Beyond structure: Structure conformity of local fiscal expenditure on S&T and regional innovation

Abstract

Abstract:

In the context of fiscal constraints faced by local governments, it is an imperative issue to improve the allocation of science and technology (S&T) expenditure and enhance the efficiency of regional innovation systems. Research and development activities can be divided into basic research, applied research, and experimental development. Based on the resource-based view, extant studies suggest that the structure of local S&T expenditure as a critical resource endowment, directly shapes innovation performance. Beyond the resource-based view, local governments must weigh central mandates and peer competition—rather than efficiency alone—when setting S&T budgets, owing to multidimensional performance metrics.

Extant literature shows that local governments exhibit two distinctive traits when allocating S&T expenditure under the institutional pressure. First, local government complies the S&T strategies of central government. Within China’s centralized political system, subnational governments consistently align their fiscal priorities with those of the central government. When a national S&T initiative is announced, local governments rapidly mobilize resources to establish similar projects—such as provincial-level science parks, key laboratories, and engineering research centers—that closely reflect the central policy blueprint. Second, there is a convergence in S&T expenditure across local governments. As fiscal S&T expenditure has become a key performance metric in governmental evaluation systems, competition among local governments in the S&T domain has significantly intensified. In pursuit of competition advantage, local officials routinely benchmark their S&T expenditures against peer regions and recalibrate their budgetary allocations in response. This strategic behavior results in a noticeable homogenization of S&T funding patterns across local governments.

Although existing studies indicate that local governments align their fiscal S&T expenditures with both central and peer governments, few studies have examined the impact of such conformity on regional innovation performance. Furthermore, while prior research has mainly examined convergence in the scale of S&T expenditure, little attention has been given to structural conformity in fiscal S&T expenditure. Under the current fiscal constraints, how local governments choose the structure of S&T expenditures to improve regional innovation performance is a critical issue.Based on organizational legitimacy theory, this study examines the relationship between compliance, convergence of local government of S&T expenditure structure and regional innovation, as well as the moderating role of local official turnover. Using an unbalanced panel dataset from 31 provinces (excluding Hong Kong, Macao, and Taiwan) from 2013 to 2022, we employ a fixed-effects ordinary least squares (OLS) model.

The findings reveal that compliance with central government in fiscal S&T expenditure structure is positively associated with regional innovation. That is, when local governments align their S&T expenditure structure with that of the central government, they gain access to central S&T resources and policy support, thereby fostering regional innovation. Conversely, there is an inverted U-shaped relationship between convergence with peer governments and regional innovation. The moderate level of conformity in S&T expenditure structure among local governments helps accumulate R&D resources and facilitates innovation; however, beyond a certain threshold, the costs of homogenization outweigh the legitimacy benefits, ultimately hindering regional innovation. Furthermore, the local official turnover weakens the positive relationship between compliance and regional innovation but does not significantly affect the relationship between convergence and regional innovation.

Key words: organizational legitimacy, structure conformity, fiscal expenditure on S&T, local government, central government, regional innovation

摘要：

我国地方财政科技支出增速放缓,如何进一步优化地方财政科技支出决策,提升区域创新水平,成为亟待解决的现实问题。本文从组织合法性视角出发,探讨了地方政府在面临中央政府制度约束和同级地方政府竞争背景下,如何进行科技财政一致性决策获取合法性,以促进自身创新发展,具体研究了地方财政科技支出结构的遵从一致性和趋同一致性与区域创新的关系,以及地方官员变更的调节作用。本文利用固定效应OLS模型,对2013-2022年我国31个省级行政区域(香港、澳门、台湾除外)的面板数据开展实证研究。研究结果表明:地方财政科技支出结构遵从一致性与区域创新之间呈正向关系,即地方财政科技支出结构与中央政府保持一致,通过获取中央科技资源支持促进区域创新发展;而趋同一致性与区域创新之间呈倒U型关系,即地方政府间保持适度相似,能够积累研发要素促进区域创新,然而超过某一阈值后,追求同质性成本大于合法性收益,不利于区域创新。此外,地方官员变更削弱了遵从一致性与区域创新之间的正向关系,但并未对趋同一致性与创新之间的关系产生影响。本文丰富了组织合法性视角下政府行为一致性的效果研究,为地方财政科技支出战略决策提供有益参考。

