农村电子商务发展对林区内部收入差距与共同富裕的影响

doi:10.11707/j.1001-7488.LYKX20230525

Abstract

Abstract:

Objective: In the process of realizing a Chinese-style modernization with shared prosperity for all citizens, this study examines the impact and mechanisms of rural e-commerce development on income gap and shared prosperity in forested areas. It aims to provide valuable insights for reducing income gap within rural communities, achieving an organic unity of efficiency and equity, and promoting shared prosperity. Method: The study treats the“comprehensive demonstration policy of e-commerce into rural areas”as a quasi-natural experiment for the development of rural e-commerce and utilizes five waves of panel data from the China family panel studies (CFPS) spanning from 2012 to 2020. It employs a supervised double machine learning method to analyze the impact and mechanisms of rural e-commerce development on both the macro-level village-level intra-regional income gap among all forest farmer households within each forested village and the micro-level intra-regional income gap among individual forest farmer households within each village, which can help to answer the question of how rural e-commerce development contributes to shared prosperity. Result: 1) Rural e-commerce development significantly reduces the gini coefficient of annual income for all forest farmer households within each forested villages and the relative deprivation index among individual forest farmer households within each forested village, implying that rural e-commerce can effectively lower income gap within forested areas. These results remain robust after a series of sensitivity tests. 2) The reduction of income gap within forested areas due to rural e-commerce development is primarily achieved by substantially increasing the income of low-income forest farmer households that below the 40th percentile and below the mean income, thereby promoting shared prosperity. 3) The promotion of non-agricultural employment among forest farmer households, the enhancement of entrepreneurial activities among forest farmer households, and the increase in the value of agricultural products are the primary pathways through which rural e-commerce development reduces income gap within forested areas. 4) Rural e-commerce development has a greater income-increasing effect on forest farmer households with low skill levels, low social capital, and below the poverty line, indicating its inclusive characteristic. Conclusion: Through an empirical study with a large micro-database, the balancing effect between equity and efficiency demonstrated by rural e-commerce as an important manifestation of the digital economy in rural forest areas is verified. Under the wave of digital economy development, this study not only provides new empirical evidence of rural e-commerce in narrowing the internal income gap in forest areas, but also provides important policy insights for promoting common prosperity.

Key words: rural e-commerce development, shared prosperity, income gap, double machine learning

CLC Number:

S7-9
F320

Dan Pan,Luyi Luo,Kaiwen Ji,Fanbin Kong. Impact of Rural E-Commerce Development on Intra-Regional Income Gap and Shared Prosperity in Forested Areas[J]. Scientia Silvae Sinicae, 2024, 60(5): 35-50.

Figures/Tables 9

Fig.1

Table 1

Variable definitions and descriptive statistics"

