Research on the impact of digital inclusive finance on the contribution rate of agricultural science and technology progress in China-An empirical study based on 31 interprovincial panel data

doi:10.6048/j.issn.1001-4330.2024.S1.032

Abstract

Abstract:

【Objective】 With the development of digital inclusive finance, its financial inclusiveness, universality and diversity of service types are of great significance to the improvement and development of the contribution rate of agricultural scientific and technological progress.【Methods】 This paper systematically examines the impact of digital inclusive finance on the contribution rate of agricultural science and technology progress based on the panel data of 31 provincial administrative units in China from 2011 to 2020.【Results】 The results show that: digital financial inclusion can significantly increase the contribution rate of agricultural science and technology progress, and the conclusion is still robust after replacing the econometric model, but there is dimensional heterogeneity and regional heterogeneity in its impact; the breadth of financial coverage and the depth of financial use positively affect the contribution rate of agricultural science and technology progress, while the degree of digitization is negatively affecting it; digital financial inclusion has a positive impact on the contribution rate of agricultural science and technology progress in the eastern and central regions, but not in the western regions; and digital financial inclusion has a negative impact on the contribution rate of agricultural science and technology progress in the western regions.The analysis of spatial effects shows that the contribution rate of agricultural science and technology progress shows a positive spatial spillover effect, and digital financial inclusion has a significant positive effect on the local contribution rate of agricultural science and technology progress, while it is not conducive to the improvement of the contribution rate of agricultural science and technology progress in neighboring regions.【Conclusion】 Therefore, the development of digital inclusive finance in rural areas should be further strengthened, the digital literacy and financial knowledge of rural residents should be improved, and the development of digital inclusive finance should be adapted to local conditions to promote the coordinated development of regions.

Key words: digital inclusive finance; contribution rate of technological progress; digital literacy; knowledge

摘要：

【目的】分析数字普惠金融对我国农业科技进步贡献率的影响。【方法】基于2011~2020年我国31个省级行政单的面板数据,系统考察了数字普惠金融对农业科技进步贡献率的影响。【结果】数字普惠金融可以显著提高农业科技进步贡献率,在更换计量模型后结论依旧稳健,但其影响存在维度异质性和区域异质性;金融覆盖广度和金融使用深度正向影响农业科技进步贡献率,而数字化程度则是负向影响;数字普惠金融在东中部地区对农业科技进步贡献率具有正向影响,却并不利于西部地区农业科技进步贡献率的发展;农业科技进步贡献率表现出正向的空间溢出效应,数字普惠金融对当地的农业科技进步贡献率具有显著的正向影响,而不利于相邻地区的农业科技进步贡献率的提高。【结论】应进一步加强数字普惠金融在农村的发展,提高农村地区居民的数字素养和金融知识储备,因地制宜的发展数字普惠金融促进地区间的协调发展。

关键词: 数字普惠金融, 科技进步贡献率, 数字素养, 知识储备

CLC Number:

ZHU Wenbin, SUN Xu, CHENG Yulan. Research on the impact of digital inclusive finance on the contribution rate of agricultural science and technology progress in China-An empirical study based on 31 interprovincial panel data[J]. Xinjiang Agricultural Sciences, 2024, 61(S1): 206-216.

朱文斌, 孙旭, 陈玉兰. 数字普惠金融对我国农业科技进步贡献率的影响[J]. 新疆农业科学, 2024, 61(S1): 206-216.

Figures/Tables 8

Tab.1 Descriptive statistics of variables

	变量 Variant	单位 Unit	均值 Average value	标准误差 Standard error	最小值 Minimum values	最大值 Maximum values
被解释变量 Explained variable	农业科技进步贡献率 (GTAP)	%	33.694	21.380	2.714	97.079
解释变量 Explanatory variable	数字普惠金融总指数(DIF)	-	216.235	97.030	16.220	431.927
	覆盖广度(COV)	-	196.669	96.556	1.960	397.001
	使用深度(DEP)	-	211.121	98.187	6.760	488.683
	数字化程度(DIG)	-	290.142	117.252	7.580	462.227
控制变量 Control variable	城镇化率(urb)	%	58.021	13.179	22.710	89.600
	固定资产投资(fai)	%	1.747	1.029	0.010	5.086
	农业财政支出(afe)	%	13.507	8.957	1.993	54.799
	产业结构高级化(iss)	-	2.395	0.122	2.132	2.834
	科技创新发展(innov)	专利数量/万人	11.177	13.152	0.382	74.383

Tab.2 Benchmark regression results

	(1)	(2)	(3)	(4)	(5)	(6)
DIF	0.135^***	0.280^***	0.299^***	0.296^***	0.307^***	0.305^***
DIF	(0.036)	(0.031)	(0.029)	(0.029)	(0.033)	(0.033)
urb		0.777^***	0.699^***	0.591^***	0.492^***	0.482^***
urb		(0.112)	(0.107)	(0.102)	(0.098)	(0.096)
afe			0.099^*	0.12 ${7^{}}^{}$	0.123^*	0.119^*
afe			(0.048)	(0.053)	(0.055)	(0.055)
fai				0.080	0.084	0.081
fai				(0.054)	(0.053)	(0.050)
innov					-0.048	-0.044
innov					(0.027)	(0.026)
iss						0.592
iss						(0.495)
常数项 Constant term	2.599^***	-1.291^*	-1.31 ${5^{}}^{}$	-0.946^*	-0.507	-0.974
常数项 Constant term	0.135^***	0.280^***	0.299^***	0.296^***	0.307^***	0.305^***
个体固定 Individual fixation	YES	YES	YES	YES	YES	YES
时间固定 Fixed time	YES	YES	YES	YES	YES	YES
R²	0.963 5	0.964 9	0.965 2	0.965 5	0.965 5	0.965 5
F	13.661 3	40.916 6	38.424 3	32.224 2	25.769 4	21.047 3
N	310	310	310	310	310	310

