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Investment incentives and the relative demand for skilled labor: Evidence from accelerated depreciation policies in China

Lexin Zhao and Hongsheng Fang

China Economic Review, 2022, vol. 73, issue C

Abstract: This study evaluates the effects of China's 2014 and 2015 accelerated depreciation policies on the relative demand of firms for skilled labor. We develop a simple model to explore how the policies affect the relative demand of firms for skilled labor and illustrate the roles of financing constraints and tax compliance in mediating the policy effects. We then employ a firm-level dataset from China's A-share listed companies and use a quasi-experimental design to examine the model predictions. We find that the policies significantly increase the relative demand of firms for skilled labor. The channels underlying the policy effects are that the policies generate additional cash flow for firms, stimulate investment and, thus, raise the demand of firms for skilled labor with the presence of capital–skill complementarity. We also find that the positive effects of the policies on the relative demand for skilled labor are primarily significant for firms with strong financing constraints and high tax compliance. Moreover, we document the positive effects of the policies on R&D investment, firm value added, productivity, workers' benefits, and corporate social responsibility performance, which further corroborate our main results.

Keywords: Tax incentives; Accelerated depreciation; Relative demand for skilled labor; Financing constraints; Tax compliance (search for similar items in EconPapers)
JEL-codes: D22 G31 H32 J23 J24 J31 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:73:y:2022:i:c:s1043951x2200044x

DOI: 10.1016/j.chieco.2022.101786

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China Economic Review is currently edited by B.M. Fleisher, K. X. D. Huang, M.E. Lovely, Y. Wen, X. Zhang and X. Zhu

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