变量类型 Variable type	变量名称 Variable name	变量定义赋值及单位 Variable definition and units	均值 Mean value	标准差Standard deviation
因变量 Dependent variable	林区各村庄内部所有林农家庭收入差距 Intra-regional income gap among all forest farmer households within each forested village	林区各村庄内部所有林农家庭年收入的基尼系数 Gini coefficient of annual income for all forest farmer households within each forested village	0.401	0.122
		林区各村庄内部所有林农家庭年收入的泰尔指数 Theil index of annual income for all forest farmer households within each forested villages	0.319	0.212
		林区各村庄内部所有林农家庭年收入的MLD指数 MLD index of annual income for all forest farmer households within each forested villages	0.406	0.268
		林区各村庄内部所有林农家庭年收入的RMD指数 RMD index of annual income for all forest farmer households within each forested villages	0.309	0.102
	各村庄内部单个林农家庭之间收入差距 Intra-regional income gap among individual forest farmer households within each forested village	林区各村庄内部单个林农家庭年收入的$ \mathrm{K}\mathrm{a}\mathrm{k}\mathrm{w}\mathrm{a}\mathrm{n}\mathrm{i} $指数 $ \mathrm{K}\mathrm{a}\mathrm{k}\mathrm{w}\mathrm{a}\mathrm{n}\mathrm{i} $ index of annual income for individual forest farmer household within each forested village	0.411	0.293
		林区各村庄内部单个林农家庭年收入的$ \mathrm{P}\mathrm{o}\mathrm{d}\mathrm{d}\mathrm{e}\mathrm{r} $指数 $ \mathrm{P}\mathrm{o}\mathrm{d}\mathrm{d}\mathrm{e}\mathrm{r} $ index of annual income for individual forest farmer household within each forested villages	0.521	0.657
核心解释变量 Main explanatory variable	农村电子商务发展 Development of rural e-commerce	林农家庭$ i $所在的县区当年是否被“电子商务进农村综合示范政策”所覆盖：1=是，0=否 Whether the county where the forest farmer households $ i $ located is covered by “comprehensive demonstration policy of e-commerce into rural areas” in that year: 1 = Yes, 0 = No	0.289	0.453
控制变量 Control variables	户主年龄 Household head’s age	户主实际年龄（岁） Actual age of the head of the household (years)	50.931	12.234
	户主性别 Household head’s gender	户主性别：1=男，0=女 Gender of the head of the household: 1 = male, 0 = female	0.602	0.489
	户主受教育程度 Household head’s education level	户主受教育程度：1=文盲，2=小学，3=初中，4=高中， 5=大专，6=本科，7=硕士，8=博士 Household head’s education level: 1 = illiterate, 2 = primary school, 3 = junior high school, 4 = high school, 5 =associate degree, 6 = bachelor’s degree, 7 = master’s degree, 8 = doctorate	2.160	1.051
	户主婚姻情况Household head’s marital status	户主婚姻状况：1=在婚、同居，0=未婚、离婚、丧偶 Household head’s marital status: 1 = married or living together; 0 = unmarried, divorced, or widowed	0.871	0.335
	户主健康程度 Household head’s health status	户主健康程度：1=非常健康，2=很健康，3=比较健康， 4=一般，5=不健康 Household head’s health status: 1 = very healthy, 2 = quite healthy, 3 = fairly healthy, 4 = moderately healthy, 5 = unhealthy	3.236	1.270
	家庭规模 Family size	家庭成员数量 Number of family members (people)	4.326	1.919
	家庭房产情况 Property ownership	家庭房产总值 Total value of family real estate/10⁴ yuan	18.000	68.000
	家庭金融资产 Family financial assets	家庭金融资产总值 Total value of family financial assets/10⁴ yuan	2.400	6.600
	家庭生产性固定资产 Family productive fixed assets	家庭生产性固定资产总值 Total value of family productive fixed assets/10⁴ yuan	1.700	48.000
	家庭年龄结构 Family’s age structure	家庭65岁以上的老年人人口数/家庭成年人人口数 Number of elderly individuals aged 65 and above in the family divided by the number of adult individuals in the family	0.128	0.334
	县域产业结构 County-level industrial structure	县域第二产业增加值/县域地区生产总值 County-level secondary industry value added divided by the county-level regional GDP	0.337	0.152
	县域人口密度 County-level population density	县域年末人口总数/县域行政区域面积 Total population at the end of the year in the county divided by the administrative area of the county ( ten thousand people per square kilometer)	263.608	210.249
	县域财政自给率 County-level fiscal self-sufficiency rate	县域一般公共预算收入/县域一般公共预算支出 General public budget revenue at the county level divided by general public budget expenditure at the county level	0.277	0.235

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变量 Variables	基尼系数Gini coefficient	泰尔系数Theil coefficient	MLD指数MLD index	RMD指数RMD index
农村电子商务发展 Rural e-commerce development	?0.017*** （0.006）	?0.028*** （0.010）	?0.069*** （0.012）	?0.016*** （0.005）
控制变量Control variables	是Yes	是Yes	是Yes	是Yes
地区固定效应Regional fixed effects	是Yes	是Yes	是Yes	是Yes
时间固定效应 Time fixed effects	是Yes	是Yes	是Yes	是Yes
样本量Sample size	952	952	952	952

变量Variables	$ \mathrm{K}\mathrm{a}\mathrm{k}\mathrm{w}\mathrm{a}\mathrm{n}\mathrm{i} $指数 $ \mathrm{K}\mathrm{a}\mathrm{k}\mathrm{w}\mathrm{a}\mathrm{n}\mathrm{i} $ index	$ \mathrm{P}\mathrm{o}\mathrm{d}\mathrm{d}\mathrm{e}\mathrm{r} $指数 $ \mathrm{P}\mathrm{o}\mathrm{d}\mathrm{d}\mathrm{e}\mathrm{r} $ index
农村电子商务发展 Rural e-commerce development	?0.018***（0.004）	?0.121*（0.064）
控制变量Control variables	是Yes	是Yes
地区固定效应 Regional fixed effects	是Yes	是Yes
时间固定效应Time fixed effects	是Yes	是Yes
样本量Sample size	9 831	9 831

变量Variables	改变样本分割比例Changing sample split ratio		更换机器学习算法Switching machine learning algorithm
变量Variables	样本随机分割为3组 Sample was randomly split into 3 groups	样本随机分割为8组 Sample was randomly split into 8 groups	随机森林算法 Random forest algorithm	梯度增加算法 Grad boost algorithm	神经网络算法 Neural network algorithm
农村电子商务发展 Rural e-commerce development	?0.017*** （0.004）	?0.018*** （0.004）	?0.023*** （0.005）	?0.016*** （0.004）	?0.034*** （0.004）
控制变量Control variables	是Yes	是Yes	是Yes	是Yes	是Yes
地区固定效应 Regional fixed effects	是Yes	是Yes	是Yes	是Yes	是Yes
时间固定效应Time fixed effects	是Yes	是Yes	是Yes	是Yes	是Yes
样本量Sample size	9 831	9 831	9 831	9 831	9 831

