东北地区城市女性就业水平空间分异机制

doi:10.18306/dlkxjz.2020.08.006

Abstract

Abstract:

Females are important force in promoting social development. As the most direct way for women to participate in social and economic developments, employment has always been an important topic in scientific research. Taking the old industrial bases in Northeast China as an example, this study explored the spatial and temporal characteristics and driving mechanism of urban female employment level by means of spatial analysis. The results show that: 1) The level of urban female employment in the old industrial bases in Northeast China from 2000 to 2015 was generally low, mainly at medium and low levels; the medium level was mainly found in the central and southern regions, and the lower level was mainly distributed in the north. 2) From the analysis of influencing factors, it can be seen that higher education, convenient transportation, developed industries, the proportion of women with spouses, the proportion of the elderly aged 65 and above, and the proportion of households with three or more generations had a positive effect on the level of urban female employment, while demographic pressure had a negative effect on female employment level. Obviously, a complete family plays an extremely important role in female employment. 3) The government should integrate all sectors of society, encourage social capital to participate in the development of the elderly and childcare, and provide more and better quality services to families with strong needs for elderly care and childcare. In addition, promote the "family" culture of "respecting the old, loving the young, and being friendly with neighbors", encourage family members to participate in housework together, build an equal relationship between men and women in housework, create a harmonious family environment and social atmosphere, and relieve women conflict between work and housework.

Key words: female employment, spatial pattern, spatial error/lag model, influencing factors, Northeast China

FU Zhanhui, MEI Lin, ZHENG Rumin, WANG Tongtong. Spatial differentiation mechanism of urban female employment rate in Northeast China[J].PROGRESS IN GEOGRAPHY, 2020, 39(8): 1308-1318.

Figures/Tables 8

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References 53

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变量		计算方法	均值	SD	数值范围
因变量	女性就业水平Y (%)	女性就业人数/15~64岁人口	0.408	0.064	0.277~0.524
自变量
女性教育水平	低教育水平X₁(%)	高中及以下人数/15~64岁人口	0.813	0.054	0.692~0.893
女性教育水平	高教育水平X₂(%)	专科及以上人数/15~64岁人口	0.062	0.031	0.026~0.141
城市发展水平	城市道路便捷度X₃(m²/km²)	城市道路面积/市区面积	0.696	0.287	0.008~3.796
	城市规模X₄ (百万人)	市区常住人口	1.071	1.076	0.195~4.802
	服务业发展水平X₅(万元/人)	服务业增加值/城市人口	1.902	0.873	0.620~3.716
	工业发展水平X₆(万元/人)	工业增加值/城市人口	2.710	2.973	0.315~17.073
社会文化环境	女性有配偶比重X₇(%)	女性有配偶/15岁及以上女性人口	0.729	0.030	0.658~0.780
	女性无配偶比重X₈(%)	女性无配偶/15岁及以上女性人口	0.272	0.030	0.220~0.342
	育儿压力X₉(%)	0~4岁儿童/15~64岁人口	0.039	0.008	0.021~0.056
	老龄化X₁₀(%)	65岁及以上人数/15~64岁人口	0.117	0.023	0.055~0.148
	养育负担X₁₁(%)	(0~4岁+65岁及以上人数)/15~64岁人数	0.156	0.020	0.101~0.184
	家庭代际关系X₁₂(%)	三代及以上家庭户数/总户数	0.103	0.019	0.074~0.132

年份	Moran's I	P值	Z值
2000	0.193	0.022	2.108
2010	0.242	0.002	3.069
2015	0.227	0.004	2.889

指标	SLM		SEM
指标	LM-Lag	Robust LM-Lag	LM-Error	Robust LM-Error
统计值	0.202	0.653	4.796	6.635
P值	2.041	0.153	0.029	0.010
Log-likelihood	75.132		76.778

变量	SLM			SEM
变量	系数	t值	Z值	系数	t值	Z值
ln X₁	-0.376	-0.535	0.593	-0.603	-0.862	0.388
ln X₂	0.174	1.068	0.286	0.141	1.888	0.057^*
ln X₃	0.036	1.820	0.069^*	0.039	1.955	0.051^*
ln X₄	0.023	0.658	0.511	0.020	0.586	0.558
ln X₅	-0.058	-1.335	0.182	-0.060	-1.406	0.160
ln X₆	0.050	1.468	0.142	0.053	1.694	0.093^*
ln X₇	2.323	1.437	0.151	2.710	1.719	0.086^*
ln X₈	-0.017	-0.028	0.978	0.094	0.155	0.877
ln X₉	-0.068	-0.703	0.482	-0.060	-0.625	0.532
ln X₁₀	0.354	1.442	0.149	0.409	1.736	0.083^*
ln X₁₁	-0.684	-1.853	0.064^*	-0.777	-2.210	0.027^**
ln X₁₂	1.026	2.839	0.005^***	1.067	3.073	0.002^***
W^*dep.var/spat.aut	0.044	0.383	0.702	0.253	2.022	0.043
R²	0.550			0.553

Spatial differentiation mechanism of urban female employment rate in Northeast China

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