Enterprises' Digital Transformation and Perception of Economic Policy Uncertainty
FANG Mingyue, NIE Huihua, RUAN Rui, SHEN Xinyi
College of Economics and Management, China Agricultural University; School of Economics, Renmin University of China; Center for China Fiscal Development, Central University of Finance and Economics
Summary:
Perceived economic policy uncertainty, defined as the subjective perception of consumers, managers, or other decision makers that economic policy is likely to change, is one of the greatest challenges faced by enterprises. Especially in recent years, the international political and economic spheres have been rife with uncertainty because of the impact of COVID-19, international trade friction, and regional conflicts, further increasing economic policy uncertainty. Therefore, economists are increasingly paying attention to economic policy uncertainty. The literature shows that in general, such uncertainty discourages business investment, reduces hiring and trade, lowers enterprises' output, and may impede long-term economic growth. Therefore, it is important to study ways to reduce enterprises' perception of economic policy uncertainty. The arrival of the digital economy provides a solution to this dilemma. In the digital economy, enterprises transform their production and operation systems, management models, and core business processes with the help of digital technologies, creating disruptive innovations and changes. This process is called “digital transformation.” We argue that through digital transformation and by introducing digital technologies such as artificial intelligence, big data, and cloud computing, enterprises can, to some extent, alleviate the deficiencies arising from their limited access to information and limited ability to process information, thus reducing their perception of economic policy uncertainty. We use 2012-2020 data on Chinese A-share listed manufacturing companies and find that companies' digital transformations effectively reduce their perception of economic policy uncertainty. The financial data are from the CSMAR database. We use textual analysis to extract words related to economic policy and uncertainty from the annual reports of the listed companies to construct firm-level economic policy uncertainty (FEPU) and firm-level indicators of digital transformation. In the baseline regression, the OLS estimates suggest that for a one standard deviation increase in a company's digital transformation, its perception of economic policy uncertainty decreases by 3.86%. In the robustness tests, the baseline results hold when we use the share of fixed assets related to the digital economy as a proxy for digital transformation, control for annual report characteristics (tone, sentence length), and exclude the possible strategic reporting behavior of companies in their annual reports. We use various methods to address potential endogeneity, such as controlling for high dimensional fixed effects, the Bartik instrumental variable method, and the synthetic difference-in-differences method (SDID), and our main results still hold. Finally, we explore two main channels through which digital transformation reduces companies' perception of economic policy uncertainty: reduced information asymmetry and improved information processing capabilities. The two main contributions of our paper are as follows. First, we enrich the literature on economic policy uncertainty by revealing a new way to reduce perceived uncertainty. Unlike previous studies, we use a firm-level economic policy uncertainty perception index to identify the uncertainty perception of different companies. Meanwhile, we analyze how to reduce enterprises' perception of economic policy uncertainty from the perspective of digital transformation, thus filling a gap in the literature.Second, we find that an enterprise's digital transformation can reduce its perception of economic policy uncertainty, thus providing new insight into the effects of digital transformation. This paper is the first to study the effect of enterprises' digital transformations on their perception of economic policy uncertainty. As enterprises' policy expectations heavily influence their behaviors such as investment, hiring, and R&D, this paper reveals the deeper reasons or mechanisms behind enterprises' behavior and performance related to digital transformation. Our research has important policy implications for maintaining economic policy stability and promoting the digital transformation of manufacturing enterprises. First, economic policies must be consistent and uniform to reduce uncertainty. With stable expectations, enterprises can have stable investment, hiring, and R&D, i.e., stable expectations can stabilize growth. Second, our research provides insight into how to promote the integration of the digital and real economies. We demonstrate that the digital transformation of enterprises can reduce their perception of economic policy uncertainty and thus promote the development of the real economy. Therefore, to accelerate the development of the digital economy, relevant departments should prioritize supporting the digital transformation of enterprises that are vulnerable to international and domestic macroeconomic situations and economic cycles.
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