变量Variables	剔除并行政策的影响 Exclude the impact of parallel policies		剔除异常值的影响Removing the influence of outliers
变量Variables	信息进村入户工程政策Information entering villages and households project policy	宽带中国政策Broadband China policy	剔除异常值的影响Removing the influence of outliers
农村电子商务发展Rural e-commerce development	?0.017*** （0.004）	?0.019*** （0.004）	?0.009** （0.004）
控制变量Control variables	是Yes	是Yes	是Yes
地区固定效应Regional fixed effects	是Yes	是Yes	是Yes
时间固定效应 Time fixed effects	是Yes	是Yes	是Yes
样本量Sample size	9831	9831	8639

变量Variables	根据林农家庭收入的40分位数划分Divide according to the 40th percentile of forest farmer households’ income		根据林农家庭收入的均值划分Divide according to the mean of forest farmer households’ income
变量Variables	高于40分位数 Above the 40th percentile	低于40分位数 Below the 40th percentile	高于均值 Above the mean	低于均值 Below the mean
农村电子商务发展 Rural e-commerce development	0.092*** （0.009）	0.292*** （0.020）	0.038*** （0.010）	0.184*** （0.015）
控制变量Control variables	是Yes	是Yes	是Yes	是Yes
地区固定效应 Regional fixed effects	是Yes	是Yes	是Yes	是Yes
时间固定效应 Time fixed effects	是Yes	是Yes	是Yes	是Yes
样本量Sample size	5 777	4 051	3 815	5 975

Impact of Rural E-Commerce Development on Intra-Regional Income Gap and Shared Prosperity in Forested Areas

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变量Variables	林农家庭非农就业 Non-farm employment among forest farmer households	林农家庭创业 Entrepreneurship within forest farmer households	林农家庭出售的农产品价值 Value of agricultural products sold by forest farmer households
农村电子商务发展 Rural e-commerce development	0.017*** （0.005）	0.007** （0.003）	0.290** （0.137）
控制变量Control variables	是Yes	是Yes	是Yes
地区固定效应Regional fixed effects	是Yes	是Yes	是Yes
时间固定效应Time fixed effects	是Yes	是Yes	是Yes
样本量Sample size	9755	9831	9797

变量Variables	技能水平异质性 Heterogeneity in skill levels		社会资本异质性 Heterogeneity in social capital		贫困家庭异质性 Heterogeneity in impoverished households
变量Variables	高技能林农家庭High-skilled forest farmer households	低技能林农家庭Low-skilled forest farmer households	高社会资本林农家庭High social capital forest farmer households	低社会资本林农家庭Low social capital forest farmer households	贫困线以上林农家庭Above poverty line forest farmer households	贫困线以下林农家庭Below poverty line forest farmer households
农村电子商务发展Rural e-commerce development	-0.089 （0.347）	0.189*** （0.027）	0.173*** （0.023）	0.268*** （0.042）	0.192*** （0.015）	0.205*** （0.025）
控制变量 Control variables	是Yes	是Yes	是Yes	是Yes	是Yes	是Yes
地区固定效应Regional fixed effects	是Yes	是Yes	是Yes	是Yes	是Yes	是Yes
时间固定效应 Time fixed effects	是Yes	是Yes	是Yes	是Yes	是Yes	是Yes
样本量Sample size	4703	5047	3459	2962	6889	2973

[1]	Fanbin Kong,Yu Lu,Caiyao Xu. Digital Economy Development, Value Realization of Forest Ecological Products, and Urban-Rural Income Gap [J]. Scientia Silvae Sinicae, 2024, 60(5): 1-21.
[2]	Fanbin Kong,Ning Wang,Caiyao Xu,Yu Lu,Yueqin Shen. Impact of Value Realization of Forest Ecological Products on Urban-Rural Income Gap in 26 Mountainous Counties of Zhejiang Province [J]. Scientia Silvae Sinicae, 2023, 59(1): 44-58.
[3]	Wenmei Liao,Jing Lin,Yueqin Shen,Fanbin Kong. Influence of Socialized Forestry Services on the Income Gap of Rural Households [J]. Scientia Silvae Sinicae, 2023, 59(1): 59-73.
[4]	Dan Pan,Luyi Luo,Yi Yu,Fanbin Kong. Influence of Forest Resource Development Project on the Urban-Rural Income Gap in Old Revolutionary Regions [J]. Scientia Silvae Sinicae, 2023, 59(1): 74-89.