Tab.2 Benchmark regression results

	(1)	(2)	(3)	(4)	(5)	(6)
DIF	0.135^***	0.280^***	0.299^***	0.296^***	0.307^***	0.305^***
DIF	(0.036)	(0.031)	(0.029)	(0.029)	(0.033)	(0.033)
urb		0.777^***	0.699^***	0.591^***	0.492^***	0.482^***
urb		(0.112)	(0.107)	(0.102)	(0.098)	(0.096)
afe			0.099^*	0.12 ${7^{}}^{}$	0.123^*	0.119^*
afe			(0.048)	(0.053)	(0.055)	(0.055)
fai				0.080	0.084	0.081
fai				(0.054)	(0.053)	(0.050)
innov					-0.048	-0.044
innov					(0.027)	(0.026)
iss						0.592
iss						(0.495)
常数项 Constant term	2.599^***	-1.291^*	-1.31 ${5^{}}^{}$	-0.946^*	-0.507	-0.974
常数项 Constant term	0.135^***	0.280^***	0.299^***	0.296^***	0.307^***	0.305^***
个体固定 Individual fixation	YES	YES	YES	YES	YES	YES
时间固定 Fixed time	YES	YES	YES	YES	YES	YES
R²	0.963 5	0.964 9	0.965 2	0.965 5	0.965 5	0.965 5
F	13.661 3	40.916 6	38.424 3	32.224 2	25.769 4	21.047 3
N	310	310	310	310	310	310

Tab.3 Robustness tests

项目Items	OLS	FE	FE	2SLS
dif	0.370^***(0.100)			0.483^***(0.109)
L.idf		0.155^***(0.026)
L2.dif			0.128^***(0.023)
控制变量Control variable	控制	控制	控制	控制
个体固定Individual fixation	YES	YES	YES	YES
时间固定Fixed time	YES	YES	YES	YES

Tab.4 Regression results of different dimensions on the contribution rate of scientific and technological progress

项目 Items	(1) 覆盖广度 Breadth of coverage	(2) 使用深度 Depth of use	(3) 数字化程度 Degree of digitization
COV	0.086^*** (0.013)
DEP		0.255^*** (0.027)
DIG			-0.231^*** (0.062)
控制变量 Control variable	YES	YES	YES
双向固定 Bidirectional fixation	YES	YES	YES
R²	0.969 8	0.971 3	0.971 4
常数项 Constant term	0.536 (0.470)	-0.399 (0.583)	3.204 (1.718)

Tab.5 Regression results on the contribution of different regions to scientific and technological progress

项目 Items	东部 Eastem	中部 Central section	西部 Western
DIF	0.553^*** (0.098)	0.251^** (0.091)	-0.121^** (0.049)
控制变量 Control variable	YES	YES	YES
双向固定 Bidirectional fixation	YES	YES	YES
R²	0.933 4	0.972 1	0.964 5
常数项 Constant term	-9.199^** (2.929)	-9.926^** (4.345)	5.438 (1.046)
N	90	130	90

Tab.6 Spatial autocorrelation test

年份 Vintage	农业科技进步贡献率 (GTAP)			数字普惠金融 (DIF)
年份 Vintage	Moran’s I	Z值	P值	Moran’s I	Z值	P值
2011	0.381	2.859	0.004	0.639	4.450	0.000
2012	0.333	2.455	0.014	0.704	4.943	0.000
2013	0.328	2.428	0.015	0.637	4.505	0.000
2014	0.333	2.447	0.014	0.614	4.352	0.000
2015	0.335	2.455	0.014	0.561	4.010	0.000
2016	0.285	2.119	0.034	0.629	4.476	0.000
2017	0.290	2.149	0.032	0.624	4.450	0.000
2018	0.275	2.049	0.040	0.609	4.319	0.000
2019	0.279	2.069	0.039	0.625	4.420	0.000
2020	0.247	1.870	0.061	0.639	4.505	0.000

Tab.7 Robustness test of different models to regression results

变量 Variant	空间滞后模型 SAR	空间误差模型 SEM	空间杜宾模型 SDM
DIF	0.501^*** (0.094)	0.563^*** (0.103)	0.685^*** (0.122)
W*DIF			-0.307^** (0.153)
rho	0.168^*** (0.052)		0.178^*** (0.057)
lambda		0.196^*** (0.058)
Sigma2_e	0.022^*** (0.002)	0.022^*** (0.002)	0.019^*** (0.002)
Log-likehood	150.140	150.455	165.441
R²	0.385 2	0.432 5	0.223 6
N	310	310	310

Tab.8 Results of spatial spillover effects of digital financial inclusion on the rate of progress in agricultural science

变量 Variant	总效应 Aggregate effect	直接效应 Direct effect	间接效应 Indirect effect
DIF	0.444^*** (0.115)	0.675^*** (0.117)	-0.231^* (0.136)

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