainty of this era is uncertainty. The main indicator for measuring economic policy uncertainty is the EPU index developed by BBD (2016). However, each region or country has only one EPU index at each point in time, so it cannot be distinguished from time fixed effects in terms of measurement, and it cannot distinguish the differences in policy uncertainty perception among different enterprises.”
——Official Account: Professor Nie Huihua
In 2020, Nie Huihua, Ruan Rui and Shen Ji published an article entitled “Enterprise Uncertainty Perception, Investment Decision-making and Financial Asset Allocation” in the World Economy magazine, providing a method for calculating the economic policy uncertainty index at the enterprise level, and using the data to analyze the impact of uncertainty perception on enterprise investment and financing. After the publication of the paper, it received widespread attention from the academic community.
In order to promote the research on economic policy uncertainty and reduce unnecessary time costs, Professor Nie Huihua and his research team have made the Enterprise Economic Policy Uncertainty Perception Index public for academic use. With authorization, CnOpenData has included this data in the public data section of the CnOpenData official website for easy browsing by scholars.
For data download and more information, please go to White Shark Online.
Database Application Guide
Data Construction Method
The indicators used to measure economic policy uncertainty in this paper are extracted from the annual report texts of listed companies using text mining methods.
With the development of computer technology, the practice of introducing unstructured data such as text into corporate finance research has become increasingly common (Tetlock, 2007; Li, 2008; Tetlock et al., 2008; Loughran and McDonald, 2014, 2016). This article refers to the practices of Baker et al. (2016) and Hassan et al. (2019), using the "lexicon method" to screen specific content texts. If specific words appear in a text, the text is identified as a text expressing certain specific meanings. This article believes that if "policy words" and "uncertainty words" appear in a sentence at the same time, it is considered that the sentence is the content of the annual report writer expressing the uncertainty of the company's economic policies.
The specific method is as follows:
- First, the PDF file of each listed company's annual report is converted into a text file through a format conversion tool, and the content of "Management Discussion and Analysis" (MD&A for short, "Board of Directors Report" in some annual reports) is extracted using regular expressions, and all numbers, English letters, and all punctuation marks and special symbols except periods are removed.
- Then, the MD&A text is divided into sentences using the Chinese period as a delimiter. Considering the language habits of Chinese, this article uses sentences as the basic unit of analysis. Assume that the number of MD&A sentences in the annual report of listed company i in year t is s. Use the programming language Python to call the Jieba word segmentation module to segment each sentence, and remove stop words (stopwords) during word segmentation. In order to minimize the ambiguity caused by word segmentation, this paper defines a user word list during word segmentation, which includes the full names and abbreviations of all A-share listed companies, the names of accounting subjects, words that express uncertainty used in subsequent text processing, and words related to the meaning of government (policy). After word segmentation, each sentence becomes a combination of a series of words, and then each sentence (s) is subjected to the following operations one by one: Search for words that appear in each sentence. If words that express uncertainty appear, it is considered to be a sentence that expresses uncertainty; if words related to government, policy, etc. and words that express uncertainty appear in a sentence at the same time, it is considered to be a sentence that expresses policy uncertainty (P). The economic policy uncertainty faced by enterprises (FEPU) is measured by the ratio of the number of uncertainty words (n) in the economic policy uncertainty sentence to the total number of MD&A words (N).
References
Note: Any use of the economic policy uncertainty perception index based on enterprises must indicate the source of the citation:
- Nie Huihua, Ruan Rui, Shen Ji, 2020, "Enterprise Uncertainty Perception, Investment Decision-making and Financial Asset Allocation", "World Economy", Issue 6, pp. 77-98.
Data Update Frequency
Updated from time to time