关键词: 组织合法性, 行为一致性, 科技支出结构, 地方政府, 中央政府, 区域创新

CLC Number:

ZHANG Bo, SUN Yu-tao. Beyond structure: Structure conformity of local fiscal expenditure on S&T and regional innovation[J]. Studies in Science of Science, 2026, 44(10): 2194-2206.

张博, 孙玉涛. 超越结构:地方财政科技结构一致与区域创新[J]. 科学学研究, 2026, 44(10): 2194-2206.

Figures/Tables 8

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	变量名称	变量符号	变量测量
因变量	区域创新	Innovation	利用该地区每万人发明专利授权量衡量区域创新水平,单位为件/万人。
自变量	遵从一致性	Compliance	利用余弦相似系数,计算该地区与中央政府的科技支出科目的一致程度。
自变量	趋同一致性	Convergence	利用余弦相似系数,计算该地区与同级政府科技支出平均水平的科目一致程度。
调节变量	地方官员变更	Turnover	借鉴以往研究,若该地区省委书记或省长发生变更时记为1,否则记为0。
控制变量	经济发展水平	GDP	利用该地区人均GDP数值衡量,单位为亿元/万人。
	产业发展水平	Industry	利用该地区第二产业增加值占GDP比重衡量产业发展程度。
	人力资本水平	HC	利用该地区每百万人在校大学生数量衡量人力资本水平。
	财政投入水平	Fiscal	利用该地区人均财政支出数额衡量财政投入水平,单位为亿元/万人。
	市场活跃程度	Market	利用该地区技术市场交易额占GDP比重测量市场交易活跃程度。

	变量名称	变量符号	变量测量
因变量	区域创新	Innovation	利用该地区每万人发明专利授权量衡量区域创新水平,单位为件/万人。
自变量	遵从一致性	Compliance	利用余弦相似系数,计算该地区与中央政府的科技支出科目的一致程度。
自变量	趋同一致性	Convergence	利用余弦相似系数,计算该地区与同级政府科技支出平均水平的科目一致程度。
调节变量	地方官员变更	Turnover	借鉴以往研究,若该地区省委书记或省长发生变更时记为1,否则记为0。
控制变量	经济发展水平	GDP	利用该地区人均GDP数值衡量,单位为亿元/万人。
	产业发展水平	Industry	利用该地区第二产业增加值占GDP比重衡量产业发展程度。
	人力资本水平	HC	利用该地区每百万人在校大学生数量衡量人力资本水平。
	财政投入水平	Fiscal	利用该地区人均财政支出数额衡量财政投入水平,单位为亿元/万人。
	市场活跃程度	Market	利用该地区技术市场交易额占GDP比重测量市场交易活跃程度。

