资本市场开放提高企业投资效率了吗?——基于“沪港通”政策的异质性影响分析

摘要/Abstract

摘要：

本文以沪港通政策实施为背景,借助PSM、DID和处理效应等因果推断方法检验了资本市场互联互通政策对微观企业融资约束及投资效率的影响。实证发现:沪港通开通可缓解成分股企业的融资约束,但融资约束的缓解对企业投资效率具有“双刃剑”作用——既弱化了企业投资不足,也激励了过度投资。尽管融资约束的缓解对过度投资呈现出一定的直接激励效应,但同时也对企业研发投资产生了明显的激励作用,并最终通过提升产品创新能力间接缓解了过度投资。

关键词: 沪港通, 融资约束, 投资效率, 创新驱动

Abstract:

The construction of the two-way opening of China’s capital market has become a prominent issue for the Chinese government since the 18^th National Congress of the Communist Party of China. Previous studies have analyzed the effect of the capital market liberalization on the macro-economy growth and volatility, market volatility and risk, market linkage and efficiency, business performance and investment, etc. By using data from the annual reports of listed companies in Shanghai stock exchange from 2012 to 2017 and constructing the policy transmission mechanisms for financing constraints, this paper makes a comprehensive analysis on the effects that Shanghai-Hongkong Stock Connect Policy has on firms’ investment efficiency and explores the underlying micro-economic connotation from the perspective of the innovation-driven investment.
Specifically, we first adopt the PSM/DID/Treatment Effect and other causal inference methods to test the effect of Shanghai-Hongkong Stock Connect Policy on the financing constraints and the investment efficiency of the constituent stocks. Result shows that the financing constraints of the underlying stocks have declined significantly since the implementation of Shanghai-Hongkong Stock Connect Policy. After classifying the “underlying stocks” into the “insufficient investment group” and the “excessive investment group”, the study finds that the Shanghai-Hongkong Stock Connect Policy elevates the investment efficiency of the “insufficient investment group” by softening the financing constraints but promotes the inefficiency of the “excessive investment group” due to the loosened constraints. This provides empirical evidence for the heterogeneous effect of the capital market liberalization on the investment efficiency of entity enterprises. Finally, we use the Treatment Effect Method to test whether the alleviated “R&D financing constraints” improve the investment efficiency of the companies with excessive investment. Result shows that though the Shanghai-Hongkong Stock Connect Policy offers “direct” impetus for excessive investment, it “indirectly” lifts firms’ ability to upgrade the production capacity and thus frustrates the excessive investment by improving the R&D investment. This also provides rational and empirical reference for understanding how the capital market liberalization synergizes the innovation-driven investment and further optimizes the growth quality of the real economy.
Potential contributions of this article are as follows: (1) Through the construction of the policy transmission mechanisms for financing constraints, this paper illustrates and empirically tests the “heterogeneous effect” of the Shanghai-Hongkong Stock Connect Policy on the investment efficiency, thereby further “dialectically” reflecting on the actual effect of the policy and expanding the research perspective of the interactive relationship between the Shanghai-Hongkong Stock Connect Policy and the investment efficiency; (2) By proving that the Shanghai-Hongkong Stock Connect Policy can relieve the R&D financing constraints, motivate innovation and “indirectly” perfect the investment efficiency, we reexamine the positive effects of the capital market liberalization on the innovation synergy and improvement of the growth quality of the real economy, and incorporate opening-up, innovation and growth to a cohesive analytical framework.

Key words: Shanghai-Hongkong Stock Connect Policy, Financing Constraints, Investment Efficiency, Innovation-driven Investment

中图分类号:

F831.4

于博, 吴菡虹. 资本市场开放提高企业投资效率了吗?——基于“沪港通”政策的异质性影响分析[J]. 财经论丛, 2021, 37(12): 70-80.

YU Bo, WU Hanhong. Does Capital Market Liberalization Improve Firms’ Investment Efficiency?Heterogeneity Analysis Based on Shanghai-Hongkong Stock Connect Policy[J]. Collected Essays on Finance and Economics, 2021, 37(12): 70-80.

图/表 10

参考文献 22

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变量	含义	计量
SA	融资约束代理变量	-0.737* 公司总资产自然对数+0.043* 公司总资产自然对数²-0.04* 公司年龄^[20]
BIAS_over	过度投资代理变量	投资方程正残差^[21]
BIAS_under	投资不足代理变量	投资方程负残差的绝对值^[21]
PB	市净率	每股股价与每股净资产的比率
Liq	股票流动性	流通股比例,即流通股占总股本的比率
List	分组虚拟变量	是否列入沪港通,列入沪港通取1,不列入取0
Period	政策冲击虚拟变量	政策实施期(2015-2017年)取1,非政策实施期(2012-2014年)取0
ListPeriod*	DID交叉项	仅当股票既列入沪港通,又在政策实施期内时取1
Lev	杠杆水平	资产负债率,即负债总额占资产总额的比率
变量	含义	计量
Cash	现金持有水平	货币资金与交易性金融资产之和占总资产的比率
FixGth	抵押融资能力	固定资产投资增长率
TOP10	股权集中度	前十大股东持股比例合计
Independence	独立董事比例	独立董事人数占董事总人数的比率
Seperation	两权分离情况	董事长与总经理兼任情况1=同一人;0=不同一人;
Management	管理费用率	管理费用占营业总收入的比率
R&D	研发支出	研发支出占总资产的比率
Year	年度	年度虚拟变量
DumInd	行业	行业虚拟变量(根据所属证监会行业分类)

