Pension insurance contribution rate, capital-skill complementarity and enterprise total factor productivity
【Abstract】In this paper, employee heterogeneity, capital-skill complementarity and knowledge spillover are incorporated into the overlapping generations model (namely, the OLG model) to obtain the optimal theoretical solution of the enterprise pension insurance contribution rate (PICR). The non-linear relationship between the PICR and the total factor productivity (TFP) is empirically tested by using the micro-data of listed companies, and the optimal value estimation of the enterprise PICR is obtained. Then, a panel double-threshold model is established to analyze the mechanism of TFP affected by employee motivation and capital-skill complementarity. The results show that the relationship between the enterprise PICR and TFP presents an inverted U type. After controlling enterprise characteristics, and the fixed effects of region, time, and industry, the enterprise PICR of 5.67% can help to achieve the maximum TFP. When the enterprise PICR is between 5.20%–9.57%, the enterprise can achieve employee motivation and capital-skill complementarity, so that the investment in high-skilled employees and R&D can jointly promote TFP. Therefore, it is the optimal range of enterprise PICR. Finally, using the quasi-natural experiment that the local governments of China adjusted the enterprise PICR in different directions around 2016, this paper empirically concludes that the optimal PICR in China is between 14% and 18%. At present, there is still room to reduce the PICR, but it must be moderate and we should be vigilant that excessive reduction hinders the improvement of enterprise TFP.
【Keywords】 pension insurance contribution rate; total factor productivity; capital-skill complementarity; employee motivation;
(Translated by HAO Dacheng)
. ① If there is no special explanation, the enterprise pension insurance in this paper refers to the basic pension insurance for urban enterprise employees, and the enterprise pension insurance contribution rate (PICR) refers to the part borne by enterprises in the basic PICR for urban enterprise employees. [^Back]
. ① Guo et al. (2013) endogenously generated technical parameter B as follows: B = μ x φ, where φ > 0. Based on this, this paper expands B and introduces the influence of employees’ capital growth rate per capita (g) and proportion of high-skilled employees (x) on technical parameter B, which is simplified to Equation (33). [^Back]
. ① Different from Zhao and Lu (2018) that chose the main business income to measure the output of enterprise, this paper chooses the added value of enterprises to make the measurement. The reason is that the main business income includes the intermediate input, which makes it fail to accurately measure the output of the enterprise. The calculation method is as follows: enterprise added value = employees’ salary + depreciation of fixed assets + operating profit + tax. [^Back]
. ② The enterprise PICR calculated by this method is the actual enterprise PICR rather than the enterprise PICR stipulated by the policy. If there is no special explanation, the enterprise PICR mentioned below is the actual enterprise PICR. [^Back]
. ① The empirical results of robustness test can be found in the attachment of China Industrial Economics (http://www.ciejournal.org). [^Back]
. ② This variable is specifically set as the proportion of the increasing sum of pension insurance payable by other enterprises in the same region and industry in that year to the increasing sum of the total payroll payable. [^Back]
. ③ In this paper, the two-stage least squares regression is carried out with the PICR of other enterprises in the same region and industry in that year as the instrumental variable. Firstly, in the decision-making equation of enterprise PICR, the PICR of other enterprises in the same region and industry in that year is significantly positive at the level of 1%. It indicates that the higher the PICR of other enterprises in the same region and industry in the same year is, the higher the enterprise PICR is, which meets the correlative hypotheses of the instrumental variable. Secondly, there is an instrumental variable corresponding to an endogenous variable in the model, and the value of Kleibergen-Paaprk LM statistic used to test the unrecognizable is 436.11, corresponding to the P-value of zero, which strongly rejects the unrecognizable original hypothesis. In addition, the value of Hansen J statistic used to test the overidentification is zero, which indicates that there is no overidentification. Therefore, the model is confirmed to make a right identification. In addition, the value of Kleibergen-Paaprk Wald F statistic used to test weak instrumental variable is 862.67, and the corresponding critical value of Stock-Yogo weak instrumental variable test at 15% level is 8.96, rejecting the original hypothesis that the enterprise PICR is a weak instrumental variable. The above test shows that it is effective to select the PICR of other enterprises in the same region and industry in that year as the instrumental variable. [^Back]
. ① The research shows that the change of social security collection organization from social security department to local tax department will increase the contribution rate and probability of participating in the social security of non-state-owned enterprises by 5% and 7%, respectively. In addition, the effect is more obvious in the regions with stronger tax collection ability. For details, please refer to Feng, J. The Paper, (2018-09-27) (https://www.thepaper.cn/newsDetail_forward_2476340). [^Back]
. ② In this paper, the data of local pension insurance collection department are obtained by manually browsing the websites of local governments. [^Back]
. ③ The implementation of the Work Plan for Reducing the Cost of Real-Economy Enterprises is in the second half of 2016, and there is a certain lag in implementing this policy in various regions. With that situation considered, this paper resets policy: when the sample year is before 2016, policy = 0; when the sample year is 2016, policy = 0.5; and when the sample year is 2017, policy = 1. The regression results are similar to the given ones in the main body of the text. [^Back]
. ① This paper divides large enterprises and small and medium enterprises based on the Measures for Classification of Large, Medium, Small and Miniature Enterprises for the Purpose of Statistics (2017) and the Industrial Classification for National Economic Activities (GB/T4754-2017) issued by the National Bureau of Statistics of China. [^Back]
. ① The detailed results can be seen in the attachment of China Industrial Economics (http://www.ciejournal.org). [^Back]
 Feng, J. & Song, Z. South China Journal of Economics (南方经济), (11): 22–33 (2006).