省份	遵从一致性		趋同一致性		省份	遵从一致性		趋同一致性
省份	2015年	2022年	2015年	2022年	省份	2015年	2022年	2015年	2022年
安徽	0.90	0.15	0.79	0.63	辽宁	0.74	0.69	0.57	0.90
北京	0.54	0.89	0.97	0.76	内蒙古	0.32	0.80	0.30	0.85
福建	0.51	0.81	0.97	0.83	宁夏	0.15	0.15	0.60	0.60
甘肃	0.24	0.90	0.89	0.86	青海	0.39	0.67	0.92	0.72
广东	0.78	0.64	0.88	0.75	山东	0.68	0.61	0.56	0.90
广西	0.68	0.36	0.96	0.81	山西	0.88	0.43	0.80	0.66
贵州	0.43	0.80	0.94	0.65	陕西	0.16	0.60	0.83	0.72
海南	0.31	0.53	0.86	0.71	上海	0.21	0.56	0.85	0.82
河北	0.59	0.76	0.97	0.90	四川	0.26	0.91	0.48	0.86
河南	0.67	0.37	0.88	0.83	天津	0.48	0.37	0.95	0.78
黑龙江	0.47	0.73	0.90	0.83	西藏	0.14	0.10	0.85	0.60
湖北	0.12	0.15	0.81	0.59	新疆	0.65	0.88	0.89	0.87
湖南	0.62	0.79	0.89	0.91	云南	0.30	0.66	0.92	0.74
吉林	0.56	0.83	0.84	0.86	浙江	0.62	0.64	0.75	0.64
江苏	0.62	0.68	0.98	0.86	重庆	0.28	0.70	0.91	0.93
江西	0.43	0.71	0.82	0.99

省份	遵从一致性		趋同一致性		省份	遵从一致性		趋同一致性
省份	2015年	2022年	2015年	2022年	省份	2015年	2022年	2015年	2022年
安徽	0.90	0.15	0.79	0.63	辽宁	0.74	0.69	0.57	0.90
北京	0.54	0.89	0.97	0.76	内蒙古	0.32	0.80	0.30	0.85
福建	0.51	0.81	0.97	0.83	宁夏	0.15	0.15	0.60	0.60
甘肃	0.24	0.90	0.89	0.86	青海	0.39	0.67	0.92	0.72
广东	0.78	0.64	0.88	0.75	山东	0.68	0.61	0.56	0.90
广西	0.68	0.36	0.96	0.81	山西	0.88	0.43	0.80	0.66
贵州	0.43	0.80	0.94	0.65	陕西	0.16	0.60	0.83	0.72
海南	0.31	0.53	0.86	0.71	上海	0.21	0.56	0.85	0.82
河北	0.59	0.76	0.97	0.90	四川	0.26	0.91	0.48	0.86
河南	0.67	0.37	0.88	0.83	天津	0.48	0.37	0.95	0.78
黑龙江	0.47	0.73	0.90	0.83	西藏	0.14	0.10	0.85	0.60
湖北	0.12	0.15	0.81	0.59	新疆	0.65	0.88	0.89	0.87
湖南	0.62	0.79	0.89	0.91	云南	0.30	0.66	0.92	0.74
吉林	0.56	0.83	0.84	0.86	浙江	0.62	0.64	0.75	0.64
江苏	0.62	0.68	0.98	0.86	重庆	0.28	0.70	0.91	0.93
江西	0.43	0.71	0.82	0.99

变量	1	2	3	4	5	6	7	8	9
1 Innovation	1
2 Compliance	0.165^***	1
3 Convergence	-0.048	0.159^***	1
4 Turnover	-0.083	-0.033	0.059	1
5 Gdp	0.784^***	0.109^*	-0.121^**	-0.113^**	1
6 Industry	-0.489^***	-0.076	-0.065	0.075	-0.309^***	1
7 HC	0.520^***	0.041	0.042	-0.027	0.560^***	-0.335^***	1
8 Fiscal	0.318^***	-0.232^***	-0.202^***	-0.083	0.342^***	-0.390^***	0.110^*	1
9 Market	0.832^***	0.011	-0.117^**	-0.109^*	0.610^***	-0.535^***	0.579^***	0.439^***	1
Min	0.10	0.04	0.24	0	2.31	0.16	31.88	0.59	0.39
Max	40.35	0.96	0.99	1	19.05	0.57	275.54	7.12	28.98
Std.	4.62	0.24	0.13	0.46	3.05	0.08	45.58	0.92	4.43
Mean	2.59	0.51	0.79	0.30	6.37	0.41	123.33	1.59	3.94
Obs.	310	285	285	310	310	310	310	310	310