变量	含义	计量
SA	融资约束代理变量	-0.737* 公司总资产自然对数+0.043* 公司总资产自然对数²-0.04* 公司年龄^[20]
BIAS_over	过度投资代理变量	投资方程正残差^[21]
BIAS_under	投资不足代理变量	投资方程负残差的绝对值^[21]
PB	市净率	每股股价与每股净资产的比率
Liq	股票流动性	流通股比例,即流通股占总股本的比率
List	分组虚拟变量	是否列入沪港通,列入沪港通取1,不列入取0
Period	政策冲击虚拟变量	政策实施期(2015-2017年)取1,非政策实施期(2012-2014年)取0
ListPeriod*	DID交叉项	仅当股票既列入沪港通,又在政策实施期内时取1
Lev	杠杆水平	资产负债率,即负债总额占资产总额的比率
变量	含义	计量
Cash	现金持有水平	货币资金与交易性金融资产之和占总资产的比率
FixGth	抵押融资能力	固定资产投资增长率
TOP10	股权集中度	前十大股东持股比例合计
Independence	独立董事比例	独立董事人数占董事总人数的比率
Seperation	两权分离情况	董事长与总经理兼任情况1=同一人;0=不同一人;
Management	管理费用率	管理费用占营业总收入的比率
R&D	研发支出	研发支出占总资产的比率
Year	年度	年度虚拟变量
DumInd	行业	行业虚拟变量(根据所属证监会行业分类)

变量	均值	中值	25%分位	75%分位	最小值	最大	标准差
SA	-3.82	-3.83	-3.96	-3.70	-4.31	-3.05	0.21
BIAS_over	0.15	0.12	0.06	0.21	0.00	0.76	0.12
BIAS_under	0.14	0.12	0.06	0.20	0.00	0.57	0.11
TOP10	0.54	0.54	0.42	0.64	0.20	0.89	0.15
Lev	0.52	0.51	0.36	0.67	0.09	0.96	0.21
FixGth	0.24	0.19	0.09	0.36	0.00	0.74	0.19
Cash	0.16	0.13	0.09	0.21	0.01	0.58	0.11
Independence	0.37	0.35	0.33	0.40	0.33	0.57	0.05
Separation	0.14	0.00	0.00	0.00	0.00	1.00	0.35
Management	0.10	0.07	0.04	0.11	0.01	0.79	0.11

变量	均值	中值	25%分位	75%分位	最小值	最大	标准差
SA	-3.82	-3.83	-3.96	-3.70	-4.31	-3.05	0.21
BIAS_over	0.15	0.12	0.06	0.21	0.00	0.76	0.12
BIAS_under	0.14	0.12	0.06	0.20	0.00	0.57	0.11
TOP10	0.54	0.54	0.42	0.64	0.20	0.89	0.15
Lev	0.52	0.51	0.36	0.67	0.09	0.96	0.21
FixGth	0.24	0.19	0.09	0.36	0.00	0.74	0.19
Cash	0.16	0.13	0.09	0.21	0.01	0.58	0.11
Independence	0.37	0.35	0.33	0.40	0.33	0.57	0.05
Separation	0.14	0.00	0.00	0.00	0.00	1.00	0.35
Management	0.10	0.07	0.04	0.11	0.01	0.79	0.11

SA全样本	2015年融资约束水平			2016年融资约束水平			2017年融资约束水平
SA全样本	ATT	标准差	T值	ATT	标准差	T值	ATT	标准差	T值
近邻匹配	0.0790^***	0.0181	4.37	0.0914^***	0.0205	4.45	0.1159^***	0.0203	5.72
半径匹配	0.0729^***	0.0118	6.18	0.0837^***	0.0126	6.64	0.0989^***	0.0140	7.04
核匹配	0.0722^***	0.0123	5.89	0.0833^***	0.0138	6.03	0.0994^***	0.0147	6.74
BIAS_over (过度投足组)	2015年过度投资水平			2016年过度投资水平			2017年过度投资水平
BIAS_over (过度投足组)	ATT	标准差	T值	ATT	标准差	T值	ATT	标准差	T值
近邻匹配	0.0809^***	0.0189	4.53	0.0875^***	0.0173	5.05	0.0760^***	0.0177	4.30
半径匹配	0.0837^***	0.0130	6.42	0.0763^***	0.0141	5.42	0.0772^***	0.0130	5.94
核匹配	0.0836^***	0.0135	6.20	0.0756^***	0.0130	5.82	0.0768^***	0.0139	5.51
BIAS_under (投资不足组)	2015年投资不足水平			2016年投资不足水平			2017年投资不足水平
BIAS_under (投资不足组)	ATT	标准差	T值	ATT	标准差	T值	ATT	标准差	T值
近邻匹配	-0.0880^***	0.0232	-3.79	-0.0981^***	0.0193	-5.08	-0.0930^***	0.0210	-4.42
半径匹配	-0.0915^***	0.0126	-7.29	-0.1077^***	0.0101	-10.63	-0.0948^***	0.0117	-8.14
核匹配	-0.0915^***	0.0126	-7.27	-0.1070^***	0.0103	-10.43	-0.0963^***	0.0120	-8.00