 Guo, K., Yu, J. & Gong, L. The Journal of World Economy (世界经济), (11): 72–92 (2013).
 Han, X., Gong, Q. & Wu, L. Economic Research Journal (经济研究), (10): 140–154 (2016).
 Ji, C. Finance & Trade Economics (财贸经济), (3): 91–99 (2014).
 Jing, P. & Hu, Q. Journal of Finance and Economics (财经研究), (4): 26–37 (2016).
 Kang, C. & Chu, T. The Journal of World Economy (世界经济), (4): 139–160 (2014).
 Lu, X. & Lian, Y. China Economic Quarterly (经济学(季刊)), (2): 541–558 (2012).
 Ma, H., Huang, G. & Wang, R. Management World (管理世界), (4): 32–46 (2017).
 Ma, S., Meng, X. & Gan, L. China Economic Quarterly (经济学(季刊)), (3): 969–1000 (2014).
 Pan, A., Liu, W. & Wang, X. Nankai Business Review (南开管理评论), (3): 35–45 (2018).
 Ren, S. & Lyu, Z. Management World (管理世界), (11): 10–23 (2014).
 Shen, G. China Economic Quarterly (经济学(季刊)), (4): 1653–1682 (2016).
 Sun, X. & Wang, Y. China Industrial Economics (中国工业经济), (5): 57–69 (2014).
 Sun, Y., Bian, S. & Mu, H. Contemporary Economic Management (当代经济管理), (7): 69–72 (2009).
 Wang, H., Li, M. & Tang, T. China Industrial Economics (中国工业经济), (11): 73–89 (2016).
 Xie, J., Wang, W. & Jiang, Y. Economic Perspectives (经济学动态), (11): 78–88 (2014).
 Yang, Y. Social Security Studies (社会保障研究), (4): 49–55 (2012).
 Yang, R. Economic Research Journal (经济研究), (2): 61–74 (2015).
 Yang, Z. OLG Model Analysis On Public Pension: Principles and Applications (公共养老金的OLG模型分析: 原理与应用). Beijing: Guangming Daily Publishing House, (2010).
 Yu, X., Cheng, Y. & Hu, Q. China Industrial Economics (中国工业经济), (1): 155–173 (2017).
 Zhao, J. & Lu, Z. Economic Research Journal (经济研究), (10): 97–112 (2018).
 Zheng, Z., Liang, X. & Huang, J. China Industrial Economics (中国工业经济), (2): 174–192 (2017).
 Angelopoulos, K., S. Asimakopoulos, and J. Malley. Tax Smoothing in a Business Cycle Model with Capital Skill Complementarity. Journal of Economic Dynamics and Control, 2015, (51): 420–444.
 Chemmanur, T. J., S. He, and D. K. Nandy. The Going-Public Decision and the Product Market. The Review of Financial Studies, 2009, 23(5): 1855–1908.
 Chete, L. N., J. O. Adeoti, F. M. Adeyinka, and O. Ogundele. Industrial Development and Growth in Nigeria: Lessons and Challenges. WIDER Working Paper, 2014.
 Claessens, S., and S. Djankov. Ownership Concentration and Corporate Performance in the Czech Republic. Journal of Comparative Economics, 1999, 27(3): 498–513.
 David, H., W. R. Kerr, and A. D. Kugler. Does Employment Protection Reduce Productivity? Evidence from U.S. States. Economic Journal, 2007, 117(521): 189–217.
 Diamond, P. A. National Debt in a Neoclassical Growth Model. American Economic Review, 1965, 55(5): 1126–1150.
 Duffy, J., C. Papageorgiou, and F. Perez-Sebastian. Capital-Skill Complementarity? Evidence from a Panel of Countries. Review of Economics and Statistics, 2004, 86(1): 327–344.
 Giannetti, M., G. Liao, and X. Yu. The Brain Gain of Corporate Boards: Evidence from China. The Journal of Finance, 2015, 70(4): 1629–1682.
 Griliches, Z. Capital-Skill Complementarity. The Review of Economics and Statistics, 1969, 51(4): 465–468.
 Hansen, B. E. Threshold Effects in Non-dynamic Panels: Estimation, Testing, and Inference. Journal of Econometrics, 1999, 93(2): 345–368.
 Hsu, P. H., X. Tian, and Y. Xu. Financial Development and Innovation: Cross-Country Evidence. Journal of Financial Economics, 2014, 112(1): 116–135.
 Johnson, R. W. The Impact of Human Capital Investment on Pension Benefits. Journal of Labor Economics, 1996, 14(3): 520–554.
 Krishnan, K., D. K. Nandy, and M. Puri. Does Financing Spur Small Business Productivity? Evidence from a Natural Experiment. Review of Financial Studies, 2014, 28(6): 1768–1809.
 Krusell, P., L. E. Ohanian, J. V. RíosRull, and G. L. Violante. Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis. Econometrica, 2000, 68(5): 1029–1053.
 Levinsohn, J., and A. Petrin. Estimating Production Functions Using Inputs to Control for Unobservables. The Review of Economic Studies, 2003, 70(2): 317–341.
 Majumdar, S. K. The Impact of Size and Age on Firm-Level Performance: Some Evidence from India. Review of Industrial Organization, 1997, 12(2): 231–241.
 Munnell, A. H., K. Haverstick, and G. Sanzenbacher. Job Tenure and Pension Coverage. Center for Retirement Research Center at Boston College Working Paper, 2006.
 Olley, G. S., and A. Pakes. The Dynamics of Productivity in the Telecommunications Equipment Industry. NBER Working Paper, 1992.