Data from: epidemic, factor misallocation and efficiency of digital enterprises: heterogeneity study of labor and capital
Data files
Sep 06, 2024 version files 5.18 MB
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Covid_20240820_.xlsx
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PSM-DID_20240820.docx
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README.md
Abstract
In order to improve the development quality of the digital economy, the factor misallocation shall be reduced effectively in the post-epidemic era. This study discussed the impact mechanism of how the labor and capital misallocation affect heterogeneously the epidemic’s effect on the efficiency of digital enterprises. The epidemic outbreak was considered a quasi-natural experiment to set a PSM-DID model and an intermediary effect model. Empirical research was carried out using the data of 1752 digital and non-digital high-tech enterprises from the fourth quarter of 2017 to the first quarter of 2022. The results show that: (1) The epidemic improved digital enterprises' efficiency, mainly from the positive effect on technological efficiency and scale efficiency. (2) The epidemic worsened the misallocation of labor but improved capital allocation. (3) Through the factor misallocation, the epidemic had a positive impact on the efficiency of digital enterprises, contributing to the worsening technical progress. Through the capital misallocation, the epidemic had a positive effect on the TFP of the digital enterprises but there is no significant evidence of its source. While through the labor misallocation had a positive effect on the TFP of the digital enterprises because of its positive effect on technological efficiency and pure efficiency.
Methods
The panel data of 1034 listed DENs and 718 listed non-digital high-tech enterprises from the fourth quarter of 2017 to the first quarter of 2022 were used, which were from the Guotai'an database and Shenzhen and Shanghai Stock Exchanges. Incomplete data, ST, *ST, suspension of listing and delisted enterprises data samples were excluded. The sample interval entertained the PSM-DID method's requirement. The min-max normalization method was used to standardize the data. The Stata 16.0 software was used for calculation.